Valuation of SalMar - An investment case
HENNING AARSTAD & LA RS-FOLKE F. MOSEBY
Master thesis, Copenhagen Business School, August 4th 2015 MSc Finance and Strategic Management Supervisor: Peter Staudt Pages (excl. bibliography & appendixes): 116 Characters (incl. spaces): 202,439
Henning Aarstad Lars-Folke F. Moseby
EXECUTIVE SUMMARY
Supply and demand expected to increase The new MAB regime recently introduced, combined with improved license utilization will increase supply BUY HOLD SELL by 3-4% annually towards 2020. Population growth, increased focus on including fish in a healthy diet and Key data 1/5/2015 changes in preferances in the EU and Asia will Target price (NOK) 145 continue to drive demand growth at a faster pace than Share price (NOK) 112,50 supply. Upside 29 % Salmon prices set to decline Sector Seafood The imbalance in supply and demand has driven Ticker OSE SALM prices to record highs in recent years, creating profits Ticker Bloomberg SALM:NO throughout the value-chain. The market cannot Share outstanding (m) 113 300 sustain this price level in the long run. We expect Market cap (NOKm) 12 746 prices on alternative sources of protein to decline. We NIBD (NOKm) 2 301 estimate salmon prices to increase in 2015, before declining and stablizing at 38 NOK/KG. Share performance Feed and biology costs projected to increase 250 Prices for marine feed ingredients remain high and on an upwards trend, feed producers consolidate and 200 gain more bargaining power. We expect a cost increase related to feed of 2 NOK/KG in 2015 and 0.5 150 in 2016. Biology costs relalated to fighting lice and 100 PD will increase by 1 NOK/KG in 2015 and 0.5 in 2016. 50 SalMar remains highly profitable 0 SalMar still struggles to realize VAP potential at their new processing plant thus generates less revenue/KG than peers. However, their cost structure enables them SalMar Peer average to create superior returns even on less revenue. We OSEBX Salmon Price project SalMar to remain highly profitable and Source: OSE; Fishpool continue to create value for shareholders.
Financials (NOK 1000) 2014 E2015 E2016 E2017 E2018 E2019 Revenues 7 160 010 8 016 514 7 876 640 7 770 810 7 912 572 8 229 075 EBITDA 2 253 348 2 447 445 1 945 225 1 631 796 1 546 414 1 608 271 EBIT 1 975 184 2 167 707 1 655 696 1 332 133 1 235 664 1 285 091 NOPAT 1 468 307 1 669 490 1 275 158 1 025 961 951 664 989 731 ROIC 20 % 23 % 17 % 13 % 12 % 12 % EBITDA margin 31 % 30 % 24 % 21 % 19 % 19 % NIBD/EBITDA 1,02 1,14 1,49 1,84 2,01 2,01 CONTENTS 1. Introduction ...... 3 1.1. Research objective ...... 3
2. Methodology and evaluation of sources ...... 4 2.1 Methodology ...... 4
2.2. Evaluation of sources...... 6
2.3. Assumptions and limitations ...... 7
3. Salmon farming industry ...... 8 3.1. Production value chain ...... 9
3.2. Production output ...... 11
3.3. Industry structure and development ...... 12
3.4. Business cycle...... 14
3.5 Sub-conclusion ...... 15
4. SalMar ...... 15 4.1. History ...... 15
4.2. Organization and operations ...... 16
4.3. Strategy and vision ...... 17
4.4. Ownership and control...... 17
4.5 Sub-conclusion ...... 19
5. External analysis ...... 19 5.1. Macro environment ...... 19
5.2. Competitive environment ...... 32
5.3. Peer group ...... 37
5.4 Sub-conclusion ...... 40
6. Internal Analysis ...... 40 6.1. Resources, capabilities, core competences and competitive advantages ...... 40
6.2. Value chain analysis ...... 44
6.3 Sub-conclusion ...... 48
7. Financial analysis ...... 48
1 | P a g e
7.1. Accounting quality ...... 49
7.2. Financial statement adjustments ...... 49
7.3. Cost of capital ...... 53
7.4. Profitability analysis ...... 58
7.5. Risk analysis ...... 69
7.6. Sub-conclusion ...... 76
8. SWOT ...... 76 8.1. Strengths ...... 76
8.2. Weaknesses ...... 76
8.3. Opportunities ...... 77
8.4. Threats ...... 77
9. Forecasting ...... 78 9.1. Supply ...... 78
9.2. Demand ...... 83
9.3. Salmon price ...... 85
9.4. Costs ...... 90
9.5. Pro forma financial statements ...... 92
9.6. Cost of capital ...... 96
9.7. Sub-conclusion ...... 99
10. Valuation ...... 99 10.1. Present value approach ...... 100
10.2. Relative valuation approach ...... 103
10.3. Sensitivity and scenario analysis ...... 106
10.4. Verification ...... 110
10.5. Sub-conclusion ...... 113
11. Conclusion ...... 113 12. Thesis in perspective ...... 115 13. Bibliography ...... 117 14. Appendixes ...... 127
2 | P a g e
1. INTRODUCTION
Norway is a leading producer of seafood and production of farmed Atlantic salmon is among its most important industries. The industry is growing rapidly as demand for animalistic protein is increasing. The industry players have developed tremendously in terms of size and profitability over the last decades due to consolidation and technological advancement (Marine Harvest, A, 2014). SalMar is one of the world`s largest producers of farmed salmon, and is widely recognized as one of the most profitable companies in the industry (SalMar, K, 2015). As we are both Norwegian business students we find it interesting to gain insight into this important industry. Furthermore, we are interested in learning more about SalMar and how they have established themselves as a highly profitable company within a very competitive industry. We both study finance and strategy and believe a valuation is a good fit for our thesis as it is necessary to combine both strategic and financial aspects to be able to perform a high quality valuation. This enables us to put into practice a broad range of theories and concepts acquired throughout our studies.
1.1. Research objective The objective of this thesis is to determine the fair price of SalMar shares according to relevant theoretical frameworks such as present value models and multiples. We aim to create a solid foundation for an investment decision and to uncover whether the share is inaccurately valued in the market. Hence our research objective is to determine:
“What is the fair share price of SalMar as of May 1st 2015?”
To answer the research objective we must first gain insight into the industry, its value drivers, SalMar´s capability to compete in the market, and their financial performance. We have designed several research and sub-questions to gain comprehension about these topics and to structure the thesis:
Industry: What characterizes the salmon farming industry? How is the value-chain composed? How has the industry developed? SalMar: What characterizes SalMar? How has SalMar developed? 3 | P a g e
How are SalMar´s operations organized? Drivers: What are the main value drivers of the industry? What macro environmental factors affect SalMar? How is SalMar´s competitive environment? Competitive capability: How capable is SalMar to compete in the market? What are SalMar´s competitive capabilities? How is SalMar´s value-chain designed? Performance: How has SalMar performed financially? How profitable has SalMar been compared to peers? Is SalMar financially solid? Forecasting: How will SalMar´s cash flow develop? How will the main value drivers develop? What is SalMar´s future cost of capital? Valuation: What is SalMar´s share price according to theory? What share price do the present value models suggest? What share price do the relative valuations indicate? How do changes in our projections affect the share price? How probable is it that our estimated share price is accurate?
2. METHODOLOGY AND EVALUATION OF SOURCES
The overall objective of this thesis is to calculate the fair share price for SalMar. All financial modeling and calculations are in accordance with the structure from Petersen and Plenborg (2012), complemented by some theories harmonizing with their structure.
2.1 Methodology An in-depth understanding of both the industry and company at hand is needed to perform a financial valuation. To gain insight about the macro factors driving the salmon farming industry the PESTEL framework is used. This framework helps structure the analysis and includes a broad range of relevant macro factors influencing the company’s environment. However, the PESTEL framework is an extension of the PEST framework and there are multiple variations and extensions e.g. STEEP, SLEPT, SPECTACLES and so on. Therefore it is important to match the
4 | P a g e framework to the industry and objective at hand. The salmon farming industry is highly regulated, affected by the environment, political relationships, economic factors and so forth, hence our choice of the extended version of the framework. Moreover, a macro environment analysis is complex and it is difficult to define borders between the company, its industry, and wider environment, which all are subject to the analysts’ subjective interpretation. Historical development is not guaranteed to continue in the future.
To develop an understanding of the competitive environment and the attractiveness of the industry, Porter’s five forces framework is used. Porter´s framework provides understanding about how value is shared amongst the players; moreover the framework emphasizes an external perspective of the company’s environment rather than an internal focus. On the other hand the analysis assumes buyers, suppliers, competitors, and new entrants to be unrelated, and not operate in networks outside of the industry observed.
To analyze SalMar’s resources and capabilities the VRIO framework is used. However, to gain deeper insight about core competences providing competitive advantages, we have combined it with a framework similar to VRIO composed by Grant (2013). The VRIO framework is based on the resource-based view (RBV) and was introduced by Barney (2002). The framework uses internal competences, which it bundles with resources to create sustainable competitive advantages for the company. The perspective of the RVB is the company as a bundle of research and capabilities, which is in strict opposition to the holistic view, which considers companies as organisms with complex feedback-controlled mechanisms focused on boundary mechanisms. As a result the RVB is criticized for not having managerial implications (Kraaijenbrink, Spender, & Groen, 2010).
The company specific analysis is supplemented by a value chain analysis. This analysis is based on Porter’s generic value chain, which aims to assess the level of self-sufficiency and cost- structure for SalMar through the value chain. It provides a generic framework to analyze both the behavior of costs as well as existing potential sources of differentiation. However, as the framework is merely internal it is an appropriate supplement to our external analysis.
To compute cost of capital and perform a historical financial analysis we have used the framework designed by Petersen and Plenborg (2012). However, some calculations provided are
5 | P a g e based on theories originating from Aswath Damodaran. Yet other parts are based on the DuPont framework, which is also portrayed by Petersen and Plenborg (2012).
To summarize our analysis the SWOT framework is applied as it presents the most important findings from the external and internal analysis in a structured fashion.
The external and internal analysis findings are used to design pro forma financial statements for the future. The forecasts are based on the structure suggested by Marine Harvest`s Industry Handbook and analysts´ industry reports. The design of pro forma financial statements is based on theory from Petersen and Plenborg (2012). However, some assumptions are taken in order to make the model applicable for SalMar and the salmon farming industry. These assumptions will of course be elaborated in its respective section. The pro forma statements will serve as the basis for the present value models.
To calculate a theoretical share price for SalMar we have chosen to use three different approaches, the discounted cash flow model (DCF), economic value added model (EVA), and relative valuation. These models are based on different assumptions regarding the determination of the enterprise value, which will be elaborated in the respective sections. The models are chosen as they are widely acknowledged to provide accurate valuations, due to their practical approach and because they supplement each other well (Petersen & Plenborg, 2012). In accordance with Petersen and Plenborg (2012), we provide both a scenario and sensitivity analysis to examine how changes in main value driver affect the share price. We look at the reliability of our calculations by comparing them to consensus (analysts` targets) in addition to a Monte Carlo simulation.
2.2. Evaluation of sources As the thesis is written from an external perspective only publically available information is included. These sources include official governmental databases, analyst reports written by industry experts, commodity and financial statistics, annual reports, and articles. We acknowledge that it is possible that these sources contain faults and biases and the fact that errors in the information would alter the result of the thesis. However, this is the basis for any analysis based on secondary information.
6 | P a g e
We have applied an industry-specific document called the Industry Handbook 2014. The document is written by Marine Harvest who proclaims that the purpose of the document is to educate analysts and investors about the salmon farming industry. This source has been used extensively throughout the process of writing this thesis. We acknowledge that the document might be biased as Marine Harvest has self-interest in presenting data in a fashion favorable to the company. However, the Industry Handbook is cited by leading investment analysts giving the document authority. Still, we have been critical when adopting facts and concepts from this source. We have also used analyst industry reports from investment banks. We are aware that these are sales documents thus are information gathered from these is interpreted with carefulness.
2.3. Assumptions and limitations The purpose of this thesis is to answer the research objective, which is to determine the fair share price of SalMar. Answering this is an extensive process thus some assumptions and limitations are necessary in order to allow focus on issues related to valuation.
We assume the reader of this thesis to have a general understanding of economic and financial theory in addition to knowledge of strategic concepts. Therefore we will only briefly describe models and theory applied. The thesis in written from the perspective of an external analyst providing foundation for investment decisions. Hence, only publically available information is applied and we have not been in contact with any insiders. The stock market is constantly changing and new information is available every day. We have therefore chosen to only consider information up to a cut-off date, which is set to April 30th 2015. We have chosen to use historical data 8 years back in time for most analytical purposes. This is based on the fact that the salmon farming industry is cyclical and such a historical span is necessary to capture the whole cycle as the average across cycles provide the most accurate insight. This is also the period SalMar has been publically listed. When referring to salmon, we always mean Atlantic salmon unless specified otherwise. All companies included in the peer group participate in all steps of the value chain to some degree. However, some are also integrate into supporting activities (such as fish feed
7 | P a g e
production). Some companies are also geographically differentiated both in terms of production and end-markets. These differences are ignored for simplicity in our analysis, which may lead to a skewed peer analyses and relative valuation.
3. SALMON FARMING INDUSTRY
This section aims to answer the research question:
“What characterizes the salmon farming industry?”
The fish farming industry holds the sole purpose of raising fish commercially as a substitute for the stagnating wild catch (Marine Harvest, A, 2014). The farming takes place in quiet waters where the conditions are suitable. Salmon culture can be traced back to the start of the 19th century in the UK where fresh waters were stacked with Parr (last stage of freshwater growth) to enhance wild returns for anglers. The modern form of sea cage culture was first commenced in Norway in the 1960’s to raise salmon to marketable size. The early success in Norway prompted the development of salmon culture in countries such as Scotland, Chile, and Canada with more (FAO, A, 2015).
Figure 3.1 - Global harvest volume (1000 tons) 2 500
2 000 Growth 125% Est. Growth 20% 1 500 Est. CAGR 3% 1 000
500
0
Historical Forecast Source: Marine Harvest
Today all major production is located within 40 and 70º latitude in the Northern Hemisphere, and 40 and 50º in the Southern Hemisphere (Norway, Chile, UK, Faroe Islands, Ireland, North America, Tasmania and New Zealand) (FAO, A, 2015). The industry has grown tremendously and is still growing vastly. Figure 3.1 shows that the total harvest volume has more than doubled since 2000, with a compounded annual growth rate (CAGR) of 7%. However, the growth is
8 | P a g e expected to decline over the foreseeable according to Kontali (Marine Harvest, A, 2014). The total increase in harvested tons is estimated to be 20% until 2020 translating to a CAGR of roughly 3%. This is a result of productions levels pushing the biological boundaries. Future growth can no longer be driven solely by industry/regulators´ decisions alone, but must be subject to implementation of means to reduce the industry’s biological footprint. To achieve sustainable growth, progress in technology and pharmaceuticals are important as well as regulations and intercompany cooperation (Marine Harvest, A, 2014).
3.1. Production value chain The value chain of salmon production is an extensive and thorough process, which can take up to 40 months (Marine Harvest, A, 2014). The processes are facilitated to mirror the natural process the wild salmon go through. Figure 3.2 shows the whole production value chain.
Figure 3.2 - Production value chain
Source: Marine Harvest
The life-cycle starts with parent fish, called broodstock, which are selected based on characteristics such as color, and growth rate. The eggs from the female are mixed with the sperm from the males producing fertilized eggs. The egg develops a visible embryonic eye, and is
9 | P a g e referred to as eyed-eggs. The eyed-eggs are put in fresh water hatcheries with a temperature of approximately 8°C (Hansen, 1998) and there are roughly 5,000 eyed-eggs per liter of water.
About three months after fertilization, the eyed-eggs hatch and tiny fish called alevins arise. The alevins do not feed at this stage; they get their nutrition from a yolk sac attached to their body. The phase last for several weeks until the alevins starts feeding.
When the alevins release their yolk sac they are ready to feed and the alevins are now referred to as fry and are fed dry pellets specifically designed to meet the frys nutrition requirements. This ensures fast growth. Initially the fry weights 0.2 grams and are 2.5 cm long (Frøystein & Kure, 2013).
When the fry reach weights around 6 grams they are moved to lager tanks to continue their freshwater growth, the fry now changes to a green-brown color and are called parr. Under temperature conditions of around 15°C the parr will grow very rapidly (Frøystein & Kure, 2013). When the parr reach a weight of between 50 and 60 gram they are vaccinated to ensure robustness and resistance to common diseases (Marine Harvest - A, 2014), which is also required by law (Stortinget, 2011).
After the parr has undergone the physiological change enabling them to survive in seawater they are called smolt. The phase is called smoltification and occurs when the parr weights between 60 and 80 grams (Frøystein & Kure, 2013). The smolt is then transported in large tanks to seawater pens. It is necessary that this happens within a short time frame after the parr has become smolt, if it takes too long time the smolt might desmoltify and become parr again (Frøystein & Kure, 2013).
Once the smolt is deployed in the sea they are for the first time referred to as salmon. In the sea the salmon are kept in net pens where they can grow and mature. The salmon is separated into different nets based on size and batch in order to aid sorting and controlled transfers of specific fish types. After between a year or two at sea the salmon has grown to the desired size of 4.5-5.5 KG and is ready to be slain and gutted. After this process it is referred to as head-off-gutted (HOG).
10 | P a g e
3.2. Production output After the salmon is slain and gutted it is sold as a commodity. Salmon is considered an important source of protein for human consumption. It is considered healthy compared to other sources of animal protein, with high content of Omega-3 fatty acids, and rich on vitamins and minerals (Marine Harvest, A, 2014). Salmon is sold either fresh or frozen. However, producers have in recent years begun processing the salmon into filets, steaks, etc. This is referred to as value- adding processing (VAP). VAP has eased consumption and increased popularity. These products are also sold at a much higher price per KG.
Growing salmon requires much less compared to other sources of animal protein such as beef, poultry, and pork. The feed conversion ratio (FCR), which is how much feed is required to grow 1 KG of meet, is 1.2 KG for salmon and 2.2 for poultry, which is the closest alternative. Salmon is also superior to other sources of animal protein in terms of protein retention with edible meat per 100 KG feed of 57 KG, almost 3 times higher than poultry meat (Marine Harvest, A, 2014).
In addition to its resource efficient production, farmed fish is also a climate friendly source of animal protein. The carbon footprint from the production is abundantly lower than its substitutes, e.g. compared to beef the carbon footprint is ten times smaller. Freshwater is a scarce renewable natural resource. The freshwater consumption used to produce salmon is three times less than poultry and ten times less than cattle (Marine Harvest, A, 2014).
Figure 3.3 shows the price per KG of salmon, beef, pork, poultry and lamb. Salmon prices have been higher than the prices of other sources of protein over the past 20 years.
Figure 3.3 - Protein sources (NOK/KG) 50 40 30 20 10 0
Salmon Beef Pork Poultry Lamb Source: Indexmundi
11 | P a g e
However, if we look at the relative price change over the past 20 years from figure 3.4 we can see that the salmon price is by far the most stable. Relatively speaking both beef and poultry has become much more expensive compared to salmon over the last years.
Figure 3.4 - Protein sources indexed (NOK/KG) 300
200
100
0
Salmon Beef Pork Poultry Lamb Source: Indexmundi
Even though 70% of the world’s surface is covered by water, only 6.5% of the protein for human consumption originates from this element. The UN projects a population will rise to 9.6 billion by 2050, which will increase the need for protein by approximately 40% assuming the consumption per capita remains constant (Marine Harvest, A, 2014). As mentioned, the access to land-based animal protein is scarce; a solution to the problem can be increased use of fish proteins. As the supply from wild catch is stagnant at 1 million tons annually, the general supply of seafood in the world is shifting towards aquaculture (Marine Harvest, A, 2014).
3.3. Industry structure and development In the beginning the salmon farming industry was made up by a lot of small companies, local ownership was cherished, and there was no industry leader. During the late 1990´s a consolidation wave hit the industry and has held a tight grip ever since (Marine Harvest, A, 2014). Today 79 companies are producing 100% of the Norwegian supply of farmed salmon. The consolidation becomes even more evident considering that only 24 companies produces 80% of the total Norwegian biomass (weight of live fish) (Marine Harvest, A, 2014).
Norway is by far the largest producer of salmon, the closest competitor is Chile whereas sustainable production also occurs in both North America and the UK as shown in figure 3.5
12 | P a g e
Figure 3.5 - Production by country (tons) 1 500 000
1 000 000
500 000
0 Norway Chile UK North America Top 5 Total Source: Marine Harvest
Even though there were no major players during the early days of the industry, the consolidation has brought ahead a number of giants, Marine Harvest being by far the largest producer and also the only company represented in all major markets (figure 3.6). Even though Marine Harvest is the largest company there are other large players and all of the top 5 companies are Norwegian listed on the Oslo Stock Exchange.
Figure 3.6 - Top five producers (tons) Norway Chile UK North America Marine Marine Marine Cooke 264 000 56 000 50 000 41 500 Harvest Harvest Harvest Aquaculture The Lerøy Marine 157 000 Cermaq 51 000 Scottish 27 000 28 000 Seafood Harvest Salmon Pesquera Scottish Salmar 128 000 50 400 25 000 Cermaq 21 000 Los Fiordos Seafarms Empresas Grieg Northern Cermaq 56 000 47 700 18 000 16 000 Aquachile Seafood Harvest Grieg Cooke Grieg 55 000 Camanchaca 38 800 17 400 7 000 Seafood Aquaculture Seafood Top 5 660 000 243 900 137 400 113 500 Others 490 000 186 100 2 600 16 500 Total 1 150 000 430 000 140 000 130 000 Top 5 % 57,39 % 56,72 % 98,14 % 87,31 % Source: Marine Harvest
The main markets for salmon consumptions have historically been the EU region, Russia, Asia and North America. The main routes have been Norway serving the EU, Russia, and Asia; Chile serving the US, and Asia; Canada serving North America, mainly the US. The UK also mainly
13 | P a g e serves their domestic market with limited export. However, the traditional set up is shifting and new routes are established. Even though the frozen salmon category is diminishing, the Norwegian fresh salmon now faces fierce competition from Chilean frozen salmon. Increased competition between Norwegian and Chilean salmon in the Japanese market, and increase in exports from Scotland and Norway to the US indicates that the traditional trade routes are changing (Marine Harvest, A, 2014).
3.4. Business cycle The salmon farming industry has historically been subject to a cyclic pattern. Figure 3.7 illustrates the correlation between the salmon price/KG, EBIT/KG, and the EBITDA-margin. This cyclic pattern is caused by supply and demand mechanisms combined with lag in production. Producers increase production when they experience high prices and margins as this is interpreted as increased demand. However, as described in section 3.1, the production of salmon takes between 24 and 40 months, so the increased supply reaches the market years later. During this time lag, the market might have changed drastically, and the increased production might be too high, inevitably causing prices to drop, resulting in diminishing margins. The weak margins are interpreted as a decrease in demand and producers decrease production, which again takes time to affect the market. During this time lag, the market may change again, and production is reduced and prices and margins increase again. This process historically repeats itself with intervals of approximately 4-6 years from peak to peak, hence the cyclic pattern (Asche & Trond, 2011).
Figure 3.7 - Salmon price, EBIT/KG and EBITDA margin 60 30 %
40 20 %
20 10 %
0 0 %
Salmon Price Industry EBIT/KG Industry EBITDA margin
Source: Annual reports: SALM; MHG; LSG; GSF; NRS
14 | P a g e
3.5 Sub-conclusion The process of farming salmon is a long process, requiring quality in all steps, thus most salmon farming companies are fully integrated, producing everything from broodstock to
consumer-ready products. The industry has grown tremendously and so has the players through continuous consolidation and organic growth; the top five produces more than 50% of total output. Production takes place only in a very limited number of locations, yet foreign
competition has increased in recent years, especially from Chile. The industry is cyclical driven by demand and production lag, historically averaging at four to six years.
4. SALMAR
This section aims to answer the research question:
“What characterizes SalMar?”
4.1. History SalMar was founded in Frøya, Sør-Trøndelag, in February in 1991 by Gunnar Witzøe after the acquisition of a single license and a harvesting plant. The acquisition was of a company going into bankruptcy. At the time the Norwegian salmon farming industry mainly exported frozen or fresh HOG. The Norwegian aquaculture was in a turbulent period, which ended with the fall of the fish farmers’ own sales organization “Fiskeoppdretternes Salgslag AL”. This event laid the foundation for the restructuring the Norwegian aquaculture has undergone to substantially increase its level of industrialization. Throughout the years SalMar has grown mainly through mergers and acquisitions, but also through obtaining new licenses.
In 1995 SalMar began its smolt production through an acquisition of Follasmolt AS and leased a hatchery as enforcement. In 1997 Kverva Holding AS became sole owner of SalMar. In 2000 SalMar establish their first operations outside Central Norway through a 49% acquisition of Senja Sjøfarm AS in Troms. In 2001 the first and only operations outside Norway was established through Norskott Havbruk AS, a 50/50 joint venture with Lerøy Seafood Group owning 100% of Scottish Sea Farms Ltd. In 2005 SalMar divested all operations not considered to be core. In 2006 Kverva Holding AS sold 42.5% of their SalMar shares to a limited number of investors, in addition to acquiring the remaining 51% shares in Senja Sjøfarm AS. In 2007 SalMar was listed on the Oslo Stock Exchange under the ticker SALM. After going public,
15 | P a g e
SalMar has continued to grow, especially vertically, through acquisitions in both licenses for farming, smolt, and broodstock. In 2010 SalMar’s new harvest and processing, plant InnovaMar was finished as the world’s most innovative and modern plant (SalMar, A, 2015). After starting out with only one license SalMar is today the third largest producer of salmon. Their value chain stretches from broodstock, roe, and smolt to harvesting, processing, and sales. Today SalMar holds 100 licenses in Norway and harvested 154,800 tons in 2014 (SalMar, B, 2015).
4.2. Organization and operations SalMar ASA is a fully vertically integrated salmon farming enterprise employing over 1,000 people. Figure 4.1 shows an overview of SalMar’s operations and at which geographical location the tasks are performed. SalMar’s head office is located at Frøya, the Central Norway division, the same location as the InnovaMar processing plant. Central Norway is by far their largest location holding 52 licenses and a total HOG of 75,200 tons in 2014. The second largest location is Northern Norway with 32 licenses and a total HOG of 37,500. The smallest site is Rauma with a total HOG of 16,500 tones divided between 16 licenses. In terms of utilization of the licenses both Central and Northern Norway are above the Norwegian average with 1,446 and 1,541 tones HOG per license. However, Rauma’s utilization of the licenses lies below the Norwegian average with only 1,031 tons per license. In addition to the Norwegian operations SalMar also has a sales office in Japan and a 50/50 joint venture with LSG in Scotland contributing 13,400 tons HOG for SalMar (SalMAr, J, 2015).
Figure 4.1 - SalMar operations Smolt/Juveniles Farming Processing Sales & Distribution Central Norway SalMar Farming AS Follasmolt AS 52 icenses SalMar Processing AS SalMar Sales AS Lagstein Fisk AS - 60% Rauma Gruppen AS - 75.5% InovaMar facility 16 licenses Northern Norway
Troms Stamfiskstasjon AS SaMar Nord AS 32 licenses UK/Japan Scottish Sea Farms Ltd. - 50% SalMar Japan KK Source: SalMar
16 | P a g e
4.3. Strategy and vision SalMar states that all their growth must be sustainable environmentally, socially, and financially. They also proclaim that growth has gone hand in hand with an outstanding financial performance throughout their history, and as the aquaculture industry is developing rapidly there is great potential for future growth. To gain a reinforced focus on the foundation of “today’s SalMar” they have created a new vision to guide the company ahead (SalMar, K, 2015):
“Passion for Salmon”
Although SalMar will continue to pursue its stated aim of cost leadership, SalMar will move their focus from outcome to performance through excellence at all levels and in all aspects of their operations. The belief is that the best biological results will pave the way for the best financial results, and further enhance their position as the most cost-effective producer of farmed salmon in the world.
To be able to build upon this vision SalMar is depended on the existence of a winning culture throughout the organization. The source of SalMar’s corporate culture is the shared passion for salmon and the “What we do today we do better than yesterday” mentality (SalMar, K, 2015).
4.4. Ownership and control In publicly listed companies there are two essential questions to be asked, who are the owners and how much do they own? These questions are used to assess whether the identity of the owners has implications for their objectives and how they exercise their power (Thomsen & Conyon, 2012). Thomson and Conyon (2012) argue that ceteris paribus, larger owners will have stronger incentives to monitor the management of the company, in addition to more power to enforce it.
For many years the sole owner of SalMar was Kverva AS a holding company where SalMar´s founder Gustav Witzøe controls over 90% of the shares. When SalMar was listed on OSE Kverva sold parts of its shares and is now listed with 53.40% of SalMar’s shares. Today Kverva is an investment company focused on the marine sector, and is based on a fundamental belief in the strong long-term demand for seafood (Kverva, 2015). The second largest shareholder is Folketrygdfondet with 7.30% of the shares. Folketrygdfondet is a long-term financial investment
17 | P a g e institution owned by the Norwegian Ministry of Finance, that manages the Government Pension Fund Norway (Folketrygdfondet, 2015). The rest of the owners are mainly institutional investors, which holds relatively small positions of less than 2%. A vast majority of the shares are owned by long-term investors, which will likely ensure a stabile future for SalMar on the owner side. This means that from a theoretical perspective, SalMar has owners likely to monitor the executives in addition to the power to enforce governance and control (Thomsen & Conyon, 2012). This is supported by the fact that the chair of Kverva AS, Bjørn Flatgård, is also the chair of SalMar. Furthermore, the founder of SalMar and majority owner of Kverva AS, Gunnar Witzøe, is both a board member and an executive, indicating a strong will to monitor.
Separation of ownership and control arose when SalMar decided to enlist on OSE and Kverva AS sold 46.6% of their stake. According to agency theory, are boards created so that the owners will have control over the company even when professional managers are hired to run the company on their behalf (Fama & Jensen, 1983). The board of directors is elected by the shareholders thus represent the owners of the company (Thomsen & Conyon, 2012). SalMar’s board consist of 7 members, which according to Jensen (1993) is a perfect size as larger boards are less likely to function effectively as well as being easier targets for executives´ beliefs. Nevertheless, the most discussed aspect of board structure is independence, due to the logic that agents cannot monitor themselves, and other agents with a vested interest cannot be expected to produce good results (Thomsen & Conyon, 2012). Of the seven members of SalMar’s board, three are deemed dependent according to annual reports (SalMar, B, 2015). However, two of the members are employee representatives and should not be deemed independent, giving the argument that only two of SalMar’s seven directors are independent, implying that executives of SalMar holds great power over the board. However, we observe that Mr. Witzøe, which is the largest owner, en executive, and a board member, in addition to founder, holds great influence over the board and with his stake on the owner side we feel confident that both ownership structure and control are in good hands. As a safety mechanism to ensure that the board performs well there is a separate committee in charge of nominating board members, which is independent from both the board and executives (SalMar, B, 2015).
18 | P a g e
4.5 Sub-conclusion SalMar has grown from one license in 1991 to going public in 2007 and is today one of the largest players in the industry. They aim to be the industry`s cost leader and for performance
excellence in every step of the value chain. They are today fully integrated in production of salmon. The company is owned mainly by two institutional investors; one being the founder, the other a Norwegian governmental pension fund, both with long-term perspective.
5. EXTERNAL ANALYSIS
This section aims to answer the research question: “What are the main value drivers of the industry?”
To make sound forecasts we must first gain insight into what factors influence the salmon farming industry. Therefore it is important to gain comprehension about the underlying drivers of these factors in order to forecasts the development in the supply, demand, price, and costs. For this purpose we apply the PESTEL-framework to map macro environmental factors and Porter´s five forces to map competitive environment forces.
5.1. Macro environment SalMar is a Norwegian company with an overwhelming majority of its production located in Norway, as described in section 4.2. Their most important target markets are, in descending order: the EU, Asia, North America, and Norway (SalMar, B, 2015). The macro environment analysis will therefore focus on elements affecting operations in Norway, and factors influencing supply and demand in terms of export. The objective is to map the most important external opportunities and threats SalMar might be facing.
5.1.1. Political The market for salmon is very much global as described in section 3.3. Because production is located only in certain regions and exported for consumption globally (Marine Harvest, A, 2014), political policies, relationships and trade barriers are important factors to consider when forecasting supply and demand.
The Norwegian government´s policy is to be the market leader within seafood and measures are continuously taken to retain this position. They initiated the establishment of the Norwegian
19 | P a g e
Seafood Council to promote and support marketing activities for Norwegian seafood both locally and internationally (Norwegian Seafood Council, A, 2015).
The government also works constantly to maintain and establish trade agreements. Norway is a member of the World Trade Organization (WTO) and the European Free Trade Association (EFTA), which eases trade to member countries, in addition to external countries with free trade agreements with EFTA. Today Norway has 27 bilateral free trade agreements with 37 countries, whereof 25 stem from the EFTA membership. For a complete list of trade agreements and ongoing negotiations see appendix 1 (Norwegian Seafood Council, B, 2015; Regjeringen, C, 2014). Even though Norway has many trade agreements, there are still barriers and political challenges affecting export of Norwegian salmon. The impact of these will be further described in section 5.1.3.
The political relationship between Norway and China has been difficult since 2010, when the Nobel Peace Prize was awarded to the Chinese human rights activist Liu Xiaobo (Price, 2015; Regjeringen, D, 2015).
The US imposed an import restriction on Norwegian salmon in 1991, which allowed for a preference for salmon from other exporting countries to establish. Furthermore, the US and EU is now in the final stages of signing a free trade agreement. This will present challenges, as the EU producers would gain superior competitive conditions to Norwegian. The EU is also in talks with Canada regarding a similar free trade agreement (Norwegian Seafood Council, C, 2015; Regjeringen, E, 2014).
Russia joined WTO in 2012 and committed to reduce taxation on imported salmon from 10% to 3% by 2017 (Norwegian Seafood Council, C, 2015). However, the situation in Ukraine has affected this market severely for Norwegian producers. Following Russia´s annexation of Crimea in March 2014, the “western world” employed economic sanctions against Russia. They answered on August 7th 2014 by implementing a full import stop on several products from the west, including Norwegian salmon. The ban was announced to last one year; however, this is highly uncertain (Sonne & Troianovski, 2014). Additionally, the import stop does not apply to countries such as Chile, which amplifies the problem from a Norwegian perspective. Russia was
20 | P a g e able to quickly replace import from Norway to import from Chile instead as illustrated in figure 5.1 (Bjerke & Hågensen, 2015).
Figure 5.1 - Export to Russia (1000 tons wfe) 2014 15 12 9 6 3 0
Norwegian export Chilean export Source: SEB
5.1.2. Economic There are several economic factors influencing the salmon farming industry. This section will examine the most important, as insight into these factors will aid forecasting of production costs and cost of capital.
Fish feed is a vital production input for salmon Figure 5.2 - Salmon feed composition farming. It represents approximately 50-60% of total Fish Other production costs (Marine Harvest, A, 2014). Fish feed meal 8 % 14 % is composed of several ingredients; both marine Veg oil Veg commodities such as fish meal and fish oil, and 21% meal 48 % agricultural commodities such as wheat, soybean meal, Fish oil 9% and rapeseed oil. Figure 5.2 illustrates the typical composition of salmon feed. Source: Marine Harvest
The suppliers of the commodities used in fish feed charge cost-plus prices; meaning prices are fluctuating with the prices of the underlying commodities, transferring the risk over to the fish farmers (Directorate of Fisheries, 2015; Marine Harvest, A, 2014). The price developments of relevant commodities are shown in figure 5.3. The figure illustrates some volatility and future prices are not easily predicted. Fish oil prices have increased dramatically since 2009 before peaking in December 2014 and are now slightly down, yet still remain high compared to other feed ingredients. Fish meal prices have recently passed an all-time high and remain a source of uncertainty, and is expected to remain costly compared to agricultural commodities. However, 21 | P a g e wheat prices are relatively low with a stable balance in supply and demand. Soybean meal prices peaked in 2014 and are now slightly down. Rapeseed oil prices have experienced pressure since 2011, as well as other vegetable oils, as there is increasing demand for bio diesel (Index Mundi, 2015; Marine Harvest, A, 2014). In sum, we observe that marine ingredients are both more expensive and on an upwards trend compared to agricultural ingredients which are much cheaper and on a slightly downwards trend.
Figure 5.3 - Commodities (NOK/Ton) 20 000 15 000 10 000 5 000 0
Fishmeal Fish Oil Wheat Soybean Meal Rapeseed Oil Source: Indexmundi
Foreign currency exchange fluctuations imply limited risk for SalMar. Sales in foreign currencies are hedged on transaction date. Contract sales are hedged when the contract is entered. Foreign exchange risk related to costs is also limited as most input factors and salaries are settled in NOK (SalMar, B, 2015).
SalMar finances its operations by use of both equity and debt. All interest-bearing debt is in NOK from Norwegian banks. The loan portfolio carries floating interest rates (SalMar, B, 2015). This implies exposure to the fluctuations in the interest rate. The rate on these loans closely follows the key policy rate set by the Norwegian Central Bank. This rate was adjusted down from 5.75% in September 2008 as a response to the financial turbulence in order to stimulate the economy. Since 2009 the rate has been between 2.5% and 1.25%, where it is now, at a historical low (Norges Bank, A, 2015). The rate is expected to remain low, and analysts predict a cut of 0.25% within 2015 and that the rate will be constant at 1% over the next years (Jacobsen & Cook, 2015). This is of course speculation, nonetheless; we assume that the cost of debt will not fluctuate significantly in the foreseeable future. Figure 5.4 shows the historical key policy rate and the expected development along with the probability of different rates as expected by the central bank.
22 | P a g e
Figure 5.4 - Key policy rate (%) 7 6 5 4 3 2 1 0
Key policy rate 30 % 50 % 70 % 90 % Source: Norges Bank
5.1.3. Socio-cultural Socio-cultural aspects and population growth drives demand for salmon. Insight about these aspects are important in order to forecast demand as need for protein, health focus, and reputation has significant impact on consumption of Norwegian salmon.
As the world population grows the need for protein increases (section 3.2). The International Monetary Fund projects that the world population will increase by 1.18% annually towards 2020. The population estimates are shown in figure 5.5. As discussed in section 3.2, animal protein is scarce and as a result we expect population growth to increase demand for salmon and non- animalistic sources of protein.
Figure 5.5 - Population estimates (millions) 7 700 7 600 7 500 7 400 7 300 7 200 7 100 7 000 6 900
Source: International Monetary Fund, World Economic Outlook Database
The United Nations has stated that “Fish is a food of excellent nutritional value, providing high quality protein and a wide variety of vitamins and minerals, including vitamins A and D, phosphorus, magnesium, selenium and iodine in marine fish” (Marine Harvest, A, 2014, p. 13). With the increasing focus from governments and media on maintaining a healthy diet, and the
23 | P a g e improved knowledge of the health benefits from eating fish, there is only reason to believe that the demand for salmon will increase. This projection is also supported by the product innovation in processed salmon products (VAP). New products, such as loins, in smarter and portion-sized packages, make it easier for people to incorporate salmon in their diets (Norwegian Seafood Council, D, 2015).
Norwegian salmon has a strong position in most main markets. The EU is by far the largest salmon market. In 2014, 44% of all Atlantic salmon was consumed in the EU (Bjerke & Hågensen, 2015) and 72% of all salmon exported from Norway was consumed in the EU (SalMar, B, 2015). The average salmon consumption per capita is 1.8 KG (Norwegian Seafood Council, C, 2015). EU is a price sensitive market, but with positive growth prospects for Norwegian salmon. In Sweden, Norwegian salmon has a market share of 98% and enjoys a strong preference among the population with consumption per capita of 5.8 KG and a growth potential of 25% over the next five years. In Italy there are also positive prospects, from 2004 to 2012 per capita consumption of salmon increased by 50% to approximately 1 KG; this trend is expected to continue over the coming 5 years. In Portugal the salmon market share is 95% and with a trend of salmon taking larger shares of the total seafood consumption. In Poland the market share is 87%, and in 2012 alone the growth in consumption of salmon increased by 92% to 1.2 KG per capita. In Spain consumption of salmon per capita is 1.25 KG, the growth in 2012 was 9.1%, which is expected to continue for the next five years. In the UK the market share is 40%. This market traditionally favors Scottish producers, but there is an ongoing shift in preference towards Norwegian salmon. In Germany per capita consumption is 1.3 KG with a stable 96% market share. Ukraine experienced a price increase of 37% in 2013, and the market share is almost 100% (Norwegian Seafood Council, C, 2015).
The US is the second largest salmon market consuming 18% of all salmon in 2014 (Bjerke & Hågensen, 2015). Still, only 7% of the food consumed is seafood. 75% eat seafood less than once every month, and more than 50% eat seafood less than 6 times a year. Salmon consumption per capita is 0.9 KG and Norwegian salmon´s market share is only 10%, the same for Scotland, while Canada and Chile (both 40%) dominate the market (Norwegian Seafood Council, C, 2015). As mentioned in section 5.1.1, the US imposed import restrictions in 1991, which allowed for these
24 | P a g e preferences to establish, and there is no clear trend for the development in this market regarding Norwegian salmon. (Norwegian Seafood Council, C, 2015).
Russia has traditionally been the most important market for Norwegian salmon. In the period 2007-2011 growth was 18% annually and in 2012 the consumption per capita was 1.1 KG. This trend was expected to continue; however, due to the situation in Ukraine described in section 5.1.1, this market is no longer available to Norwegian producers.
Norway is one of the most important markets for Norwegian salmon. The total seafood consumption has been stable over the last 10 years at approximately 100.000 tons, with a salmon consumption per capita of 7.6 KG. The growth in salmon consumption was 23% in 2012 alone and the trend is expected to last, at least over the next five years (Norwegian Seafood Council, C, 2015).
The demand for salmon is also increasing due to changing trends in Asia. Salmon is becoming more recognized as a quality product and thus incorporated in traditional food such as sushi. The traditional ingredients in sushi have been Coho salmon and trout, but because of supply shortages of these, Atlantic salmon is becoming increasingly more popular (Norwegian Seafood Council, C, 2015).
In Japan consumption is mostly raw, where salmon represents 15%, of which the Norwegian market share is 19% while Chile´s is close to 80%. The Norwegian seafood council expects Norway´s share to increase over the next five years and has intensified its marketing efforts to gain a larger market share (Norwegian Seafood Council, C, 2015).
South-East Asia (Singapore, Indonesia, Malaysia, Thailand, Taiwan, and Vietnam) is becoming increasingly more important. Norwegian salmon is still in the introduction phase, but has already gained an average market share of 71% for total salmon and 83% of fresh salmon across these markets. Growth is expected to be 11% over the next five years, driven by population growth, increased economic growth and purchasing power (Norwegian Seafood Council, C, 2015).
China is an important market where Norwegian salmon had an 83% market share in 2010. However, due to the controversy surrounding the 2010 Nobel Peace Prize described in section 5.1.1, Norwegian salmon now have a market share of less than 70%. Still, growth is estimated to
25 | P a g e be 20-25% in the next five years. Seafood consumption is now estimated to be 3.1 KG per capita. Depending on region, 33-88% eats salmon during a year, and the trend is positive (Norwegian Seafood Council, C, 2015).
5.1.4. Technological The salmon farming industry has changed dramatically in terms of technology since its beginning; from most of the work being manual, to today´s highly automated processes. The focus of R&D efforts has been on increasing efficiency in terms of feed costs and reduced costs related to biology. The technology used in fish farming is now fairly standardized around the world, new developments and knowledge spreads at a constant pace (Marine Harvest, A, 2014). However, there are continuous efforts made to optimize production:
Ocean farming is a concept developed by SalMar, which makes it possible to farm in less sheltered areas. The technology is based on off-shore oil constructions combined with traditional fish farming equipment. The idea is submersible fixed structurs, slack-anchored, floating steadily in areas with depths between 100 and 300 meters. The construction facilitates for all handling of the fish without the need for external boats, throughout the process from smolt to harvest ready fish. Farming at more remote locations lessens the burden and impact on sensitive coastal areas such as fjords and bays and reduces the risk of lice and PD. SalMar has received a site and license for R&D purposes. A pilot project was started in the spring of 2014; however, there is no clear indication for whether the project was successful or when it might be fully operational (SalMar, C, 2013).
Closed-containment production is another innovation. Sulefisk has made a submersible closed containment cage with a floating collar construction called Ecomerden. It is supposed to help hold down lice levels, thus save cost related to prevention and treatments during outbreaks. It will also provide a more balanced and calm marine environment, hence, offer a better feed factor, fewer mortalities and optimize utilization of MAB. The drawbacks are, in addition to the uncertainty of an untested product, higher costs for electricity and oxygen. Sulefisk has been granted an R&D site and license for Ecomerden and plans to be operative from mid May 2015 (Mutter, 2015)
Land-based farming in Norway has so far been for R&D purposes only. However, in other countries such as Denmark, it has been used for commercial purposes for a few years (Langsand 26 | P a g e
Laks, 2015). The Norwegian government has yet to establish clear regulations for commercial use. They have gathered a commission whose report was presented on January 14th 2015. It recommends the government to allow commercial land-based farming under the requirement of licenses, which should to be granted without any fees or number restrictions, and to award them on a rolling basis. This is currently a source of much debate in the Norwegian salmon farming industry. The government is expected to make a decision during the near future (Holm, 2015).
As of now the R&D licensed capacity of land-based farming represent no immediate threat to the sea-based farming companies. Furthermore, we cannot see any reason why the established players should not be involved in this type of farming, should the concept be allowed on a commercial scale and proven profitable. However, the CEO of Marine Harvest has stated that he does not see the use for moving production to land. He argues that the only reason for doing so would be to mitigate the problem of lice, and that this problem should be solved in the sea rather than fleeing the problem (Villegas, Seaman, & Ramsden, 2015).
5.1.5. Environmental Environmental conditions affect growth rates, diseases, and mortality among the biomass, which all influence costs. Furthermore, it is important to avoid escapes, which will inflict deprecations from authorities. Insight about these factors is important in order to forecast harvest volumes and costs.
The temperature of the seawater is highly correlated with the growth rate of the salmon. Warmer temperatures allow for faster growth and vice versa (Marine Harvest, A, 2014). However, higher temperatures are also accompanied by increased risk of biological hazards, which will be explained later in this section (Grimnes, Birkeland, Jakobsen, & Finstad, 1996). The optimal temperature range is between 8 and 14 degrees Celsius. Temperatures below or above this range have a negative impact on the fish´s appetite, which affects growth negatively. The seawater temperature in Norway vary as much as 10 degrees with an average of 10 degrees; all elements considered, the Norwegian coast offer supreme conditions for salmon farming (Marine Harvest, A, 2014). However, the average seawater temperature has increased in recent years and the trend appears to continue. Figure 5.6 illustrates the seawater temperatures for the period 2011 – 2014 (Sjømat Norge, 2015).
27 | P a g e
Figure 5.6 - Norwegian seawater temperature (celcius) and y-o-y 18 16 2014; 9 % 14 12 Optimal: 8 - 14 C 2011; 4 % 10 2008; 2 % 2012; 2 % 8 2007 2009; -1 % 2013; -1 % 6 4 2 2010; -8 % 0
2011 2012 2013 2014 2015 Source: Sjømat Norge
Salmon lice are the most common parasite in salmon farming. Lice occur naturally in seawater, however, due to the number of hosts the problem is aggravated at salmon farming sites. Lice may spread between cages at a farm, but also over greater areas by water currents. The problem is mitigated by several means such as by the use of cleaner fish (Wrasse) that eats lice, mechanical removal, and medicinal products (Sjømat Norge, 2015). The regulations demand action when the number of lice exceeds a limit of 0.5 lice per fish. If this limit is breached the Norwegian Food Safety Authority may force the farmer to harvest the fish immediately. There is also strict guidance for use of medicines. Previously, frequent outbreaks of diseases, high mortality and treatments with antibiotics, resulted in significant economic losses in the industry. All farmed salmon are now vaccinated and thus most bacterial infections are prevented. The most prominent viral infections today, which there are no treatment against, are Infectious Pancreatic, Infectious Salmon Anemia, and Pancreatic Disease (PD). The vaccines against viral infections are not as effective as vaccines against bacterial infections (Directorate of Fisheries, 2015). The mortality due to diseases represents by far the most prominent cause of loss in production as illustrated in figure 5.7.
PD is the most common and represents the largest challenges among the viral infections. PD is caused by a virus, which can cause reduced appetite, muscle injuries, and eventually mortality. Outbreaks of these diseases and others need to be mitigated through continuous control, monitoring, vaccination, and sometimes even medical treatment in form of medicines, all very costly (Marine Harvest, A, 2014).
The Norwegian government has stated firmly that preventing escapes are given high priority to avoid farmed salmon from affecting the stock of natural wild fish. These concerns regard changes
28 | P a g e in the wild fish´s genetics and spreading of lice and other diseases. The government has also established a pool, financed by the entire salmon farming industry, to pay for costs related to removing escaped farmed salmon. Other initiatives include increased inspection and control activities, in addition to the establishment of a commission to investigate causes of escapes, build experience and recommend regulatory improvements (Directorate of Fisheries, 2015). However, from a financial perspective escaped fish represent less than 1% of the loss in production (figure 5.7). Still it is important to minimize escapes in order to avoid bad publicity and maintain good relations with authorities as escapes may negatively affect the process of obtaining licenses and may trigger other deprecations.
Figure 5.7 - Loss in production 2005-2013 Mortality Declassified Escapes Other Error 78,28 % 4,91 % 0,84 % 14,10 % 1,87 % Source: Directorate of Fisheries
5.1.6. Legal The legal environment secures competiveness and sustainability. However, it also limits growth opportunities. Therefore insights about regulations are important to forecast supply growth.
Norway is the world´s leading producer of seafood and the second largest exporter after China. Farmed fish represents 70% of this export. The industry is of great importance to Norway, thus highly scrutinized, with several governmental bodies controlling operations; the most pronounced is the Ministry of Trade, Industry and Fisheries. Numerous laws regulate the salmon farming industry including the Aquaculture Act, the Food Act, and the Animal Welfare Act. Furthermore, there are regulations governing the allocation of aquaculture licenses, sites, and operations. The main purpose of these is to secure profitability, competiveness, and sustainability (Directorate of Fisheries, 2015).
A license and site is required to engage in salmon farming in Norway. These are subject to fees, awarded and allocated in rounds as decided by the Ministry of Trade, Industry and Fisheries. There are volume limits per license called maximum allowed biomass (MAB), defined as the maximum biomass of live fish each producer can farm on a license in the sea at any given time. This implies an intricate correlation between MAB and harvest volumes. The MAB system was introduced in 2005 and revised several times since, lastly in 2011. The MAB limit per license in
29 | P a g e
Norway is now 780 tons, except in Troms and Finnmark, where it is 945 tons per license. Given the MAB per license, the average annual harvest volume in Norway per license is approximately 1,200 tons (Marine Harvest - A, 2014). In addition to MAB, there are limitations regarding production volume at each individual site, determined by carrying capacity. License prices (fees) have historically been NOK 5m (NOK 4m for Troms and Finnmark) (Regjeringen, A, 2006). Fish farming licenses are transferable and due to their scarcity they have been known to trade for between NOK 20-70m (Marine Harvest, A, 2014). As of now the total number of licenses is 973 and total MAB is 789,465 tons (Directorate of Fisheries, 2015).
Recently the Norwegian government has decided to increase the MAB by 6% every second year as long as it is deemed environmentally sustainable. This will be done by increasing the number of licenses (Regjeringen, B, 2014). These new licenses will be granted both through auctions and at fixed prices. These licenses are so-called “green licenses”, which have higher standards and requirements for sustainability and environmental footprint than the previous licenses. To obtain a green license one old license must be traded in to obtain two new green licenses. This new MAB regime is expected to increase MAB by 3-5% annually if used sustainably (Ramsden, 2014).
Figure 5.7 - Biomass and MAB 1 000 000 800 000 31% 24% 600 000 19% 19% 400 000 12%12% 9% 11% 10% 6% 7% 4% 4% 200 000 3% 2% 3% 3% -4% -3% -4% 0
Biomass at sea Total MAB y-o-y biomass Source: Directorate of Fisheries
Figure 5.7 displays the total biomass at sea is approaching the total MAB. The MAB has been fairly stable since 1994, this can be seen in context with the number of licenses which also has been fairly stable over the over the same period as shown in figure 5.8.
30 | P a g e
Figure 5.8 - Number of licenses 1 000 800 600 400 200 0
Total licenses Source: Directorate of Fisheries
From 2009, the graph 5.7 also illustrates monthly total biomass in the sea, this shows that the biomass does not stand constant through the year but starts low when the smolt is released in the pens and rises as the salmon grow. As the MAB capacity is close to being breached there are now discussions on different ways to sustainably increase the capacity in the years to come, additionally to the new MAB regime. As mentioned, the live biomass at sea is not constant through the year and today´s MAB regime is not considered flexible enough by some of the top producers. They want to introduce a rolling average as a replacement for the “constant” MAB system. The argument is that this would increase total output and give more flexibility in terms of harvesting larger volumes throughout the entire year. However, some believe only today´s system can ensure sustainable growth (Ramsden, 2014).
The ministry may also regulate the maximum biomass capacity for individual companies (Regjeringen, A, 2006; Regjeringen, B, 2014). If a company gains control of more than 15% of the total licensed MAB in Norway, it is required to apply for approval by the ministry. Such approvals may be granted on grounds such as R&D and apprenticeships in coastal regions. However, no company can control more than 50% of MAB in any given region (Marine Harvest, A, 2014).
5.1.7. Summary macro environment Norway has numerous trade agreements easing export; still political difficulties with Russia and China represent challenges. Feed prices are increasing due to suppliers` consolidation and increased prices on underlying raw materials. Demand growth is driven by increased population, focus on healthy diets, and change in preferences towards Norwegian salmon. There are several new farming technologies in pipeline; land-based farming may be worth looking into if proven
31 | P a g e profitable on a commercial scale. Challenges related to biology, such as lice and PD, are increasing as seawater temperatures are rising. The industry is highly regulated and access to licenses; their restrictions, price, MAB, and other covenants represent limits for growth opportunities.
5.2. Competitive environment After conducting an analysis of the macro factors, we will now take a closer look at the competitive environment within the industry. A study by Möller & Rajala (2007) based on the research of Ravi S. Achrol (1997) suggests that one of the fundamental shifts in the 21st century is from a inter-organizational exchange relationship towards a network perspective of value creation involving different types of network organizations (Möller & Rajala, 2007). Further arguments by Nalebuff & Brandenburger (1997) suggest that the traditional competitive environment analysis overlooks the relationship established by complementors. Hence to gain comprehension of competitive forces it is suggested using a value-net framework, mapping the whole game with the players and the relationship to one another resulting in zero-sum outcomes (Nalebuff & Brandenburger, 1997). The clear difference between a value-net and a traditional Porter’s five forces analysis is the added force of complementors, where the industry players has to both compete and cooperate to create a larger pie and get a bigger piece of it. However, the salmon farming industry in Norway is dominated by large fully vertically integrated players, and new value-adding companies are often, as mentioned in section 3.3, implemented in the value chain through acquisitions. Even though there are a few strategic cooperation’s in the industry, the main focus is to grow larger and get more integrated in the value chain, going for fully self- sufficiency instead of relying on suppliers and supporting activities from other industry players. Based on this argumentation we will perform a Porter’s five forces analysis to assess the competitive environment of the industry and discard the value-net approach.
5.2.1. Threat from substituting products The price the customers are willing to pay for a product depends largely on the availability of substitute products and the price of the substitutes compared to the underlying asset (Grant, 2013). Figure 5.9 illustrates that as a source of protein for human consumption, fish only represents 6%. However, if we define salmon as a source of animalistic protein, we see from figure 5.10 that fish has a far greater percentage (20%).
32 | P a g e
Figure 5.9 - Protein sources for human consumption Figure 5.10 - Production distribution of protein
Fish Animal Pork 20 % 38.90% 30% Other 54.60% Poultry Mutton 26% Fish & Goat Beef 6.5% 4 % Other 18% 2 % Source: Marine Harvest Source: Marine Harvest
As we can see from figure 5.9 and 5.10, there are several alternatives to salmon in the market. One of the most important parameters for the use of substituting products is the price (Winer, 1986). After comparing prices of different sources of protein in section 3.2, we know that that the salmon price is relatively high and volatile. Furthermore, the salmon price is more cyclical. This cyclical pattern is a result of the long production cycle and the short shelf life (Marine Harvest, A, 2014).
Salmon holds some superb health benefits, mentioned in section 3.2 and 5.1.3, which cannot be found to the same degree in substitutes. With the health benefits of salmon in mind we consider what Monroe (1973) calls the buyers’ subjective perceptions of price. From his research we can see that given the salmon’s superior attributes the perceived price may not be as high considering that substitutes have less attributes.
Even though the health benefits of salmon are superior compared to its substitutes, the highly volatile prices, and the fact that the price is higher, we conclude the threat of substitutes is high.
5.2.2. Threat of new entrants As mentioned in section 3.3, the salmon farming industry has been and is in a wave of consolidation, which has led to a high concentration of market participants. The top 5 players in the industry produce over 50% of the total framed salmon. We can see that the trend in the industry is vertical integration where fully integrated companies control the whole value chain. Given the industry structure, immense amounts of capital are required to start up and compete with the well-established fully integrated companies.
33 | P a g e
Even though the industry is composed of large fully integrated companies there are still quite many companies performing supporting activities in the industry. A way to become a player in the industry could be through a supporting activity and focus on growth and expansion. However, there is a trend in the market where the companies performing supporting activities are acquired by the top players to enhance and strengthen their position as a fully integrated company.
To be able to start as a salmon farmer you need to obtain licenses, which are both expensive and difficult as they are only issued at specific times as described in section 5.1.6. Due to the long production cycle and volatility in the market, economies of scale are of great importance to succeed as a wholly integrated salmon farming company.
In addition to the immense capital requirement and regulatory barriers there are also environmental aspects to take into consideration. Only a few places are suitable for salmon farming. However, the Norwegian government is considering opening up for land-based farming on a commercial scale, as described in section 5.1.4. There are companies planning to build plants with capacity of 3,600 tons a year (iLaks, 2014). However, these numbers compose no real threat to the fully integrated traditional sea-based farming companies as the top 5 players produce a combined total of 660,000 tons in Norway (Marine Harvest, A, 2014).
In sum, we conclude that the threat of new entrants is low due to the high capital requirements, regulations, environmental conditions, and the low threat of land based salmon farming the threat of new entrants to the industry is low.
5.2.3. Bargaining power of buyers Determination of the bargaining power of the buyers is based on the supply and demand of the product. If the supply is high or the demand is low the buyer holds the higher bargaining power. The production of salmon is fairly standardized and the products are homogenous when we talk about salmon after primary processing, Porter (2008) argues that if the product is standardized or undifferentiated, and the buyers believe that they always can find an equivalent product, they tend to play one vendor against another. However, the Norwegian salmon has through extensive cooperation between the Norwegian Seafood Council (NSC) and the Norwegian producers been able to get an image of exclusivity and high quality in most markets (Norwegian Seafood Council, A, 2015).
34 | P a g e
It is easier to distinguish between the products after the secondary processing like filleting and smoking, also referred to as VAP. However, the seafood industry in Europe is highly fragmented with more than 4,000 players (Marine Harvest, A, 2014). Most of the companies are small but there are also several companies of significant size in the secondary processing industry. According to Marine Harvest (2014) customers are willing to pay for quality and VAP. There is expected an increase in demand for convenience products such as ready-to-cook fish and high quality vacuum packed fresh salmon filets.
For salmon farmers only participating in the primary processing of slaughtering and gutting it is almost impossible to differentiate from competitors as the product is homogenous and the prices are established by the equilibrium of supply and demand. It is easier to differentiate for farmers participating in secondary processing. However, there are over many players within processing and the switching costs are close to zero. Porter (2008) argues that the bargaining power of buyers is high when switching costs are low; hence we conclude that the bargaining power of buyers is high even though some companies in the secondary processing business holds some advantages.
5.2.4. Bargaining power of suppliers The most important input factor for farming salmon is feed, which constitute approximately 55- 60% of production costs (SalMar, B, 2015). When we examine the bargaining power of suppliers we look at the relative power the producers of salmon feed has towards the farmers. However, as mentioned, many of the large companies are fully or partly vertically integrated. Hence the dependence of suppliers differs between companies, as some are fully or partly self-sufficient in terms of input factors such as feed production.
However, even though companies might be partly or fully self-sufficient on feed they must purchase the raw materials on the open market where they are traded as commodities and prices are decided by supply and demand. Over the recent years prices for fish feed has increased, directly impacting the profitability for the farming companies (GSF, A, 2015).
As on the farming side of the industry, there has been heavy consolidation on the supplier side. Over the last 15 years the suppliers has increased their bargaining power as there today are only three players controlling the market (Marine Harvest, A, 2014; Porter, 2008). Figure 5.11 and 5.12 illustrate the evolution of the fish feed industry from 1998 -2013. 35 | P a g e
Figure 5.11 - Feed producers market share 1998 Figure 5.12 - Feed producers market share 2013
Biomastr Other Polarfeed 4% 9% 2 % BioMar NorAqua 26% 9% Skretting Skretting BioMar 44% 38 % 12% EWOS EWOS 37 % 22%
Source: Marine Harvest Source: Marine Harvest
Based on the high concentration of the fish feed producers, and the fact that even though the self- sufficient farming companies must buy the raw material on the open market, we conclude the bargaining power of suppliers to be high.
5.2.5. Rivalry among existing competitors After years of consolidation in the market, the salmon farming industry is controlled by a few large players who make profits through economies of scale, though with a clear leader in Marine Harvest (Marine Harvest, A, 2014), though the rivalry is somewhat restricted due to extensive governmental regulations (Regjeringen, A, 2006). The top industry players still consolidate the market further as well as continue to push the margins by continuous vertical integration. The high investments needed to compete with the established companies translate to substantial exit barriers. This is by Porter (2008) high-lighted as one of the main contributors to fierce industry rivalry. In sum, we conclude the rivalry amongst existing competitors to be high.
5.2.6 Summary competitive environment Figure 5.13 summarizes the competitive forces. All forces, except the threat of new entrants, are considered to be high. At glance the industry might look unattractive; fierce rivalry, low barging power towards both buyers and suppliers, in addition to strong competition from substituting products. However, due to the strong position for the vertically integrated companies, the regulation and high salmon prices we conclude that the industry holds great potential for the already established players whilst being unattractive for new entrants.
36 | P a g e
Figure 5.13 - Competitive environment (Porter´s five forces)
High High High High
Low
Substitutes New Entrants Buyer Power Supplier Power Market rivalery Source: Own research
5.3. Peer group To conclude on the relative performance for SalMar it necessary to consider how they perform relative compared to its competitors. To conduct this comparison accurately it is decisive to look at a set of industry peers that have similar outlooks for long-term growth and return on invested capital (Goedhart, Koller, & Wessels, 2010). In addition, the peers must be comparable in other characteristics; such as accounting policies, and all financial statement analysis must be adjusted for transitory items (Petersen & Plenborg, 2012). In reality there are rarely any truly comparable peers. This issue must be addressed; hence it has been important to choose peers, which hold approximately the same vertical integration level as SalMar in order to ensure equal characteristics.
To ensure that the prerequisites for good peers are met, we look at the Seafood index at Oslo Stock Exchange (OSE), which contains 10 companies in addition to SalMar. However, some of the companies do not engage in fish farming and are thus excluded. Some of the companies hold significant stakes in production of other types of fish as well as no or little production in Norway. In addition, a top 5 competitor, Cermaq, who seemingly match SalMar in terms of the conditions required is left out as a peer. The reason for this is the fact that before the divestment of their feed production EWOS to Bain Capital in 2013, more than 60% of their revenue derived from the feed segment, hence comparing historical financials would add little value. Moreover, Cermaq is now sold to Mitsubishi Corporation and taken off OSE as privately held company (Cermaq, B, 2015).
After excluding companies based on the criteria listed above, we are left with four companies similar to SalMar in term of financials and operations: Marine Harvest (MHG), Lerøy Seafood Group (LSG), Grieg Seafood (GSF), and Norway Royal Salmon (NRS). 37 | P a g e
MHG is the world’s largest producer of salmon with an approximate market share of 21.51% of the total market and 22.96% of the Norwegian market (Marine Harvest, A, 2014). Marine Harvest is also by far the largest company in terms of market cap with approximately NOK 42bn (OSE, A, 2015). The company is fully vertically integrated and is either wholly self-sufficient or aspiring to become so in all parts of the value chain. MHG is also geographically diversified with production in several countries reducing risk and providing the best market access as they for instance can go around trade embargos.
LSG is the world second largest producer of salmon with an approximate market share of 8.49% of the total market and 13.65% of the Norwegian market (Marine Harvest, A, 2014). When it comes to market cap LSG has the 3rd largest on the OSE Seafood Index with approximately NOK 13bn, about 200 million less than SalMar at second (OSE, B, 2015). In addition to the production of salmon, which contributes to roughly 80% of total sales, the group has become a large player within whitefish as well. LSG is the leading exporter of seafood from Norway and has high focus on VAP and sales. Subsequently they have a global sales network through subsidiaries and have 14 processing facilities located in different European countries (LSG, A, 2015).
GSF is the world´s fifth largest producer of salmon with an approximate market share of 4.32% of the total market and 4.78% of the Norwegian market (Marine Harvest - A, 2014). Their market cap of approximately NOK 2.9bn is sixth largest on the OSE Seafood index (OSE, C, 2015). However, due to the similarities in the value chain and exposure to market factors we believe them to be a worthy peer. GSF is involved in the whole value chain. However, they are not fully self-sufficient in all parts. This is something they strive to be and are investing heavily in (GSF, A, 2015). GSF is today present in Canada, UK and Norway, and holds a total production capacity of 90,000 tons gutted weight which they have yet to fully exploit (GSF, A, 2015).
38 | P a g e
NRS is the ninth largest producer of salmon in Norway with an approximate market share of 1.57% of the total market and 2.52% of the Norwegian market (Marine Harvest, A, 2014). They have the seventh highest market cap on OSE Seafood Index, just below GSF with approximately NOK 2.7bn (OSE, D, 2015), hence NRS has a fairly high market cap compared to their market share in HOG. However, NRS has a close sphere of partners and through their sales division they sold over 62,000 tons to over 45 countries (NRS, A, 2015).
To ensure that the peer requirements are fulfilled and to get some insight into the peer group, this section will introduce a short analysis of historical returns, to get some insight into how peers have performed and if they have the same exposure to external events.
Figure 5.14 shows how the companies have performed relative to each other in the period from June 2007 to April 2015. As we can see, SalMar’s stock price has increased the most from the index year. However, NRS was not listed on OSE before March 2011 and from the new base in 2011 we can see that NRS stock has outperformed SalMar, even though SalMar has the second best performing stock in that period as well. Furthermore, we can see that all share prices increase and decrease at the same time, indicating that they react to the same exposure.
Figure 5.14 - Stock prices indexed in 2007 and 2011 450 400
400 300
350 200
300 100
250 0
200
150
100
50
0
SalMar Marine Harvest Lerøy Grieg NRS Source: Yahoo Finance 39 | P a g e
5.4 Sub-conclusion The most important macro environmental factors affecting SalMar is supply, demand, and costs; MAB, population growth, feed prices and biological challenges. Prices for some
underlying feed commodities are increasing. Demand is increasing driven by population growth and health focus. Biological challenges related to lice and PD are intensifying. Governmental regulations limit growth and MAB. SalMar’s competitive environment is composed by large vertically integrated companies, resulting in fierce rivalry, making it unattractive for new entrants, still profitable for established players. All peers are
homogenous, large, vertically integrated, and participate in most of the same steps of the
value chain.
6. INTERNAL ANALYSIS
This section aims to answer the research question: “How capable is SalMar to compete in the market?”
The internal analysis will help us determine SalMar´s strengths and weaknesses, thus aid the forecasting of harvest volume and costs. In this section we will apply tools derived from both Grant (2013) and Ireland, Hoskisson & Hitt (2011) in order to explore SalMar´s resources and capabilities and to determine if they have any competitive advantages over its rivals. We will analyze SalMar´s value chain using theory from Porter´s generic value chain, in order to aid our forecasting.
6.1. Resources, capabilities, core competences and competitive advantages “Strategy is concerned with matching a firm´s resources and capabilities to the opportunities that arises in the external environment” (Grant, 2013, p. 112).
Resources, capabilities, and core competencies are the foundation of a company’s competitive advantage. According to Kothandaraman and Wilson (2001) are resources are bundled to create organizational capabilities, and in turn the capabilities are the source of the company’s core competencies which again is the basis of competitive advantages.
Resources range from individual to social and organizational occurrences. One resource alone rarely produces a competitive advantage; more often a unique bundling of several resources is
40 | P a g e necessary. Resources are often divided into two or three categories, but the consensus is that there exist tangible and intangible resources. Tangible resources can be observed and quantified; examples include property, plant and equipment, financials, organizational structure, and access to raw materials. Intangible resources are more difficult to observe, analyze and imitate; examples include an organization´s culture, scientific and innovative capacity, reputation, brand, and image (Grant, 2013; Ireland, Hoskinsson, & Hitt, 2011). Analysts have a tendency to focus on tangible resources. However, intangible resources more often serve superiorly as the foundation for sustainable competitive advantage (Grant, 2013).
Capabilities occur when resources are combined to yield a particular mission. Such missions, or tasks, range widely and include aligning the organization´s functions toward cost efficiency, human resource selection, marketing and R&D activities (Grant, 2013; Ireland, Hoskinsson, & Hitt, 2011).
Core competencies are capabilities that provide the organization with a competitive advantage. McKinsey & Co endorses identifying no more than three or four core competencies to build strategy upon. Sustaining more may prove adverse as fully exploiting core competencies demands focus and considerable attention (Ireland, Hoskinsson, & Hitt, 2011).
6.1.1. Identifying resources and capabilities The first step in the process of identifying resources and capabilities is to determine the key success factors (KSF) in the industry; from there we will identify the resources and capabilities to match the industry´s KSFs (Grant, 2013).
As mentioned in section 3.2 and 5.2.3, the salmon farming industry is homogeneous with little or no means to diversify products, except for VAP. Therefore, the industry´s number one KSF is cost efficiency in order to secure profitable margins. This implies an important relationship of cost per KG harvested. Firms emphasize size, obtained through organic growth and M&As, in order to achieve economies of scale. The number of licenses and the utilization of licensed MAB are also important for economies of scale. Larger firms have higher flexibility in production and thus achieve higher license utilization; HOG per license (SalMar, F, 2015). Firms aim at full vertical integration in order to secure self-sufficiency, cost control, and quality in broodstock, eggs, and smolt. Some firms also integrate fish feed production as it represents a large portion of total costs and the quality greatly affects growth rates. Efficiency is also driven by constant focus 41 | P a g e on innovation and R&D in harvest and production processes, in addition to property, plant and equipment, and VAP. Processes for good husbandry are also critical for efficiency as it reduces costs related to diseases and escapes. Finally, optimal location of sites and plants are also critical as ideal locations provide benefits such as minimizing costs of transportation, easing market access, and securing ideal farming conditions (Marine Harvest, A, 2014).
SalMar, as many of its competitors, strive for economies of scale trough maximizing license utilization, organic growth and M&A activity. They have successfully undertaken several M&As and grown to be one of the industry´s largest players. They are fully vertically integrated performing all steps in production of salmon, allowing for self-sufficiency. However, they do not produce fish feed. They have constant focus on innovation and can pride themselves with having one of the industry´s most efficient processing facilities, InnovaMar. They also have one of the industry´s best smolt production abilities, which permits smolt release throughout the year, in contrast to most competitors who release more seasonally. As mentioned in section 5.1.4, they are working on a new ocean-based farming method, which might be a breakthrough in terms of reduction of costs related to biology. They also focus on VAP and recently introduced a high-end fish filet called Frøya (Johnsen, 2013). SalMar´s locations in Norway offer optimal farming conditions, low transportation costs (aided by alliances) and market access with only a few limitations due to some political matters, which were described in section 5.1.1 (SalMar, B, 2015).
6.1.2. Appraising resources and capabilities To determine which of SalMar´s resources and capabilities constitute core competences and in turn provide SalMar with competitive advantages we will apply the VRIO-framework and Grant´s (2013) framework for assessing resources and capabilities.
The VRIO framework is comprised of four questions and the answers help determine if the capability serves as a core competence: Is the capability valuable in order to exploit opportunities or defuse threats in the external environment? Is the capability rare or do most others also hold it? Is the capability costly to imitate? And finally, given the three previous questions, is the organization ready and able to exploit the capability? (Ireland, Hoskinsson, & Hitt, 2011).
According to Grant (2013) a capability represents a competitive advantage only when two conditions are met; it must be both scarce and relevant. A capability may be common within an 42 | P a g e industry, thus necessary in order to compete, but not a source of competitive advantage if it is widely available. It is also a requisite that the capability is relevant to address the industry´s KSFs. Furthermore, the capability providing competitive advantage will erode over time and its sustainability is determined by an additional four criteria: durability, transformability, replicability, and the ease of appropriating the returns to competitive advantages. This means that the capability must be durable to provide advantage in the long-term. If it is easily transferable (bought) any advantage may erode quickly. If it cannot be transferred, competitors must developed it by imitation, if the capability is easily replicated the advantage will wear down quickly. It should also be clear who benefits from the capability´s advantage; owners or employees. The less clear property rights are, the harder it is to allocate the capability to a competitive advantage (Grant, 2013).
Figure 5.15 shows that SalMar capabilities assessed according to the criteria of the two methods described above. It illustrates that SalMar has only one sustainable competitive advantage over its competitors; their capability to innovate in order to increase cost efficiency. This is based on their resources in smolt release and production, in addition to InnovaMar, the most efficient production and processing facility in the industry, and their R&D in ocean farming.
Figure 5.15 - Appraisal of resources and capabilities Resources Capability Valuable/relevant Rare/scarce Imitable Able Consequence Implication License utilization License amount Economies Competitive Average Yes No Yes Yes Organic growth of scale parity returns M&A Vertical integration Sustainable Above Self- Smolt Yes No/Yes Yes Yes competitive average sufficiency Feed advantage returns PPE Temporary Average to VAP Innovation Yes Yes Yes/no Yes competitive above R&D advantage average Farming conditions Location Competitive Average Transportation costs Yes No Yes Yes benefits parity returns Market access Source: Own research; Ireland et al (2011); Grant (2013)
Grant´s (2013) criteria of scarcity and relevance, is similar to the VRIO questions about the capability being valuable and rare and therefore included in the same figure as the VRIO. However, Grant (2013) also introduces a matrix to determine which resources and capabilities
43 | P a g e
SalMar should focus on. The resources and capabilities’ strategic importance and relative strength can be mapped to help divide them into four categories: irrelevance, superfluous strengths, key weaknesses, and key strengths.
SalMar should focus on maintaining and developing its key strengths. Economies of scale: continue to strive for license utilization, always be involved in license award rounds, organic growth and M&A activity. Innovation: continues improvement of PPE, VAP and R&D. Location benefits: hold on to their sites with optimal farming conditions, and further decrease transportation costs. Furthermore, SalMar should look to improve their weaknesses of self- sufficiency: they should consider becoming fully self-sufficient by undertaking their own fish feed production, and look for ways to increase their market access (appendix 2).
6.1.2. Summary resources, capabilities, core competences and competitive advantages The analysis of resources and capabilities shows that SalMar has most resources and capabilities necessary to match the industry´s KSFs. However, many of these are not rare, as several competitors also possess them. Therefore, SalMar has few sources of sustainable competitive advantage, yet enough to make them the industry`s cost leader. They also have some weaknesses related to self-sufficiency, they should consider addressing.
6.2. Value chain analysis As mentioned in the industry analysis in section 3.1 the value chain of farming salmon is long, complex, and holds several individual steps. By using the framework from Porter’s Generic Value Chain we can distinguish between primary and supporting activities (Grant, 2013). Further we will look at how dependent SalMar is on input factors provided by other companies in the industry.
6.2.1. Primary activities
6.2.1.1. Eggs/Broodstock Smolt The value chain of producing salmon starts with the broodstock, which are the parent fish used to provide the eggs by mixing the female eggs and the male milt (sperm). SalMar is self-sufficient in eggs at all their sites thus control the quality of their eggs and are not reliant on costly external
44 | P a g e inputs. By engaging in broodstock SalMar is fully backwards integrated in the traceable supply chain of salmon farming (SalMar, D, 2014).
SalMar is also fully self-sufficient in hatching the eggs, the moving of fry from incubators to fresh water tank, and the smoltification process where juvenile transit from a life in freshwater to a sea-going existence (SalMar, D, 2014). In contrast to some of the other salmon farming companies, SalMar is not in need of additional smolt from external providers, which is a strength compared to some of the competitors. The smolt is produced in six different plants near the three major farming sites all but one are wholly owned (Langstein is 60%). The plants have available fresh water supply, and has undergone investments in recycling which makes it possible to produce more smolt, and with less usage of water (SalMar, E, 2015). SalMar is, in contrast to the industry standard, focusing on season-independent smolt production, which gives more flexibility when it comes to adapting supply to demand.
6.2.1.2. Farming The farming takes place in net-pens, which are large, enclosed nets suspended in the sea by floating devices and solid anchoring. The fish is kept in seawater until it reaches a desirable weight of 4.5 - 5.5 KG; this is the most time-consuming step of the value chain and also considered the core of the industry. SalMar controls all aspect of the operations themselves. In 2014 SalMar harvested a total of 141,000 tons of salmon which was the third highest for a single producer that year (SalMar, B, 2015; Marine Harvest, B, 2015; LSG, B, 2015; GSF, A, 2015; NRS, B, 2015). SalMar has an overlying goal to be the most cost efficient farmer; hence getting the highest growth rate on the lowest feed ratio is of great importance.
SalMar is striving to optimize their farming process by innovative technology, and invests in the plans for conducting farming operations on deeper waters. Ocean Farming is a subsidiary that will develop and implement new technologies and build the expertise required for this next generation of fish farming (SalMar, C, 2013).
6.2.1.3. Processing As mentioned in section 3.2 there are two types of processing; primary and secondary. SalMar has its processing plant InnovaMar conducting comprehensive harvesting and VAP operations located close to the largest farming site SalMar Central Norway. InnovaMar is considered to be
45 | P a g e the most innovative and efficient salmon harvesting and processing plant in the industry. Since the opening of InnovaMar in 2010 SalMar has been able to bring large harvest volumes to one plant, enhancing economies of scale as well as providing flexibility and better utilization of the entire salmon. However, they still struggle to fully realize the VAP potential and produce less processed products than peers (SalMar, F, 2015)
SalMar has a strategic alliance with one of the main competitors Lerøy. SalMar harvest the salmon from Lerøy’s sites in Central Norway and Lerøy will harvest the salmon from SalMar Northern Norway at their Aurora plant (TDN Finans, 2014). The alliance is constructed to ensure better quality of the salmon and reduce costs related to moving live fish by well boats. Apart from this strategic alliance SalMar does all its processing at the InnovaMar plant and is thus fully self-sufficient. Value added processing is important for SalMar and new products are constantly being developed, making it easier for the consumers to prepare.
6.2.1.4. Sales and distribution The salmon that is produced by SalMar is sold through an in-house sales force and through close partners. SalMar uses proximity to markets to secure efficient use of high quality raw material that has been through a traceable and controlled production process. Even though some of the business is not in-house, it is done by close partners and SalMar is nearly 100% self-sufficient in sales and distribution. The InnovaMar plant provides capacity for all kinds of storage and good internal logistics to ensure safe and efficient handling of the products.
6.2.2. Supporting activities
6.2.2.1. Transportation Transportation is regarded a supporting activity as it is not directly involved in the growth of the fish. Transportation is related to the movement of the salmon between the stages of the value- chain. For instance moving smolt in trucks to open waters, or moving harvest ready salmon to the harvesting plant in well boats. SalMar has made investments in all aspects of the value chain and this process is conducted 100 % in-house.
6.2.2.2. Fish feed Even though fish feed is directly involved in the growth of the salmon, the production of feed is not; hence fish feed is considered a supporting activity. Fish feed of high quality is of major
46 | P a g e importance directly affecting growth rates. Unfortunately SalMar does not engage in feed production, neither for internal nor external use. Over the recent years feed prices have increased rapidly, and, as mentioned, constitute over 50% of production costs. By engaging in production of fish feed to become self-sufficient SalMar could gain more control over quality as well as an even stronger position as a fully vertically integrated farming company. Even though the initial cost of this would be high, SalMar would probably reduce costs in the long-term, which coincide their goal to be the most cost efficient farming company and perform excellence in every part of the production.
6.2.3. Cost structure in the value chain There are a significant number of cost-related tasks throughout the value chain. However, it is difficult to allocate the exact cost to the individual step as costs such as feed, salaries and maintenance often overlap. Figure 5.16 shows how the main cost components are distributed in the process of farming salmon. As the figure shows, the cost of feed is by far the largest cost contributor. Processing and smolt represent approximately 10% of the contribution each. The most cost-intensive tasks are those directly involving handling of the salmon. The other costs which also sums up to approximately 10% include amongst other; direct and indirect costs, administration, and insurances.
Figure 5.16 - Cost distribution in the value chain Sales & Feed Processing Smolt Salary Transportation Maintenance Depreciation Mortallity Other Marketing 50,20 % 10,20 % 9,35 % 6,11 % 4,13 % 3,32 % 3,12 % 2,27 % 0,61 % 10,69 % Source: Marine Harvest
6.2.4. Summary value chain analysis Figure 5.17 shows that SalMar has established a fully integrated system for farming, processing, sales, and distribution of farmed salmon, thus controlling the whole value chain, only being reliant on external supply for fish feed. Moreover figure 5.17 also shows how the revenue is distributed through the production value-chain, and is based on the total revenue contribution from each step of the value chain (Cermaq, A, 2010; Kontali, 2011). As we can see from the figure the highest revenue contributor is farming operations and the second largest is fish feed. Comparing this with figure 5.16 above, it becomes evident that SalMar could cut costs by integrating and become self-sufficient in feed production. Even though eggs hold little contribution to the overall revenue it is of great importance to have quality eggs, as this affect the
47 | P a g e rest of the value chain. Hence it is utterly important for SalMar, who strives for excellence, to keep this and every other steps of the value chain in-house.
Figure 5.17 - Salmon farming industry value chain Supporting activities Transportation Fish feed
Self-sufficient P O % of revenue distribution 0,87 % 36,77 % Processing Primary Activities Eggs Spawning Smolt Farming Sales Distribution Primary Secondary Self-sufficient P P P P P P P P % of revenue distribution 0,35 % 3,66 % 47,38 % 5,92 % 2,44 % 2,61 % Source: Marine Harvest
6.3 Sub-conclusion SalMar has many of the capabilities necessary to compete successfully in the industry, still few sources of sustainable competitive advantage. Their smolt and processing capabilities
represent their key strengths. SalMar has established a fully integrated system for farming, processing, sales and distribution of salmon, undertaking all steps of the value chain ensuring quality, control and stability. However, they are not fully self-sufficient as they do not participate in fish feed production.
7. FINANCIAL ANALYSIS
This section aims to answer the research question: “How has SalMar performed financially?”
The financial analysis will be conducted to supplement the strategic analysis and gain insights to be used in the forecasting. To determine the level and trend of profitability and financial risk associated with SalMar we will compare the numbers with the peer group (Petersen & Plenborg, 2012). The salmon farming industry moves in cycles as described in section 3.4, hence a long time horizon is essential to capture the average through tops and lows. SalMar was listed on OSE in June 2007 hence our time period for the historical data will start June 2007, even though one of the peers was not listed until March 2011 (OSE, D, 2015).
48 | P a g e
7.1. Accounting quality In financial statement analysis an important aspect is to look at the quality of reported numbers in annually and quarterly reports. Throughout history we have time on time seen companies manipulating financial reports to make themselves look healthier for regulators, and equity- and debt holders (Petersen & Plenborg, 2012). According to Penman (2010) “Quality of earnings is the degree to which current earnings serve as an indicator of future earnings” (Petersen & Plenborg, 2012, p. 334). In the definition recurring items are looked upon as having high quality whilst transitory/special items are considered of lower quality (Petersen & Plenborg, 2012). This will be taken into consideration when reformulating the income statement and balance sheet.
It is important to look at accounting flexibilities in the income statement and balance sheet. Biased accounting numbers in the income statement are likely to occur under circumstances where: transaction span has a long time horizon, complex transactions like derivatives, complex accounting standards, high degree of personal discretion of standards, and when different methods can be chosen by management (Petersen & Plenborg, 2012). In the salmon farming industry products are traded at market prices, and complex derivatives are not usually used on a large scale. In the balance sheet posts such as depreciation and inventory holds great potential for biases. However, the accounting standard is the same over the whole industry in addition to governmental injunctions on independent audit reports, which we believe ensures good accounting quality in all financial reports used.
7.2. Financial statement adjustments Both SalMar and its peers report their financial data using International Financial Reporting Standards (IFRS) (all income statements and balance sheets can be found in appendixes 3-7). However, the IFRS does not distinguish between operating and financial items. When calculating the financial ratios to measure a company’s profitability it is crucial to reformulate both balance sheet and income statement to distinguish between operational and financial items, as it is the company’s operations that primarily drive the value creation (Petersen & Plenborg, 2012). The financial statements for both SalMar and the peer group have been reformulated accordingly to Petersen and Plenborg (2012) and all classification has been done with respect to this. Reformulating the income statement into an analytical income statement divides the accounting items into “operational” and “financial”. The operational accounting items refer to core
49 | P a g e operations whilst the financial items refer to the non-core operations. The operating earnings are key performance measures because it shows the firms profit from core business regardless of how it has been financed (Petersen & Plenborg, 2012). In order to match the items in the analytical income statement with the related items in the balance sheet, the balance sheet also has to be reformulated (Petersen & Plenborg, 2012). A significant number of the items will not need any explanation as they are obviously connected to their respective classification.
This section will offer argumentation when justification of the classification is more intricate. Since both SalMar and its peers have almost identical items on their financial statements, specific clarification for each company is not necessary, only a general description for all companies is provided. This might lead to some deviation amongst item names between the different companies (all reformulated analytical income statements and balance sheets can be found in appendix 3-7).
7.2.1. Income statement adjustments Excess value of inventory from acquisitions: From the annual reports it is clear that all acquisitions are related to SalMar’s core activity of farming salmon. However, in SalMar’s annual report from 2011 it is clearly stated that with regards to the sale of fish obtained through acquisitions, the elements associated with the cost of production are recognized under the “cost of goods sold”. Those elements associated with an estimated fair value are recognized in the “excess value of inventory from acquisitions”. The post is not recurring every year, furthermore, fair value is only an accounting item in the same way as depreciation and amortization and do not affect cash flows. As a result we treat “excess value of inventory from acquisitions” as non-core.
Fair value adjustment of the biomass: As mentioned in the “excess value of inventory from acquisitions” fair value is an accounting item, hence “fair value adjustment of the biomass” will also be treated as non-core. The fair value adjustment is used to measure live fish at its current value according to the spot price in the market (SalMar, B, 2015). Even though the adjustments are recurring, they fluctuate from NOK -356m to NOK 528m for SalMar, hence the difficulty of producing reliable forecasts. Thus they will not be forecasted. Excluding it from core operations will give less noise in NOPAT estimates for analytical purposes. The post is thus treated equally to depreciation and amortization, and do not affect free cash flows to firm (FCFF).
50 | P a g e
Onerous contracts: “Onerous contracts” is an item, which only occurs for SalMar in 2011, and it is related to losses on forward contracts with fixed price. This is used to hedge against the fluctuations in the spot market and is clearly a financial decision. Even though the contracts are related to core operations the use of financial hedging is a financial decision, as of this gains and losses on these contracts are classified as financial items (Petersen & Plenborg, 2012)
Exceptional biological items: This post is defined as losses due to destruction of salmon required by authorities after outbreaks of lice, PD, and single events of escaped fish. The costs are measured in full production cost as well as cost related to cleanup and shutdown of site. Due to the circumstances of the post not being recurring we treat this post as non-core even though it is related to the core operation. The main reason for this choice is the problems of forecasting meaningful number for the future as well as the theory from Petersen and Plenborg (2012) on special items.
Non-recurring gains on acquisitions: As indicated by the name, this post is non-recurring. Even though it affects core operations as all acquisitions performed by companies in the peer group, we will treat this post according to Petersen and Plenborg (2012), which states that non-recurring items should be treated in the same way as financial items.
Income from associated companies: All investments in associated companies are related to the value chain of farming and sale of salmon, which is considered core operations for all companies in the peer group. Even though acquisitions are regarded as financial decisions, gains and losses from acquisitions are considered operational items as they all relate to core activities. This post is also recurring hence treaded differently from those that are non-recurring. In compliance with Petersen and Plenborg (2012), the relevant balance sheet items are included in the invested capital.
Tax on core operations: As the accounting item “tax” relates to both operating and financing items it is necessary to divide the tax into core and non-core for analytical purposes (Petersen & Plenborg, 2012). Accounting practices does not distinguish between where the tax derives from, and according to Petersen and Plenborg (2012) the segregation can be accomplished by estimating the tax shield from net financial expenses, which is calculated as:
( )
51 | P a g e
When determining the tax rate, either marginal or effective tax rate can be used as a proxy (Petersen & Plenborg, 2012). Since SalMar has all their borrowings in Norway and all peers are listed on OSE we have chosen the Norwegian marginal tax rate as a proxy for the corporate tax rate.
7.2.2. Balance sheet adjustments Investments in associated companies and joint ventures: As mentioned all associated companies and joint ventures are related to the value chain of farming and sale of salmon. In addition, Petersen and Plenborg (2012) argue that the items on the balance sheet and income statement should be treated likewise; hence we treat this post as core.
Pension fund assets & liabilities: All items related to pension are part of employee compensation and should hence be treated the same way as payroll expenses, which are considered core.
Receivable from parent company: “Receivables from parent company” are treated as financial items, as this item clearly has nothing to do with core operations.
Bank deposits, cash and cash equivalents: Cash and cash equivalents are usually considered as excess cash, which either can be paid out as dividends, used to buy back own shares, or reduce debt without affecting operations (Petersen & Plenborg, 2012). The post may however include cash that is needed in the day-to-day operations; hence cash can be separated into operating and excess cash (Petersen & Plenborg, 2012). However, operating and excess cash is not separated in company’s balance sheets. Moreover, to divide the post, additional information, not publicly available must be obtained. Petersen and Plenborg (2012) argue that the consequence of reclassification of operating cash are likely to be modest in most cases, hence we treat it like a financial post. In addition bank deposits are interest-bearing and should contribute to reduce NIBD.
Deferred tax assets & liabilities: Deferred tax items in the balance sheet is a nominal amount calculated on the basis of temporarily differences between accounting and tax values, in addition to tax loss carried forward at the end of the financial year (SalMar, B, 2015). Deferred tax can be treated as both financial and operational depending on the purpose (Petersen & Plenborg, 2012). The uncertainty about both time and amount for the liabilities to be settled define them as
52 | P a g e provisions. The actual amount to be paid to settle the liability depends on both on the tax rate at the time of settlement and timing, which depends on future investments of the firm. If the company invests a constant amount in perpetuity, deferred tax might in principle never be settled. Due to analytical purposes and the fact that deferred tax is directly related to core tangible and intangible assets (SalMar, B, 2015) we recognize deferred tax as operational item.
Tax payable: Compared to deferred tax items, “tax payable” has no uncertainty with regard to settlement. The post “tax payable” arises because the company pays insufficient tax on account during the fiscal year (Petersen & Plenborg, 2012). This can be because realized earnings are higher than what was expected; hence we treat the post as core-operations in compliance with Petersen and Plenborg (2012).
Public duties payable: “Public duties payable” is recognized as core operation. The annual reports do not describe in detail what the post includes, however, as the fish farming industry is highly regulated, we believe it is fair to assume that the duties are related to the core operations.
7.3. Cost of capital Cost of capital is a central concept in financial analysis and is applied in many different contexts. Providers of financing to the firm expect a return on their capital; order of repayment and riskiness of the business affect their expected return. The equity holders are the last to get paid; shareholders carry a greater risk and require a higher return as compensation. As providers of financing may invest their funds elsewhere in the market, the only accurate measure reflecting investors’ opportunity cost is market value of equity and debt.
Companies are generally funded by both debt and equity and the weighted average cost of capital (WACC) represents the required rate of return for investors based on cost of equity and debt (Petersen & Plenborg, 2012). This section will explain the calculations and the numbers behind the historical WACC, the full calculations can be found in appendix 8. For valuation purposes we will forecast a WACC, which will be addressed in section 9.3. The WACC will be used to measure economic value added (EVA) in the profitability analysis (section 7.4.). The WACC is calculated as:
( ) ( ) ( )
53 | P a g e
In order to determine the WACC of SalMar we will now calculate and assess each component of the formula.
7.3.1. Capital structure The WACC is highly affected by the capital structure of the company. Since the WACC calculation is over a historical period we use the actual debt and equity ratios from the respective year when calculating the WACC.
7.3.2. Cost of equity
The cost of equity (re) is used to estimate the owners’ required rate of return for investing in the company. The most common way to calculate this is to use the Capital Asset Pricing Model (CAPM) (Petersen & Plenborg, 2012). However, there are several models for this purpose and another way to calculate re is the Fama-French three-factor model, which differs from CAPM in its definition of systematic risk. Nevertheless, Koller, Goedhart, Wessels and Copeland (2005), suggest the use of CAPM as best-practice for calculating WACC. CAPM is based on three factors; the risk-free rate (rf), the equity beta (βe), the market risk premium (rm-rf), and the basic idea that investors´ are able to diversify sufficiently to eliminate unsystematic risk. Based on
CAPM re is calculated as:
( )
In addition, firm-specific measures can be added through a liquidity premium (Petersen &
Plenborg, 2012). re for SalMar varies between 5.84 and 9.03 for the historical period. The next section will provide a justification for the estimates related to the calculation of re.
7.3.2.1. Risk-free rate
The rf express how much an investor can earn without taking any risk. According to Petersen and
Plenborg (2012), the best estimate for rf would be a zero-β portfolio. However, both cost and problems of constructing such a portfolio proves that it is not useful in practice; hence government bonds are used as a proxy for rf, as the underlying assumption is that government bonds are risk-free (Petersen & Plenborg, 2012). We have chosen Norwegian government bonds as our proxy as it is important that the government bond is denoted in the same currency as the underlying cash flows to address issues such as inflation. Petersen and Plenborg (2012) argue that a 10- or 30-year government bond should be applied. 10-year bond often match the underlying cash flow better, however, it might also suffer from illiquidity affecting the yield (Petersen &
54 | P a g e
Plenborg, 2012), and hence 10-year government bonds are chosen. The rate on 10-year Norwegian government bonds has varied between 4.78% and 2.52% over the historical period; the respective rate for each year is used for calculation of WACC.
7.3.2.2. Systematic risk
Equity beta (βe) is used to measure the covariance between the returns on a specific stock, and the return on the market portfolio also referred to as firm-specific or systematic risk. According to Petersen and Plenborg (2012), the most common way to estimate the beta is to use regression on historical stock returns. However, Damodaran (1999) argues that there are clear limitations of using a simple regression beta. To gain a better estimation of the systematic risk Damodaran (1999) present various estimation alternatives. After careful considerations we have landed on the bottom-up approach to calculate the β for both SalMar and its peers (appendix 8.1).
The bottom-up approach is chosen as it significantly lowers the standard error compared to a single regression beta. In addition it can be adjusted to reflect changes in the firm’s business mix and financial leverage over time (Damodaran, 1999).
The bottom-up approach bases the estimation of beta on companies in the same business. The peer group is used for this purpose. The procedure begins with calculating regression betas on historical stock returns for each of the companies in the peer group. The calculation for beta using regression is defined as:
An important factor in the regression calculation is the choice of index. Damodaran (1999) argues that S&P 500 is an ideal index as it is weighted and includes enough shares. However, after talking to several analysts following SalMar we have concluded that the best index for a Norwegian salmon farming company is Oslo Stock Exchange Benchmark Index (OSEBX). As we know the Oslo Stock Exchange (OSE) is heavily skewed towards oil, which have a low influence on the performance of SalMar, the bottom-up approach makes even more sense. The time period is also important. Damodaran (1999) discusses the importance of the trade-off between statistic validity due to a large number of observations and the fact that companies might change over time. SalMar has only been listed since 2007 and their business mix and leverage
55 | P a g e has not change drastically over the period. We conclude that it is of higher importance to capture the whole cycle of the industry rather than small company-specific changes. Hence the regression is based on an 8 year time period. Lastly it is important to choose the correct return interval. As returns are more volatile from day to day than on yearly basis, and the fact that there are non- trading days that could make noise for the estimation, Damodaran (1999) suggests a monthly time interval as best practice, hence we have used monthly intervals.
Over time, betas tend to move towards one (Damodaran A. A., 1999). Hence a post-regression adjustment is needed. There are several ways to do this and different theory suggests different weights. We have chosen to follow the Bloomberg approach to adjustment, which is calculated:
After the regression betas are calculated for each company in the peer group, we need to find the unlevered/asset beta (βa) for SalMar. This is done by creating an average beta for the peer group, which we unlever with the formula:
( ) ( ( )
After this procedure we are left with asset beta for SalMar, which in the historical period is 0.60.
To get the equity beta (βe) we now need to reliever the asset beta with the debt/equity ratio in each period using the formula:
( ( ) ( ))
After the complete equity beta calculations we see that the beta for SalMar varies between 0.67 and 0.96 with an average of 0.74 over the historical period. The beta estimations over the historical period indicate that investing in the SalMar’s equity involves less systematic risk than investing in the market portfolio (Petersen & Plenborg, 2012). This might be caused by the fact that SalMar is not directly affected by changes in oil-prices, which severely affects the OSEBX. However, according to industry analysts, OSEBX still is the best benchmark index (Bjerke & Hågensen, 2015; Molnes & Eizentas, 2015; Strat & Steffenrud, 2015; Marine Harvest, A, 2014). We conclude that SalMar is less risky than the market portfolio.
56 | P a g e
7.3.2.3. Market risk premium The market risk premium is the spread between historical returns and returns on the market portfolio and risk-free investments (Petersen & Plenborg, 2012). As the market risk premium cannot be observed in the market as a concrete number, it must be determined through research and studies. A common way to estimate the risk premium is through the ex-post approach where the differences in historical returns in the stock market and risk-free investments 50 to 100 years back in time are assessed. The idea is according to Petersen and Plenborg (2012) that historical risk premium is a reasonable indicator for the future. Another approach is the ex-ante where the consensus amongst analysts is used to find the markets risk premium. Amongst other, both Damodaran and Fernandez, provide extensive research on the market risk premium in nearly all countries in the world (Damodaran B. A., 2015; Fernandez, 2014). In addition, Damodaran and Fernandez operate only with current estimations, not historical. However, in Norway PWC in cooperation with “Norwegian Finance analytics union” publish a risk premium survey every year. We believe that the proximity to the market gives unique insights; hence we believe the survey to mirror a sound estimate. According to PWC is the market risk premium is stabile on 5% for the whole period, expect for 2012 and 2013 with respectively 5.5% and 6% (PWC, 2014).
7.3.2.4. Company-specific adjustments According to Petersen and Plenborg (2012) company-specific measures can be used to adjust for illiquidity in a stock. They argue that investors require up to 5% extra in premium for illiquidity in specific stocks. In addition, a market survey conducted in Norway indicates that investors demand a small stock premium up to 5% for companies with a market cap lower than NOK 5bn (PWC, 2014). We believe that the two measures are somewhat the same and that investors would not require an additional 10% to the market premium for stocks listed on stock exchanges. Both SalMar and their peers are trade regularly on OSE (OSE, E, 2015). However, all companies in the peer group do not have a market cap exceeding NOK 5bn in every year. Hence, a small stock premium is added for some of the companies in the peer group. These premiums can be found in the WACC calculations in appendix 8.2.
57 | P a g e
7.3.3 Cost of debt The cost of debt (rd) refers to the required return of rate debt holders need to provide debt financing for companies. There is several ways to compute rd and the required rate on NIBD consist of three variables: risk-free rate, corporate tax rate, and credit spread, which is equivalent to the risk premium on debt (Petersen & Plenborg, 2012). rd is calculated as:
( ) ( )
To gain an estimation of the borrowing rate after tax, information about the corporate tax rate is needed. The applied tax rate was 28% until 2013 when it adjusted to 27%, as described in section 7.2.1. A good proxy for credit spread can be credit rating (Damodaran, E, 2012). Another way is to look at bonds. However, as the rd calculated is for an historical period we wish to use the actual rd paid. Hence the rd is calculated as:
This calculation yields the exact rate of debt for the period hence is concluded to be superior in terms of historical use. Given the equation SalMar’s rd varies between 2.74% and 9.48% (appendix 8.2).
7.3.4. Summary cost of capital The WACC for the historical period lies between 5.58% and 8.03%. The WACC will be used in the profitability analysis in the next section.
7.4. Profitability analysis In this section we look at the historical performance of SalMar compared to its peers. Profitability is crucial to ensure a company´s survival and to satisfy shareholders return. According to Petersen and Plenborg (2012) the company’s historical profitability is an important part of defining the future expectations. To assess the profitability we perform an analysis based on the Du Pont model recommended by Petersen and Plenborg (2012) in addition we will look at some industry-specific measures for profitability.
As a general approach to profitability we will analyze the EBITDA-margin. It gives investors a clean view of a company’s core operations as it excludes depreciation and amortization (Petersen
58 | P a g e
& Plenborg, 2012). Figure 7.1 shows EBITDA-margin for SalMar and all peers, in addition to a peer average.
Figure 7.1 - EBITDA margin 40% 30% 20% 10% 0% -10% Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
From the comparison of the margins in figure 7.1 we can see that the SalMar is by far the most effective producer, which supports the findings from section 6.1 of SalMar being cost efficient. Furthermore, by comparing with the yearly average salmon price (appendix 9) we can see that the fluctuations in EBITDA margin are in line with fluctuations in the spot price. This also indicates that SalMar will perform well in other profitability measures. We observe that NRS is the least efficient producer, this can be seen in context with their organizational structure, focusing on sales from partners. By taking a closer look at the peer average, a clear cyclical pattern is detected, which was also discussed in section 3.4.
7.4.1. Economic value added The return on invested capital (ROIC) is an overall profitability measure for a company’s operations. ROIC express the return on capital invested in a firms net operating assets as a percentage. In a valuation context ROIC is a significant factor since a higher ROIC, ceteris paribus, gives a higher estimated value. The higher the ROIC, the cheaper the financing can be achieved. ROIC is calculated as (Petersen & Plenborg, 2012):
( )
When interpreting the ROIC and other ratios it is important to address both the level of returns and the development over time. The level of returns can be determined both by benchmarking compared to peers, or by comparing with the WACC. However, the development is best
59 | P a g e measured by comparing with peers (Petersen & Plenborg, 2012). Further benchmarking against peers might give details whether change in returns are firm- or industry-specific.
Figure 7.2 displays that SalMar outperforms the peer group average in all years, which was expected from the EBITDA-margin. However, the spot price was almost the same in 2008 and 2012, indicating that SalMar’s costs have increased disproportionally with harvest volume; increasing cost per KG. This can also be seen in context with the opening of InnovaMar, increasing operating expenses and salaries, without being fully operational over the period (SalMar, H, 2013) (appendix 3). We can see that industry leader MHG struggles in yielding a high ROIC even though their EBITDA-margin was solid compared to peers. However, more unexpected is NRS´s strong ROIC performance compared to EBITDA-margin. This might be explained by the hypothesis that a low level of invested capital will yield a high ROIC (Damodaran, I, 2007).
Figure 7.2 - ROIC
20%
10%
0%
-10% Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
As mentioned the level of the ROIC can be analyzed through the WACC. Figure 7.3 illustrates the relationship between ROIC and WACC for SalMar. When SalMar produce a ROIC which is higher than the WACC SalMar creates what is called above normal profit (Petersen & Plenborg, 2012). Figure 7.3 below shows that SalMar’s ROIC is above WACC in all years, indicating above normal profits.
60 | P a g e
Figure 7.3 - ROIC and WACC 25% 20% 15% 10% 5% 0%
ROIC WACC Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
If we subtract WACC from ROIC it leaves the expression Economic Value Added (EVA) (Petersen & Plenborg, 2012). In figure 7.4 SalMar’s EVA over the historical period is displayed and clearly illustrates the positive EVA in all years creating profit from operations for both equity and debt holders. EVA is calculated as:
( )
Figure 7.4 - EVA SalMar (NOK 1000) 1 000 000 800 000 600 000 400 000 200 000 0
Source: Own calculations; SalMar annual reports
7.4.2. Decomposition of ROIC As stated in the previous section ROIC measures a company’s return on invested capital in operation, however ROIC is not able to explain whether EVA is driven by a better relationship between revenue and expenses or improved capital utilization (Petersen & Plenborg, 2012). To be able to answer this, ROIC must be further decomposed into profit margin and turnover rate. The relationship between ROIC, profit margin, and turnover rate should yield the same number as the formula in the section 7.4.1 and can be described as:
61 | P a g e
7.4.2.1. Profit Margin The profit margin describes the relationship between a company’s revenue and expenses, and expresses operating income as a percent of net revenue (Petersen & Plenborg, 2012). In general, a high profit margin is attractive. The profit margin is calculated as:
( )
As we can see from figure 7.5 SalMar has a superior profit margin to their peers´, and the cyclical pattern in the industry reveal itself through the peer average yet again. A common denominator for 2008 and 2012 when the average profit margin was quite modest, are low salmon prices. In 2008 salmon traded at an average price of 26.35 NOK/KG and in 2012 it was 26.58 NOK/KG (Fishpool, 2015).
Figure 7.5 - Profit margin
20%
10%
0%
-10% Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
7.4.2.2. Turnover rate of invested capital The turnover rate expresses a company’s ability to utilize their invested capital. To find out how many days the invested capital is tied up, we divided the number of days in a year by the turnover rate. Turnover rate is defined as:
Figure 7.6 shows that NRS clearly outperforms SalMar and the rest of the peer group in terms of turnover rate. According to Petersen and Plenborg (2012), a high turnover rate is normal in service industries which do not have to make the same amount of investments. NRS business model consist to a large degree of sales from partners, explaining the low invested capital
62 | P a g e compared to peers, hence strengthening the hypothesis mentioned in section 7.4.1. SalMar and the rest of the peer group all perform on the same level.
Figure 7.6 - Turnover rate 4,00 3,00 2,00 1,00 0,00
Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
By decomposing ROIC into profit margin and turnover rate we can clearly see that SalMar’s high ROIC is driven by the profit margin. This implies that SalMar has been able to generate a higher profit than competitors despite an increase in cost per KG for the industry. SalMar has either more revenue per KG or have been handling the higher cost levels per KG better compared to peers and thus is a cost leader as discussed in section 6.1.2.
7.4.2.3. Index and common-size analysis The above analysis has provided insight about how profit margin and turnover rate have developed over time. However, both ratios are vague in the description of why they have evolved as they have. In order to understand the evolution of the ratios better, they must be decomposed further, which can be done either by indexing (trend analysis), or performing a common-size analysis (Petersen & Plenborg, 2012).
As the turnover rate remains fairly stable and we know that the industry is capital intensive, we do not wish to spend time analyzing the turnover rate further. However, index and common-size analysis of SalMar`s and the peer group`s balance sheet can be found in appendix 10.
Even though the turnover rate is fairly stable over the entire industry, the profit margin varies over time and within peer group. We wish to address this closer through a common-size analysis of the reformulated income statement, however, an index analysis is also provided in appendix 10.
63 | P a g e
In contrast to the trend analysis, the common-size scales each items as a percent of a benchmark, which is usually revenue (Petersen & Plenborg, 2012). However, we have chosen a more industry-specific benchmark (harvest volumes) for further investigation, as this gives an indication on how the performance are relative to their inputs, in addition a common-size revenue analysis can be found in appendix 10.
By conducting a common-size analysis it becomes clear that the peer group is more efficient in gaining sales revenue per KG than SalMar, this can clearly be seen in figure 7.7. The total common-size analysis can be found in appendix 10.
Figure 7.7 - Common-size: Sales revenue/KG 6000 %
4000 %
2000 %
0 %
SalMar Peers Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
We observe from figure 7.7 that SalMar has been closing the gap to their peers and trend is positive. It also becomes evident that SalMar has much lower cost per KG as can be seen in figure 7.8.
Figure 7.8 - Common-size: Operating costs/KG 4000 % 3000 % 2000 % 1000 % 0 %
SalMar Peers Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
The two figures show that the gap between SalMar and its peers, in terms of costs, is much larger than the gap in sales income. The relationship between net revenue and costs is in favor of
64 | P a g e
SalMar and the relationship gives SalMar a strong NOPAT against KG compared to the peer group. The relationship is shown in figure 7.9.
Figure 7.9 - Comon-size: NOPAT/KG 1500 %
1000 %
500 %
0 %
-500 % SalMar Peers Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
As the analysis shows, the gap between SalMar and the peers have become smaller over the period on both sales revenue and operating costs. However, as figure 7.9 illustrates, the gap between SalMar’s and the peers’ NOPAT is stabile at the same level except for 2011, this year SalMar tried to hedge against fluctuations in the spot price and ended up selling large portion of their harvest below spot price (SalMar, G, 2012).
7.4.3. Residual income While the EVA gives us an indication on how much economic profit is created for the company through operations, we will now address how value is added from the owners´ perspective. To find out how the owners´ economic profit is impacted by financial leverage we will look at profitability through residual income (Petersen & Plenborg, 2012).
While ROIC is a measurement of the invested capital, return of equity (ROE) measures the profitability taking both operating and financial leverage into account (Petersen & Plenborg, 2012), or as Damodaran (2007) describes it; the ROE ratio is a measurement of the return, after cost of debt are serviced, attributable to shareholders. The effect of interest income from cash and book value of equity (BVE) is included in the ROE whilst excluded in the ROIC. ROE is calculated as:
65 | P a g e
However there are certain factors affecting the level and trend in ROE. These are operating profitability (ROIC), net borrowing interest rate after tax (NBC), and Financial leverage (NBID/BVE). This can be shown through the relationship:
( )
The two calculations should always yield the same number, however due to reformulation in income statement and balance sheet the two calculations yields slightly different numbers. For the purpose of valuation the ROE based on operating profitability, NBC, and financial leverage will be used.
Damodaran (2007) argues that that the interest from cash and equity is polluting ROE and suggest that a non-cash ROE is created to get a clearer picture of the actual return derived from operations, this can be calculated as:
( )
The two calculations are appropriate for different purposes. If we are to compare the ratio to the riskiness of only the operating assets of the firm, the non-cash ROE is preferable. However, as we will compare ROE to the cost of equity (re), as defined by the CAPM, the traditional ROE is chosen.
As we can see from figure 7.10 below SalMar perform better on the ROE measure than the peer group in all years, and is leader in all years except 2013, when NRS had a record year with high earnings in addition to low NIBD. The historical ROE indicates that SalMar is able to generate satisfactory net income contributing to shareholder wealth.
66 | P a g e
Figure 7.10 - ROE
30%
10%
-10%
-30% Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
To further analyze the contribution to owners, we compare the ROE with re. We use re instead of WACC because the cost of debt has already been taken into consideration when calculating the
ROE (Petersen & Plenborg, 2012). By deducting re from ROE we can calculate the value added for the owners; this is defined as residual income. From figure 7.11 we can see SalMar has created value for the shareholder during all years of the historical period. Residual income is calculated as:
( )
Figure 7.11 - Residual income SalMar (NOK 1000)
900 000 700 000 500 000 300 000 100 000 -100 000
Source: Own calculations; SalMar annual reports
7.4.4. Industry-specific efficiency measures Figure 7.12 shows the relationship between enterprise value and harvest volume for the period. The parameter is common in the industry as it identifies investors’ direct exposure to the salmon market. SalMar has traded above the rest of the peer group until 2013, which considering the above analysis indicates better prospects compared to peers prior to 2013.
67 | P a g e
Figure 7.12 - EV/KG 130
80
30
-20
Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
The EV/KG multiple does however not take company profitability into account. Hence figure 7.13 below shows the companies` profitability measured in EBIT per KG harvest volume. Since the fish farming industry is recognized as a homogenous industry EBIT/KG has become an important target for analyzing companies cost efficiency (Bjerke & Hågensen, 2015; Strat & Steffenrud, 2015; Molnes & Eizentas, 2015). The figure shows that SalMar has been a cost leader in the industry for several years, with Lerøy being the closest competitor. The multiple is highly volatile due to the fluctuations in salmon prices. As the industry rivalry tightens and the players are getting closer to their MAB capacity, cost efficiency will become an important internal factor to influence competitive strength and value creation in the years to come.
Figure 7.13 - EBIT/KG 20 15 10 5 0 -5 Peer average SalMar MHG LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
Another measure of performance is efficiency in terms of utilization of licenses. Figure 7.14 that SalMar is able to produce more salmon per license than peers. However, GSF claims to hold licenses with a total capacity of 90,000 HOG, which will be fully utilized in the years to come (GSF, B, 2015). NRS can be rated in two ways because they have 35 own licenses, in addition to 47 licenses as the part of a cooperation that sell salmon for a group of partners, in addition NRS
68 | P a g e claims that they will be able to increase HOG on their 35 licenses to 45,000 tons (NRS, B, 2015). For analytical purposes the total sold HOG will be used for NRS as this reflects their income in the best way.
Figure 7.14 - HOG/License 2014 SalMar MHG LSG GSF NRS1 NRS2 Licenses 100 226 141 48 35 82 HOG 141 000 258 021 158 258 39 248 22 356 59 000 HOG/License 1 410 1 142 1 122 818 639 720 Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
7.4.5. Summary profitability analysis Overall we conclude the historical profitability and performance of SalMar to be best practice compared to the peers. The main reason for SalMar’s dominant profitability has been the cost structure where we see that SalMar is able to generate the lowest costs per KG of HOG. However, SalMar has struggled to obtain the same sales revenue per KG as peers. Their cost leadership has to some extent decreased; however, this has been offset by a trend of higher sales revenue per KG maintaining the NOPAT gap to peers constant. We have seen that SalMar performs well on industry-specific measures and that SalMar creates the highest HOG per license. As a result we believe that SalMar will continue to retain cost leadership in addition to create higher sales revenue compared to KG over the coming years, where the utilization of InnovaMar will play an important role.
7.5. Risk analysis Liquidity is a crucial subject for any business, without it a company cannot pay its bills or carry out profitable investments. The greatest influencer of liquidity risk is the company’s ability to create positive net cash flows both in the short- and long-term. Poor liquidity leads to a higher cost of debt through a self-enforcing spiral of negative effects, which in the worst case can lead to bankruptcy (Petersen & Plenborg, 2012).
This section will give a clear picture about both short- (ability to meet short term obligations) and long-term (financial health and ability to meet all future obligations) liquidity risk for SalMar and its competitors. As in section 7.4 selected ratios will be benchmarked against the peer group as well as assessing development over time
69 | P a g e
7.5.1. Short-term ratios The current ratio explains the likelihood that current assets will cover the cost of current liabilities in case of liquidation, and is defined as:
According to Petersen and Plenborg (2012), the basic idea is that the larger the ratio, the greater the likelihood that sale of current assets to be able to cover the different liabilities. Petersen and Plenborg (2012) argue that a current ratio greater than 2 is an indication of low short-term liquidity risk. However, this rule of thumb is difficult to apply between different industries, and from figure 7.15 we can see that the industry average lies between 2 and 3 for all years except 2008.
Figure 7.15 - Current ratio 5 4 3 2 1 0
Peer average SalMar MGH LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
We also observe that SalMar is amongst the top of the peers indicating that SalMar is associate with less risk than some peers.
Another variation of the current ratio, called quick ratio, excludes the impact of inventory. The basic idea is that only the most liquid current assets should be included. This is due to the fact that liquidation will probably not be at book values in the case of bankruptcy. The quick ratio is defined as (Petersen & Plenborg, 2012):
70 | P a g e
Since the quick ratio only includes the most liquid current assets it is perceived to be a relatively more conservative indicator of short-term liquidity risk (Petersen & Plenborg, 2012).
Figure 7.16 - Quick ratio 2,0 1,5 1,0 0,5 0,0
Peer average SalMar MGH LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
The quick ratio for SalMar and the peer group is illustrated in figure 7.16, and we can see that SalMar is no longer the top performer, which now is LSG. The impact of the difference between current and quick ratio indicates that a large amount of SalMar’s current assets comes from inventory, which represent unsold products, whilst LSG to a larger extent holds receivables representing future cash flows (Petersen & Plenborg, 2012). There is a clear outlier in 2013 when SalMar had a quick ratio of 1.59 due to high cash and bank deposits coming from the divestment of their shares in Bakkafrost AS (SalMar, D, 2014).
Lastly, analyzing the short-term liquidity risk we will assess the liquidity cycle. We have now assessed to what extent SalMar is able to handle their current liabilities given their current assets. The liquidity cycle assesses how many days it takes to convert working capital to cash. The liquidity cycle is calculated as:
Figure 7.17 shows that SalMar is a mid-performer, NRS is the top performer over the period, with LSG close behind. NRS’s low liquidity cycle could be due to the cooperating partnership
71 | P a g e described in section 5.3, only taking in fish they already have a contract on. However, we can also relate the low liquidity cycle to the quick ratio, indicating that LSG is able to generate cash faster than competitors due to low inventories. On the other hand we see that GSF is the worst performer indicating high inventories, this is also supported by the fact that GSF was also the worst performer in quick ratio.
Figure 7.17 - Liquidity cycle 300
200
100
0
Peer average SalMar MGH LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
7.5.2. Long-term ratios The most common indicator on long-term liquidity risk is financial leverage, which can be calculated in different ways (Petersen & Plenborg, 2012). However, as all calculations provide identical results we define financial leverage as:
Figure 5.18 illustrates the historical financial leverage of SalMar and the peer group. The more leverage, the higher long-term liquidity risk. Looking at the book values of equity and debt we find that SalMar has debt leverage almost at the same level as the average of the peers, even though there are some fluctuation from year to year they are on a stable level between 0.96 and 1.85.
72 | P a g e
Figure 5.18 - Financial leverage (book values) 2,50 2,00 1,50 1,00 0,50 0,00
Peer average SalMar MGH LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
Petersen and Plenborg (2012) argue that if market values are available they should be used, as they are closer to realizable value. Figure 5.19 shows that if we use market value of equity SalMar is the industry leader. Furthermore, we can see that the financial leverage reaches a critical period for GSF in 2008 and 2011 due to a year-end low share price (appendix 6). However, all peers hold a satisfactory level of leverage over the past three years according to both market and book values.
Figure 5.19 - Financial leverage (market values) 10 8 6 4 2 0
Peer average SalMar MGH LSG GSF NRS Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
Another measurement for long-term liquidity risk is the interest coverage ratio (ICR), which is calculated as: ( )
The ICR intends to measure a company’s ability to meet net financial expenses (Petersen & Plenborg, 2012). Moreover, the ratio tells us how many times operating profit covers the net financial expenses. Some analysts replace EBIT with cash flow from operations, as EBIT is not a
73 | P a g e cash flow, however due to the analytical purpose we believe EBIT to be sufficient in determining the long-term liquidity risk.
Figure 7.20 - Interest coverage ratio 30
20
10
0
Peer average SalMar MGH LSG GSF NRS Critical line
Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
Figure 7.20 shows that the interest coverage ratio fluctuates severely from both year-to-year and company-to-company, and in years with low salmon price some of the peers are under or close to the critical ratio. It is also important to notice that in some years the ratio was not applicable due to abnormal values. In 2009 the interest coverage ratio for SalMar was 229.03, this was mainly due to low interest-bearing debt, a falling interest rate in the period, in addition to change in value of relevant currencies (SalMar, L, 2011). In 2010 GSF had an ICR of 205.86 and NRS 5940.98. In 2010 GSF had by far their strongest financial year over the historical period (appendix 6), in addition to currency positions realized with gain leading to historical high EBIT and net financial profits. NRS also had a very profitable year (appendix 7) in addition to high financial income caused by gains from associates (NRS, 2011). Figure 7.20 show that there is no clear trend, nor consecutive market leader. However, it is worth mentioning that both SalMar and LSG never fall below an ICR of 2.
Lastly in our long-term liquidity analysis, we consider NIBD/EBITDA. This is a ratio widely recognized by analysts, and can be found in all the major investment banks´ sector publications (Bjerke & Hågensen, 2015; Molnes & Eizentas, 2015; Strat & Steffenrud, 2015). The ratio evaluates the long-term liquidity risk by assessing the time in years it takes to pay back their debt if NIBD and EBITDA are held constant. Analysts appreciate the ratio because it takes into account the company’s ability to take on more debt. The rule of thumb indicates that ratios higher than 4 or 5 indicate that the company is unlikely to be able to handle their debt as well as take on
74 | P a g e additional debt for future growth. This is only a rule of thumb and the right level should be addressed through an industry benchmark.
In addition to being a good measure for analysts The NIBD/EBITDA ratio is also used as a covenant for SalMar’s bank loans indicating that the rule of thumb is applicable for the industry. From figure 7.21 we can see that the covenant has been 4.5 except for 2011 when the banks where tightening their long-term loan terms, and in 2012 when SalMar negotiated better terms to gain more financial freedom (SalMar, H, 2013). Thus SalMar has newer broken their covenant. In addition SalMar has negotiated terms that allows having NIBD/EBITDA up to 6.0 for 3 quarters in the year (SalMar, B, 2015).
We observe that NRS and GSF have been struggling to keep their NIBD/EBITDA level under the critical line. This indicates that they have had limited opportunity to take on debt for future growth. We also note that NRS and GSF have struggled to reach constant growth in HOG such as SalMar (appendixes 3, 6 and 7). Furthermore, MHG and LSG are steady below SalMar’s covenant indicating reasonable debt levels and ability to increase debt for growth.
Figure 7.21 - NIBD/EBITDA 15
10
5
0
Peer average SalMar MGH LSG GSF NRS Critical line Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS
The risk analysis indicates that SalMar has a sound financial risk profile. We have performed a credit analysis as a sanity check. The full credit rating can be found in appendix 11 and supports the notion that SalMar has low financial risk.
7.5.3. Summary risk analysis After assessing different liquidity ratios for both short- and long-term, we conclude that the financial risk for SalMar is low. However, on a short-term basis SalMar could improve the time they use to generate cash. Still as SalMar is in no way close of a bankruptcy and we do not see
75 | P a g e any problem with this; SalMar more than satisfy all long-term debt ratios, indicating low financial risk.
7.6. Sub-conclusion The EBITDA margin indicated that SalMar would outperform the peer group in terms of financial profitability. The rest of the analysis also supports this. However, SalMar has been
suffering from less income from sales per KG than the peer group. Still, SalMar´s cost
structure is highly effective and we conclude that their financial advantage builds on a foundation of a superior cost efficiency, resulting in a higher ROIC than WACC in every year
thus EVA. SalMar should be able to increase their earnings when the InnovaMar facility is optimized and fully utilized; hence we do not believe that SalMar’s ability to create higher returns than their competitors will evaporate in any near future. Moreover, SalMar has a
steady liquidity, even though they are not a clear industry leader, they still provide sufficient liquidity resulting in low financial risk.
8. SWOT
The strategic and financial analysis has provided insight about external factors representing opportunities and threats, and internal factors representing strengths and weaknesses for SalMar. This section summarizes the key findings from the external and internal analysis.
8.1. Strengths One of SalMar´s main strengths is their cost efficiency. They have the best cost/KG ratio in the industry. They are also the industry´s leader in license utilization, meaning they harvest more fish per license than most peers. The main reason for this is that they have one of the best smolt release capabilities allowing them to release smolt year-round while others release more seasonally. These factors combined with long-term oriented ownership have made it possible for SalMar to retain strong financial statements and creating healthy returns for shareholders.
8.2. Weaknesses SalMar is fully vertically integrated in the process of producing salmon. However, feed is one of the most important input factors in salmon production. SalMar does not participate in feed production and must buy this input externally. This exposes them to the risk of fluctuation in
76 | P a g e prices and quality, which is unfortunate as feed quality has a significant impact on growth rates. This weakness is aggravated by the fact that one of SalMar´s competitors produce feed and the supplying industry is undergoing continuous consolidation increasing their barraging power. Another weakness is their lack of progress in VAP. They have unrealized VAP potential, which should have been a strength, however, they continue to struggle to realize this potential. They have invested heavily in their plant called InnovaMar, which processes salmon and produces VAP. The plant was finished and operational in September 2010 and has begun VAP production, which recent years´ sales margins illustrate. However, the potential is still not realized and their sales margins are thus lower than competitors more developed in VAP.
8.3. Opportunities The industry has historically enjoyed increasing demand and the trend seems to continue. Demand growths at a higher pace than supply thus all produced salmon are sold. Demand is driven by increased need for protein due to population growth, focus of healthy diets and enhanced image of eating salmon. Furthermore, the new MAB regime recently introduced will allow for higher MAB. Producers still have unrealized potential for higher utilization which is aided by warmer seawater temperatures; increasing growth rates and reduces the production cycle length. Lastly, the industry is still consolidating; larger players are acquiring smaller companies to grow non-organically.
8.4. Threats The volatility in prices of salmon feed ingredients remains a source of threat for salmon producers, as they pay on a cost-plus basis thus carrying all risk. The prices on agricultural ingredients are on a downward trend, while marine ingredients remain high. Biology costs related to prevention and treatment of lice and PD outbreaks is increasing and as a result reducing profits. The situation is not aided by the fact that prices on alternative sources of protein such as poultry, pork and beef are declining as their feed are not dependent on marine ingredients. Historically the salmon price has fluctuated significantly, and is now at record high levels. Prices are the main value driver of the industry and a large decline would put stress on the profitability.
77 | P a g e
Figure 8.1 - SWOT Strengths Weaknesses • Cost efficiency • No feed production • License utilization • Inferior sales margins • Year-round smolt release • Unable to realize VAP potential • Financial resources • Limited diversification Opportunities Threats • Increasing demand • Feed price • New MAB regime • Lice and PD (biology costs) • Increase license utilization • Declining prices on substitutes • Non-organic growth • Volatile sales price Source: Own research
9. FORECASTING
This section aims to answer the research question: “How will SalMar´s cash flow develop?”
In order to create pro forma income statement, balance sheet, and cash flow statement we must make forecasts. The strategic and financial analysis will serve as the basis for these forecasts. The analysis revealed that the most important factors influencing salmon farming companies are supply, demand, prices and costs related to feed and biology. To forecast these items, we have looked into the underlying drivers and made projections. We have also forecasted items related to cost of capital. Other items believed to remain stable are forecasted as an average over the historical period. There are several approaches to do this, the most common being using a percentage of sales revenue (Petersen & Plenborg, 2012). However, due to the volatility in salmon prices, we have decided to forecast these items as a percentage of harvest volume. We have chosen to forecast for the period 2015 – 2019, and for the terminal period from 2020 onwards representing a steady state. Forecasting this far into the future is difficult and anything beyond this point is too speculative in our opinion.
9.1. Supply This section will provide insight into growth factors affecting production in Norway and the forecasting is thus focused on Norwegian supply rather than global supply. The best predictors of future supply are standing biomass, feed sales, seawater temperatures, smolt release, and vaccine
78 | P a g e sales (Marine Harvest, A, 2014). In addition we consider the recently introduced new MAB regime and inflation in main markets.
The new MAB regime, mentioned in section 5.1.6, is expected to increase Norwegian supply by 3-5% annually. Figure 9.1 illustrates the development in harvest volume and change year-over- year (y-o-y) for the period 2007 to 2014. The supply growth during the period 2012 to 2014 has ranged from -3.4% to +6.2% (Bjerke & Hågensen, 2015). The Norwegian supply appears to have stabilized as it has approached 1.2 million tons in recent years, which is also the current MAB. We believe MAB and license constraints will keep cyclicality low and keep supply growth in Norway fairly stable as harvest approaches the legal limit.
Figure 9.1 - Norwegian harvest (1000 tons) and y-o-y 1 200 000 18% 1 000 000 16% 800 000 10% 600 000 6% 6% 400 000 2% 200 000 -3% 0
Source: SEB
Historically the MAB limit has not constrained production; the growth in supply was unaffected by government limitations and the industry was highly cyclical, as described in section 3.4, 5.1.6, and shown in figure 5.7. However, from 2012 the harvest volumes have approached the legal MAB limit; as mentioned, this indicates that supply will stabilize as production reaches its constraints.
9.1.1. Short-term supply The best short-term indicator of future supply is standing biomass and feed sales; in addition seawater temperatures also have a significant impact (Marine Harvest, A, 2014).
Our calculations show that y-o-y biomass is up 3.3% from 2013 to 2014 as illustrated in figure 9.2 (Akvafakta FHL, 2009 - 2015).
79 | P a g e
Figure 9.2 - Biomass (tons) and y-o-y 1 200 000 7% 1 000 000 800 000 4% 600 000 4% 3% 3% 400 000 200 000 0
Source: Akvafakta FHL
Elements affecting salmon growth rates are seawater temperatures and feed. Akvafakta assembles statistics for feed sales, the latest report show that sales are up 4% year-to-date (y-t-d) (Akvafakta FHL, 2009 - 2015). Furthermore, the seawater temperature is up 8.9% from 2013 to 2014 y-o-y and 5.6% since 2007 as shown in figure 5.6 in section 5.1.5. In sum, considering the change in biomass, the significant increase in seawater temperatures and feed sales, we estimate 4% growth in supply for 2015.
9.1.2. Medium-term supply Smolt release is a good indicator of medium-term supply as it takes up till 24 months from when smolt are released to the salmon is harvest ready, as described in section 3.1. Figure 9.3 illustrates smolt release from 2010 to 2014 and y-o-y, which was up 2.92% from 2013 to 2014. Considering the last 12 months (May to April) smolt releases were up 0.37%. Releases in April were up 9.84% y-o-y from 2014 to 2015 and up 8.27% for the period January to April (Akvafakta FHL, 2009 - 2015). However, as releases are typically cyclical through the year we put emphasis on the yearly numbers and estimate 3% supply growth for 2016.
80 | P a g e
Figure 9.3 - Smolt release (millions) 100 80 60 2010; 11% 2013; 10% 40 2011; 8% 2009; 2% 2014; 3% 20 0 2012; -7%
2010 2011 2012 2013 2014 y-o-y Source: Akvafakta FHL
All smolt are vaccinated three months prior to release and procurement takes some time. Thus can numbers for sale of vaccines serve as an indicator of supply for 2017 (Marine Harvest, A, 2014). Figure 9.4 illustrates vaccine sales from 2010 to 2014 and y-o-y, which was up 3.5% from 2013 to 2014. Considering the last 12 months (May to April) vaccine sales were up 1.9%. Sales in April were up 56.3% y-o-y from 2014 to 2015 and down 5.7% for the period January to April (Pharmaq, 2007 - 2015). Thus we also estimate 3% supply growth for 2017.
Figure 9.4 - Vaccine sales (million doses) 80 2008; 28% 2011; 28% 60 2009; 8% 40 2013; 4% 2014; 4% 2010; -1% 20 2012; -9% 0
2010 2011 2012 2013 2014 y-o-y Source: Pharmaq
9.1.3. Long-term supply Until 2012 supply growth was at the discretion of the farming companies, as described earlier. Now that standing biomass approaches the legal capacity limit issues of new licenses and license utilization largely determine supply growth. As discussed in section 5.1.6, the new license system is expected to increase supply by 3-5% annually. Further growth must come from increased license utilization. License utilization entails harvesting as much salmon as possible under the
81 | P a g e
MAB limit. This implies emphasis on growth rates, mortality, harvest weight, etc. which are all influenced by the biological environment (seawater temperatures and sanitary conditions).
We have calculated the mortality rate for each year from 2007 to 2014 and y-o-y based on data from the Directorate of Fisheries (2015). The mortality rate has come down from 15.9% in 2007 to 8.9% in 2014. Most of the decline has been achieved post 2012, which we attribute to farmers´ increased focus on biology as production has begun to approach the MAB limit. We interpret this development as increased focus on utilization only in recent years. To reflect this we have weighted the y-o-y numbers towards today. The result is a weighted average y-o-y mortality rate of -1.2%, which translates to increased supply. Lice levels are down 26% in the period January to April y-o-y from 2014 to 2015 (Sjømat Norge, 2015). There is also an increase in active cleaner fish of 9.3% y-o-y and deployment of cleaner fish increased 6.8% y-o-y (Sjømat Norge, 2015). Considering the growth from the new MAB regime and increased utilization as a result of declining mortality rate, less lice and more cleaner fish, we estimate 3.2% supply growth for 2018 and 3.5% for 2019.
9.1.4. Terminal supply When using discounted cash flow valuation methods the most important input is the terminal growth rate. Only small variations in the terminal growth rate change the terminal value significantly and the influence becomes aggravated as the rate approaches the discount rate. The terminal growth rate is constant indefinitely, which implies that it cannot be higher than growth in the economy the company operates within, as a company cannot grow forever at a higher pace than the economy (Damodaran, D, N/A).
The salmon price in the terminal period is projected to be equal to the price in the last forecasting period. The terminal growth rate is thus determined by growth in harvest in the terminal period. As we expect demand for salmon only to increase as the population and economy grow, we also assume that the salmon farming companies will grow at the same rate. The salmon farming industry is not domestically restricted rather global. However, some markets are much more important than others as described in section 5.1. We have therefore chosen to focus on these main markets. We use the historical CPI inflation as a proxy for economic growth. The terminal growth rate is calculated to be 2.01%, which is the average inflation across the main salmon markets over the period 2009 – 2014 as shown in figure 9.5.
82 | P a g e
Figure 9.5 - CPI inflation main markets (%) 2009 2010 2011 2012 2013 2014 North America -0,03 1,71 3,03 1,79 1,20 1,76 East Asia & Pacific 1,45 3,11 5,23 2,97 2,77 2,24 European Union 0,95 1,67 3,31 2,72 1,39 0,22 Norway 2,17 2,40 1,30 0,71 2,13 2,03 Average 2,01 Source: World Bank
9.1.5. Norwegian supply summary Our estimated supply growth for the period 2015 to 2020 is shown in figure 9.6. The projections are in accordance with the expected growth from new MAB.
Figure 9.6 - Supply growth Year E2015 E2016 E2017 E2018 E2019 Terminal Supply growth 4,00 % 3,00 % 3,00 % 3,20 % 3,50 % 2,01 % Source: Own research
9.2. Demand Demand is forecasted on the basis of consumption and export combined with trade and political barriers as well as socio-cultural factors.
As described in section 5.1.3, almost all major markets show promising prospects. Figure 9.7 shows consumption in main markets for the period 2008 to 2014 and 2013 to 2014 y-o-y. Demand increased across all markets from 2013 to 2014 except Russia, which decreased 9% due to the import stop mentioned in section 5.1.1 (Bjerke & Hågensen, 2015; Marine Harvest, A, 2014).
Figure 9.7 - Salmon consumption (1000 tons HOG) and 2013-2014 y-o-y 900 000 800 000 27% 700 000 19% 600 000 7% 8% 14% 12% 13% 500 000 400 000 -9% 300 000 200 000 -37% 100 000 0
2008 2009 2010 2011 2012 2013 2014 y-o-y Source: SEB; Marine Harvest
83 | P a g e
Other markets have more than compensated for the decrease in Russian consumption and import. Figure 9.8 shows Norwegian export to main markets in 2013 and 2014, in addition to y-o-y. Export to Russia decreased by 51% from 2013 to 2014. However, total Norwegian export was up 5% in the same period (Akvafakta FHL, 2009 - 2015).
Figure 9.8 - Norwegian export 1 000 000 800 000 24% 22% 11% 8% 600 000 3% 400 000 200 000 -51% 0
2013 2014 y-o-y Source: Akvafakta FHL
Figure 9.9 shows Norwegian export to main markets in January through February in 2014 and 2015, in addition to y-o-y. Even though the Russian market was unavailable to Norwegian producers, total export was up 8% for the period (Akvafakta FHL, 2009 - 2015). This illustrates that the loss of export to Russia does not represent any significant problem for Norwegian producers as other markets, especially the EU, compensate for the Russian market.
Figure 9.9 - Norwegian export 150 000 32% 25% 19% 11% 21% 100 000
50 000 -100% 0
2014 Jan-Feb 2015 Jan-Feb y-o-y Source: Akvafakta FHL
In sum, the development in consumption and export, increased need for protein as the population grows, and focus on healthy diets, all indicates increased demand in the future.
84 | P a g e
9.3. Salmon price The salmon price is the most important value drivers of the industry. Prices are historically highly correlated with the stock prices of the salmon farming companies (figure 9.10).
Figure 9.10 - Stock prices and Salmon prices 300 250 200 150 100 50 0
SalMar Marine Harvest Lerøy Grieg NRS Salmon Price Source: Yahoo Finance
The salmon price is set in equilibrium between supply and demand. However, demand has historically increased faster than supply, pushing the equilibrium upwards resulting in higher prices, which have been all-time high in recent years. We expect this trend to continue only for a limited time before supply and demand becomes more balanced as MAB approaches the limit. Figure 9.11 shows salmon prices for the period 2007 to 2014, y-o-y, and trend.
Figure 9.11 - Salmon price (NOK/KG), Global supply y-o-y and Trendline 50 18% 40 12% 30 7% 20 6% 3% 10 -2% -1% 0
Source: Fishpool
As global demand has not yet significantly restricted price development we have chosen to focus on global supply when forecasting prices. Global supply is considered, as Norwegian supply alone does not determine spot prices. This method is commonly used among analysts and is also suggested by the Industry Handbook (Bjerke & Hågensen, 2015; Molnes & Eizentas, 2015; Strat & Steffenrud, 2015; Marine Harvest, A, 2014). We compare y-o-y change in global supply with
85 | P a g e y-o-y change in salmon price, which historically show a strong correlation (Marine Harvest, A, 2014). By running a regression analysis we gain insight on demand side that can be used to assess the accuracy of the regression. As illustrated in figure 9.12, using data from 2007 to 2014 suggests that the demand growth during the period has been 10%, which is incorrect according to the historical data (Bjerke & Hågensen, 2015; Marine Harvest, A, 2014). The actual demand growth over the period has been 7.23%, which reveal that the data is skewed. The regression analysis also provides a low correlation coefficient (R²) of 0.5644, which indicates that the observed data is poorly replicated by the input (Gravetter & Wallnau, 2011). We observe that 2013 (circled) stands out and deem the regression´s weak explanatory power to be caused by 2013 being an outlier.
Figure 9.12 - Global supply change vs. Salmon price (NOK/KG) change 2008-2014 50% 45% 40% 35% 30% 25% 20% 15% y = -2,3935x + 0,2317 10% R² = 0,5644 5% 0% -5% -5% 0% 5% 10% 15% 20% -10% -15% -20% -25% Source: Own calcluations; Marine Harvest; Fishpool
However, as figure 9.13 shows, by removing 2013 the correlation coefficient becomes much stronger (R² = 0.95) and according to the new regression the demand growth over the period 2007 - 2014 has been 7-8%, which is in alignment with the historical data.
86 | P a g e
Figure 9.13 - Global supply change vs. Salmon price (NOK/KG) change 2008-2012, 2014 30%
20% y = -1,9624x + 0,1488 10% R² = 0,95
0% -5% 0% 5% 10% 15% 20% -10%
-20%
-30% Source: Own calcluations; Marine Harvest; Fishpool
The data for 2014 illustrates that demand growth and supply growth are now back to more normal levels of pre 2013. The regression without 2013 is thus used and by incorporating our supply growth estimates it provides the salmon price forecasts shown in figure 9.14.
Figure 9.14 - Salmon regression price forecasts Year E2015 E2016 E2017 E2018 E2019 Terminal NOK/KG 43,13 47,01 51,24 55,65 60,11 66,68 Source: Own calculations
As the EU by far is the largest market for salmon accounting for 70% of the Norwegian export and 44% of the global market it is natural to estimate the price in EUR and then convert to NOK. Figure 9.15 illustrates the regression analysis of y-o-y change in global supply with y-o-y change in salmon price in EUR for the same period as above (without 2013). Although we observe that the R² is now lower, this regression is merely to obtain an equation since we already have proven the correlation between price change and global supply change.
87 | P a g e
Figure 9.16 - Global supply change vs. Salmon price (EUR/KG) change 2008-2012, 2014 40% 30% 20% y = -1,8495x + 0,143 10% R² = 0,6938 0% -5% 0% 5% 10% 15% 20% -10% -20% -30% Source: Own calcluations; Marine Harvest; Fishpool
The forecasted prices using regression in EUR and prices after conversion to NOK using the latest exchange rate forecasts (DNB, 2015) are shown in figure 9.17.
Figure 9.17 - Salmon regression price forecasts after currency conversion Year E2015 E2016 E2017 E2018 E2019 Terminal EUR/KG 5,15 5,60 6,09 6,60 7,12 7,88 NOK/EUR 8,30 8,40 8,50 8,50 8,50 8,50 NOK/KG 42,77 47,07 51,80 56,14 60,53 66,94 Source: Own calculations; DNB
We believe the price growth to continue only for a limited time, as mentioned above. This is based on the belief that the MAB limit will soon begin to stabilize supply and we expect to see a more balanced relationship between supply and demand, as mentioned in section 9.1, and thus prices will level out.
Prices of alternative sources of protein are influenced by feed prices. Feed represents a vast majority of costs related to production of alternative sources of protein such as poultry, swine, and cattle (Bjerke & Hågensen, 2015). Prices for feed ingredients for these protein sources are on a downward trend as shown in section 5.1.2 and illustrated in figure 5.3. As prices for these feed ingredients are declining we assume that the feed prices for alternative sources of protein will follow.
Salmon feed does not benefit from this decline in the same manner as feed for alternative protein sources. Even though salmon feed consists of many of the same ingredients, it also contains a significant proportion of marine ingredients (14% fish meal and 9% fish oil) (Marine Harvest, A,
88 | P a g e
2014). As figure 5.3 in section 5.1.2 illustrates, prices on these commodities are remaining high. We therefore assume that salmon feed prices are not declining at the same rate as feed for substitute protein sources. Based on this assumption we predict that the sales prices for other protein sources will decline creating a more challenging competitive environment for salmon in terms of price.
EU is by far the largest market and very price sensitive, as mentioned in section 5.1.3. Price sensitivity, combined with expectations of price decline in alternative sources of protein, indicate that salmon prices cannot continue to increase indefinitely. The situation is also aggravated by a strengthening EUR/NOK (Takla, 2015). We therefore deem the salmon prices calculated by regression unsustainable. This notion is supported by prof. Ragnar Tveterås, who makes the argument that expectations of prices above 40 NOK/KG in the long run are unsustainable. He reasons that it would not be possible for retailers in Europe to reflect such prices and still make profits as customers would chose alternative products. Retailers would discontinue marketing salmon, which inevitably would result in a price drop. (Berg, 2013)
We are confident in the regression analysis in the short run and estimate a price of 42.77 NOK/KG for 2015. However, we are hesitant to extrapolate the regression indefinitely, as prices in recent years have been all-time highs, and in the light of the arguments presented above. We believe that we will see a price decline post 2015, which is in accordance with the forward prices shown in figure 9.18.
Figure 9.18 - Salmon forward prices Year E2015 E2016 E2017 E2018 E2019 Terminal NOK/KG 39,27 40,60 38,70 35,60 35,60 35,60 Source: Fishpool
In conclusion, we project spot prices to increase in 2015 before declining until 2018 and then stabilizing at what we believe is a sustainable price as shown in figure 9.19.
Figure 9.19 - Salmon price forecasts Year E2015 E2016 E2017 E2018 E2019 Terminal NOK/KG 42,77 40,60 38,70 38,00 38,00 38,00 Source: Own calculations
89 | P a g e
9.4. Costs As the Norwegian farming industry is approaching the MAB, costs become increasingly important to remain profitable. Figure 5.20 illustrates the cost distribution in salmon production according to data from the Directorate of Fisheries (2015). Feed and the category “other”, which contain biological factors, account for the largest costs; together they represent 67% of total production costs. They are also historically the main drivers of cost inflation, growing at a higher pace than other costs. Thus feed and biology are the main focus of our cost forecasting.
Figure 9.20 - Production cost distribution (NOK/KG HOG) 12 10 8 6 4 2 0
2008 2009 2010 2011 2012 2013 Source: Directorate of Fisheries
9.4.1. Feed costs Feed costs are driven by prices on the underlying commodities as explained in section 5.1.2. Several salmon farming companies stated in their annual reports that they expect a rise in feed cost of NOK 1 per KG feed (LSG, B, 2015; Marine Harvest, B, 2015; SalMar, B, 2015). This translates to an increase of NOK 1.2 per KG salmon using the feed conversion ratio explained in section 3.2.
We have used the feed composition ratios for ingredients described in section 5.1.2 in order to compile a basket of salmon feed. Figure 9.21 illustrates the price development of salmon feed since 2005.
90 | P a g e
Figure 9.21 - Basket of salmon feed (NOK/Ton) and Trendline 7 000 6 000 5 000 4 000 3 000 2 000 1 000 0
Source: Indexmundi
As discussed in section 5.1.2, prices of agricultural commodities are declining. However, marine feed ingredients such as fish meal and fish oil remain high. This implies that a basket of salmon feed does not benefit significantly from agricultural price declines and we observe that salmon feed remains costly and on an upwards trend. However, feed prices cannot increase indefinitely. We forecast a cost increase related to feed of 2 NOK/KG in 2015 and 0.5 NOK/KG in 2016.
9.4.2. Biological costs Biological costs relate mainly to actions taken to treat and prevent lice and PD outbreaks. As discussed in section 5.1.5, the average seawater temperature is rising resulting in a more challenging farming environment with higher sanitary costs as lice outbreaks are associated with higher temperatures. However, as of now the level of lice is below the government limit of 0.5 and the trend is downwards (Sjømat Norge, 2015) as illustrated in figure 9.22.
Figure 9.22 - Adult female lice and Legal limit requirement 0,8 0,6 0,4 0,2 0,0
2009 2010 2011 2012 2013 2014 2015 Source: Sjømat Norge
Keeping the lice level low means intensive treatments, which are costly. Lerøy estimated in their Q4 report that sea lice treatments alone could be NOK 1-5 per KG depending on region (LSG, C, 2014). Marine Harvest has stated that 1/6 of its operating costs or NOK 5 per KG is used to treat 91 | P a g e diseases (Norne Securities, 2015). SalMar states that their production costs are increasing as a result of greater biological challenges particularly related to fighting lice, and expect higher cost per harvested KG in 2015 (SalMar, B, 2015). To fight lice outbreaks the salmon farmers have increased the use of cleaner fish and number of treatments (Sjømat Norge, 2015).
2014 was the worst year so far in terms of PD outbreaks, and outbreaks are expected to continue at the same levels in the foreseeable future according to the Norwegian Veterinary Institute (Gjevre & Jansen, D, 2014). We believe costs related to biological challenges will level out as the industry will build knowledge and mitigate the situation. We forecast a cost increase related to biology of 1 NOK/KG for 2015 and 1 NOK/KG for 2016.
In sum, due increased costs related to feed and biology we forecast costs to increase by 3 NOK/KG in 2015 and 1.5 NOK/KG in 2016 for the Norwegian salmon farming industry.
9.5. Pro forma financial statements After forecasting the main value drivers we have acquired the necessary insight to create pro forma financial statements to be used in the valuation. The construction of these follows the setup suggested by Petersen and Plenborg (2012). The complete pro forma income statement, balance sheet and cash flow statement can be found in appendix 12.
9.5.1. Pro forma income statement
9.5.1.1. Revenue We have considered SalMar´s historical harvest volumes, the Norwegian growth estimates, and company-specific capabilities to forecast SalMar´s harvest volumes. SalMar is self-sufficient in smolt production and, in contrast to several competitors; SalMar has adequate capacity to produce smolt in order to grow their harvests. Furthermore, SalMar has the unique ability to release smolt throughout the year while other producers release smolt more seasonally (SalMar, I, 2015).
Historically the total Norwegian harvest volume has grown each year. Some producers have had both increases and decline y-o-y, while SalMar´s volumes have only increased (appendix 3); we assume this will be the case also in the future. Furthermore, we assume that SalMar will be able to trade in old licenses in order to obtain new green licenses, which will increase their capacity,
92 | P a g e without triggering antitrust deprecations. Figure 9.23 shows our forecast for SalMar´s harvest volumes.
Figure 9.23 - SalMar harvest volume (tonns) E2015 E2016 E2017 E2018 E2019 Terminal 161 766 167 428 173 288 179 699 186 887 190 643 Source: Own calculations
We have calculated SalMar`s historical sales price by dividing their sales revenue by harvest volume. We assume that all harvested salmon is sold as it has in the historical period (Marine Harvest, A, 2014). The premium over spot prices is then calculated as the difference between sales prices and spot prices. We observe that the premium has been significantly greater since 2010, which we attribute to the opening of the InnovaMar processing plant, which produces VAP products on a much lager scale than pre 2010. As discussed in section 7.4.2.3, SalMar has historically generated lower revenue per KG harvested; we believe this stems from their inability so far to realize all VAP potential at their new plant, thus lagging behind some peers in terms of sale premiums. However, the trend for SalMar is positive and they are approaching the peer average in sales price (section 7.4.2.3). The premium has differed from year to year and we have thus chosen to use a weighted average over the historical period with emphasis post 2010. The result is an average sales premium of 15.87% on spot prices, which is assumed to be constant over the forecasting horizon and in the terminal period. Our projections for SalMar`s sales prices are shown in figure 9.24.
Figure 9.24 - SalMar sales prices (NOK/KG) E2015 E2016 E2017 E2018 E2019 Terminal 49,56 47,04 44,84 44,03 44,03 44,03 Source: Own calculations
Sales revenue is obviously a function of sales price and volume and is estimated in accordance with our explicit forecasts. Other operating revenues and income from associated companies represent only a small share of net revenue; these are calculated as a percentage of harvest volume and forecasted merely as an average over the historical period. As SalMar is only involved in production of salmon we assume that also these revenue items can be connected to harvest. Our forecast for SalMar`s net revenue is shown in figure 9.25.
93 | P a g e
Figure 9.25 - Net revenue forecast E2015 E2016 E2017 E2018 E2019 Terminal Sales revenue 8 016 514 7 876 640 7 770 810 7 912 572 8 229 075 8 394 456 Other operating revenues 31 730 32 841 33 990 35 248 36 658 37 394 Income from associated companies 139 464 144 345 149 397 154 925 161 122 164 360 Net revenue 8 187 708 8 053 826 7 954 197 8 102 744 8 426 854 8 596 210 Source: Own calculations
9.5.1.2. Costs Our cost forecast for SalMar is based on 2014 costs per KG as the historical average does not reflect their increased focus on VAP in recent years. SalMar is the industry`s cost leader and they have historically significantly lower costs per KG harvested than its peers, in addition to having the best HOG/license ratio as described in section 7.4.2.3. We believe SalMar will be able to retain this position and that they are better equipped than its peers to face the challenges arising from increased costs related to feed and biology described in section 5.1.5 and 9.4. Figure 9.26 shows our forecast for SalMar´s cost per KG. We estimate an increase in costs in 2015 of 2 NOK/KG related to feed and 1 NOK/KG related to biology. We expect costs to increase in 2016 by 0.5 NOK/KG related to feed and 0.5 NOK/KG related to biology. All other costs items are expected to remain on 2014 levels. We assume costs per KG will level out after 2016 and remain stable as SalMar already made the necessary investments to handle larger harvest volumes thus operate with excess capacity.
Figure 9.26 - SalMar cost forecast (NOK/KG) 2014 E2015 E2016 E2017 E2018 E2019 Terminal Change in stock 1,05 1,05 1,05 1,05 1,05 1,05 1,05 Cost of goods sold -21,56 -23,56 -24,06 -24,06 -24,06 -24,06 -24,06 Salaries and payroll expenses -4,59 -4,59 -4,59 -4,59 -4,59 -4,59 -4,59 Other operating expenses -7,38 -8,38 -8,88 -8,88 -8,88 -8,88 -8,88 Forecasted total operating cost -32,48 -35,48 -36,48 -36,48 -36,48 -36,48 -36,48 Source: Own calculations
9.5.1.3. Depreciation and write downs Depreciation of PPE and write-downs are calculated as a percentage of non-current assets. We expect these percentages to remain at the same level as in 2014 as there are no indications that they will increase disproportionally to non-current assets. There are no major investments scheduled during the forecasting horizon.
94 | P a g e
9.5.1.4. Tax core operations Tax on core operations is calculated as a percentage of EBIT and forecasted as an average over the historical period.
9.5.2. Non-core operations Interest income, financial income and other financial expense are calculated as a percentage of NIBD and forecasted as an average over the historical period.
Interest expenses are calculated as a percentage of NIBD and are forecasted as an average of SalMar´s historical cost of debt as well as a credit analysis. The credit analysis is performed in accordance with Petersen and Plenborg (2012) and can be found in appendix 11.
Fair value adjustment of biomass, onerous contracts, exceptional biological items, and non- recurring gains are not forecasted, as these items are highly volatile, transitory (non-recurring) and should be removed for valuation purposes according to Petersen and Plenborg (2012) thus, earnings measures only permanent items as described in section 7.2.2.
9.5.3. Pro forma balance sheet Non-current assets, current assets, non-interest-bearing debt, and equity are all calculated as a percentage of harvest volume and forecasted as an average over the historical period.
NIBD is calculated as a percentage of invested capital and forecasted as an average over the historical period.
9.5.4. Pro forma cash flow statement Figure 9.27 shows the pro forma cash flow statement, which is based on the forecasted income statement and balance sheet. We assume all free cash flow to equity will be paid out as dividends.
95 | P a g e
Table 9.27 - Pro forma cash flow statement E2015 E2016 E2017 E2018 E2019 Terminal NOPAT 1 669 490 1 275 158 1 025 961 951 664 989 731 1 009 621 Depreciation of PP&E 277 325 287 032 297 078 308 070 320 393 326 832 Write downs 2 413 2 497 2 584 2 680 2 787 2 843 Change in net operating working capital 338 245 -57 626 -59 643 -65 257 -73 159 -38 227 CAPEX -310 596 -481 476 -498 327 -528 118 -566 867 -457 008 Free cash flow to firm (FCFF) 1 976 877 1 025 585 767 654 669 039 672 885 844 061 Change in net interest-bearing debt 497 488 97 938 101 366 110 909 124 338 64 970 Net financial profit/loss 189 316 230 251 238 310 246 651 255 777 266 008 Tax non-core operations (tax shield) -51 115 -62 168 -64 344 -66 596 -69 060 -71 822 Free cash flow to equity (FCFE) 2 612 566 1 291 607 1 042 986 960 003 983 940 1 103 217 Dividends -2 612 566 -1 291 607 -1 042 986 -960 003 -983 940 -1 103 217 Cash surplus 0 0 0 0 0 0 Source: Own calculations
9.6. Cost of capital Several elements affecting cost of capital have been forecasted to be different from the historical period. We have therefore decided to calculate a new WACC, which will be used for discounting cash flows in the forecasting horizon and terminal period. All WACC calculations including beta estimates can be found in appendix 13.
9.6.1. Cost of equity Cost of equity is calculated using the same equation as in section 7.3.2, and determined to be
6.70% for the forecasting horizon, and 8.44% in the terminal period (as rf is estimated to 3.39% in the steady state). It is worth noting that we do not add any company specific liquidity or small company premiums, as we do not have any reason to expect SalMar´s market value to decrease to a level where it becomes relevant, furthermore, the calculations are based on book values which are historically lower than market values. The following sections will provide the reasoning behind the forecasted cost of equity.
9.6.1.1. Risk-free rate As in the historical period, we have used 10-year Norwegian government bonds as a proxy for the risk-free rate. The rates on these bonds have dropped from 4.78% in 2007 to 2.52% in 2014 and the average over the historical period has been 3.39%. The rate had a falling trend in 2014 and ended on 1.61 (Norges Bank, 2015). We believe the historical average is a weak indication of future development. Analysts predict that the rate of Norwegian government bonds will be 1.65% on average for 2015 (Trading Economics, 2015). We share their belief and also forecast that the
96 | P a g e rate will remain steady throughout the forecasting period. However, in the terminal period, which represents an indefinite steady state, a rate of 1.65% is too low considering the fluctuations over the past 20 years. We forecast a rate of 3.39% for the terminal period, which is the average over our historical period (2007 – 2014).
9.6.1.2. Systematic risk In the historical beta analysis we used a bottom-up approach for estimating beta as the one of the main purposes of the historical financial analysis was to compare SalMar to the peer group. For the future we believe a regression beta yields a more firm-specific measure of risk.
We have produced a regression analysis as described in section 7.3.2.2. The result provided a raw beta of 0.62, as shown in figure 9.28, for a regression summary see appendix 13.1.
Figure 9.28 - Beta regression analysis 0,30
0,25
y = 0,6192x + 0,0154 0,20 0,15
0,10
0,05 OSEBX 0,00 -0,30 -0,25 -0,20 -0,15 -0,10 -0,05 0,00 0,05 0,10 0,15 0,20 -0,05
-0,10
-0,15
-0,20
-0,25 SALM Source: Own calculations; OSE
The raw beta is then adjusted using the same method Figure 9.29 - Regression beta as discussed in section 7.3.2.2, resulting in an SALM OSEBX Variance of returns 0,0079 0,0043 adjusted levered beta of 0.75. The beta was then Standard deviation of returns 0,0890 0,0656 unlevered, which yielded a beta of 0.6 (figure 9.29). Correlation (SALM, OSEBX) 0,4566 Raw beta by regression 0,6192 This is almost identical to the bottom-up unlevered Post-regression adjusted beta beta giving confidence in both. The unlevered beta is Bloomberg adjustment factors 0,3333 0,6667 SalMar adjusted beta 0,7461 re-levered for each year of the forecasting period and Corporate tax rate (average) 27,75 % the terminal period. However, since our debt/equity Average debt/equity 0,3461 Unlevered regression beta 0,5969 Source: Own calculations; OSE 97 | P a g e ratio is equal in all periods, the levered beta is also constant at 0.88. As a second sanity check we have done a fundamental beta analysis in accordance with Petersen and Plenborg (2012), which can be found in appendix 13.1. The fundamental analysis suggests that SalMar has a neutral risk profile, thus a beta of between 0.85 and 1.15 is appropriate, which is an interval our estimate fall comfortably within. Thus we forecast SalMar´s beta to be 0.88 in each forecasting period and the terminal period.
9.6.1.3. Market risk premium For the historical period the market risk premium was set to exact historical rates in accordance with information gathered by PWC (PWC, 2014). However, looking forward we use Damodaran´s estimate of 5.75% as his research is the most recent and provides a better match to the average over last three years (Damodaran, C, 2015).
9.6.2. Cost of debt Cost of debt for the historical period was calculated according to SalMar´s reported numbers, providing actual cost of debt for each year. Looking forward we have used the interest rate described in section 9.2.2 providing a cost of debt of 5.21% throughout the forecasting period and the terminal period.
9.6.3. Capital structure Capital structure is estimated using ratios from the pro forma balance sheet, as market values are not available. These provide a constant equity ratio of 60.76% and debt ratio of 39.24%, thus a debt-to-equity ratio of 64.59%, throughout the forecasting horizon and terminal period. This is derived from the choice of forecasting model, which forecast debt and equity as a percentage of harvest volume, thus the ratios are constant.
9.6.4. Corporate tax rate The corporate tax rate in Norway is 27% and we expect this rate to remain stable throughout the forecasting period and the terminal period as there has been few adjustments historically (KPMG, 2015).
9.6.5. Summary cost of capital We forecast SalMar´s WACC to be 5.56% throughout the forecasting period and 6.62% in the terminal period. The WACC calculation can be found in appendix 13.2.
98 | P a g e
9.7. Sub-conclusion We forecast larger supply throughout the forecasting horizon as a result of increased license utilization, increased growth rates, improved biological conditions and the new MAB regime.
We also expect demand to increase as consumption and export rise, driven by demand for protein and focus on healthy diets. We predict salmon prices to increase in 2015, before declining until 2018 and then leveling out at a sustainable price. We expect costs to increase,
driven by higher feed prices and biology costs related to fighting lice and PD. The pro forma income statement will result in an increased NOPAT for 2015, before declining; yet indicate healthy profits throughout the forecasting horizon and terminal period. The pro forma balance
sheet will remain strong with a low NIBD/EBITDA ratio. The pro forma cash flow statement results in positive cash flow for each year in the forecasting horizon and the terminal period. We forecast SalMar´s WACC to be stable at 5.56% in the forecasting horizon and 6.62% in the terminal period.
10. VALUATION
This section aims to answer the research question:
“What is SalMar´s share price according to theory?”
“The value of any asset (or liability for that matter) is calculated as the future income generated by the asset discounted to present value with a discount factor which takes into consideration the time value of money and risk associated with the income generated by the asset.” (Petersen & Plenborg, 2012, p. 208)
Performing a valuation is a complex task and it is essential to understand the technical issues of a valuation as the modeling require a high level of understanding related to the industry drivers, and the company specific measures influencing future cash flows (Petersen & Plenborg, 2012).
There are several approaches to a valuation. However, as described in section 2.1 we have chosen the present value approach in addition to a relative valuation based on multiples to ensure that the findings from the present value models are sound. All valuation calculations are based on the forecasts in section 9.
99 | P a g e
10.1. Present value approach The present value estimate the fundamental value of SalMar based on our projection of the cash flows from section 9.2.4 and the discount factor estimated in section 9.3. There are a wide variety of present valuation models. We have chosen the discounted cash flow approach and the excess return approach as explained in section 2.1.
10.1.1. DCF valuation The discounted cash flow model is by far the most popular of the present value approaches and is widely adopted by analysts and researchers (Petersen & Plenborg, 2012). We have chosen the enterprise value approach, which base the value of SalMar on the free cash flow to the firm (FCFF), which is calculated as:
In the formula NOPAT is the net operating profit after tax, ∆NWC is the change in net working capital, and ∆CAPEX is the changes in capital expenditures. The FCFF are merged into the two staged discounted cash flow model which is calculated according to Petersen and Plenborg (2012) as:
∑ ( ) ( )
The first step of the model calculates the enterprise value for the forecasting horizon; the second part of the formula calculates the value for the terminal period and is referred to as Gordon growth model where the g represents the constant growth rate for the terminal period (Petersen & Plenborg, 2012). Output from the DCF calculations can be seen in figure 10.1. SalMar has positive cash flows in both the forecasted period and the terminal period; this is a good fit with the financial analysis in section 7.4 predicting a sustainable economic future, in addition to the fact that the cyclical pattern is beginning to diminish as discussed in section 9.1. The formula above discounts all cash flows by the WACC calculated in section 9.3. Furthermore, it assumes that all cash flows occur at the end of the year by equal contribution of each day through the year. Thus the possibility of adjusting for revenue occurred from December 31st to our cut-off date of May 1st (121 days). This is achieved by applying the formula:
( ) 100 | P a g e
NIBD is extracted from EV to get the market value of equity, which is then divided by number of shares outstanding to get the theoretical share price of NOK 145.62. This represents an upside of 29% compared to the actual share price of NOK 112.50 on May 1st 2015 (OSE, F, 2015).
Figure 10.1 - Discounted cash flow E2015 E2016 E2017 E2018 E2019 Terminal Free cash flow to firm (FCFF) 1 976 877 1 025 585 767 654 669 039 672 885 844 061 WACC 5,56 % 5,56 % 5,56 % 5,56 % 5,56 % 6,62 % Discount factor WACC 0,95 0,90 0,85 0,81 0,76 Present value of FCFF to firm 1 872 672 920 314 652 547 538 740 513 276 Present value of FCFF in forecasting horizon 4 497 549 Growth terminal period 2,01 % Present value of FCFF in terminal period 13 967 271 Estimated value of enterprise 31/12/2014 18 464 820 Days since 31/12/2014 121 Enterprise value adj for revenue occured medio 18 799 289 NIBD primo 2 300 747 Estimated market value of equity 16 498 542 Shares outstanding (x1000) 113 300 Share price 1/5/2015 145,62 Source: Own caluclations; Petersen and Plenborg (2012)
As we can see from figure 10.1 the majority of the EV (76%) comes from FCFF in the terminal period. This is result of the terminal period reflects that the majority of the returns from holding a stock infinitively come from price appreciation (Damodaran, H). The higher value from the terminal period, the more uncertainty regarding the estimates. However, in accordance with Damodaran, we believe our estimates to be fair.
10.1.2 EVA valuation The economic value added model builds on the excess return approach, which according to Petersen and Plenborg (2012) has gained increasing attention from researchers and analysts recently. In contrast to the DCF model, the EVA model relies on accrual accounting data (Petersen & Plenborg, 2012). However, the two models are technically equivalent, hence should yield the exact same value if performed correctly. To obtain an EV the EVA is calculated as:
101 | P a g e
In the same way as the FCFF in the DCF, the EVA is merged into the two-stage model, which is calculated according to Petersen and Plenborg (2012) as:
∑ ( ) ( )
The model uses the invested capital from the last fiscal year as a starting point, before the present value of all future EVAs are added. In addition we can see that the second part of the formula is Gordon growth model, the same as the DCF. The output from the EVA is shown in figure 10.2. The EVA model also yields positive numbers in all periods and the exact same estimated share price of NOK 145.62, which is found by adding the invested capital primo with the present value from both the forecasting horizon and the terminal period. The same approach as with the DCF is applied to adjust for revenue occurred medio to arrive at a share price on May 1st 2015.
Figure 10.2 - Economic value added E2015 E2016 E2017 E2018 E2019 Terminal NOPAT 1 669 490 1 275 158 1 025 961 951 664 989 731 1 009 621 Invested capital primo 7 438 024 7 130 637 7 380 209 7 638 517 7 921 142 8 237 987 WACC 5,56 % 5,56 % 5,56 % 5,56 % 5,56 % 6,62 % Cost of capital 413 890 396 785 410 673 425 046 440 773 545 307 Economic value added (EVA) 1 255 600 878 373 615 288 526 618 548 958 464 315 Discount factor WACC 0,95 0,90 0,85 0,81 0,76 Present value of EVA 1 189 415 788 212 523 028 424 056 418 744 Invested capital primo 7 438 024 Present value of EVA in forecasting horizon 3 343 455 Growth terminal period 2,01 % Present value of EVA in terminal period 7 683 340 Estimated value of enterprise 31/12/2014 18 464 820 Days since 31/12/2014 121 Enterprise value adj for revenue occured medio 18 799 289 NIBD primo 2 300 747 Estimated market value of equity 16 498 542 Shares outstanding (x1000) 113 300 Share price 1/5/2015 145,62 Source: Own caluclations; Petersen and Plenborg (2012)
As opposed to the DCF model, only 42% of the enterprise value comes from the terminal period in the EVA model. This implies that the EVA model is less sensitive to the terminal period compared to DCF. This is because the model´s base is invested capital where most of the value is created and only excess returns are added (Petersen & Plenborg, 2012). This makes the EVA model less sensitive to growth estimates changes, and complements the findings from the DCF as the two models yield the exact same price.
102 | P a g e
10.2. Relative valuation approach Valuations based on multiples are different from discounting future cash flows or excess returns. This method builds on comparing a company to peers using different parameters; hence the name relative valuation. The method is commonly used by analysts due to its low level of complexity and high speed. In reality, performing a high quality relative valuation with multiples is both quite complicated and time consuming, as differences in accounting policies and special items must be accounted for (Petersen & Plenborg, 2012). The DCF and EVA methods build on our forecasts thus largely reflective of our expectations. Relative valuations are, in contrast, based on market and book values, which makes this method a good supplement to our present value models.
Different multiples are used to value the total enterprise and to value equity (Petersen & Plenborg, 2012). We have chosen to use both enterprise value-based and equity value-based multiples. Figure 10.3 show the strengths and weaknesses of the multiples used.
Figure 10.3 - Multiple characteristics Multiple Strenghs Weakness Unaffected by capital structure Disregards costs EV/Sales Unaffected by accounting policies May be biased (e.g. discounts to boost sales)
Unaffected by capital structure EV/EBITDA Close to cash flows from operations Non-recurring items must be adjusted Unaffected by differences in depreciation and tax
Unaffected by capital structure Biased to differences in depreciation EV/EBIT Unaffected by taxes Non-recurring items must be adjusted
Biased to differences in taxes EV/NOPAT Unaffected by capital structure Non-recurring items must be adjusted Investments must be adjusted
Indicates if earnings are above cost of capital M/B Affected by capital structure Classification of assets and liabilities irrelevant
P/E Classification of income and expenses irrelevant Affected by capital structure Source: Petersen and Plenborg (2012)
In a perfect world all companies used in a multiple analysis should have the same economic characteristics and outlook, accounting policies, and exclude transitory items. When using equity- based multiples the companies should also have identical expected growth rates, cost of capital and profitability. Furthermore, when using EV/EBIT-multiples, the companies should also have
103 | P a g e the same tax rate, EV/EBITDA requires equal depreciation rate, and EV/sales requires identical EBITDA-margins. However, all these requirements are seldom met in reality and multiples are still used, and should thus be interpreted with care (Petersen & Plenborg, 2012). We acknowledge that not all requirements are met in our case, still we feel confident that the members of our peer group are similar enough to provide sound results. This is also supported by analysts` use of the same peers (Bjerke & Hågensen, 2015; Strat & Steffenrud, 2015; Molnes & Eizentas, 2015). We have used multiples based on historical numbers as well as future estimates as “a valuation based on forward looking information yield on average more accurate value estimates.” (Petersen & Plenborg, 2012, p. 243). Figure 10.4 shows multiples for 2014 and estimates for 2015.
Figure 10.4 - Multiples Enterprise value-based multiples Equity value-based multiples EV/Sales EV/EBITDA EV/EBIT EV/NOPAT M/B P/E 2014 E2015 2014 E2015 2014 E2015 2014 E2015 2014 E2015 2014 E2015 MHG 1,84 1,91 8,79 9,67 10,79 12,53 16,30 11,41 2,57 2,24 40,21 13,76 LSG 1,19 1,20 6,66 7,49 7,97 10,17 10,48 9,06 1,61 1,72 11,76 10,97 GSF 1,77 0,99 9,75 7,94 13,74 12,12 17,39 11,25 1,39 1,30 22,32 13,01 NRS 1,29 1,12 14,83 9,19 18,15 13,50 19,84 11,43 2,69 2,77 10,15 17,41 Median 1,53 1,16 9,27 8,57 12,27 12,33 16,85 11,33 2,09 1,98 17,04 13,39 Harmonic mean1,47 1,23 9,22 8,48 11,56 11,95 15,11 10,68 1,90 1,85 15,80 13,42 SALM 2,10 1,94 6,68 6,35 7,62 7,17 10,25 9,31 2,48 2,94 10,49 7,05 Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS; Bloomberg
SalMar`s EV/Sales multiples for both 2014 and E2015 are above the median and harmonic mean implying that they are either currently overpriced or have better prospects than peers. Our financial analysis proved that SalMar generates less revenue per KG than its peers; still they have a high enterprise value, boosting this multiple. We have discovered that SalMar is the industry´s cost-leader. This multiple does not consider cost structure and are therefore less explanatory for SalMar´s value. However, SalMar`s EV/EBITDA, EV/EBIT and EV/NOPAT multiples are below the median and harmonic mean implying underpricing. We believe that the market has not acknowledged SalMar`s cost effectiveness and capability to create value even on low revenue per KG and that the company is thus undervalued and trading at a discount (Petersen & Plenborg, 2012).
104 | P a g e
The equity based multiple M/B for SalMar is above 1 in both 2014 and E2015, which implies that that they earn a return above its cost of capital and are therefore traded above its book value of equity. We also observe that SalMar`s M/B is above both the median and harmonic mean and that they are expected to outperform all peers on this parameter in 2015; indicating a superb ability to create value for equity holders which is also supported by our financial analysis. The P/E implies what the market is willing to pay for earnings but also reflect growth expectations. SalMar`s P/E ratio is under the median and harmonic mean in both periods, which implies that the market is expecting other peers to have better growth prospects and that they are willing to pay more for peers‘ earnings (Petersen & Plenborg, 2012).
Multiples can also be used to illustrate stock prices and test results from present value models (Petersen & Plenborg, 2012). For valuation purposes the harmonic mean multiples are used to smooth out the peer group multiples in order to avoid the impact of extreme values. This is according to Petersen and Plenborg (2012) generally supported by research, for instance by Baker and Ruback (1999), who argue that “the harmonic mean generates more accurate value estimates than multiples based on mean, median, and value-weighted mean.” (Petersen & Plenborg, 2012, p. 234). The multiples yield different stock prices (figure 10.5). The 2014 prices are based on our financial analysis whilst the 2015 prices are based on Bloomberg estimates.
Figure 10.5 - Relative valuation based on multiples Enterprise value-based multiples Equity value-based multiples EV/Sales EV/EBITDA EV/EBIT EV/NOPAT M/B P/E 2014 E2015 2014 E2015 2014 E2015 2014 E2015 2014 E2015 2014 E2015 Stock price 72,56 62,12 162,99 158,49 181,23 203,94 195,84 157,43 86,16 70,88 169,46 214,06 Source: Own calculations; annual reports: SALM; MHG; LSG; GSF; NRS; Bloomberg
The EV/Sales yields a low price. As mentioned above, we do not put much emphasis on this due to the low explanatory power of this multiple. The other enterprise-based multiples yield prices above the present value models. EV/EBITDA provides the price closest to the present value models. This is the multiple closest to cash flows from operations which also includes costs. In contrast to EV/EBIT and EV/NOPAT, EV/EBITDA eliminates the effects of differences in depreciation and taxes, making it the most accurate multiple as these characteristics differ across companies. The equity multiples also have a large spread; the M/B yields a low price indicating
105 | P a g e that SalMar has a higher book-to-market value ratio than its peers. The P/E ratio provides a high price because the market is willing to pay more for peers´ earnings and growth.
In sum the multiple analyses demonstrates that SalMar is currently undervalued thus trading at a discount with a large spread in prices, averaging at NOK 144.60.
10.3. Sensitivity and scenario analysis Valuations based on discounted cash flows are depended on our projections. It is useful to perform both a sensitivity analysis and scenario analysis as only small changes in the projections may have significant impact on the estimated value.
10.3.1. Sensitivity analysis Valuation estimates based on the present value approach is sensitive to changes in the key value drivers, especially the variables in the terminal period are sensitive due to the assumption of perpetuity. Hence a valuation should always be accompanied by a sensitivity analysis of changes in the key value drivers (Petersen & Plenborg, 2012).
As identified through the strategic analysis the key value drivers are salmon price, cost per KG, and harvest volumes. We analyze how the stock price is affected by changes in cost per KG and sales price in the terminal period. In the terminal period, harvest volume is determined by the terminal growth rate and it is therefore useful to consider the result of changes in this rate. From the financial analysis we found the WACC to be of great importance and the fact that it is used to discount the cash flows indicates that changes in WACC also should be considered together with the other parameters in the sensitivity analysis. To ensure that WACC range in our sensitivity matrix is appropriate we have used a range that catches outliers from our historical period (appendix 8).
From figure 10.6 we can see how a change in the terminal growth rate accompanied by a change in WACC affects our stock price estimations. Changes in the terminal period growth rate have a significant impact on the share price; this is however expected, as a higher growth rate would result in higher harvest volumes and the DCF models emphasis value created in the terminal period. It implies that SalMar is highly sensitive to changes in terminal growth and WACC with a share price spread of 46.37% in the range we define as realistic.
106 | P a g e
Figure 10.6 - Sensetivity: Terminal growth/WACC WACC Pessimistic Realistic Optimistic Growth #REF! 0,51 % 1,01 % 1,51 % 2,01 % 2,51 % 3,01 % 3,51 % 5,12 % 145,62 160,89 180,39 206,16 241,81 294,35 379,53 Optimistic 5,62 % 133,34 145,62 160,89 180,39 206,16 241,81 294,35 6,12 % 123,24 133,34 145,62 160,89 180,39 206,16 241,81 Realistic 6,62 % 114,80 123,24 133,34 145,62 160,89 180,39 206,16 7,12 % 107,64 114,80 123,24 133,34 145,62 160,89 180,39 7,62 % 101,48 107,64 114,80 123,24 133,34 145,62 160,89 Pessemistic 8,12 % 96,14 101,48 107,64 114,80 123,24 133,34 145,62 Source: Own calculations
As from the calculations in the sensitivity matrix above we can see that changes in WACC have severe impact on the share price and a change in WACC alone in the realistic interval yields a spread of NOK 27.55 or roughly 17%. We wish to take a closer look at changes related to the underlying assumptions of WACC. For instance if we adjust the beta post-regression, the WACC will drop from 5.56% in the forecast period to 5.04% and from 6.62% to 6.10% in the terminal period yielding a new base case share price of NOK 165.36 which is an upside of 13.56% from the base case of the present value models. However, changing beta estimates from regression to bottom-up would have no severe impact on the WACC.
If our risk-free rate were to stay constant through the forecasting horizon and terminal period, the WACC would be constant at 5.56%. The result would be a share price of NOK 182.67, an upside of 25.58% from the base case of the present value models. This indicates that our risk-free rate estimation in the terminal period has severe influence on the share price.
As we have calculated a constant rate of debt over the forecast and terminal period we will not look at changes in cost of equity or debt. However, we look at how different estimates of market risk premium will affect our share price in the DCF model. If we were to change from Damodaran’s estimate of 5.75% to a more conservative estimate of 5% (PWC, 2014), the WACC would drop to 5.16% in the forecast period and 6.22% in the terminal period yielding a new DCF based share price of NOK 160.32, roughly a 10% upside from the base case of the present value models
From analyzing the impact of changes in the underlying assumptions of the WACC, we learned that these changes greatly affect the share price, emphasizing the importance of a thorough analysis before estimating WACC. 107 | P a g e
After looking at changes in terminal growth and WACC we would now like to see how our estimated share price reacts to changes in two most important value drivers; sales price and cost per KG.
Figure 10.7 and 10.8 show that the forecasted sales price and cost per KG for SalMar also is sensitive to changes. As our model builds on the assumption that the sales price has to be equal in 2019 and the terminal period the price were changed for 2019 so that the analysis could be carried out in a sound way.
As mentioned in section 9.3 a spot price on farmed salmon over NOK 40 will not be sustainable in the long run. However, the sales prices we have calculated are based on the average selling price for SalMar’s salmon (VAP and HOG). Figure 10.7 illustrates that even a 5% change in the sales price will have high influence on the share price.
Figure 10.7 - Sensitivity: Terminal sales price per kg/WACC WACC Pessimistic Realistic Optimistic Sales price #REF! 37,75 39,74 41,83 44,03 46,23 48,55 50,97 5,12 % -3,29 62,98 132,73 206,16 279,58 356,68 437,63 Optimistic 5,62 % -0,90 56,46 116,83 180,39 243,94 310,68 380,75 6,12 % 0,90 51,52 104,80 160,89 216,98 275,87 337,70 Realistic 6,62 % 2,31 47,65 95,38 145,62 195,86 248,61 304,00 7,12 % 3,45 44,54 87,80 133,34 178,87 226,69 276,89 7,62 % 4,38 41,99 81,57 123,24 164,92 208,67 254,61 Pessemistic 8,12 % 5,16 39,85 76,37 114,80 153,24 193,60 235,98 Source: Own calculations
The share price also fluctuates with changes in cost per KG. Figure 10.8 illustrates the spread, which is as much as 122.74% in the realistic scenario range.
Figure 10.8 - Sensitivity: Terminal cost per kg/WACC WACC Pessimistic Realistic Optimistic Cost #REF! -42,81 -40,78 -38,83 -36,48 -35,14 -33,38 -31,71 5,12 % 1,30 67,29 130,13 206,16 249,83 306,68 360,70 Optimistic 5,62 % 3,91 60,75 114,89 180,39 218,01 266,99 313,52 6,12 % 5,88 55,81 103,36 160,89 193,93 236,95 277,82 Realistic 6,62 % 7,42 51,93 94,33 145,62 175,08 213,43 249,87 7,12 % 8,66 48,82 87,06 133,34 159,91 194,51 227,39 7,62 % 9,68 46,26 81,10 123,24 147,45 178,97 208,91 Pessemistic 8,12 % 10,54 44,12 76,11 114,80 137,03 165,97 193,46 Source: Own calculations
108 | P a g e
Even though sales and costs are reduced and increased by the same percentage (5%) in each interval, the prices yielded differ when the price and cost change. This is due to the fact that we in addition have other operating revenues and income from associated companies, the cost per KG however covers all cost aspects for SalMar.
In sum, we can see that it is important to have good predictions for key value drivers and WACC as changes in these factors will have significant influence over the yielded share price from the DCF, especially in the terminal period. This further emphasizes the importance of basing the DCF model on a thorough analysis.
10.3.2. Scenario analysis We are confident in our base case analysis Figure 10.9 - Scenario analyis and valuation. However, to provide a Case Optimistic Pessimistic reasonable spread in outcomes we have Supply growth 6 % 2 % constructed an optimistic scenario and a Demand growth Constant Decrease Price (NOK/KG) 42,3 35 pessimistic scenario. The scenarios are Cost (NOK/KG) 31,48 38,98 based on changes in main value drivers; all Stock price NOK 198,44 77,21 else equal. A summary of changes in value Spread from base case 36 % -47 % drivers, share prices and spreads from both Spread from 1/5/2015 76 % -31 % Source: Own calculations our base case and May 1st 2015 are displayed in figure 10.9.
10.3.2.1 Optimistic case In the optimistic case we assume growth from the new MAB regime to surpass expectations and provide supply growth of 6% annually throughout the forecasting horizon. Demand will continue to grow at today`s pace. Salmon prices increase by 2 NOK/KG due to Russian import ban being lifted and weakened NOK. Feed costs decline by 1 NOK/KG due to marine commodity price decline. Lice and PD outbreaks remain stable at today`s level.
10.3.2.2. Pessimistic case The pessimistic case assumes that the new MAB regime is deemed unsustainable thus postponed combined with biological factors decreasing license utilization resulting in supply growth of only 2%. Slow Norwegian growth in Asia due to unchanged political relationship with China and unsuccessful efforts in increasing market shares in Japan and South-East Asia. Prices on 109 | P a g e alternative sources of protein decline severely and put pressure on salmon prices resulting in stable prices of 35 NOK/KG. Feed costs increase by 3.5 NOK/KG as suppliers face higher commodity prices and gain more bargaining power due to continued consolidation. Lice and PD outbreaks increase requiring more treatments resulting in increased biology related costs of 3 NOK/KG.
10.4. Verification To determine whether our estimates are reliable we will perform a Monte Carlo simulation. We will also compare our estimates to consensus (analysts` targets) to make sure the valuation is sensible.
10.4.1. Monte Carlo simulation As verification for our share price estimation from the DCF calculations we perform a Monte Carlo simulation. When we looked at the sensitivity analysis we could see how the share price reacted to changes in one or two parameters one at the time. The Monte Carlo simulation allows us to run thousands of simulations with random variables within a set distribution (Bandimarte, 2014). The simulation will run our DCF model x number of times changing the variables we find important and give us accuracy measures of our estimations.
10.4.1.1. Input variables The first step of the Monte Carlo valuation is to choose a set of variables. As discussed, sales price, cost per KG, and harvest volumes the most important factors regarding the share price of SalMar. In the sensitivity analysis we used growth rate as our parameter for changes in harvest volumes as it is decided by the growth rate in the terminal period. However, since the Monte Carlo simulation will be used to change the assumptions for the variables in all years harvest volume changes is used.
The second step is to decide upon the distribution. The most common is normal distribution, which use standard deviation based on historical data as range for the random variables (Bandimarte, 2014). However, the industry has changed drastically over the historical period, the MAB is, as mention in section 5.1.6, approaching the limit and harvest volumes cannot be expected to have similar growth as during the historical period. The spot price has reached historical high levels in recent years after growth we cannot expect to continue. With the
110 | P a g e increasing demand we cannot see that the spot price decline drastically either. Cost per KG has increased over the historical period. Still, we cannot see any reason why cost per KG should neither increase nor decline drastically. Farming companies face challenges related to biology and feed costs, yet they are increasing utilization, i.e. has SalMar increased their production output by almost 100,000 tons HOG over the historical period, without increase their cost per KG by the same rate. Due to this argumentation we have chosen triangular distribution. The triangular distribution uses a minimum, most likely, and a maximum when producing the random variables (Bandimarte, 2014). We find this approach more applicable than the normal distribution, as we can use assumptions instead of relying solely on historical standard deviations in a changing industry.
We chose to use a -10% change for the minimum values, and a +10% change for the maximum value in both cost per KG and sales price. This would change our estimate by a random variable within ±10% of our initial estimate in all forecasting horizon and terminal period. As mentioned in section 10.1.1, the sales price must be equal in the last year of the forecasting period and the terminal period, and this was of course taken into consideration in the simulation. The harvest volume was set at a range of ±3,500 tons for the min and max. The new MAB regime and increased utilization will increase harvest volumes. After looking into the underlying drivers we find it difficult to believe that harvest will differ very much from our estimates. This is based on the MAB and the industry`s increasing utilization, which will eliminate any large decline. We have also predicted that demand will continue to outgrow supply, also limiting the downside.
10.4.1.2. Simulation result Figure 10.10 - Monte Carlo summary To perform the simulation we used the Excel add-in Monte Carlo statistics Values Simulations 100 000 Oracle Crystal Ball. As figure 10.10 illustrate, the Base case 145,62 add-in ran 100,000 DCF models with random Mean 150,75 Median 145,72 variables, for full summary see appendix 14. The Standard deviation 57,27 mean over the simulations is NOK 150.75, which is Variance 3 280 quite close to our base case of NOK 145.62. Skewedness 0,81 Kurtosis 5,16 However, the mean can be misleading due to the fact Minimum -44,68 that the average formula does not account for outliers. Maximum 792,09 Range 836,76 From figure 10.10 we can se that our spread between Source: Own calculations
111 | P a g e minimum and maximum price is 836.67 with a min of -44.68 and a max of 792.09, indicating that the mean might be too high due to outliers, this is further supported by the skewedness. To account for outliers we have also looked at the median, comma, as it eliminates extreme values. Our median is NOK 145.72, which is only NOK 0.10 from the base case, indicating that the assumptions in our base case are fair. We have also considered the standard deviation where our simulation yielded 57.27%, to further comment on this we have look at Damodaran’s estimates of standard deviation of equity in different industries. As he does not present any specific measure for aquaculture we first looked at farming and agriculture where Damodaran’s estimates indicated a standard deviation of 41.59%, however, by further investigation we found that Damodaran determines SalMar as a food processing company, which have a standard deviation of 42.05% (Damodaran, F, 2015; Damodaran, G, 2015).
Gundersen and Engelschiøn (2012) have computed the standard deviation of equity for salmon from 2004 to 2012. Their study shows that from 2004 to 2012 the standard deviation has increased from around 20% to above 50%. Even though Damodaran’s calculations are more recent than the study by Gundersen and Engelschiøn (2012), we find their study to be more precise as it is focused directly on salmon farming. This further supports that our simulation is valid. As the share price was NOK112.50 at the cut-off date, we have tested the probability for the share price being higher NOK 112.5 based on our estimates. The simulation found a 74.52% chance for the theoretical share price being above the price at cut-off. Furthermore, we found the probability for the price to be within a range of ± NOK15 from the base case of the present value models, which according to the simulation is 22.64%, indicating that our estimate is in the ballpark (appendix 14).
In sum, after performing a Monte Carlo simulation with 100,000 simulations we have gained positive insight about our initial DCF estimates, both mean and median were close to our result, and the standard deviation is reasonable considering the industry. We believe that we have provided strong estimates for a theoretical share price in our DCF model.
112 | P a g e
10.4.2. Comparison with consensus Figure 10.11 - Target price comparison We have estimated that SalMar`s shares have a Investment bank Target price (NOK) potential upside of 29% from its closing price on Pareto 150,00 st Norne 150,00 May 1 2015. This implies that our forecasts are Artic 140,00 more positive than the market view. Thus a SEB 133,00 comparison to analysts` target prices will help Swedbank 110,00 determine if our projections are too optimistic. Average 136,60 Median 140,00 Figure 10.11 shows different Norwegian Our estimate 145,62 investment banks` target prices for SalMar. We Price 1/5/2015 112,50 observe a large spread in targets; ranging from Source: Own calculations; Pareto; NOK 150 to NOK 110, averaging at NOK 136.60 Norne; Artic; SEB; Swedbank and a median of NOK 140, almost all above the actual price on May 1st 2015. Our estimate is comfortably within the consensus range giving confidence in our valuation.
10.5. Sub-conclusion
The theoretical approaches suggest different values. The present value models, DCF an EVA, provided identical results and suggested a share price of NOK 145.62. The multiple-based
valuations yielded different results averaging at NOK 144.60. The scenario and sensitivity analysis illustrated that the value of SalMar is highly sensitive to changes in the underlying value drivers. The scenario analysis´ optimistic and pessimistic cases implied prices between
NOK 77.21 and 198.44. The sensitivity analysis of main value drivers yielded prices between NOK 87.06 and 216.98. The Monte Carlo analysis and comparison with consensus proved that our estimates are very probable.
11. CONCLUSION
This section aims to answer the research objective: “What is the fair share price of SalMar on May 1st 2015?”
The purpose of this thesis has been to determine the fair share price for SalMar as of May 1st 2015. In order to end the thesis with a reliable result we have conducted a comprehensive analysis of the salmon farming industry and SalMar from both a strategic and financial perspective.
113 | P a g e
The analysis discovered that the industry is capital intensive and characterized by consolidation and large, fully integrated players in a highly competitive rivalry. Salmon will face an increased threat from substitute products as prices on alternative sources of protein are becoming relatively cheaper. However, our analysis also shows that attributes like health benefits, trends, and a growing population will keep growth in the market.
The analysis revealed that the most important value driver is the salmon spot price. The spot price has historically been extremely volatile due to biological factors and the production cycle. However, as we are approaching the MAB, the industry cyclicality is decreasing and the salmon price has been stably high in recent years. Other important value drivers are: harvest volume, which is expected to increase in line with the new MAB regime; demand, which will continue to outgrow supply driven by increased population and shift in trends; costs related to feed and biology, which will increase and continue to represent a large proportion of costs.
The analysis also proved that the farming companies are fairly equal in terms of competitiveness. SalMar has few sustainable competitive advantages, yet they have all the necessary capabilities to be profitable. Their foremost capability is their cost effectiveness, which makes them the industry cost leader. However, the analysis also revealed that SalMar generates less sales revenue per KG than peers. Nevertheless, the analysis gave indications that SalMar has decreased the gap to their peers in recent years and that a full utilization of the InnovaMar facility will reduce the gap further. In sum, the cost structure enables SalMar to create value even on low revenue per KG.
The analysis provided the necessary insights to produce sound forecasts for harvest volumes, demand, sales prices and costs. The forecasts were then used to create the pro forma financial statements that serve as the foundation for our present value models. As a sanity check for our estimates we compared our DCF and EVA results with both multiples and analysts` targets. Moreover, we looked at two alternative scenarios and performed several sensitivity analyses, which illustrated that the share price is highly sensitive to our forecasts regarding spot price, supply, costs related to feed and biology, growth rate, and WACC. We also performed a Monte Carlo simulation of our DCF, which supported the likelihood of our estimated share price.
To conclude on a fair share price for SalMar we believe it is important to consider all the different value estimates, however, we emphasis the DCF/EVA value. Figure 11.1 shows all the
114 | P a g e different results and spreads. As the figure illustrates, both the median and mean from all analysis rest close to the DCF/EVA price. Furthermore, the Monte Carlo simulation that ran our DCF model 100,000 times gave indications that these estimates seemed fair.
Figure 11.1 - Summary valuation 1/5/2015 Mean Median
DCF & EVA 145,62 145,62 EV/Sales 62,12 72,56 EV/EBITDA 158,49 162,99 EV/EBIT 181,23 203,94 EV/NOPAT 157,43 195,84 M/B 70,88 86,16 P/E 169,46 214,06 Scenario analysis 77,21 198,44 Growth sensetivity 123,24 180,39 Cost sensetivity 87,06 193,93 Price senesetivity 87,80 216,98 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 210 220 230 112,50 145,07 157,96 Source: Own calculations
We have confidence in that our analysis is sound and conclude that the fair share price for SalMar on May 1st has an upside of 29% from the actual closing price of NOK 112.50 at
NOK 145.
12. THESIS IN PERSPECTIVE
After finishing our analysis and writing this thesis we have gained extensive in-depth knowledge about the salmon farming industry. As a result, new perspectives regarding our thesis have emerged. Salmon farming is a capital-intensive industry; hence a sound cost structure is of importance. However, through writing this thesis we have also found sustainability to be of great importance. The industry players are of course centered on creating economic value, still it seems to be a common agreement that this has to happen within sustainable boundaries and that sustainability is more important than vastly increased growth. It would therefore be interesting to look at investments regarding closer control of sustainability factors such as integrated fish feed productions for SalMar.
115 | P a g e
In addition to the new MAB regime recently introduced by the government there are forces in the industry that wish to apply new standards for controlling the biomass, e.g. the rolling average presented by the some of the largest companies. An interesting perspective could be to look at how different suggestions for the new biomass regulations would have affected future supply in the Norwegian marked.
Organic growth is limited as an effect of the MAB. However, as the companies still aim for further growth, acquisitions simply to obtain new licenses and increased capacity is still very much relevant in the industry. We could therefore have included a merger case looking at the value of synergies between SalMar and a possible target.
All analysis is done on a company-wide basis. We could however have investigated the different segments (sites) separately. This could have provided even more depth to our analysis. We would then have investigated the different sites and their individual characteristics to gain insights about local biological conditions, capacity and cost structures.
116 | P a g e
13. BIBLIOGRAPHY
Achrol, R. S. (1997). Changes in the Tehory of International Relations in Marketing: Towards a Network Paradigm. Journal of the Academy of Marketing and Management, 56-71.
Akvafakta FHL. (2009 - 2015). Månedsrapport. Trondheim: Akvafakta FHL.
Asche, F., & Trond, B. (2011). The economics of salmon aquaculture. John Wiley & Sons.
Baker, M., & Ruback, R. (1999). Estimating Industry Multiples. Cambridge: Harvard University.
Bandimarte, P. (2014). Handbook in monte Carlo Silulation. New Jersey: Wiley.
Barney, J. (2002). Gaining and sustaining competitive advantage. Prentice Hall.
Berg, A. (2013, December 13). Ønsker 55 kroner kiloen for laks. Fiskeribladet Fiskaren, pp. 8-9.
Bjerke, M., & Hågensen, D. (2015). SEB Salmon market update. Oslo: SEB Equity Research.
Cermaq, A. (2010). Annual Report. Cermaq.
Cermaq, B. (2015). Om oss. Retrieved April 30, 2015, from Cermaq: http://www.cermaq.com/wps/wcm/connect/msno-content-no/mainstream-norway/about- us/
Damodaran, A. A. (1999). Eestimating Risk parameters. New York: Stern School of Business.
Damodaran, B. A. (2015). Data: Current. Retrieved April 30, 2015, from Damodaran online: http://people.stern.nyu.edu/adamodar
Damodaran, C, A. (2015, January). Country Default Spreads and Risk Premium. Retrieved April 30, 2015, from Damodaran Online: http://people.stern.nyu.edu/adamodar/
Damodaran, D, A. (N/A). NYU Stern. Retrieved April 30, 2015, from http://pages.stern.nyu.edu/~adamodar/New_Home_Page/valquestions/stablegrowthrate.ht m
Damodaran, E, A. (2012). Investment valuation: Tools and techniques for determining the value of any asset. John Wiley & Sons.
117 | P a g e
Damodaran, F, A. (2015). Standard Deviations by Sector. Retrieved April 30, 2015, from Damodaran Online: http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/optvar.html
Damodaran, G, A. (2015). Industry Breakdown. Retrieved April 30, 2015, from Damodaran Online: http://people.stern.nyu.edu/adamodar/New_Home_Page/databreakdown.html#company
Damodaran, H, A. (n.d.). Growth Rates and Terminal Value - DCF Valuation. New York: Stern Business School.
Damodaran, I, A. (2007). Return on Capital (ROC), Return on Invested Capital (ROIC). New York: Stern School of Business.
Directorate of Fisheries. (2015). Aquaculture Statistics. Retrieved April 30, 2015, from Directorate of Fisheries: http://www.fiskeridir.no/english/statistics/norwegian- aquaculture/aquaculture-statistics
DNB. (2015). Morgenrapport. Oslo: DNB.
Fama, F., & Jensen, M. (1983). Agency Problems and Residual Claims. Journal of Law and Economics, 327-349.
FAO, A. (2015). Salmo salar. Retrieved April 30, 2015, from FAO: http://www.fao.org/fishery/culturedspecies/Salmo_salar/en
Fernandez, P. (2014, June 2014). Market Risk Premium Used in 88 Countries in 2014: A Survey with 8,228 Answers. Retrieved April 30, 2015, from social science research network: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2450452
Fishpool. (2015). Price history – weekly, monthly and annual average. Retrieved April 30, 2015, from Fishpool: http://fishpool.eu/price-information/spot-prices/history/
Folketrygdfondet. (2015). About us. Retrieved April 30, 2015, from Folketrygdfondet: http://www.folketrygdfondet.no/about-us/category390.html
118 | P a g e
Frøystein, K., & Kure, E. H. (2013). Optiaml Salmon Production - Producing Smolt Under Uncertainty. Throndheim: Norwegian University of Science and Technology.
Gjevre, A.-G., & Jansen, D, M. (2014). The surveillance programme for pancreas disease (PD). Norwegian Veterinary Institute.
Goedhart, M., Koller, T., & Wessels, D. (2010). Valuation: Measuring and Managing the Value of Companies. John Wiley & Sons, Inc.
Grant, R. M. (2013). Contemporary Strategy Analysis. John Wiley and Sons Ltd.
Gravetter, F. J., & Wallnau, L. B. (2011). Essentials of Statistics for the Behavioral Sciences. Belmont: Wadsworth Cengage Learning.
Grimnes, A., Birkeland, K., Jakobsen, P. J., & Finstad, B. (1996). Lakseslus - nasjonal og internasjonal kunnskapsstatus. Trondheim: Norsk institutt for naturforskning og kulturminneforskning.
GSF, A. (2015). Annual Report 2014. Grieg Seafood.
GSF, B. (2015). About us. Retrieved April 30, 2015, from grieg seafood: http://www.griegseafood.no/en/
Gundersen, L., & Engelschiøn, K. (2012). Deriviatives in a market with low liquidity a study of risk factors associated with trading at the market place Fish Pool ASA. Ås: Universitetet for Miljø og Biovitenskap.
Hansen, T. (1998). Oppdrett av laksesmolt. Landbruksforlaget.
Haugan, B. (2015, April 30). Mener Sjømatrådet har for høy partyfaktor. Retrieved April 30, 2015, from E24: http://e24.no/boers-og-finans/marine-harvest/mener-sjoematraadet-har- for-hoey-partyfaktor/23452840
Holm, J. C. (2015). Fisk på Land. Oslo: Nærings- og fiskeridepartementet.
IFFO. (2015, March 03). Fish Oil Market to Reach US$1.7 Billion by 2018 due to Flourishing Aquaculture Industry in China. Retrieved April 30, 2015, from IFFO.
119 | P a g e iLaks. (2014, October 03). Søker om Norges største FoU-tillatelse i Fredrikstad. Retrieved April 30, 2015, from ilaks: http://www.ilaks.no/soker-om-norges-storste-fou-tillatelse-i- fredrikstad/
Index Mundi. (2015). Comodity prices. Retrieved April 30, 2015, from indexmundi: http://www.indexmundi.com/commodities/
Ireland, D. R., Hoskinsson, R. E., & Hitt, M. A. (2011). The Management of Strategy: Concepts. South-Western Cengage Learning.
Jacobsen, D. H., & Cook, M. H. (2015, March 19). Uendret styringsrente. Retrieved April 30, 2015, from Finans Norge: https://www.fno.no/aktuelt/nyheter/2015/03/uendret- styringsrente/
Jensen, M. (1993). The Modern Industrial Revolution, Exit and Failure of Internal Control Systems. Journal of Finance, 831-880.
Johnsen, V. (2013, May 07). Velg laksen som passer deg. Retrieved April 30, 2015, from side2: http://www.side2.no/3621503.html
Koller, T., Goedhart, M., Wessels, D., & Copeland, T. (2005). Valuation, measuring and managing the value of companies. John Wiely & Sons, Inc.
Kontali. (2011). Potensial for økt verdiskapning i lakse- og ørreetoppdrettsnæringen. SINTEF Fiskeri og Havbruk AS.
Kothandaraman, P., & Wilson, D. T. (2001). The Future of Competition: Value-Creating Networks. Journal of Industrial Marketing Management, 379-389.
KPMG. (2015). Corporate tax rates table. Retrieved April 30, 2015, from KPMG: http://www.kpmg.com/global/en/services/tax/tax-tools-and-resources/pages/corporate- tax-rates-table.aspx
Kraaijenbrink, J., Spender, J.-C., & Groen, A. J. (2010). The Resource-Based View: A Review and Assessment of Its Critiques. Journal of Management, 349-372.
120 | P a g e
Kverva. (2015). About us. Retrieved April 30, 2015, from Kverva: http://www.kverva.no/en/2015-02-12-12-39-21/about-kverva
Langsand Laks. (2015). Technology. Retrieved April 2015, 2015, from Langsand laks: http://langsandlaks.dk/technology/
LSG, A. (2015). Leroy in brief. Retrieved April 30, 2015, from lerøy seafood group: https://www.leroyseafood.com/en/Business/About-us/Leroy-in-brief/
LSG, B. (2015). Annual Report 2014. Lerøy Seafood Group.
LSG, C. (2014). Q4 report. Lerøy.
Malone, T. F. (2009). Feeding aquaculture in an era of finite resources. North Carolina State University.
Marine Harvest, A. (2014). Industry Handbook. Retrieved April 30, 2015, from Marine Harvest: http://marineharvest.com/investor/industry-handbook/
Marine Harvest, B. (2015). Annual Report 2014. Marine Harvest.
Molnes, K. J., & Eizentas, V. (2015). Thematic Report: Salmon Farming Sector. Norne Securities.
Monroe, K. B. (1973). Buyers' Subjective Perceptions of Price . Journal of Marketing Research, 70-80.
Mutter, R. (2015, March 22). Norwegian farm gears up for closed-containment salmon production. Retrieved April 30, 2015, from Fish farming international: http://fishfarminginternational.com/norwegian-producer-gears-up-for-closed- containment-salmon-production/
Möller, K., & Rajala, A. (2007). Rise of Startegic Nets - New Modes of Value Creation. Helsinki: Helsinki School of Economics, Department of Marketing and Management.
Nalebuff, B. J., & Brandenburger, A. M. (1997). Co-opetition: Competitive and Cooperative Business Strategies for the Digital Economy. Strategy and Leadership, 28-33.
121 | P a g e
Norges Bank. (2015). Government bonds daily observations. Retrieved April 30, 2015, from Norges Bank: http://www.norges-bank.no/en/Statistics/Interest-rates/Government-bonds- daily/
Norges Bank, A. (2015). Key policy rate. Retrieved April 30, 2015, from Norges Bank: http://www.norges-bank.no/en/Monetary-policy/Key-policy-rate/
Norne Securities. (2015). Salmon Farming Sector. Norne Securities.
Norwegian Seafood Council, C. (2015). Markedsplaner. Retrieved April 30, 2015, from Seafood: http://seafood.no/Markedsf%C3%B8ring/Markedsplaner
Norwegian Seafood Council, A. (2015). About us. Retrieved April 30, 2015, from Seafood: http://en.seafood.no/About-us/Norwegian-Seafood-Council
Norwegian Seafood Council, B. (2015). Norge og EFTAs avtaler. Retrieved April 30, 2015, from Seafood: http://seafood.no/Markedsinformasjon/Markedsadgang/Frihandelsavtaler/Norge- og-EFTAs-avtaler
Norwegian Seafood Council, D. (2015). Selger laksen seg selv? Retrieved April 30, 2015, from Norwegian Seafood: http://blogg.seafood.no/2015/05/selger-laksen-seg-selv/
NRS. (2011). Annual Report 2010. Norway Royal Salmon.
NRS, A. (2015). Organisasjon. Retrieved April 30, 2015, from Norway Royal Salmon: http://norwayroyalsalmon.com/organisasjon/
NRS, B. (2015). Annual Report 2014. Norway Royal Salmon.
OSE, A. (2015). Marine Harvest. Retrieved April 30, 2015, from Oslo børs: http://www.oslobors.no/markedsaktivitet/#/details/MHG.OSE/overview
OSE, B. (2015). Lerøy Seafood Group. Retrieved April 30, 2015, from Oslo børs: http://www.oslobors.no/markedsaktivitet/#/details/LSG.OSE/overview
OSE, C. (2015). Grieg Seafood. Retrieved April 30, 2015, from Oslo børs: http://www.oslobors.no/markedsaktivitet/#/details/GSF.OSE/overview
122 | P a g e
OSE, D. (2015). Norway Royal Salmon. Retrieved April 30, 2015, from Oslo børs: http://www.oslobors.no/markedsaktivitet/#/details/NRS.OSE/overview
OSE, E. (2015). Oslo Seafood index. Retrieved April 30, 2015, from Oslo Børs: http://www.oslobors.no/markedsaktivitet/#/details/OSLSFX.OSE/overview
OSE, F. (2015, April 30). SalMar. Retrieved April 30, 2015, from Oslo Stock Exchange: http://www.oslobors.no/markedsaktivitet/#/details/SALM.OSE/overview
Penman, S. (2010). Financial Statement Analysis and Security Valuation. McGarw-Hill.
Petersen, C. V., & Plenborg, T. (2012). Financial Statement Analysis: Valuation, Credit Analysis, and Executive Compensation. Pearson Education Ltd.
Petersen, T., & Thomsen, S. (2000). Economic and Systematic Explanations of Ownership Concentration Among Europe's Largest Companies. International Journal of the Economics of Business, 367-381.
Pharmaq. (2007 - 2015). Fiskevaksiner i Norge. Pharmaq statistikk.
Porter, M. E. (2008). The Five Competitive Forces That Shape Strategy. Harvard Business Review, 78-93.
Price, N. P. (2015). Nobel Peace Price 2010. Retrieved April 30, 2015, from Nobel peace price: http://nobelpeaceprize.org/en_GB/laureates/laureates-2010/
PWC. (2014). Risikopremie i det norske markedet. PWC.
Ramsden, N. (2014, March 7). Upping Norway’s salmon production: What do the players say? Retrieved April 30, 2015, from Undercurrent news: http://www.undercurrentnews.com/2014/03/07/upping-norways-salmon-production-what- do-the-players-say/
Regjeringen, A. (2006). Akvakulturloven. Retrieved April 30, 2015, from regjeringen: www.regjeringen.no/upload/kilde/fkd/reg/2005/0001/ddd/pdfv/255327-l- 0525_akvakulturloveneng.pdf
123 | P a g e
Regjeringen, B. (2014). Stortings melding 16. Retrieved April 30, 2015, from regjeringen: https://www.regjeringen.no/contentassets/6d27616f18af458aa930f4db9492fbe5/no/pdfs/st m201420150016000dddpdfs.pdf
Regjeringen, C. (2014, Desember 13). Norges frihandelsavtaler. Retrieved April 30, 2015, from Regjeringen: https://www.regjeringen.no/nb/tema/naringsliv/frihandelsavtaler/partner- land/id438843/
Regjeringen, D. (2015). Frihandel og Næringssammarbeid - Kina. Retrieved April 30, 2015, from Regjeringen: https://www.regjeringen.no/en/topics/business-and-industry/frihandel- og-naringssamarbeid/kina
Regjeringen, E. (2014, April 04). Viktige konsekvenser for Norge. Retrieved April 30, 2015, from Regjeringen: https://www.regjeringen.no/link/3e5fbd58e94c430c92e1552eb9f0cddd.aspx?id=755310
SalMar, A. (2015). About SalMar - History. Retrieved April 30, 2015, from Salmar: http://salmar.no/About-SalMar/History
SalMar, B. (2015). SalMar Annual report 2014.
SalMar, C. (2013). Havbasert Fiskeoppdrett. Frøya: SalMar.
SalMar, D. (2014). Annual Report 2013. Frøya: SalMar.
SalMar, E. (2015). Smolt. Retrieved April 30, 2015, from Salmar: http://salmar.no/Om- SalMar/Virksomhetsomrader/Smolt
SalMar, F. (2015). Processing. Retrieved April 30, 2015, from salmar: http://salmar.no/About- SalMar/Business-Areas/Processing
SalMar, G. (2012). Annual Report 2011. Frøya: SalMar.
SalMar, H. (2013). Annual Report 2012. Frøya: SalMar.
SalMar, I. (2015). Fry and smolt - hatchery production. Retrieved April 30, 2015, from Salmar: http://salmar.no/About-SalMar/Business-Areas/Freshwater
124 | P a g e
SalMAr, J. (2015). Business areas. Retrieved April 30, 2015, from Salmar: http://salmar.no/About-SalMar/Business-Areas
SalMar, K. (2015). The SalMar Culture, shared values, shared culture. Retrieved April 30, 2015, from Salmar: http://salmar.no/About-SalMar/Culture
SalMar, L. (2011). Annual Report 2010. Frøya: SalMar.
Sjømat Norge. (2015). Lusedata i Excel. Retrieved April 30, 2015, from Lusedata: http://lusedata.no/statistikk/excel/
Sonne, P., & Troianovski, A. (2014, August 7). Russia Bans Food Imports in Retaliation for Western Sanctions. Retrieved April 30, 2015, from The Wall Street Journal: http://www.wsj.com/articles/russia-bans-food-imports-in-retaliation-to-western-sanctions- 1407403035
Stortinget. (2011, January 1). Forskrift om drift av akvakulturanlegg (akvakulturdriftsforskriften). Retrieved April 30, 2015, from Lovdata: https://lovdata.no/dokument/SF/forskrift/2008- 06-17-822/KAPITTEL_4#%C2%A746
Strat, V., & Steffenrud, H. C. (2015). Sector Update: Fish Farming. Swedbank.
Takla, E. (2015, April 23). Valutaanalytiker: Snart må du betale 9 kroner for både en euro og en dollar. Retrieved April 30, 2015, from Dagens Næringsliv: http://www.dn.no/nyheter/okonomi/2015/04/23/0659/Valuta/valutaanalytiker-snart-m-du- betale-9-kroner-for-bde-en-euro-og-en-dollar
TDN Finans. (2014, February 10). SalMar og Lerøy inngår industrielt samarbeid. Retrieved April 30, 2015, from Dagens Næringsliv: http://www.dn.no/nyheter/2012/02/23/salmar- og-leroy-inngar-industrielt-samarbeid
Thomsen, S., & Conyon, M. (2012). Corporate Governance: Mechanisms and Systems. Copenhagen: McGraw Hill.
125 | P a g e
Trading Economics. (2015). Norway Government Bond 10Y Forecast. Retrieved April 30, 2015, from Trading Economics: http://www.tradingeconomics.com/norway/government-bond- yield/forecast
Villegas, A., Seaman, T., & Ramsden, N. (2015, March 09). NASF blog: Marine Harvest CEO shoots down land-based salmon farming. Retrieved April 30, 2015, from Undercurrent news: http://www.undercurrentnews.com/2015/03/09/dont-be-alone-wolf-uk-supplier- tells-the-youth-in-seafood/
Winer, R. S. (1986). A Reference Price Model of Brand Choice for Frequently Purchased Products. Journal of Consumer Reasearch, 250-256.
126 | P a g e
14. APPENDIXES
Appendix 1 – Free trade agreements Ongoing negotiations: Algeria, India, Indonesia, China, Malaysia, Russia/Belarus/Kazakhstan, Thailand, and Vietnam.
Current agreements: Albania, Bosnia-Herzegovina, Canada, Chile, Colombia, Costa Rica, Panama, Egypt, Gulf Cooperation Council, Hong Kong, Israel, Jordan, Lebanon, Macedonia, Morocco, Mexico, Montenegro, Palestine, Peru, Serbia, Singapore, South-Korea, Southern African Custom Union, Tunisia, Turkey, and Ukraine.
Cooperation declarations: Philippines, Georgia, Mauritius, MERCOSUR, Mongolia, Myanmar, and Pakistan.
Bilateral agreements: European Free Trade Association (EFTA), Faroe Islands, Greenland, European Economic Area (EEA).
Appendix 2 – Grant matrix: SalMar`s strengths and weaknesses
127 | P a g e
Appendix 3 – SalMar financial statements
Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Sales revenue 1 665 530 1 704 242 2 376 262 3 399 868 3 795 746 4 180 414 6 228 305 7 160 010 Other operating revenues 12 157 10 014 1 042 29 564 33 299 24 377 17 555 25 877 Total operating revenues 1 677 687 1 714 256 2 377 304 3 429 432 3 829 045 4 204 791 6 245 860 7 185 887 Change in stock of goods in progress and finished goods 47 750 103 844 25 567 401 629 395 900 390 297 324 914 162 119 Excess value of inventory from acquisitions -17 641 -9 303 - -33 587 -20 259 - - - Cost of goods sold -836 652 -922 016 -1 162 445 -2 013 312 -2 373 168 -2 715 056 -3 376 109 -3 337 411 Gross Profit 871 144 886 781 1 240 426 1 784 162 1 831 518 1 880 032 3 194 665 4 010 595 Salaries and payroll expenses -217 808 -240 393 -265 517 -313 290 -391 745 -483 215 -623 053 -710 430 Other operating expenses -191 270 -253 701 -311 973 -402 453 -705 891 -885 983 -1 086 299 -1 142 953 EBITDA 462 066 392 687 662 936 1 068 419 733 882 510 834 1 485 313 2 157 212 Depreciation of PP&E -50 671 -55 225 -66 578 -93 962 -132 000 -169 621 -220 820 -275 765 Write down of PP&E and other intangible assets (impairment losses) - - -11 600 -1 668 -543 -547 -5 000 -2 399 Operating profit/loss before fair value adjustment of biomass 411 395 337 462 584 758 972 789 601 339 340 666 1 259 493 1 879 048 Fair value adjustment of the biomass 94 234 -32 996 -4 624 181 023 -356 693 290 417 528 176 -232 349 Onerous contracts - - - - 3 635 - - - Exceptional biological items - - - - -60 070 -54 614 - - Non-recurring gains on acquisitions - - - - - 62 390 161 755 - Operating profit/loss (EBIT) 505 629 304 466 580 134 1 153 812 188 211 638 859 1 949 424 1 646 699 Other interest income 4 706 3 485 330 5 639 5 276 2 956 9 958 9 057 Other financial income 364 364 30 066 18 495 2 774 50 177 374 357 2 044 Interest expenses -47 104 -72 178 -32 078 -49 597 -98 791 -150 224 -168 053 -124 193 Other financial expenses -13 935 -13 683 -1 119 -14 931 -34 992 -27 173 -1 596 -902 Net financial profit/loss -55 969 -82 012 -2 801 -40 394 -125 733 -124 264 214 666 -113 994 Income from associated companies 31 600 12 248 56 769 147 365 97 999 93 909 157 980 96 136 Profit/Loss before tax 481 260 234 702 634 102 1 260 783 160 477 608 504 2 322 070 1 628 841 Tax -129 431 -65 874 -163 217 -302 667 -13 106 -127 062 -418 695 -413 364 Net profit/loss for the year 351 829 168 828 470 885 958 116 147 371 481 442 1 903 375 1 215 477 Minority´s share of net profit/loss -49 249 16 11 300 2 517 14 072 113 335 22 977 Majority´s share of net profit/loss 351 878 168 579 470 869 946 818 144 855 467 370 1 790 041 1 192 500 Earnings per share (NOK) 3,45 1,64 4,58 9,19 1,41 4,20 15,80 10,53 Diluted earnings per share (NOK) 3,45 1,64 4,58 9,19 1,41 4,20 15,80 10,53
128 | P a g e
Tax Adjustments (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax -129 431 -65 874 -163 217 -302 667 -13 106 -127 062 -418 695 -413 364 Tax non-core operating items (tax shield) -5 775 34 807 2 079 -29 972 156 554 -48 700 -244 241 93 513 Tax core operations -123 656 -100 681 -165 296 -272 695 -169 660 -78 362 -174 454 -506 877
Analytical Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Sales revenue 1 665 530 1 704 242 2 376 262 3 399 868 3 795 746 4 180 414 6 228 305 7 160 010 Other operating revenues 12 157 10 014 1 042 29 564 33 299 24 377 17 555 25 877 Income from associated companies 31 600 12 248 56 769 147 365 97 999 93 909 157 980 96 136 Net revenue 1 709 287 1 726 504 2 434 073 3 576 797 3 927 044 4 298 700 6 403 840 7 282 023 Change in stock of goods in progress and finished goods 47 750 103 844 25 567 401 629 395 900 390 297 324 914 162 119 Cost of goods sold -836 652 -922 016 -1 162 445 -2 013 312 -2 373 168 -2 715 056 -3 376 109 -3 337 411 Gross profit 920 385 908 332 1 297 195 1 965 114 1 949 776 1 973 941 3 352 645 4 106 731 Salaries and payroll expenses -217 808 -240 393 -265 517 -313 290 -391 745 -483 215 -623 053 -710 430 Other operating expenses -191 270 -253 701 -311 973 -402 453 -705 891 -885 983 -1 086 299 -1 142 953 EBITDA 511 307 414 238 719 705 1 249 371 852 140 604 743 1 643 293 2 253 348 Depreciation of PP&E -50 671 -55 225 -66 578 -93 962 -132 000 -169 621 -220 820 -275 765 Write down of PP&E and other intangible assets (impairment losses) - - -11 600 -1 668 -543 -547 -5 000 -2 399 EBIT 460 636 359 013 641 527 1 153 741 719 597 434 575 1 417 473 1 975 184 Tax core operations -123 656 -100 681 -165 296 -272 695 -169 660 -78 362 -174 454 -506 877 NOPAT 336 980 258 332 476 231 881 046 549 937 356 213 1 243 019 1 468 307
NON-CORE OPERATIONS Other interest income 4 706 3 485 330 5 639 5 276 2 956 9 958 9 057 Other financial income 364 364 30 066 18 495 2 774 50 177 374 357 2 044 Interest expenses -47 104 -72 178 -32 078 -49 597 -98 791 -150 224 -168 053 -124 193 Other financial expenses -13 935 -13 683 -1 119 -14 931 -34 992 -27 173 -1 596 -902 Net financial profit/loss -55 969 -82 012 -2 801 -40 394 -125 733 -124 264 214 666 -113 994 Fair value adjustment of the biomass 94 234 -32 996 -4 624 181 023 -356 693 290 417 528 176 -232 349 Excess value of inventory from acquisitions -17 641 -9 303 - -33 587 -20 259 - - - Onerous contracts - - - - 3 635 - - - Exceptional biological items - - - - -60 070 -54 614 - - Non-recurring gains on acquisitions - - - - - 62 390 161 755 - Net non-core operations 20 624 -124 311 -7 425 107 042 -559 120 173 929 904 597 -346 343 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax non-core operating items (tax shield) -5 775 34 807 2 079 -29 972 156 554 -48 700 -244 241 93 513 Net Income 351 829 168 828 470 885 958 116 147 371 481 442 1 903 375 1 215 477
129 | P a g e
Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 ASSETS Non-current assets Licenses, patents, etc. 1 009 335 914 116 935 916 1 406 483 1 483 752 1 702 152 2 030 710 2 451 271 Goodwill 69 139 196 932 205 458 306 999 433 348 433 348 433 348 447 372 Property, plant and equipment 348 222 416 084 533 286 872 035 1 126 446 1 268 803 1 859 324 2 017 575 Investments in associated companies and joint ventures 258 203 257 615 268 508 866 809 918 869 948 575 402 338 523 711 Investments in shares and other securities 1 001 975 1 025 1 426 762 15 760 384 519 Pension fund assets 1 119 1 637 4 904 3 901 2 023 2 492 802 1 592 Other long-term receivables 7 530 5 485 12 720 12 276 4 609 4 029 5 225 13 403 Total non-current assets 1 694 549 1 792 844 1 961 817 3 469 929 3 969 809 4 375 159 4 732 131 5 455 443 Current assets Biological assets (unfinished products) 905 675 971 454 1 011 518 1 580 934 1 420 788 1 986 213 3 077 150 3 114 684 Inventories (raw materials and finished products) 63 979 97 768 103 176 128 973 227 935 303 682 171 539 206 454 Accounts receivable 124 325 148 596 252 155 409 707 505 280 660 944 662 149 888 219 Receviable from parent company 165 552 83 - - - - - Other current receivables 57 321 33 604 73 163 136 266 144 993 245 501 217 584 292 644 Bank deposits, cash and cash equivalents 47 809 23 541 148 424 107 062 47 621 55 336 1 070 998 166 963 Total current assets 1 199 274 1 275 515 1 588 519 2 362 942 2 346 617 3 251 676 5 199 420 4 668 964 Total assets 2 893 823 3 068 359 3 550 336 5 832 871 6 316 426 7 626 835 9 931 551 10 124 407
EQUITY AND LIABILITIES 2007 2008 2009 2010 2011 2012 2013 2014 Equity Share capital 25 750 25 750 25 750 25 750 25 750 28 325 28 325 28 325 Share premium fund 112 880 112 879 112 880 112 880 112 880 415 286 415 286 415 286 Other paid in-equity 6 547 15 551 20 454 25 685 38 337 49 957 32 822 34 834 Retained earnings 1 176 832 1 160 184 1 540 158 2 187 391 1 915 741 2 338 170 4 246 868 4 598 535 Minority interests 649 898 914 118 011 122 228 136 300 337 808 60 622 Own shares - -150 -350 -350 -325 -325 -325 -325 Total equity 1 322 658 1 315 112 1 699 806 2 469 367 2 214 611 2 967 713 5 060 784 5 137 277 Non-current liabilities Pension liabilities 2 741 5 233 5 784 1 714 1 213 528 - - Deferred tax liabilities 460 067 481 813 498 508 787 188 738 475 872 398 1 199 557 1 262 594 Long-term debt to credit institutions 687 336 758 171 746 071 1 760 567 2 028 537 2 098 240 1 974 521 1 780 174 Financial leasing liabilities 77 721 65 764 68 070 108 606 173 460 125 188 471 716 411 388 Total non-current liabilities 1 227 865 1 310 981 1 318 433 2 658 075 2 941 685 3 096 354 3 645 794 3 454 156 Current liabilities Short-term debt to credit institutions 88 394 183 999 118 073 51 431 501 754 596 288 397 186 276 667 Accounts payable 98 713 133 022 204 394 351 042 412 802 762 765 515 856 409 485 Tax payable 89 867 46 271 146 293 148 088 66 399 7 008 25 843 321 839 Public duties payable 22 076 19 137 19 710 48 023 52 980 43 192 93 532 143 757 Other current liabilities 44 250 59 837 43 627 106 845 126 195 153 515 192 556 381 226 Total current liabilities 343 300 442 266 532 097 705 429 1 160 130 1 562 768 1 224 973 1 532 974 Total liabilities 1 571 165 1 753 247 1 850 530 3 363 504 4 101 815 4 659 122 4 870 767 4 987 130 Total liabilities and equity 2 893 823 3 068 359 3 550 336 5 832 871 6 316 426 7 626 835 9 931 551 10 124 407
130 | P a g e
Analytical Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses, patents, etc. 1 009 335 914 116 935 916 1 406 483 1 483 752 1 702 152 2 030 710 2 451 271 Goodwill 69 139 196 932 205 458 306 999 433 348 433 348 433 348 447 372 Property, plant and equipment 348 222 416 084 533 286 872 035 1 126 446 1 268 803 1 859 324 2 017 575 Investments in associated companies and joint ventures 258 203 257 615 268 508 866 809 918 869 948 575 402 338 523 711 Other long-term receivables 7 530 5 485 12 720 12 276 4 609 4 029 5 225 13 403 Total non-current assets 1 692 429 1 790 232 1 955 888 3 464 602 3 967 024 4 356 907 4 730 945 5 453 332
Current assets Biological assets (unfinished products) 905 675 971 454 1 011 518 1 580 934 1 420 788 1 986 213 3 077 150 3 114 684 Pension fund assets 1 119 1 637 4 904 3 901 2 023 2 492 802 1 592 Inventories (raw materials and finished products) 63 979 97 768 103 176 128 973 227 935 303 682 171 539 206 454 Accounts receivable 124 325 148 596 252 155 409 707 505 280 660 944 662 149 888 219 Receviable from parent company 165 552 83 - - - - - Other current receivables 57 321 33 604 73 163 136 266 144 993 245 501 217 584 292 644 Total current assets 1 152 584 1 253 611 1 444 999 2 259 781 2 301 019 3 198 832 4 129 224 4 503 593
Non-interest-bearing debt Deferred tax liabilities 460 067 481 813 498 508 787 188 738 475 872 398 1 199 557 1 262 594 Accounts payable 98 713 133 022 204 394 351 042 412 802 762 765 515 856 409 485 Pension liabilities 2 741 5 233 5 784 1 714 1 213 528 - - Tax payable 89 867 46 271 146 293 148 088 66 399 7 008 25 843 321 839 Public duties payable 22 076 19 137 19 710 48 023 52 980 43 192 93 532 143 757 Other current liabilities 44 250 59 837 43 627 106 845 126 195 153 515 192 556 381 226 Total non-interest-bearing debt 717 714 745 313 918 316 1 442 900 1 398 064 1 839 406 2 027 344 2 518 901
Operating working capital 434 870 508 298 526 683 816 881 902 955 1 359 426 2 101 880 1 984 692
Invested capital net operating assets 2 127 299 2 298 530 2 482 571 4 281 483 4 869 979 5 716 333 6 832 825 7 438 024
NON-CORE OPERATIONS Equity Share capital 25 750 25 750 25 750 25 750 25 750 28 325 28 325 28 325 Share premium fund 112 880 112 879 112 880 112 880 112 880 415 286 415 286 415 286 Other paid in-equity 6 547 15 551 20 454 25 685 38 337 49 957 32 822 34 834 Retained earnings 1 176 832 1 160 184 1 540 158 2 187 391 1 915 741 2 338 170 4 246 868 4 598 535 Minority interests 649 898 914 118 011 122 228 136 300 337 808 60 622 Own shares - -150 -350 -350 -325 -325 -325 -325 Total equity 1 322 658 1 315 112 1 699 806 2 469 367 2 214 611 2 967 713 5 060 784 5 137 277
Net interest-bearing debt Financial leasing liabilities 77 721 65 764 68 070 108 606 173 460 125 188 471 716 411 388 Long-term debt to credit institutions 687 336 758 171 746 071 1 760 567 2 028 537 2 098 240 1 974 521 1 780 174 Short-term debt to credit institutions 88 394 183 999 118 073 51 431 501 754 596 288 397 186 276 667 Interest-bearing debt 853 451 1 007 934 932 214 1 920 604 2 703 751 2 819 716 2 843 423 2 468 229 Investments in shares and other securities 1 001 975 1 025 1 426 762 15 760 384 519 Bank deposits, cash and cash equivalents 47 809 23 541 148 424 107 062 47 621 55 336 1 070 998 166 963 Interest-bearing assets 48 810 24 516 149 449 108 488 48 383 71 096 1 071 382 167 482 Net interest-bearing debt 804 641 983 418 782 765 1 812 116 2 655 368 2 748 620 1 772 041 2 300 747
Invested capital net financial assets 2 127 299 2 298 530 2 482 571 4 281 483 4 869 979 5 716 333 6 832 825 7 438 024
131 | P a g e
Appendix 4 – Marine Harvest financial statements
Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Revenue 14 028 700 13 486 900 14 500 200 15 191 400 16 132 800 15 463 500 19 199 400 25 531 300 Purchase of goods -9 116 800 -8 733 900 -8 690 900 -7 690 700 -8 398 600 -9 666 500 -9 998 500 -13 677 400 Changes in inventories (unfinished and finished products) -41 900 79 500 ------Fair value adjustment of bio assets 399 600 -198 400 301 200 1 091 700 -1 514 000 350 200 6 118 300 5 007 700 Fair value (excess of cost) adjustment of bio assets aquired and harvested -750 000 -80 400 ------Fair value uplift on harvested fish ------4 323 700 -5 518 500 Salary and personnel expenses -2 165 000 -2 139 800 -2 167 400 -2 202 500 -2 177 800 -2 418 600 -2 674 300 -3 320 900 Restructuring costs -196 300 -241 000 -169 500 -4 400 -21 800 -800 -272 800 -52 900 Other operating expenses -1 304 300 -1 393 800 -1 448 200 -1 453 800 -2 063 200 -2 163 600 -2 581 900 -3 350 000 Income/loss from associated companies 66 600 5 800 69 500 202 000 -8 500 88 300 221 800 149 500 Depreciation -791 800 -685 300 -687 700 -653 000 -666 700 -677 200 -762 500 -966 800 Write downs and impairment losses -12 100 -1 579 400 -373 100 -5 000 -67 000 -500 -65 000 -24 100 Change in provision for onerous contracts - - - -14 300 -5 800 -6 100 -124 700 23 700 Other non-operational items ------74 400 -168 200 Earnings before interest and taxes (EBIT) 116 700 -1 479 800 1 334 100 4 461 400 1 209 400 968 700 4 661 700 3 633 400 Financial income 463 600 5 900 ------Net interest expense -380 900 -485 400 -392 900 -367 800 -405 800 -382 800 -640 200 -544 600 Other financial items -52 000 -457 400 28 700 -207 900 342 900 -320 000 -252 400 -1 213 700 Net currency effects - -844 600 690 600 366 800 236 400 523 300 -311 700 -388 400 Net financial profit/loss 30 700 -1 781 500 326 400 -208 900 173 500 -179 500 -1 204 300 -2 146 700 Earnings before taxes 147 400 -3 261 300 1 660 500 4 252 500 1 382 900 789 200 3 457 400 1 486 700 Taxes -110 400 409 300 -358 300 -1 143 900 -261 700 -376 500 -1 026 800 -752 000 Net earnings from ongoing operations 37 000 -2 852 000 1 302 200 3 108 600 1 121 200 412 700 2 430 600 734 700 Income from discountinued operations/assets held for sale -31 900 - - - - - 91 900 204 800 Profit or loss for the year 5 100 -2 852 000 1 302 200 3 108 600 1 121 200 412 700 2 522 500 939 500 Minority´s share of net profit/loss -400 -600 5 900 30 500 5 500 4 000 7 400 3 900 Majority´s share of net profit/loss 5 500 -2 852 600 1 296 300 3 078 000 1 115 700 408 600 2 515 100 935 600 Earnings per share (NOK) 0,01 -0,82 0,37 0,87 0,31 0,11 0,67 2,28 Diluted earnings per share (NOK) 0,01 -0,82 0,37 0,87 0,31 0,11 0,67 1,78
Tax Adjustments (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Taxes -110 400 409 300 -358 300 -1 143 900 -261 700 -376 500 -1 026 800 -752 000 Tax non-core operations (tax shield) 153 412 644 364 -128 268 -241 948 383 068 -45 864 -56 781 715 527 Tax core operations -263 812 -235 064 -230 032 -901 952 -644 768 -330 636 -970 019 -1 467 527
Analytical Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Revenue 14 028 700 13 486 900 14 500 200 15 191 400 16 132 800 15 463 500 19 199 400 25 531 300 Income/loss from associated companies 66 600 5 800 69 500 202 000 -8 500 88 300 221 800 149 500 Net revenue 14 095 300 13 492 700 14 569 700 15 393 400 16 124 300 15 551 800 19 421 200 25 680 800 Changes in inventories (unfinished and finished products) -41 900 79 500 ------Purchase of goods -9 116 800 -8 733 900 -8 690 900 -7 690 700 -8 398 600 -9 666 500 -9 998 500 -13 677 400 Gross profit 4 936 600 4 838 300 5 878 800 7 702 700 7 725 700 5 885 300 9 422 700 12 003 400 Salary and personnel expenses -2 165 000 -2 139 800 -2 167 400 -2 202 500 -2 177 800 -2 418 600 -2 674 300 -3 320 900 Other operating expenses -1 304 300 -1 393 800 -1 448 200 -1 453 800 -2 063 200 -2 163 600 -2 581 900 -3 350 000 EBITDA 1 467 300 1 304 700 2 263 200 4 046 400 3 484 700 1 303 100 4 166 500 5 332 500 Depreciation -791 800 -685 300 -687 700 -653 000 -666 700 -677 200 -762 500 -966 800 Write downs and impairment losses -12 100 -1 579 400 -373 100 -5 000 -67 000 -500 -65 000 -24 100 EBIT 663 400 -960 000 1 202 400 3 388 400 2 751 000 625 400 3 339 000 4 341 600 Tax core operations -263 812 -235 064 -230 032 -901 952 -644 768 -330 636 -970 019 -1 467 527 NOPAT 399 588 -1 195 064 972 368 2 486 448 2 106 232 294 764 2 368 981 2 874 073
NON-CORE OPERATIONS Financial income 463 600 5 900 ------Net interest expense -380 900 -485 400 -392 900 -367 800 -405 800 -382 800 -640 200 -544 600 Net currency effects - -844 600 690 600 366 800 236 400 523 300 -311 700 -388 400 Other financial items -52 000 -457 400 28 700 -207 900 342 900 -320 000 -252 400 -1 213 700 Net financial profit/loss 30 700 -1 781 500 326 400 -208 900 173 500 -179 500 -1 204 300 -2 146 700 Fair value adjustment of bio assets 399 600 -198 400 301 200 1 091 700 -1 514 000 350 200 6 118 300 5 007 700 Fair value (excess of cost) adjustment of bio assets aquired and harvested -750 000 -80 400 ------Fair value uplift on harvested fish ------4 323 700 -5 518 500 Change in provision for onerous contracts - - - -14 300 -5 800 -6 100 -124 700 23 700 Restructuring costs -196 300 -241 000 -169 500 -4 400 -21 800 -800 -272 800 -52 900 Other non-operational items ------74 400 -168 200 Income from discountinued operations/assets held for sale -31 900 - - - - - 91 900 204 800 Net Non-Core operations -547 900 -2 301 300 458 100 864 100 -1 368 100 163 800 210 300 -2 650 100 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax non-core operations (tax shield) 153 412 644 364 -128 268 -241 948 383 068 -45 864 -56 781 715 527 Net Income 5 100 -2 852 000 1 302 200 3 108 600 1 121 200 412 700 2 522 500 939 500
132 | P a g e
Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 ASSETS Non-current assets Licenses 5 566 600 5 766 500 5 409 500 5 442 500 5 577 500 5 435 300 6 036 100 6 514 900 Deferred tax assets 27 000 230 500 54 500 118 600 160 100 73 900 178 800 147 300 Goodwill 3 344 600 2 239 900 2 142 600 2 111 600 2 146 100 2 115 500 2 374 900 2 416 900 Other intangible assets 135 900 160 000 136 000 132 900 123 100 114 200 188 400 166 500 Property, plant and equipment 3 894 700 4 243 600 3 518 100 3 885 100 4 167 500 4 111 900 6 677 400 8 257 200 Other shares 829 400 78 900 118 800 124 200 92 100 1 008 600 132 100 166 100 Investments in associated companies - 513 500 520 100 678 900 624 400 647 300 900 400 978 200 Other non-current assets - - - - 25 800 73 200 8 800 14 500 Total non-current assets 13 798 200 13 232 900 11 899 600 12 493 800 12 916 600 13 579 900 16 496 900 18 661 600 Current assets Inventory 917 400 1 074 500 742 700 775 800 783 000 819 700 1 751 100 2 400 800 Biological assets 5 553 900 5 620 600 5 351 100 7 278 100 6 285 200 6 207 900 9 536 600 10 013 900 Accounts receivables 1 883 400 1 903 400 1 672 100 1 844 900 1 914 900 1 782 000 3 191 400 3 360 200 Other receivables 667 500 532 400 551 600 817 200 609 800 592 700 1 086 500 1 110 500 Cash 362 600 372 600 172 200 319 000 279 100 335 300 439 100 1 195 200 Restricted cash ------167 100 213 100 Total current assets 9 384 800 9 503 500 8 489 700 11 035 000 9 872 000 9 737 600 16 171 800 18 293 700 Assets held for sale ------1 059 000 19 000 Total assets 23 183 000 22 736 400 20 389 300 23 528 800 22 788 600 23 317 500 33 727 700 36 974 300
EQUITY AND LIABILITIES Equity Share capital 2 609 200 2 609 200 11 621 400 9 915 400 10 766 400 11 619 700 16 318 500 14 702 200 Other equity 9 840 400 6 970 300 -205 900 2 584 800 - - - - Minority interest 34 400 45 100 45 000 70 500 75 800 69 000 27 800 16 000 Total equity 12 484 000 9 624 600 11 460 500 12 570 700 10 842 200 11 688 700 16 346 300 14 718 200 Non-current liabilities Deferred tax liabilities 1 199 700 732 900 1 142 600 2 237 900 2 351 900 2 543 700 3 365 000 3 568 900 Long-term interest-bearing debt 5 856 900 6 747 700 5 116 900 5 107 300 6 589 500 5 338 500 7 710 100 10 669 100 Other long-term liabilities 136 400 116 700 99 800 571 100 99 300 414 700 976 200 2 334 400 Total non-current liabilities 7 193 000 7 597 300 6 359 300 7 916 300 9 040 700 8 296 900 12 051 300 16 572 400 Current liabilities Short-term interest-bearing debt 1 249 200 1 365 500 130 300 429 700 157 000 377 800 686 700 7 000 Accounts payables 1 349 700 1 729 200 1 339 800 1 450 200 1 481 800 1 452 500 2 232 600 2 039 200 Other short-term liabilities 907 100 2 419 800 1 048 600 1 112 200 1 180 300 1 475 400 1 967 700 3 112 300 Current tax liabilities - - 50 800 49 700 86 600 26 200 252 600 525 200 Total current liabilities 3 506 000 5 514 500 2 569 500 3 041 800 2 905 700 3 331 900 5 139 600 5 683 700 Liabilities held for sale ------190 500 - Total liabilities 10 699 000 13 111 800 8 928 800 10 958 100 11 946 400 11 628 800 17 381 400 22 256 100 Total equity and liabilities 23 183 000 22 736 400 20 389 300 23 528 800 22 788 600 23 317 500 33 727 700 36 974 300
133 | P a g e
Analytical Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses 5 566 600 5 766 500 5 409 500 5 442 500 5 577 500 5 435 300 6 036 100 6 514 900 Deferred tax assets 27 000 230 500 54 500 118 600 160 100 73 900 178 800 147 300 Goodwill 3 344 600 2 239 900 2 142 600 2 111 600 2 146 100 2 115 500 2 374 900 2 416 900 Other intangible assets 135 900 160 000 136 000 132 900 123 100 114 200 188 400 166 500 Property, plant and equipment 3 894 700 4 243 600 3 518 100 3 885 100 4 167 500 4 111 900 6 677 400 8 257 200 Investments in associated companies - 513 500 520 100 678 900 624 400 647 300 900 400 978 200 Other non-current assets - - - - 25 800 73 200 8 800 14 500 Total non-current assets 12 968 800 13 154 000 11 780 800 12 369 600 12 824 500 12 571 300 16 364 800 18 495 500
Current assets Inventory 917 400 1 074 500 742 700 775 800 783 000 819 700 1 751 100 2 400 800 Biological assets 5 553 900 5 620 600 5 351 100 7 278 100 6 285 200 6 207 900 9 536 600 10 013 900 Accounts receivables 1 883 400 1 903 400 1 672 100 1 844 900 1 914 900 1 782 000 3 191 400 3 360 200 Other receivables 667 500 532 400 551 600 817 200 609 800 592 700 1 086 500 1 110 500 Total current assets 9 022 200 9 130 900 8 317 500 10 716 000 9 592 900 9 402 300 15 565 600 16 885 400
Non-interest-bearing debt Deferred tax liabilities 1 199 700 732 900 1 142 600 2 237 900 2 351 900 2 543 700 3 365 000 3 568 900 Accounts payables 1 349 700 1 729 200 1 339 800 1 450 200 1 481 800 1 452 500 2 232 600 2 039 200 Other long-term liabilities 136 400 116 700 99 800 571 100 99 300 414 700 976 200 2 334 400 Other short-term liabilities 907 100 2 419 800 1 048 600 1 112 200 1 180 300 1 475 400 1 967 700 3 112 300 Current tax liabilities - - 50 800 49 700 86 600 26 200 252 600 525 200 Total non-interest-bearing debt 3 592 900 4 998 600 3 681 600 5 421 100 5 199 900 5 912 500 8 794 100 11 580 000
Operating working capital 5 429 300 4 132 300 4 635 900 5 294 900 4 393 000 3 489 800 6 771 500 5 305 400
Invested capital net operating assets 18 398 100 17 286 300 16 416 700 17 664 500 17 217 500 16 061 100 23 136 300 23 800 900
NON-CORE OPERATIONS Equity Share capital 2 609 200 2 609 200 11 621 400 9 915 400 10 766 400 11 619 700 16 318 500 14 702 200 Other equity 9 840 400 6 970 300 -205 900 2 584 800 - - - 0 Minority interest 34 400 45 100 45 000 70 500 75 800 69 000 27 800 16 000 Total equity 12 484 000 9 624 600 11 460 500 12 570 700 10 842 200 11 688 700 16 346 300 14 718 200
Net interest-bearing debt Long-term interest-bearing debt 5 856 900 6 747 700 5 116 900 5 107 300 6 589 500 5 338 500 7 710 100 10 669 100 Liabilities held for sale ------190 500 0 Short-term interest-bearing debt 1 249 200 1 365 500 130 300 429 700 157 000 377 800 686 700 7 000 Interest-bearing debt 7 106 100 8 113 200 5 247 200 5 537 000 6 746 500 5 716 300 8 587 300 10 676 100 Other shares 829 400 78 900 118 800 124 200 92 100 1 008 600 132 100 166 100 Cash 362 600 372 600 172 200 319 000 279 100 335 300 439 100 1 195 200 Restricted cash ------167 100 213 100 Assets held for sale ------1 059 000 19 000 Interest-bearing assets 1 192 000 451 500 291 000 443 200 371 200 1 343 900 1 797 300 1 593 400 Net interest-bearing debt 5 914 100 7 661 700 4 956 200 5 093 800 6 375 300 4 372 400 6 790 000 9 082 700
Invested capital net financial assets 18 398 100 17 286 300 16 416 700 17 664 500 17 217 500 16 061 100 23 136 300 23 800 900
134 | P a g e
Appendix 5 – Lerøy Seafood financial statements
Income Statement (1000NOK) 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenues 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 764 714 12 579 465 Other operating gains ------53 805 117 409 Cost of materials -4 698 675 -4 279 152 -5 177 492 -5 479 869 -6 184 793 -6 499 768 -7 039 813 -8 450 392 Change in inventories - - 135 068 -132 291 318 613 57 449 258 380 447 053 Salaries and other personnel costs -579 004 -664 377 -690 477 -777 845 -967 789 -1 031 872 -1 094 464 -1 270 880 Other operating costs -472 158 -579 295 -586 743 -691 791 -858 107 -853 884 -1 004 148 -1 262 518 EBITDA 541 061 534 229 1 154 163 1 805 875 1 484 797 774 866 1 938 474 2 160 137 Depreciation -153 846 -197 023 -204 007 -219 624 -271 899 -291 768 -307 175 -369 480 Impairment loss ------33 000 -5 500 -1 982 Operating profit before biomass adjustment 387 215 337 206 950 156 1 586 251 1 212 898 450 098 1 625 799 1 788 675 Adjustment of biomass to fair value 15 838 -36 369 60 483 298 538 -615 767 294 735 764 229 -327 414 Operating profit 403 053 300 837 1 010 639 1 884 789 597 131 744 833 2 390 028 1 461 261 Income from associated companies 35 509 13 716 62 744 122 006 19 741 24 831 192 188 91 939 Net financial items -69 736 -150 507 -86 105 -66 272 -81 884 -95 153 -101 840 -119 790 Profit before tax 368 826 164 046 987 278 1 940 523 534 988 674 511 2 480 376 1 433 410 Taxation -89 262 -36 994 -257 137 -510 952 -156 311 -182 749 -593 981 -328 939 Annual profit 279 564 127 052 730 141 1 429 571 378 677 491 762 1 886 395 1 104 471 Minority´s share of net profit/loss 2 550 2 322 653 10 062 -4 028 10 963 153 043 48 557 Majority´s share of net profit/loss 277 014 124 730 729 488 1 419 507 382 705 480 797 1 733 352 1 055 916 Earnings per share 5,75 2,33 13,62 26,25 7,01 8,81 31,76 19,35 Diluted earnings per share 5,71 2,33 13,62 26,25 7,01 8,81 31,76 19,35
Tax Adjustments (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Taxation -89 262 -36 994 -257 137 -510 952 -156 311 -182 749 -593 981 -328 939 Tax non-operating items (tax shield) 15 091 52 325 7 174 -65 034 195 342 -55 883 -178 845 120 745 Tax core operations -104 353 -89 319 -264 311 -445 918 -351 653 -126 866 -415 136 -449 684
Analytical Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Operating revenues 6 290 898 6 057 053 7 473 807 8 887 671 9 176 873 9 102 941 10 764 714 12 579 465 Other operating gains ------53 805 117 409 Income from associated companies 35 509 13 716 62 744 122 006 19 741 24 831 192 188 91 939 Net revenue 6 326 407 6 070 769 7 536 551 9 009 677 9 196 614 9 127 772 11 010 707 12 788 813 Cost of materials -4 698 675 -4 279 152 -5 177 492 -5 479 869 -6 184 793 -6 499 768 -7 039 813 -8 450 392 Change in inventories - - 135 068 -132 291 318 613 57 449 258 380 447 053 Gross Profit 1 627 732 1 791 617 2 494 127 3 397 517 3 330 434 2 685 453 4 229 274 4 785 474 Salaries and other personnel costs -579 004 -664 377 -690 477 -777 845 -967 789 -1 031 872 -1 094 464 -1 270 880 Other operating costs -472 158 -579 295 -586 743 -691 791 -858 107 -853 884 -1 004 148 -1 262 518 EBITDA 576 570 547 945 1 216 907 1 927 881 1 504 538 799 697 2 130 662 2 252 076 Depreciation -153 846 -197 023 -204 007 -219 624 -271 899 -291 768 -307 175 -369 480 Impairment loss ------33 000 -5 500 -1 982 EBIT 422 724 350 922 1 012 900 1 708 257 1 232 639 474 929 1 817 987 1 880 614 Tax on core operations -104 353 -89 319 -264 311 -445 918 -351 653 -126 866 -415 136 -449 684 NOPAT 318 371 261 603 748 589 1 262 339 880 986 348 063 1 402 851 1 430 930
NON-CORE OPERATIONS Adjustment of biomass to fair value 15 838 -36 369 60 483 298 538 -615 767 294 735 764 229 -327 414 Net financial items -69 736 -150 507 -86 105 -66 272 -81 884 -95 153 -101 840 -119 790 Net non-core operations -53 898 -186 876 -25 622 232 266 -697 651 199 582 662 389 -447 204 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax on non-core operations (tax shield) 15 091 52 325 7 174 -65 034 195 342 -55 883 -178 845 120 745 Net income 279 564 127 052 730 141 1 429 571 378 677 491 762 1 886 395 1 104 471
135 | P a g e
Balance Sheet (1000NOK) 2007 2008 2009 2010 2011 2012 2013 2014 ASSETS Non-current assets Deferred tax asset - - 4 461 3 697 6 546 21 545 11 807 42 263 Buildings, land and operating assets 1 149 128 1 294 818 1 225 399 1 586 334 1 836 384 2 094 539 2 377 012 2 676 716 Licences, rights and goodwill (immaterial assets) 2 832 305 2 959 927 2 959 611 3 847 760 3 878 873 3 972 053 3 987 141 4 234 391 Shares in associated companies 289 474 277 455 272 970 338 864 329 168 331 056 735 071 566 965 Shares available for sale 26 423 23 161 23 115 22 989 23 173 18 281 5 553 8 066 Long-term receivables 681 6 274 11 928 8 129 8 453 8 607 26 171 32 263 Pension assets 535 469 ------Total non-current assets 4 298 546 4 562 104 4 497 484 5 807 773 6 082 597 6 446 081 7 142 755 7 560 664 Current assets Biological assets 1 494 133 1 676 164 1 858 562 2 706 733 2 370 938 2 724 944 3 727 361 3 681 993 Other inventories 265 008 223 158 236 311 290 379 328 045 326 225 358 482 524 947 Accounts receivable 690 800 772 440 876 127 1 013 932 934 443 995 289 1 486 428 1 427 796 Other receivables 219 885 159 844 130 734 176 282 148 395 199 083 316 192 302 692 Cash and cash equivalents 537 738 388 486 707 989 1 357 096 1 597 429 1 082 797 872 513 1 360 272 Total current assets 3 207 564 3 220 092 3 809 723 5 544 422 5 379 250 5 328 337 6 760 976 7 297 700 Total assets 7 506 110 7 782 196 8 307 207 11 352 195 11 461 847 11 774 419 13 903 731 14 858 364
EQUITY AND LIABILITIES Equity Share capital 53 577 53 577 53 577 54 577 54 577 54 577 54 577 54 577 Own shares -8 687 -12 355 -12 355 -12 355 -20 479 -330 -330 -330 Share premium reserve 2 601 390 2 601 390 2 601 390 2 731 690 2 731 690 2 731 690 2 731 690 2 731 690 Other equity 1 111 733 1 101 073 1 639 076 2 671 798 2 497 047 2 528 638 3 969 263 4 476 377 Minority interests 20 830 20 658 18 568 548 564 534 931 649 381 793 747 817 282 Total equity 3 778 843 3 764 343 4 300 256 5 994 274 5 797 766 5 963 956 7 548 947 8 079 596 Non-current liabilities Long-term interest-bearing debt 1 724 699 1 672 761 1 504 707 2 221 701 2 429 365 2 402 770 2 356 803 2 767 118 Deferred tax liabilities 643 529 669 327 834 877 1 260 028 1 083 693 1 230 458 1 486 972 1 531 262 Pension liabilities 12 012 13 211 14 990 9 025 7 812 7 646 3 227 6 878 Other long-term liabilities (derivatives) - 4 150 826 1 312 7 168 44 788 36 700 131 980 Total non-current liabilites 2 380 240 2 359 449 2 355 400 3 492 066 3 528 038 3 685 662 3 883 702 4 437 238 Current liabilities Accounts payable 508 294 544 757 615 996 638 213 705 165 826 677 1 059 434 1 053 524 Short-term loans 566 594 841 921 646 105 434 121 760 977 911 884 682 574 469 276 Public duties payable 37 743 49 014 55 671 74 312 62 386 66 915 103 656 70 073 Taxes payable 76 154 16 631 93 551 395 233 322 105 88 925 320 344 335 062 Other short-term liabilities 158 242 206 081 240 228 323 976 285 410 230 400 305 074 413 595 Total current liabilities 1 347 027 1 658 404 1 651 551 1 865 855 2 136 043 2 124 802 2 471 082 2 341 530 Total liabilities 3 727 267 4 017 853 4 006 951 5 357 921 5 664 081 5 810 464 6 354 784 6 778 768 Total equity and liabilities 7 506 110 7 782 196 8 307 207 11 352 195 11 461 847 11 774 419 13 903 731 14 858 364
136 | P a g e
Analytical Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Deferred tax asset - - 4 461 3 697 6 546 21 545 11 807 42 263 Licences, rights and goodwill (immaterial assets) 2 832 305 2 959 927 2 959 611 3 847 760 3 878 873 3 972 053 3 987 141 4 234 391 Buildings, land and operating assets 1 149 128 1 294 818 1 225 399 1 586 334 1 836 384 2 094 539 2 377 012 2 676 716 Long-term receivables 681 6 274 11 928 8 129 8 453 8 607 26 171 32 263 Shares in associated companies 289 474 277 455 272 970 338 864 329 168 331 056 735 071 566 965 Total non-current assets 4 271 588 4 538 474 4 474 369 5 784 784 6 059 424 6 427 800 7 137 202 7 552 598
Current assets Biological assets 1 494 133 1 676 164 1 858 562 2 706 733 2 370 938 2 724 944 3 727 361 3 681 993 Other inventories 265 008 223 158 236 311 290 379 328 045 326 225 358 482 524 947 Pension assets 535 469 ------Accounts receivable 690 800 772 440 876 127 1 013 932 934 443 995 289 1 486 428 1 427 796 Other receivables 219 885 159 844 130 734 176 282 148 395 199 083 316 192 302 692 Total current assets 2 670 361 2 832 075 3 101 734 4 187 326 3 781 821 4 245 541 5 888 463 5 937 428
Non-interest bearing debt Accounts payable 508 294 544 757 615 996 638 213 705 165 826 677 1 059 434 1 053 524 Deferred tax liabilities 643 529 669 327 834 877 1 260 028 1 083 693 1 230 458 1 486 972 1 531 262 Public duties payable 37 743 49 014 55 671 74 312 62 386 66 915 103 656 70 073 Pension liabilities 12 012 13 211 14 990 9 025 7 812 7 646 3 227 6 878 Taxes payable 76 154 16 631 93 551 395 233 322 105 88 925 320 344 335 062 Other short-term liabilities 158 242 206 081 240 228 323 976 285 410 230 400 305 074 413 595 Total non-interest-bearing debt 1 435 974 1 499 021 1 855 313 2 700 787 2 466 571 2 451 021 3 278 707 3 410 394
Operating working capital 1 234 387 1 333 054 1 246 421 1 486 539 1 315 250 1 794 520 2 609 756 2 527 034
Invested capital net operating assets 5 505 975 5 871 528 5 720 790 7 271 323 7 374 674 8 222 320 9 746 958 10 079 632
NON-CORE OPERATIONS Equity Share capital 53 577 53 577 53 577 54 577 54 577 54 577 54 577 54 577 Own shares -8 687 -12 355 -12 355 -12 355 -20 479 -330 -330 -330 Share premium reserve 2 601 390 2 601 390 2 601 390 2 731 690 2 731 690 2 731 690 2 731 690 2 731 690 Other equity 1 111 733 1 101 073 1 639 076 2 671 798 2 497 047 2 528 638 3 969 263 4 476 377 Minority interests 20 830 20 658 18 568 548 564 534 931 649 381 793 747 817 282 Total equity 3 778 843 3 764 343 4 300 256 5 994 274 5 797 766 5 963 956 7 548 947 8 079 596
Net interest-bearing debt Short-term loans 566 594 841 921 646 105 434 121 760 977 911 884 682 574 469 276 Other long-term liabilities (derivatives) - 4 150 826 1 312 7 168 44 788 36 700 131 980 Long-term interest-bearing debt 1 724 699 1 672 761 1 504 707 2 221 701 2 429 365 2 402 770 2 356 803 2 767 118 Interes-bearing debt 2 291 293 2 518 832 2 151 638 2 657 134 3 197 510 3 359 442 3 076 077 3 368 374 Shares available for sale 26 423 23 161 23 115 22 989 23 173 18 281 5 553 8 066 Cash and cash equivalents 537 738 388 486 707 989 1 357 096 1 597 429 1 082 797 872 513 1 360 272 Interest-bearing assets 564 161 411 647 731 104 1 380 085 1 620 602 1 101 078 878 066 1 368 338 Net interest-bearing debt 1 727 132 2 107 185 1 420 534 1 277 049 1 576 908 2 258 364 2 198 011 2 000 036
Invested capital net financial assets 5 505 975 5 871 528 5 720 790 7 271 323 7 374 674 8 222 320 9 746 958 10 079 632
137 | P a g e
Appendix 6 – Grieg Seafood financial statements
Income Statement (1000 NOK) 2007 2008 2009 2010 2011 2012 2013 2014 Sales revenues 1 021 810 1 477 029 1 612 619 2 446 490 2 046 991 2 050 065 2 404 215 2 665 284 Other income 46 542 10 474 8 746 10 161 16 568 28 217 20 041 9 943 Total operating revenues 1 068 352 1 487 503 1 621 365 2 456 651 2 063 559 2 078 282 2 424 256 2 675 227 Change in inventories of work in progress 205 859 51 637 158 085 -10 412 197 753 -1 202 314 - - Raw materials and consumables used -746 174 -903 678 -900 581 -932 118 -1 087 430 - -968 978 -1 153 526 Salaries and personell expenses -136 246 -165 148 -193 300 -238 409 -238 382 -276 103 -302 223 -339 592 Other operating expenses -196 814 -332 645 -410 541 -592 752 -603 585 -642 374 -675 156 -774 460 Other gains and losses - - 80 -763 201 -53 786 63 815 Share of profit from associated companies and JV - - - 4 747 13 704 12 744 5 645 10 002 Total operating expenses -873 375 -1 349 834 -1 346 257 -1 769 707 -1 717 739 -2 108 100 -1 939 926 -2 193 761 Operating profit before depreciation and fair value adjustment of the biomass 194 977 137 669 275 108 686 944 345 820 -29 818 484 330 481 466 Depreciation -72 486 -106 144 -118 300 -115 912 -136 984 -157 075 -133 468 -135 387 Amortisation of licenses and other intangible assets -1 155 -4378 -3 282 -3 662 -3222 -4 270 -2 569 -5 222 Impairment of fixed assets - -38 012 ------Impairment of goodwill and licenses - -161988 ------Reversal of previous amortisation of licenses - - - 72 385 - - - - Operating profit before fair value adjustment of the biomass 121 336 -172 853 153 526 639 755 205 614 -191 163 348 293 340 857 Fair value adjustment of the biomass -44 075 -35 747 115 276 207 629 -395 180 98 063 267 450 -127 108 Net operating profit 77 261 -208 600 268 802 847 384 -189 566 -93 100 615 743 213 749 Financial income 26488 37 207 136 333 54 675 31 141 3 173 33 381 50 758 Financial expenses -65 815 -271 172 -89 606 -51 882 -61 963 -111 520 -106 437 -106 480 Net financial profit/loss -39 327 -233 965 46 727 2 793 -30 822 -108 347 -73 056 -55 722 Income from associated companies -1 897 700 1 985 7 590 25 165 -913 2 244 2 865 Net associated companies and financial items -41 224 -233 265 48 712 10 383 -5 657 -109 260 -70 812 -52 857 Profit before tax 36 037 -441 865 317 514 857 767 -195 223 -202 360 544 931 160 892 Tax 16 165 97 461 -86 640 -226 727 72 064 55 170 -113 945 -22 806 Net profit for the year 52 202 -344 404 230 874 631 040 -123 159 -147 190 430 986 138 086 Minority´s share of net profit/loss 782 ------Majority´s share of net profit/loss 51 420 -344 404 230 873 631 039 -123 159 -147 188 430 985 138 086 Earnings per share (NOK) 0,80 -4,50 2,45 5,65 -1,11 -1,33 3,90 1,25 Diluted earnings per share (NOK) 0,80 -4,50 2,45 5,64 -1,11 -1,33 3,90 1,25
Tax Adjustments (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax 16 165 97 461 -86 640 -226 727 72 064 55 170 -113 945 -22 806 Tax on non-core operations (tax shield) 23 353 131 519 -45 361 -79 186 119 281 2 880 -52 486 49 364 Tax core operations -7 188 -34 058 -41 279 -147 541 -47 217 52 290 -61 459 -72 170
Analytical Income Statment (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Sales revenues 1 021 810 1 477 029 1 612 619 2 446 490 2 046 991 2 050 065 2 404 215 2 665 284 Other income 46 542 10 474 8 746 10 161 16 568 28 217 20 041 9 943 Income from associated companies -1 897 700 1 985 7 590 25 165 -913 2 244 2 865 Net Income 1 066 455 1 488 203 1 623 350 2 464 241 2 088 724 2 077 369 2 426 500 2 678 092 Change in inventories of work in progress 205 859 51 637 158 085 -10 412 197 753 - - - Raw materials and consumables used -746 174 -903 678 -900 581 -932 118 -1 087 430 -1 202 314 -968 978 -1 153 526 Salaries and personell expenses -136 246 -165 148 -193 300 -238 409 -238 382 -276 103 -302 223 -339 592 Other operating expenses -196 814 -332 645 -410 541 -592 752 -603 585 -642 374 -675 156 -774 460 Other gains and losses - - 80 -763 201 -53 786 63 815 Share of profit from associated companies and JV - - - 4 747 13 704 12 744 5 645 10 002 EBITDA 193 080 138 369 277 093 694 534 370 985 -30 731 486 574 484 331 Depreciation -72 486 -106 144 -118 300 -115 912 -136 984 -157 075 -133 468 -135 387 Amortisation of licenses and other intangible assets -1 155 -4 378 -3 282 -3 662 -3 222 -4 270 -2 569 -5 222 EBIT 119 439 27 847 155 511 574 960 230 779 -192 076 350 537 343 722 Tax core operations -7 188 -34 058 -41 279 -147 541 -47 217 52 290 -61 459 -72 170 NOPAT 112 251 -6 211 114 232 427 419 183 562 -139 786 289 078 271 552
NON-CORE OPERATIONS Financial income 26 488 37 207 136 333 54 675 31 141 3 173 33 381 50 758 Financial expenses -65 815 -271 172 -89 606 -51 882 -61 963 -111 520 -106 437 -106 480 Net financial profit/loss -39 327 -233 965 46 727 2 793 -30 822 -108 347 -73 056 -55 722 Impairment of fixed assets - -38 012 ------Impairment of goodwill and licenses - -161 988 ------Reversal of previous amortisation of licenses - - - 72 385 - - - - Fair value adjustment of the biomass -44 075 -35 747 115 276 207 629 -395 180 98 063 267 450 -127 108 Net non-core operations -83 402 -469 712 162 003 282 807 -426 002 -10 284 194 394 -182 830 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax on non-core operations (tax shield) 23 353 131 519 -45 361 -79 186 119 281 2 880 -52 486 49 364 Net Income 52 202 -344 404 230 874 631 040 -123 159 -147 190 430 986 138 086
138 | P a g e
Balance Sheet (1000 NOK) 2007 2008 2009 2010 2011 2012 2013 2014 ASSETS Non-current assets Goodwill 138 661 43 616 87 583 90 540 105 373 105 108 107 310 108 708 Licences, patents, etc 849 838 831 921 818 340 926 170 987 596 976 740 994 066 1 066 184 Property, plant & equipment 639 092 794 346 819 110 923 546 1 126 699 1 141 317 1 204 208 1 424 562 Investmetns in associated companies and JV 10 879 11 579 13 619 33 456 37 387 49 229 41 190 41 937 Loan to associated companies 2 897 2 410 1 923 3 449 996 1 020 1 020 67 Available for sale financial assets 156 178 945 557 1 307 1 337 1 392 1 518 Long-term receivables 10 275 1 790 - 1 958 311 53 255 - Other intangible assets - 8 205 5 578 3 160 4 618 3 800 4 545 11 517 Total non-current assets 1 651 798 1 694 045 1 747 098 1 982 836 2 264 287 2 278 604 2 353 986 2 654 493 Current assets Inventories 34 927 44 592 49 180 58 409 67 355 65 692 74 015 88 250 Biological assets 1 067 574 1 073 341 1 367 061 1 564 041 1 404 934 1 310 142 1 766 332 1 844 097 Account receivables 111 893 157 876 188 052 265 350 223 682 124 657 177 814 254 042 Other current receivables 84 569 48 488 57 051 43 265 58 139 51 299 54 015 57 287 Cash & cash equivalents 24 318 68 146 139 778 143 727 152 622 239 885 163 913 144 003 Derivatives and other financial intruments - 8 243 20 350 - 1 178 - 518 - Total current assets 1 323 281 1 400 686 1 821 472 2 074 792 1 907 910 1 791 675 2 236 607 2 387 679 Total assets 2 975 079 3 094 731 3 568 570 4 057 628 4 172 197 4 070 279 4 590 593 5 042 172
EQUITY AND LIABILITIES Equity Share capital 306 048 306 048 446 648 446 648 446 648 446 648 446 648 446 648 Share premium fund 811 120 811 120 716 634 - - - - - Other reserves 91 459 98 383 -19 734 1 561 1 625 -51 942 -2 181 93 095 Retained earnings 57 456 -286 948 230 873 1 534 196 1 246 876 1 123 523 1 549 090 1 687 176 Own shares - - - - -5 000 -5 000 -5 000 -5 000 Total equity 1 266 083 928 603 1 374 421 1 982 405 1 690 150 1 513 230 1 988 557 2 221 919 Non-current liabilities Deferred tax liabilities 281 294 207 020 331 995 531 498 486 702 426 781 557 350 559 542 Pension obligations 4 369 4 161 1 927 2 051 1 557 1 110 610 198 Subordinated loans 9 800 13 517 13 548 14 581 18 287 - - 2 334 Borrowings 563 484 8 065 711 419 646 686 592 685 975 844 850 646 958 828 Financial leasing liabilities 123 352 213 117 198 167 168 856 179 670 156 150 170 251 236 430 Other long-term liabilities 19 096 5 882 691 3 292 2 701 - 24 056 23 640 Total non-current liabilites 1 001 395 451 762 1 257 747 1 366 964 1 281 602 1 559 885 1 602 913 1 780 972 Current liabilities Bank overdraft 337 957 ------Current portion of long-term borrowings 76 184 807 827 85 295 79 000 79 983 109 542 111 060 487 664 Current portion of financial leasing liabilities 52 498 35 305 37 383 41 726 44 662 44 730 46 149 53 231 Accounts payable 197 356 214 687 233 443 253 305 303 196 246 119 317 753 300 521 Tax payable 9 402 - - - -6 442 - 1471 50645 Accured salary expense and public tax payable 8 619 13 611 13 869 25 104 22 514 19 720 21 731 13 013 Other current liabilites 25 585 23 702 72 400 41 674 48 452 53 982 54 761 109 803 Short-term loan - 496 702 482 989 260 000 700 000 500 000 425 000 - Derivatives and other fiancial intruments - 122 532 9 672 1 605 7 887 13 805 11 631 23 475 Cash settlement - - 1 351 5 845 194 9 267 9 567 929 Total current liabilities 707 601 1 714 366 936 402 708 259 1 200 446 997 165 999 123 1 039 281 Total liabilites 1 708 996 2 166 128 2 194 149 2 075 223 2 482 048 2 557 050 2 602 036 2 820 253 Total equity and liabilities 2 975 079 3 094 731 3 568 570 4 057 628 4 172 197 4 070 279 4 590 593 5 042 172
139 | P a g e
Analytical Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Goodwill 138 661 43 616 87 583 90 540 105 373 105 108 107 310 108 708 Licences, patents, etc 849 838 831 921 818 340 926 170 987 596 976 740 994 066 1 066 184 Property, plant & equipment 639 092 794 346 819 110 923 546 1 126 699 1 141 317 1 204 208 1 424 562 Loan to associated companies 2 897 2 410 1 923 3 449 996 1 020 1 020 67 Investmetns in associated companies and JV 10 879 11 579 13 619 33 456 37 387 49 229 41 190 41 937 Long-term receivables 10 275 1 790 - 1 958 311 53 255 0 Other intangible assets - 8 205 5 578 3 160 4 618 3 800 4 545 11 517 Total non-current assets 1 651 642 1 693 867 1 746 153 1 982 279 2 262 980 2 277 267 2 352 594 2 652 975
Current assets Biological assets 1 067 574 1 073 341 1 367 061 1 564 041 1 404 934 1 310 142 1 766 332 1 844 097 Inventories 34 927 44 592 49 180 58 409 67 355 65 692 74 015 88 250 Account receivables 111 893 157 876 188 052 265 350 223 682 124 657 177 814 254 042 Other current receivables 84 569 48 488 57 051 43 265 58 139 51 299 54 015 57 287 Total current assets 1 298 963 1 324 297 1 661 344 1 931 065 1 754 110 1 551 790 2 072 176 2 243 676
Non-interest-bearing debt Deferred tax liabilities 281 294 207 020 331 995 531 498 486 702 426 781 557 350 559 542 Tax payable 9 402 - - - -6 442 - 1 471 50 645 Pension obligations 4 369 4 161 1 927 2 051 1 557 1 110 610 198 Accounts payable 197 356 214 687 233 443 253 305 303 196 246 119 317 753 300 521 Accured salary expense and public tax payable 8 619 13 611 13 869 25 104 22 514 19 720 21 731 13 013 Other current liabilites 25 585 23 702 72 400 41 674 48 452 53 982 54 761 109 803 Total non-interest-bearing debt 526 625 463 181 653 634 853 632 855 979 747 712 953 676 1 033 722
Operating working capital 772 338 861 116 1 007 710 1 077 433 898 131 804 078 1 118 500 1 209 954
Invested capital net operating assets 2 423 980 2 554 983 2 753 863 3 059 712 3 161 111 3 081 345 3 471 094 3 862 929
NON-CORE OPERATIONS Equity Share capital 306 048 306 048 446 648 446 648 446 648 446 648 446 648 446 648 Other reserves 91 459 98 383 -19 734 1 561 1 625 -51 942 -2 181 93 095 Retained earnings 57 456 -286 948 230 873 1 534 196 1 246 876 1 123 523 1 549 090 1 687 176 Share premium fund 811 120 811 120 716 634 - - - - - Own shares - - - - -5 000 -5 000 -5 000 -5 000 Total equity 1 266 083 928 603 1 374 421 1 982 405 1 690 149 1 513 229 1 988 557 2 221 919
Net interest-bearing debt Other long-term liabilities 19 096 5 882 691 3 292 2 701 - 24 056 23 640 Subordinated loans 9 800 13 517 13 548 14 581 18 287 - - 2 334 Current portion of long-term borrowings 76 184 807 827 85 295 79 000 79 983 109 542 111 060 487 664 Cash settlement - - 1 351 5 845 194 9 267 9 567 929 Borrowings 563 484 8 065 711 419 646 686 592 685 975 844 850 646 958 828 Bank overdraft 337 957 ------Short-term loan - 496 702 482 989 260 000 700 000 500 000 425 000 0 Financial leasing liabilities 123 352 213 117 198 167 168 856 179 670 156 150 170 251 236 430 Current portion of financial leasing liabilities 52 498 35 305 37 383 41 726 44 662 44 730 46 149 53 231 Derivatives and other fiancial intruments - 122 532 9 672 1 605 7 887 13 805 11 631 23 475 Interest-bearing debt 1 182 371 1 702 947 1 540 515 1 221 591 1 626 069 1 809 338 1 648 360 1 786 531 Derivatives and other financial intruments - 8 243 20 350 - 1 178 - 518 0 Available for sale financial assets 156 178 945 557 1 307 1 337 1 392 1 518 Cash & cash equivalents 24 318 68 146 139 778 143 727 152 622 239 885 163 913 144 003 Interest-bearing assets 24 474 76 567 161 073 144 284 155 107 241 222 165 823 145 521 Net interest-bearing debt 1 157 897 1 626 380 1 379 442 1 077 307 1 470 962 1 568 116 1 482 537 1 641 010
Invested capital net financial assets 2 423 980 2 554 983 2 753 863 3 059 712 3 161 111 3 081 345 3 471 094 3 862 929
140 | P a g e
Appendix 7 – Norway Royal Salmon financial statements
Income Statement (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Operating revenue 1 152 394 1 349 232 1 602 502 2 002 085 1 734 022 1 744 266 2 603 712 2 599 799 Other revenue 5 363 ------Total operating revenue 1 157 757 1 349 232 1 602 502 2 002 085 1 734 022 1 744 266 2 603 712 2 599 799 Cost of material -1 107 968 -1 272 314 -1 552 076 -1 748 681 -1 549 263 -1 540 290 -2 137 934 -2 175 278 Change in inventory and biomass - 8 161 73 192 - - - - - Personel expenses -16 669 -24 327 -33 980 -47 443 -60 595 -71 764 -85 627 -104 557 Depreciation -1 554 -6 158 -12 475 -18 555 -26 043 -30 449 -33 728 -41 412 Write-downs - - - -12 851 - - - - Other operating expenses -16 710 -27 302 -37 810 -51 765 -53 365 -71 428 -90 422 -120 488 Total operating expenses -1 142 901 -1 321 940 -1 563 149 -1 879 295 -1 689 266 -1 713 931 -2 347 711 -2 441 735 Operational EBIT 14 856 27 292 39 353 122 790 44 756 30 335 256 001 158 064 Non-recurring items ------9 919 - - Fair value adjustment - -6 646 43 573 26 339 -70 627 49 428 94 725 57 456 Income from associates ------28 834 27 136 Net operating result 14 856 20 646 82 926 149 129 -25 871 69 844 379 560 242 656 Income from associates 5 655 -10 785 6 145 19 772 -1 689 10 464 - - Gain of financial assets - - - 18 121 41 608 - 49 497 100 262 Interest income 1 503 2 662 2 047 704 338 422 338 935 Other financial income 7 743 2 154 10 097 3 295 1 407 244 88 418 Interest expenses -8 204 -16 864 -16 127 -19 466 -28 363 -35 928 -31 321 -22 434 Other financial expenses -20 -7 121 -4 362 -2 630 -4 597 -4 298 -1 870 -1 130 Net financial itmes 6 677 -29 954 -2 200 19 796 8 704 -29 096 16 732 78 051 Result before tax 21 533 -9 308 80 726 168 925 -17 167 40 748 396 292 320 707 Tax -3 531 -80 -4 189 -36 798 15 548 -9 130 -80 487 -52 422 Net result of the year 18 002 -9 388 76 537 132 127 -1 619 31 618 315 805 268 285 Majority´s share of net profit/loss 17 693 -10 094 71 137 123 528 2 140 28 191 302 434 254 348 Minority´s share of net profit/loss 307 706 5 400 8 599 -3 759 3 428 13 371 13 936 Earnings per share 0,68 -0,28 1,97 3,32 0,06 0,66 6,96 5,85 Diluted earnings per share 0,68 -0,28 1,97 3,32 0,06 0,66 6,96 5,85 Number of outstanding shares 26 288 408 36 288 408 36 288 408 37 229 198 39 611 083 43 572 191 43 572 191 43 572 191
141 | P a g e
Tax Adjustments (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax -3 531 -80 -4 189 -36 798 15 548 -9 130 -80 487 -52 422 Tax non-core operating items (tax shield) -286 7 228 -9 864 -7 382 16 866 14 -30 093 -36 587 Tax core operations -3 245 -7 308 5 675 -29 416 -1 318 -9 144 -50 394 -15 835
Analytical Income Statement (NOK 1000)2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Operating revenue 1 152 394 1 349 232 1 602 502 2 002 085 1 734 022 1 744 266 2 603 712 2 599 799 Other revenue 5 363 ------Income from associates 5 655 -10 785 6 145 19 772 -1 689 10 464 28 834 27 136 Net revenue 1 163 412 1 338 447 1 608 647 2 021 857 1 732 333 1 754 730 2 632 546 2 626 935 Change in inventory and cost of material-1 107 968 -1 264 153 -1 478 884 -1 748 681 -1 549 263 -1 540 290 -2 137 934 -2 175 278 Gross profit 55 444 74 294 129 763 273 176 183 070 214 440 494 612 451 657 Personel expenses -16 669 -24 327 -33 980 -47 443 -60 595 -71 764 -85 627 -104 557 Other operating expenses -16 710 -27 302 -37 810 -51 765 -53 365 -71 428 -90 422 -120 488 EBITDA 22 065 22 665 57 973 173 968 69 110 71 248 318 563 226 612 Depreciation and write-downs -1 554 -6 158 -12 475 -31 406 -26 043 -30 449 -33 728 -41 412 EBIT 20 511 16 507 45 498 142 562 43 067 40 799 284 835 185 200 Tax core operations -3 245 -7 308 5 675 -29 416 -1 318 -9 144 -50 394 -15 835 NOPAT 17 266 9 199 51 173 113 146 41 749 31 655 234 441 169 365
NON-CORE OPERATIONS Interest income 1 503 2 662 2 047 704 338 422 338 935 Other financial income 7 743 2 154 10 097 3 295 1 407 244 88 418 Interest expenses -8 204 -16 864 -16 127 -19 466 -28 363 -35 928 -31 321 -22 434 Other financial expenses -20 -7 121 -4 362 -2 630 -4 597 -4 298 -1 870 -1 130 Gain of financial assets - - - 18 121 41 608 - 49 497 100 262 Net financial profit/loss 1 022 -19 169 -8 345 24 10 393 -39 560 16 732 78 051 Non-recurring items ------9 919 - - Fair value adjustment - -6 646 43 573 26 339 -70 627 49 428 94 725 57 456 Net non-core operations 1 022 -25 815 35 228 26 363 -60 234 -51 111 457 135 507 Corporate tax rate (Norway) 0,28 0,28 0,28 0,28 0,28 0,28 0,27 0,27 Tax non-core operating items (tax shield) -286 7 228 -9 864 -7 382 16 866 14 -30 093 -36 587 Net income 18 002 -9 388 76 537 132 127 -1 619 31 618 315 805 268 285
142 | P a g e
Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 ASSETS Non-current assets Licenses 136 281 350 649 397 543 498 287 502 887 502 887 502 887 648 887 Total intangible assets 136 281 350 649 397 543 498 287 502 887 502 887 502 887 648 887 Property, plant and equipment Land, buildings and other real estate 903 6 192 6 850 3 392 4 021 4 103 5 474 12 746 Machinery and equipment 5 875 25 091 33 251 56 154 89 013 95 457 115 370 164 139 Boats and floting assets 3 405 14 465 15 075 48 708 76 089 72 486 84 475 105 299 Fixtures, office equipment, ect. 1 651 1 743 3 892 5 683 8 187 6 853 5 235 6 868 Total property, plant and equipment 11 834 47 491 59 068 113 937 177 310 178 899 210 554 289 052 Non-current financial assets Investments in associated 111 685 100 738 105 013 114 136 96 087 110 860 132 758 150 155 Loans to associated companies 8 450 1 000 ------Investments in shares and shareholdings 7 448 8 601 9 121 34 053 3 385 3 335 1 395 1 895 Other long-term receivables 5 177 6 249 10 782 3 760 3 766 4 673 3 127 3 000 Total non-current financial assets 132 760 116 588 124 916 151 949 103 238 118 868 137 280 155 050 Total non-current assets 280 875 514 728 581 527 764 173 783 435 800 654 850 721 1 092 989 Current assets Inventory 6 005 14 813 9 614 15 219 18 851 20 816 27 038 40 270 Biological assets 72 686 125 175 256 142 385 975 387 880 525 739 639 238 808 674 Total inventory 78 691 139 988 265 756 401 194 406 731 546 555 666 276 848 944 Accounts receivables 153 560 156 326 213 397 253 912 227 901 286 918 412 148 421 691 Other short-term receivables 12 604 14 724 20 539 40 811 43 021 31 545 68 735 174 344 Total short-term receivables 166 164 171 050 233 936 294 723 270 922 318 463 480 883 596 035 Cash and cash equivalents 1 240 22 532 1 810 4 748 6 205 9 852 53 730 61 494 Total current assets 246 095 333 570 501 502 700 665 683 858 874 870 1 200 889 1 506 473 Total assets 526 970 848 298 1 083 029 1 464 838 1 467 293 1 675 524 2 051 610 2 599 462
EQUITY AND LIABILITIES Equity Share capital 26 288 36 288 36 288 37 229 39 611 43 572 43 572 43 572 Treasury shares -330 -231 -264 -9 -1 467 - -30 -34 Share premium fund 63 660 151 339 151 339 15 525 54 936 82 029 - - Retained earnings 77 491 110 888 178 225 485 189 402 354 441 183 771 090 905 587 Total equity attributable to owners of the parent company 167 109 298 284 365 588 537 934 495 434 566 784 814 632 949 125 Non-controling interests 7 739 29 515 34 732 41 862 37 229 40 984 54 355 64 781 Total equity 174 848 327 799 400 320 579 796 532 663 607 768 868 987 1 013 906 Non-current liabilities Pension liabilities 7 661 8 216 8 130 7 719 8 480 9 040 10 320 18 733 Deferred tax liabilities 48 994 105 613 107 352 173 610 153 784 161 981 231 640 272 742 Non-current interest-bearing debt 95 168 164 580 190 730 282 481 320 884 328 292 323 084 518 788 Other non-current liabilities 7 142 ------Total non-current liabilities 158 965 278 409 306 212 463 810 483 148 499 313 565 044 810 263 Current liabilities Current interest-bearing debt 88 488 108 399 179 582 148 259 217 054 247 637 184 530 182 089 Accounts payable 93 641 101 854 180 726 254 338 219 868 292 655 382 944 426 331 Tax payable 2 985 - - 1 136 - 780 8 313 2 031 Other current liabilities 8 043 31 837 16 189 17 499 14 560 27 371 41 792 164 842 Total current liabilities 193 157 242 090 376 497 421 232 451 482 568 443 617 579 775 293 Total liabilities 352 122 520 499 682 709 885 042 934 630 1 067 756 1 182 623 1 585 556 Total equity and liabilities 526 970 848 298 1 083 029 1 464 838 1 467 293 1 675 524 2 051 610 2 599 462
143 | P a g e
Analytical Balance Sheet (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses 136 281 350 649 397 543 498 287 502 887 502 887 502 887 648 887 Property, plant and equipment 11 834 47 491 59 068 113 937 177 310 178 899 210 554 289 052 Investments in associated 111 685 100 738 105 013 114 136 96 087 110 860 132 758 150 155 Other long-term receivables 5 177 6 249 10 782 3 760 3 766 4 673 3 127 3 000 Loans to associated companies 8 450 1 000 ------Total non-current assets 273 427 506 127 572 406 730 120 780 050 797 319 849 326 1 091 094
Current assets Inventory 6 005 14 813 9 614 15 219 18 851 20 816 27 038 40 270 Biological assets 72 686 125 175 256 142 385 975 387 880 525 739 639 238 808 674 Short-term receivables 166 164 171 050 233 936 294 723 270 922 318 463 480 883 596 035 Total current assets 244 855 311 038 499 692 695 917 677 653 865 018 1 147 159 1 444 979
Non-interest-bearing debt Deferred tax liabilities 48 994 105 613 107 352 173 610 153 784 161 981 231 640 272 742 Pension liabilities 7 661 8 216 8 130 7 719 8 480 9 040 10 320 18 733 Accounts payable 93 641 101 854 180 726 254 338 219 868 292 655 382 944 426 331 Tax payable 2 985 - - 1 136 - 780 8 313 2 031 Other current liabilities 8 043 31 837 16 189 17 499 14 560 27 371 41 792 164 842 Total non-interest-bearing debt 161 324 247 520 312 397 454 302 396 692 491 827 675 009 884 679
Operating working capital 83 531 63 518 187 295 241 615 280 961 373 191 472 150 560 300
Invested capital net operating assets 356 958 569 645 759 701 971 735 1 061 011 1 170 510 1 321 476 1 651 394
NON-CORE OPERATIONS Equity Share capital 26 288 36 288 36 288 37 229 39 611 43 572 43 572 43 572 Share premium fund 63 660 151 339 151 339 15 525 54 936 82 029 - - Treasury shares -330 -231 -264 -9 -1 467 - -30 -34 Retained earnings 77 491 110 888 178 225 485 189 402 354 441 183 771 090 905 587 Non-controling interests 7 739 29 515 34 732 41 862 37 229 40 984 54 355 64 781 Total equity 174 848 327 799 400 320 579 796 532 663 607 768 868 987 1 013 906
Net interest-bearing debt Non-current interest-bearing debt 95 168 164 580 190 730 282 481 320 884 328 292 323 084 518 788 Other non-current liabilities 7 142 ------Current interest-bearing debt 88 488 108 399 179 582 148 259 217 054 247 637 184 530 182 089 Interest-bearing debt 190 798 272 979 370 312 430 740 537 938 575 929 507 614 700 877 Investments in shares and shareholdings 7 448 8 601 9 121 34 053 3 385 3 335 1 395 1 895 Cash and cash equivalents 1 240 22 532 1 810 4 748 6 205 9 852 53 730 61 494 Interest-bearing assets 8 688 31 133 10 931 38 801 9 590 13 187 55 125 63 389 Net interest-bearing debt 182 110 241 846 359 381 391 939 528 348 562 742 452 489 637 488
Invested capital net financial assets 356 958 569 645 759 701 971 735 1 061 011 1 170 510 1 321 476 1 651 394
144 | P a g e
Appendix 8 – Historical cost of capital 8.1. Bottom-up beta calculations
SalMar Bottom-Up Beta Raw Beta D/E Marine Harvest Bottom-Up Beta Raw Beta D/E MHG 1,12 0,56 SALM 0,62 0,35 LSG 0,64 0,32 LSG 0,64 0,32 GSF 1,26 1,80 GSF 1,26 1,80 NRS 0,80 0,81 NRS 0,80 0,81 Average 0,96 0,87 Average 0,83 0,82
Post-Bottom-Up Adjusted Beta Post-Bottom-Up Adjusted Beta Bloomberg adjustment factors 0,3333 0,6667 Bloomberg adjustment factors 0,3333 0,6667 Adjusted average bottom-up beta 0,9702 Adjusted average bottom-up beta 0,8872 Corporate tax rate (average) 27,75 % Corporate tax rate (average) 27,75 % Unlevered bottom-up beta 0,5952 Unlevered bottom-up beta 0,5576
Lerøy Seafood Bottom-Up Beta Raw Beta D/E Grieg Seafood Bottom-Up Beta Raw Beta D/E SALM 0,62 0,35 SALM 0,62 0,35 MHG 1,12 0,56 MHG 1,12 0,56 GSF 1,26 1,80 LSG 0,64 0,32 NRS 0,80 0,81 NRS 0,80 0,81 Average 0,95 0,88 Average 0,79 0,51
Post-Bottom-Up Adjusted Beta Post-Bottom-Up Adjusted Beta Bloomberg adjustment factors 0,3333 0,6667 Bloomberg adjustment factors 0,3333 0,6667 Adjusted average bottom-up beta 0,9660 Adjusted average bottom-up beta 0,8632 Corporate tax rate (average) 27,75 % Corporate tax rate (average) 27,75 % Unlevered bottom-up beta 0,5907 Unlevered bottom-up beta 0,6311
NRS Bottom-Up Beta Raw Beta D/E SALM 0,62 0,35 MHG 1,12 0,56 LSG 0,64 0,32 GSF 1,26 1,80 Average 0,91 0,76
Post-Bottom-Up Adjusted Beta Bloomberg adjustment factors 0,3333 0,6667 Adjusted average bottom-up beta 0,9404 Corporate tax rate (average) 27,75 % Unlevered bottom-up beta 0,6083
145 | P a g e
8.2. WACC calculations
SalMar Cost of Capital (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Average Equity Unlevered beta 0,60 0,60 0,60 0,60 0,60 0,60 0,60 0,60 0,60 Levered beta 0,67 0,75 0,67 0,72 0,96 0,83 0,69 0,66 0,7438 Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % 3,39 % Market risk premium 5,00 % 5,00 % 5,00 % 5,00 % 5,00 % 5,50 % 6,00 % 5,00 % 5,19 % Liquidity risk premium 0,10 % 0,80 % 0,10 % 0,00 % 0,60 % 0,00 % 0,00 % 0,00 % 0,20 % Cost of equity (Re) 8,24 % 9,03 % 7,43 % 7,11 % 8,54 % 6,65 % 6,70 % 5,84 % 7,443%
Debt Interest expenses -47 104 -72 178 -32 078 -49 597 -98 791 -150 224 -168 053 -124 193 -92 777 Net interest-bearing debt 804 641 983 418 782 765 1 812 116 2 655 368 2 748 620 1 772 041 2 300 747 1 732 465 Cost of debt (Rd) 5,85 % 7,34 % 4,10 % 2,74 % 3,72 % 5,47 % 9,48 % 5,40 % 5,51 %
Capital structure Shares outstanding, ultimo (x1000) 103 000 103 000 103 000 103 000 103 000 113 300 113 300 113 300 106 862 Share price, ultimo 44,00 26,00 46,00 61,50 30,00 44,70 74,00 127,50 56,71 Market value of equity 4 532 000 2 678 000 4 738 000 6 334 500 3 090 000 5 064 510 8 384 200 14 445 750 6 158 370 Net interest-bearing debt 804 641 983 418 782 765 1 812 116 2 655 368 2 748 620 1 772 041 2 300 747 1 732 465 Enterprise value 5 336 641 3 661 418 5 520 765 8 146 616 5 745 368 7 813 130 10 156 241 16 746 497 7 890 834 Equity ratio 84,92 % 73,14 % 85,82 % 77,76 % 53,78 % 64,82 % 82,55 % 86,26 % 76,13 % Debt ratio 15,08 % 26,86 % 14,18 % 22,24 % 46,22 % 35,18 % 17,45 % 13,74 % 23,87 % Debt/Equity 17,75 % 36,72 % 16,52 % 28,61 % 85,93 % 54,27 % 21,14 % 15,93 % 34,61 %
Corporate tax rate 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 27,00 % 27,00 % 27,75 %
Weighted average cost of capital (WACC) 7,63 % 8,03 % 6,79 % 5,97 % 5,83 % 5,70 % 6,74 % 5,58 % 6,53 %
Marine Harvest Cost of Capital (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Average Equity Unlevered beta 0,56 0,56 0,56 0,56 0,56 0,56 0,56 0,56 0,56 Levered beta 0,75 1,40 0,69 0,65 0,83 0,65 0,65 0,65 0,78 Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % 3,39 % Market risk premium 5,00 % 5,00 % 5,00 % 5,00 % 5,00 % 5,50 % 6,00 % 5,00 % 5,19 % Liquidity risk premium 0,00 % 0,40 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,05 % Cost of equity (Re) 8,55 % 11,87 % 7,45 % 6,77 % 7,29 % 5,67 % 6,47 % 5,75 % 7,48 %
Debt Net interest expense -380 900 -485 400 -392 900 -367 800 -405 800 -382 800 -640 200 -544600 -450 050 Net interest-bearing debt 5 914 100 7 661 700 4 956 200 5 093 800 6 375 300 4 372 400 6 790 000 9 082 700 6 280 775 Cost of debt (Rd) 6,44 % 6,34 % 7,93 % 7,22 % 6,37 % 8,75 % 9,43 % 6,00 % 7,31 %
Capital structure Shares outstanding, ultimo (x1000) 3 472 648 3 478 898 3 574 898 3 574 898 3 581 100 3 748 300 4 103 800 410 378 3 243 115 Share price, ultimo 3,49 1,05 4,23 6,17 2,59 5,12 7,39 102,90 16,62 Market value of equity 12 119 543 3 652 843 15 121 820 22 057 123 9 275 049 19 191 296 30 306 563 42 227 871 19 244 013 Net interest-bearing debt 5 914 100 7 661 700 4 956 200 5 093 800 6 375 300 4 372 400 6 790 000 9 082 700 6 280 775 Enterprise value 18 033 643 11 314 543 20 078 020 27 150 923 15 650 349 23 563 696 37 096 563 51 310 571 25 524 788 Equity ratio 67,21 % 32,28 % 75,32 % 81,24 % 59,26 % 81,44 % 81,70 % 82,30 % 70,09 % Debt ratio 32,79 % 67,72 % 24,68 % 18,76 % 40,74 % 18,56 % 18,30 % 17,70 % 29,91 % Debt/Equity 48,80 % 209,75 % 32,78 % 23,09 % 68,74 % 22,78 % 22,40 % 21,51 % 56,23 %
Corporate tax rate 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 27,00 % 27,00 % 27,75 %
Weighted average cost of capital (WACC) 7,27 % 6,92 % 7,02 % 6,48 % 6,19 % 5,79 % 6,55 % 5,50 % 6,46 %
146 | P a g e
Lerøy Seafood Cost of Capital (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Average Equity Unlevered beta 0,59 0,59 0,59 0,59 0,59 0,59 0,59 0,59 0,59 Levered beta 0,71 0,96 0,70 0,64 0,74 0,73 0,69 0,65 0,73 Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % 3,39 % Market risk premium 5,00 % 5,00 % 5,00 % 5,00 % 5,00 % 5,50 % 6,00 % 5,00 % 5,19 % Liquidity risk premium 0,00 % 0,70 % 0,00 % 0,00 % 0,10 % 0,00 % 0,00 % 0,00 % 0,10 % Cost of equity (Re) 8,35 % 9,95 % 7,48 % 6,72 % 6,90 % 6,10 % 6,71 % 5,76 % 7,25 %
Debt Interest expenses -126 504 -186 245 -95 455 -81 832 -121 821 -128 691 -120 258 -124 229 -123 129 Net interest-bearing debt 1 727 132 2 107 185 1 420 534 1 277 049 1 576 908 2 258 364 2 198 011 2 000 036 1 820 652 Cost of debt (Rd) 7,32 % 8,84 % 6,72 % 6,41 % 7,73 % 5,70 % 5,47 % 6,21 % 6,80 %
Capital structure Shares outstanding, ultimo (x1000) 54 577 54 577 54 577 54 577 54 577 54 577 54 577 54 577 54 577 Share price, ultimo 110,00 45,00 105,00 198,50 84,00 129,50 177,00 273,00 140,25 Market value of equity 6 003 510 2 455 982 5 730 624 10 833 608 4 584 499 7 067 769 9 660 194 14 899 621 7 654 476 Net interest-bearing debt 1 727 132 2 107 185 1 420 534 1 277 049 1 576 908 2 258 364 2 198 011 2 000 036 1 820 652 Enterprise value 7 730 642 4 563 167 7 151 158 12 110 657 6 161 407 9 326 133 11 858 205 16 899 657 9 475 128 Equity ratio 77,66 % 53,82 % 80,14 % 89,46 % 74,41 % 75,78 % 81,46 % 88,17 % 77,61 % Debt ratio 22,34 % 46,18 % 19,86 % 10,54 % 25,59 % 24,22 % 18,54 % 11,83 % 22,39 % Debt/Equity 28,77 % 85,80 % 24,79 % 11,79 % 34,40 % 31,95 % 22,75 % 13,42 % 31,71 %
Corporate tax rate 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 27,00 % 27,00 % 27,75 %
Weighted average cost of capital (WACC) 7,66 % 8,29 % 6,96 % 6,50 % 6,56 % 5,61 % 6,21 % 5,62 % 6,68 %
Grieg Seafood Cost of Capital (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Average Equity Unlevered beta 0,63 0,63 0,63 0,63 0,63 0,63 0,63 0,63 0,63 Levered beta 1,07 3,56 1,18 0,87 2,01 1,15 0,88 0,87 1,45 Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % 3,39 % Market risk premium 5,00 % 5,00 % 5,00 % 5,00 % 5,00 % 5,50 % 6,00 % 5,00 % 5,19 % Liquidity risk premium 1,70 % 3,50 % 1,80 % 1,00 % 3,00 % 1,60 % 0,60 % 0,40 % 1,70 % Cost of equity (Re) 11,81 % 25,76 % 11,71 % 8,85 % 16,19 % 10,05 % 8,48 % 7,26 % 12,51 %
Debt Interest expenses -56 097 -111 118 -81 945 -8 385 -8 752 -76 047 -89 729 -89 076 -65 144 Net interest-bearing debt 1 157 897 1 626 380 1 379 442 1 077 307 1 470 962 1 568 116 1 482 537 1 641 010 1 425 456 Cost of debt (Rd) 4,84 % 6,83 % 5,94 % 0,78 % 0,59 % 4,85 % 6,05 % 5,43 % 4,42 %
Capital structure Shares outstanding, ultimo (x1000) 76 512 76 512 111 662 111 662 111 662 110 412 110 412 111 662 102 562 Share price, ultimo 15,80 3,30 10,20 18,70 4,33 12,35 24,50 28,50 14,71 Market value of equity 1 208 890 252 490 1 138 952 2 088 079 483 496 1 363 588 2 705 094 3 182 367 1 552 870 Net interest-bearing debt 1 157 897 1 626 380 1 379 442 1 077 307 1 470 962 1 568 116 1 482 537 1 641 010 1 425 456 Enterprise value 2 366 787 1 878 870 2 518 394 3 165 386 1 954 458 2 931 704 4 187 631 4 823 377 2 978 326 Equity ratio 51,08 % 13,44 % 45,23 % 65,97 % 24,74 % 46,51 % 64,60 % 65,98 % 47,19 % Debt ratio 48,92 % 86,56 % 54,77 % 34,03 % 75,26 % 53,49 % 35,40 % 34,02 % 52,81 % Debt/Equity 95,78 % 644,14 % 121,11 % 51,59 % 304,23 % 115,00 % 54,81 % 51,57 % 179,78 %
Corporate tax rate 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 27,00 % 27,00 % 27,75 %
Weighted average cost of capital (WACC) 7,74 % 7,72 % 7,64 % 6,03 % 4,33 % 6,54 % 7,04 % 6,14 % 6,65 %
147 | P a g e
NRS Cost of Capital (NOK 1000) 2007 2008 2009 2010 2011 2012 2013 2014 Average Equity Unlevered beta 0,61 0,61 0,61 0,61 0,61 0,61 0,61 0,61 0,61 Levered beta 1,06 0,93 1,00 0,90 1,39 0,98 0,73 0,71 0,96 Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % 3,39 % Market risk premium 5,00 % 5,00 % 5,00 % 5,00 % 5,00 % 5,50 % 6,00 % 5,00 % 5,19 % Liquidity risk premium N/A N/A N/A N/A 3,70 % 2,90 % 1,40 % 0,60 % 2,15 % Cost of equity (Re) 10,10 % 9,13 % 9,01 % 8,04 % 13,77 % 10,38 % 8,38 % 6,66 % 9,43 %
Debt Interest expenses -8 204 -16 864 -16 127 -19 466 -28 363 -35 928 -31 321 -22 434 -22 338 Net interest-bearing debt 182 110 241 846 359 381 391 939 528 348 562 742 452 489 637 488 419 543 Cost of debt (Rd) 4,50 % 6,97 % 4,49 % 4,97 % 5,37 % 6,38 % 6,92 % 3,52 % 5,39 %
Capital structure Shares outstanding, ultimo (x1000) 26 288 36 288 36 288 37 229 39 611 43 572 43 572 43 572 38 303 Share price, ultimo N/A N/A N/A N/A 7,48 15,30 37,00 64,75 31,13 Market value of equity (book value 2007-2010) 174 848 327 799 400 320 579 796 296 291 666 655 1 612 171 2 821 299 859 897 Net interest-bearing debt 182 110 241 846 359 381 391 939 528 348 562 742 452 489 637 488 419 543 Enterprise value 356 958 569 645 759 701 971 735 824 639 1 229 397 2 064 660 3 458 787 1 279 440 Equity ratio 48,98 % 57,54 % 52,69 % 59,67 % 35,93 % 54,23 % 78,08 % 81,57 % 58,59 % Debt ratio 51,02 % 42,46 % 47,31 % 40,33 % 64,07 % 45,77 % 21,92 % 18,43 % 41,41 % Debt/Equity 104,15 % 73,78 % 89,77 % 67,60 % 178,32 % 84,41 % 28,07 % 22,60 % 81,09 %
Corporate tax rate 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 28,00 % 27,00 % 27,00 % 27,75 %
Weighted average cost of capital (WACC) 6,60 % 7,38 % 6,27 % 6,24 % 7,42 % 7,73 % 7,65 % 5,91 % 6,90 %
Appendix 9 – Salmon price
Salmon Prices (NOK/KG) 2007 2008 2009 2010 2011 2012 2013 2014 25,76 26,35 30,87 37,18 31,99 26,58 39,59 40,30
Appendix 10 – SalMar and peer group index and common-size analysis
SalMar Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Sales revenue 100 102 143 204 228 251 374 430 Other operating revenues 100 82 9 243 274 201 144 213 Income from associated companies 100 39 180 466 310 297 500 304 Net revenue 100 101 142 209 230 251 375 426 Change in stock of goods in progress and finished goods 100 217 54 841 829 817 680 340 Cost of goods sold 100 110 139 241 284 325 404 399 Gross profit 100 99 141 214 212 214 364 446 Salaries and payroll expenses 100 110 122 144 180 222 286 326 Other operating expenses 100 133 163 210 369 463 568 598 EBITDA 100 81 141 244 167 118 321 441 Depreciation of PP&E 100 109 131 185 261 335 436 544 Write down of PP&E and other intangible assets (impairment losses) (2009) - - 100 14 5 5 43 21 EBIT 100 78 139 250 156 94 308 429 Tax on core operations 100 81 134 221 137 63 141 410 NOPAT 100 77 141 261 163 106 369 436
148 | P a g e
SalMar Common-Size Analysis (Net Revenue) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Sales revenue 97,44 % 98,71 % 97,62 % 95,05 % 96,66 % 97,25 % 97,26 % 98,32 % 97,29 % Other operating revenues 0,71 % 0,58 % 0,04 % 0,83 % 0,85 % 0,57 % 0,27 % 0,36 % 0,53 % Income from associated companies 1,85 % 0,71 % 2,33 % 4,12 % 2,50 % 2,18 % 2,47 % 1,32 % 2,18 % Net revenue 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % Change in stock of goods in progress and finished goods 2,79 % 6,01 % 1,05 % 11,23 % 10,08 % 9,08 % 5,07 % 2,23 % 5,94 % Cost of goods sold -48,95 % -53,40 % -47,76 % -56,29 % -60,43 % -63,16 % -52,72 % -45,83 % -53,57 % Gross profit 53,85 % 52,61 % 53,29 % 54,94 % 49,65 % 45,92 % 52,35 % 56,40 % 52,38 % Salaries and payroll expenses -12,74 % -13,92 % -10,91 % -8,76 % -9,98 % -11,24 % -9,73 % -9,76 % -10,88 % Other operating expenses -11,19 % -14,69 % -12,82 % -11,25 % -17,98 % -20,61 % -16,96 % -15,70 % -15,15 % EBITDA 29,91 % 23,99 % 29,57 % 34,93 % 21,70 % 14,07 % 25,66 % 30,94 % 26,35 % Depreciation of PP&E -2,96 % -3,20 % -2,74 % -2,63 % -3,36 % -3,95 % -3,45 % -3,79 % -3,26 % Write down of PP&E and other intangible assets (impairment losses) 0,00 % 0,00 % -0,48 % -0,05 % -0,01 % -0,01 % -0,08 % -0,03 % -0,08 % EBIT 26,95 % 20,79 % 26,36 % 32,26 % 18,32 % 10,11 % 22,13 % 27,12 % 23,01 % Tax on core operations -7,23 % -5,83 % -6,79 % -7,62 % -4,32 % -1,82 % -2,72 % -6,96 % -5,41 % NOPAT 19,71 % 14,96 % 19,57 % 24,63 % 14,00 % 8,29 % 19,41 % 20,16 % 17,59 %
SalMar Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 63 600 65 100 77 550 78 500 103 900 116 200 128 400 154 800 Growth 2,36 % 19,12 % 1,23 % 32,36 % 11,84 % 10,50 % 20,56 %
SalMar Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Sales revenue 2619 % 2618 % 3064 % 4331 % 3653 % 3598 % 4851 % 4625 % 3670 % Other operating revenues 19 % 15 % 1 % 38 % 32 % 21 % 14 % 17 % 20 % Income from associated companies 50 % 19 % 73 % 188 % 94 % 81 % 123 % 62 % 86 % Net revenue 2688 % 2652 % 3139 % 4556 % 3780 % 3699 % 4987 % 4704 % 3776 % Change in stock of goods in progress and finished goods 75 % 160 % 33 % 512 % 381 % 336 % 253 % 105 % 232 % Cost of goods sold -1315 % -1416 % -1499 % -2565 % -2284 % -2337 % -2629 % -2156 % -2025 % Gross profit 1447 % 1395 % 1673 % 2503 % 1877 % 1699 % 2611 % 2653 % 1982 % Salaries and payroll expenses -342 % -369 % -342 % -399 % -377 % -416 % -485 % -459 % -399 % Other operating expenses -301 % -390 % -402 % -513 % -679 % -762 % -846 % -738 % -579 % EBITDA 804 % 636 % 928 % 1592 % 820 % 520 % 1280 % 1456 % 1004 % Depreciation of PP&E -80 % -85 % -86 % -120 % -127 % -146 % -172 % -178 % -124 % Write down of PP&E and other intangible assets (impairment losses) 0 % 0 % -15 % -2 % -1 % 0 % -4 % -2 % -3 % EBIT 724 % 551 % 827 % 1470 % 693 % 374 % 1104 % 1276 % 877 % Tax on core operations -194 % -155 % -213 % -347 % -163 % -67 % -136 % -327 % -200 % NOPAT 530 % 397 % 614 % 1122 % 529 % 307 % 968 % 949 % 677 %
149 | P a g e
SalMar Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses, patents, etc. 100 91 93 139 147 169 201 243 Goodwill 100 285 297 444 627 627 627 647 Property, plant and equipment 100 119 153 250 323 364 534 579 Investments in associated companies and joint ventures 100 100 104 336 356 367 156 203 Other long-term receivables 100 73 169 163 61 54 69 178 Total non-current assets 100 106 116 205 234 257 280 322
Current assets Biological assets (unfinished products) 100 107 112 175 157 219 340 344 Pension fund assets 100 146 438 349 181 223 72 142 Inventories (raw materials and finished products) 100 153 161 202 356 475 268 323 Accounts receivable 100 120 203 330 406 532 533 714 Receviable from parent company 100 335 50 0 0 0 0 0 Other current receivables 100 59 128 238 253 428 380 511 Total current assets 100 109 125 196 200 278 358 391
Non-interest-bearing debt Deferred tax liabilities 100 105 108 171 161 190 261 274 Accounts payable 100 135 207 356 418 773 523 415 Pension liabilities 100 191 211 63 44 19 0 0 Tax payable 100 51 163 165 74 8 29 358 Public duties payable 100 87 89 218 240 196 424 651 Other current liabilities 100 135 99 241 285 347 435 862 Total non-interest-bearing debt 100 104 128 201 195 256 282 351
Operating working capital 100 117 121 188 208 313 483 456
Invested capital net operating assets 100 108 117 201 229 269 321 350
SalMar Common-Size Analysis (Invested Capital) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses, patents, etc. 47,45 % 39,77 % 37,70 % 32,85 % 30,47 % 29,78 % 29,72 % 32,96 % 35,09 % Goodwill 3,25 % 8,57 % 8,28 % 7,17 % 8,90 % 7,58 % 6,34 % 6,01 % 7,01 % Property, plant and equipment 16,37 % 18,10 % 21,48 % 20,37 % 23,13 % 22,20 % 27,21 % 27,13 % 22,00 % Investments in associated companies and joint ventures 12,14 % 11,21 % 10,82 % 20,25 % 18,87 % 16,59 % 5,89 % 7,04 % 12,85 % Other long-term receivables 0,35 % 0,24 % 0,51 % 0,29 % 0,09 % 0,07 % 0,08 % 0,18 % 0,23 % Total non-current assets 79,56 % 77,89 % 78,78 % 80,92 % 81,46 % 76,22 % 69,24 % 73,32 % 77,17 %
Current assets Biological assets (unfinished products) 42,57 % 42,26 % 40,74 % 36,92 % 29,17 % 34,75 % 45,03 % 41,88 % 39,17 % Pension fund assets 0,05 % 0,07 % 0,20 % 0,09 % 0,04 % 0,04 % 0,01 % 0,02 % 0,07 % Inventories (raw materials and finished products) 3,01 % 4,25 % 4,16 % 3,01 % 4,68 % 5,31 % 2,51 % 2,78 % 3,71 % Accounts receivable 5,84 % 6,46 % 10,16 % 9,57 % 10,38 % 11,56 % 9,69 % 11,94 % 9,45 % Receviable from parent company 0,01 % 0,02 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % Other current receivables 2,69 % 1,46 % 2,95 % 3,18 % 2,98 % 4,29 % 3,18 % 3,93 % 3,08 % Total current assets 54,18 % 54,54 % 58,21 % 52,78 % 47,25 % 55,96 % 60,43 % 60,55 % 55,49 %
Non-interest-bearing debt Deferred tax liabilities 21,63 % 20,96 % 20,08 % 18,39 % 15,16 % 15,26 % 17,56 % 16,97 % 18,25 % Accounts payable 4,64 % 5,79 % 8,23 % 8,20 % 8,48 % 13,34 % 7,55 % 5,51 % 7,72 % Pension liabilities 0,13 % 0,23 % 0,23 % 0,04 % 0,02 % 0,01 % 0,00 % 0,00 % 0,08 % Tax payable 4,22 % 2,01 % 5,89 % 3,46 % 1,36 % 0,12 % 0,38 % 4,33 % 2,72 % Public duties payable 1,04 % 0,83 % 0,79 % 1,12 % 1,09 % 0,76 % 1,37 % 1,93 % 1,12 % Other current liabilities 2,08 % 2,60 % 1,76 % 2,50 % 2,59 % 2,69 % 2,82 % 5,13 % 2,77 % Total non-interest-bearing debt 33,74 % 32,43 % 36,99 % 33,70 % 28,71 % 32,18 % 29,67 % 33,87 % 32,66 %
Operating working capital 20,44 % 22,11 % 21,22 % 19,08 % 18,54 % 23,78 % 30,76 % 26,68 % 22,83 %
Invested capital net operating assets 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 %
150 | P a g e
SalMar Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses, patents, etc. 1587 % 1404 % 1207 % 1792 % 1428 % 1465 % 1582 % 1584 % 1506 % Goodwill 109 % 303 % 265 % 391 % 417 % 373 % 337 % 289 % 310 % Property, plant and equipment 548 % 639 % 688 % 1111 % 1084 % 1092 % 1448 % 1303 % 989 % Investments in associated companies and joint ventures 406 % 396 % 346 % 1104 % 884 % 816 % 313 % 338 % 576 % Other long-term receivables 12 % 8 % 16 % 16 % 4 % 3 % 4 % 9 % 9 % Total non-current assets 2661 % 2750 % 2522 % 4414 % 3818 % 3749 % 3685 % 3523 % 3390 %
Current assets Biological assets (unfinished products) 1424 % 1492 % 1304 % 2014 % 1367 % 1709 % 2397 % 2012 % 1715 % Pension fund assets 2 % 3 % 6 % 5 % 2 % 2 % 1 % 1 % 3 % Inventories (raw materials and finished products) 101 % 150 % 133 % 164 % 219 % 261 % 134 % 133 % 162 % Accounts receivable 195 % 228 % 325 % 522 % 486 % 569 % 516 % 574 % 427 % Receviable from parent company 0 % 1 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % Other current receivables 90 % 52 % 94 % 174 % 140 % 211 % 169 % 189 % 140 % Total current assets 1812 % 1926 % 1863 % 2879 % 2215 % 2753 % 3216 % 2909 % 2447 %
Non-interest-bearing debt Deferred tax liabilities 723 % 740 % 643 % 1003 % 711 % 751 % 934 % 816 % 790 % Accounts payable 155 % 204 % 264 % 447 % 397 % 656 % 402 % 265 % 349 % Pension liabilities 4 % 8 % 7 % 2 % 1 % 0 % 0 % 0 % 3 % Tax payable 141 % 71 % 189 % 189 % 64 % 6 % 20 % 208 % 111 % Public duties payable 35 % 29 % 25 % 61 % 51 % 37 % 73 % 93 % 51 % Other current liabilities 70 % 92 % 56 % 136 % 121 % 132 % 150 % 246 % 125 % Total non-interest-bearing debt 1128 % 1145 % 1184 % 1838 % 1346 % 1583 % 1579 % 1627 % 1429 %
Operating working capital 684 % 781 % 679 % 1041 % 869 % 1170 % 1637 % 1282 % 1018 %
Invested capital net operating assets 3345 % 3531 % 3201 % 5454 % 4687 % 4919 % 5322 % 4805 % 4408 %
MHG Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Revenue 100 96 103 108 115 110 137 182 Income/loss from associated companies 100 9 104 303 -13 133 333 224 Net revenue 100 96 103 109 114 110 138 182 Changes in inventories (unfinished and finished products) 100 -190 ------Purchase of goods 100 96 95 84 92 106 110 150 Gross profit 100 98 119 156 156 119 191 243 Salary and personnel expenses 100 99 100 102 101 112 124 153 Other operating expenses 100 107 111 111 158 166 198 257 EBITDA 100 89 154 276 237 89 284 363 Depreciation 100 87 87 82 84 86 96 122 Write downs and impairment losses 100 13 053 3 083 41 554 4 537 199 EBIT 100 -145 181 511 415 94 503 654 Tax on core operations 100 89 87 342 244 125 368 556 NOPAT 100 -299 243 622 527 74 593 719
MHG Common-Size Analysis (Net Revenue) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Revenue 99,53 % 99,96 % 99,52 % 98,69 % 100,05 % 99,43 % 98,86 % 99,42 % 99,43 % Income/loss from associated companies 0,47 % 0,04 % 0,48 % 1,31 % -0,05 % 0,57 % 1,14 % 0,58 % 0,57 % Net revenue 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % Changes in inventories (unfinished and finished products) -0,30 % 0,59 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,04 % Purchase of goods -64,68 % -64,73 % -59,65 % -49,96 % -52,09 % -62,16 % -51,48 % -53,26 % -57,25 % Gross profit 35,02 % 35,86 % 40,35 % 50,04 % 47,91 % 37,84 % 48,52 % 46,74 % 42,79 % Salary and personnel expenses -15,36 % -15,86 % -14,88 % -14,31 % -13,51 % -15,55 % -13,77 % -12,93 % -14,52 % Other operating expenses -9,25 % -10,33 % -9,94 % -9,44 % -12,80 % -13,91 % -13,29 % -13,04 % -11,50 % EBITDA 10,41 % 9,67 % 15,53 % 26,29 % 21,61 % 8,38 % 21,45 % 20,76 % 16,76 % Depreciation -5,62 % -5,08 % -4,72 % -4,24 % -4,13 % -4,35 % -3,93 % -3,76 % -4,48 % Write downs and impairment losses -0,09 % -11,71 % -2,56 % -0,03 % -0,42 % 0,00 % -0,33 % -0,09 % -1,90 % EBIT 4,71 % -7,11 % 8,25 % 22,01 % 17,06 % 4,02 % 17,19 % 16,91 % 10,38 % Tax on core operations -1,87 % -1,74 % -1,58 % -5,86 % -4,00 % -2,13 % -4,99 % -5,71 % -3,49 % NOPAT 2,83 % -8,86 % 6,67 % 16,15 % 13,06 % 1,90 % 12,20 % 11,19 % 6,89 %
151 | P a g e
MHG Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 335 328 326 623 327 100 295 683 343 685 392 306 343 772 418 873 Growth -2,60 % 0,15 % -9,60 % 16,23 % 14,15 % -12,37 % 21,85 %
MHG Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Revenue 4184 % 4129 % 4433 % 5138 % 4694 % 3942 % 5585 % 6095 % 4775 % Income/loss from associated companies 20 % 2 % 21 % 68 % -2 % 23 % 65 % 36 % 29 % Net revenue 4203 % 4131 % 4454 % 5206 % 4692 % 3964 % 5649 % 6131 % 4804 % Changes in inventories (unfinished and finished products) -12 % 24 % 0 % 0 % 0 % 0 % 0 % 0 % 1 % Purchase of goods -2719 % -2674 % -2657 % -2601 % -2444 % -2464 % -2908 % -3265 % -2717 % Gross profit 1472 % 1481 % 1797 % 2605 % 2248 % 1500 % 2741 % 2866 % 2089 % Salary and personnel expenses -646 % -655 % -663 % -745 % -634 % -617 % -778 % -793 % -691 % Other operating expenses -389 % -427 % -443 % -492 % -600 % -552 % -751 % -800 % -557 % EBITDA 438 % 399 % 692 % 1368 % 1014 % 332 % 1212 % 1273 % 841 % Depreciation -236 % -210 % -210 % -221 % -194 % -173 % -222 % -231 % -212 % Write downs and impairment losses -4 % -484 % -114 % -2 % -19 % 0 % -19 % -6 % -81 % EBIT 198 % -294 % 368 % 1146 % 800 % 159 % 971 % 1036 % 548 % Tax on core operations -79 % -72 % -70 % -305 % -188 % -84 % -282 % -350 % -179 % NOPAT 119 % -366 % 297 % 841 % 613 % 75 % 689 % 686 % 369 %
MHG Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses 100 104 97 98 100 98 108 117 Deferred tax assets 100 854 202 439 593 274 662 546 Goodwill 100 67 64 63 64 63 71 72 Other intangible assets 100 118 100 98 91 84 139 123 Property, plant and equipment 100 109 90 100 107 106 171 212 Investments in associated companies (2008) - 100 101 132 122 126 175 190 Other non-current assets (2011) - - - - 100 284 34 56 Total non-current assets 100 101 91 95 99 97 126 143
Current assets Inventory 100 117 81 85 85 89 191 262 Biological assets 100 101 96 131 113 112 172 180 Accounts receivables 100 101 89 98 102 95 169 178 Other receivables 100 80 83 122 91 89 163 166 Total current assets 100 101 92 119 106 104 173 187
Non-interest-bearing debt Deferred tax liabilities 100 61 95 187 196 212 280 297 Accounts payables 100 128 99 107 110 108 165 151 Other long-term liabilities 100 86 73 419 73 304 716 1 711 Other short-term liabilities 100 267 116 123 130 163 217 343 Current tax liabilities (2009) - - 100 98 170 52 497 1 034 Total non-interest-bearing debt 100 139 102 151 145 165 245 322
Operating working capital 100 76 85 98 81 64 125 98
Invested capital net operating assets 100 94 89 96 94 87 126 129
152 | P a g e
MHG Common-Size Analysis (Invested Capital) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses 30,26 % 33,36 % 32,95 % 30,81 % 32,39 % 33,84 % 26,09 % 27,37 % 30,88 % Deferred tax assets 0,15 % 1,33 % 0,33 % 0,67 % 0,93 % 0,46 % 0,77 % 0,62 % 0,66 % Goodwill 18,18 % 12,96 % 13,05 % 11,95 % 12,46 % 13,17 % 10,26 % 10,15 % 12,77 % Other intangible assets 0,74 % 0,93 % 0,83 % 0,75 % 0,71 % 0,71 % 0,81 % 0,70 % 0,77 % Property, plant and equipment 21,17 % 24,55 % 21,43 % 21,99 % 24,21 % 25,60 % 28,86 % 34,69 % 25,31 % Investments in associated companies 0,00 % 2,97 % 3,17 % 3,84 % 3,63 % 4,03 % 3,89 % 4,11 % 3,21 % Other non-current assets 0,00 % 0,00 % 0,00 % 0,00 % 0,15 % 0,46 % 0,04 % 0,06 % 0,09 % Total non-current assets 70,49 % 76,09 % 71,76 % 70,03 % 74,49 % 78,27 % 70,73 % 77,71 % 73,70 %
Current assets Inventory 4,99 % 6,22 % 4,52 % 4,39 % 4,55 % 5,10 % 7,57 % 10,09 % 5,93 % Biological assets 30,19 % 32,51 % 32,60 % 41,20 % 36,50 % 38,65 % 41,22 % 42,07 % 36,87 % Accounts receivables 10,24 % 11,01 % 10,19 % 10,44 % 11,12 % 11,10 % 13,79 % 14,12 % 11,50 % Other receivables 3,63 % 3,08 % 3,36 % 4,63 % 3,54 % 3,69 % 4,70 % 4,67 % 3,91 % Total current assets 49,04 % 52,82 % 50,66 % 60,66 % 55,72 % 58,54 % 67,28 % 70,94 % 58,21 %
Non-interest-bearing debt Deferred tax liabilities 6,52 % 4,24 % 6,96 % 12,67 % 13,66 % 15,84 % 14,54 % 14,99 % 11,18 % Accounts payables 7,34 % 10,00 % 8,16 % 8,21 % 8,61 % 9,04 % 9,65 % 8,57 % 8,70 % Other long-term liabilities 0,74 % 0,68 % 0,61 % 3,23 % 0,58 % 2,58 % 4,22 % 9,81 % 2,81 % Other short-term liabilities 4,93 % 14,00 % 6,39 % 6,30 % 6,86 % 9,19 % 8,50 % 13,08 % 8,65 % Current tax liabilities 0,00 % 0,00 % 0,31 % 0,28 % 0,50 % 0,16 % 1,09 % 2,21 % 0,57 % Total non-interest-bearing debt 19,53 % 28,92 % 22,43 % 30,69 % 30,20 % 36,81 % 38,01 % 48,65 % 31,90 %
Operating working capital 29,51 % 23,91 % 28,24 % 29,97 % 25,51 % 21,73 % 29,27 % 22,29 % 26,30 %
Invested capital net operating assets 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 %
MHG Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 335 328 326 623 327 100 295 683 343 685 392 306 343 772 418 873 Growth -2,60 % 0,15 % -9,60 % 16,23 % 14,15 % -12,37 % 21,85 %
MHG Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses 1660 % 1765 % 1654 % 1841 % 1623 % 1385 % 1756 % 1555 % 1655 % Deferred tax assets 8 % 71 % 17 % 40 % 47 % 19 % 52 % 35 % 36 % Goodwill 997 % 686 % 655 % 714 % 624 % 539 % 691 % 577 % 685 % Other intangible assets 41 % 49 % 42 % 45 % 36 % 29 % 55 % 40 % 42 % Property, plant and equipment 1161 % 1299 % 1076 % 1314 % 1213 % 1048 % 1942 % 1971 % 1378 % Investments in associated companies 0 % 157 % 159 % 230 % 182 % 165 % 262 % 234 % 173 % Other non-current assets 0 % 0 % 0 % 0 % 8 % 19 % 3 % 3 % 4 % Total non-current assets 3867 % 4027 % 3602 % 4183 % 3731 % 3204 % 4760 % 4416 % 3974 %
Current assets Inventory 274 % 329 % 227 % 262 % 228 % 209 % 509 % 573 % 326 % Biological assets 1656 % 1721 % 1636 % 2461 % 1829 % 1582 % 2774 % 2391 % 2006 % Accounts receivables 562 % 583 % 511 % 624 % 557 % 454 % 928 % 802 % 628 % Other receivables 199 % 163 % 169 % 276 % 177 % 151 % 316 % 265 % 215 % Total current assets 2691 % 2796 % 2543 % 3624 % 2791 % 2397 % 4528 % 4031 % 3175 %
Non-interest-bearing debt Deferred tax liabilities 358 % 224 % 349 % 757 % 684 % 648 % 979 % 852 % 606 % Accounts payables 403 % 529 % 410 % 490 % 431 % 370 % 649 % 487 % 471 % Other long-term liabilities 41 % 36 % 31 % 193 % 29 % 106 % 284 % 557 % 159 % Other short-term liabilities 271 % 741 % 321 % 376 % 343 % 376 % 572 % 743 % 468 % Current tax liabilities 0 % 0 % 16 % 17 % 25 % 7 % 73 % 125 % 33 % Total non-interest-bearing debt 1071 % 1530 % 1126 % 1833 % 1513 % 1507 % 2558 % 2765 % 1738 %
Operating working capital 1619 % 1265 % 1417 % 1791 % 1278 % 890 % 1970 % 1267 % 1437 %
Invested capital net operating assets 5487 % 5292 % 5019 % 5974 % 5010 % 4094 % 6730 % 5682 % 5411 %
153 | P a g e
Lerøy Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Operating revenues 100 96 119 141 146 145 171 200 Other operating gains (2013) ------100 218 Income from associated companies 100 39 177 344 56 70 541 259 Net revenue 100 96 119 142 145 144 174 202 Cost of materials 100 91 110 117 132 138 150 180 Change in inventories - - 100 -98 236 43 191 331 Gross Profit 100 110 153 209 205 165 260 294 Salaries and other personnel costs 100 115 119 134 167 178 189 219 Other operating costs 100 123 124 147 182 181 213 267 EBITDA 100 95 211 334 261 139 370 391 Depreciation 100 128 133 143 177 190 200 240 Impairment loss (2012) - - - - - 100 17 6 EBIT 100 83 240 404 292 112 430 445 Tax on core operations 100 86 253 427 337 122 398 431 NOPAT 100 82 235 397 277 109 441 449
Lerøy Common-Size Analysis (Net Revenue) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Operating revenues 99,44 % 99,77 % 99,17 % 98,65 % 99,79 % 99,73 % 97,77 % 98,36 % 99,08 % Other operating gains 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,49 % 0,92 % 0,18 % Income from associated companies 0,56 % 0,23 % 0,83 % 1,35 % 0,21 % 0,27 % 1,75 % 0,72 % 0,74 % Net revenue 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % Cost of materials -74,27 % -70,49 % -68,70 % -60,82 % -67,25 % -71,21 % -63,94 % -66,08 % -67,84 % Change in inventories 0,00 % 0,00 % 1,79 % -1,47 % 3,46 % 0,63 % 2,35 % 3,50 % 1,28 % Gross Profit 25,73 % 29,51 % 33,09 % 37,71 % 36,21 % 29,42 % 38,41 % 37,42 % 33,44 % Salaries and other personnel costs -9,15 % -10,94 % -9,16 % -8,63 % -10,52 % -11,30 % -9,94 % -9,94 % -9,95 % Other operating costs -7,46 % -9,54 % -7,79 % -7,68 % -9,33 % -9,35 % -9,12 % -9,87 % -8,77 % EBITDA 9,11 % 9,03 % 16,15 % 21,40 % 16,36 % 8,76 % 19,35 % 17,61 % 14,72 % Depreciation -2,43 % -3,25 % -2,71 % -2,44 % -2,96 % -3,20 % -2,79 % -2,89 % -2,83 % Impairment loss 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % -0,36 % -0,05 % -0,02 % -0,05 % EBIT 6,68 % 5,78 % 13,44 % 18,96 % 13,40 % 5,20 % 16,51 % 14,71 % 11,84 % Tax on core operations -1,65 % -1,47 % -3,51 % -4,95 % -3,82 % -1,39 % -3,77 % -3,52 % -3,01 % NOPAT 5,03 % 4,31 % 9,93 % 14,01 % 9,58 % 3,81 % 12,74 % 11,19 % 8,83 %
154 | P a g e
Lerøy Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 99 000 104 000 116 000 127 300 136 672 153 403 144 784 158 258 Growth 5,05 % 11,54 % 9,74 % 7,36 % 12,24 % -5,62 % 9,31 %
Lerøy Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Operating revenues 6354 % 5824 % 6443 % 6982 % 6715 % 5934 % 7435 % 7949 % 6704 % Other operating gains 0 % 0 % 0 % 0 % 0 % 0 % 37 % 74 % 14 % Income from associated companies 36 % 13 % 54 % 96 % 14 % 16 % 133 % 58 % 53 % Net revenue 6390 % 5837 % 6497 % 7078 % 6729 % 5950 % 7605 % 8081 % 6771 % Cost of materials -4746 % -4115 % -4463 % -4305 % -4525 % -4237 % -4862 % -5340 % -4574 % Change in inventories 0 % 0 % 116 % -104 % 233 % 37 % 178 % 282 % 93 % Gross Profit 1644 % 1723 % 2150 % 2669 % 2437 % 1751 % 2921 % 3024 % 2290 % Salaries and other personnel costs -585 % -639 % -595 % -611 % -708 % -673 % -756 % -803 % -671 % Other operating costs -477 % -557 % -506 % -543 % -628 % -557 % -694 % -798 % -595 % EBITDA 582 % 527 % 1049 % 1514 % 1101 % 521 % 1472 % 1423 % 1024 % Depreciation -155 % -189 % -176 % -173 % -199 % -190 % -212 % -233 % -191 % Impairment loss 0 % 0 % 0 % 0 % 0 % -22 % -4 % -1 % -3 % EBIT 427 % 337 % 873 % 1342 % 902 % 310 % 1256 % 1188 % 829 % Tax on core operations -105 % -86 % -228 % -350 % -257 % -83 % -287 % -284 % -210 % NOPAT 322 % 252 % 645 % 992 % 645 % 227 % 969 % 904 % 619 %
Lerøy Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Deferred tax asset (2009) - - 100 83 147 483 265 947 Licences, rights and goodwill (immaterial assets) 100 105 104 136 137 140 141 150 Buildings, land and operating assets 100 113 107 138 160 182 207 233 Long-term receivables 100 921 1 752 1 194 1 241 1 264 3 843 4 738 Shares in associated companies 100 96 94 117 114 114 254 196 Total non-current assets 100 106 105 135 142 150 167 177
Current assets Biological assets 100 112 124 181 159 182 249 246 Other inventories 100 84 89 110 124 123 135 198 Pension assets 100 88 ------Accounts receivable 100 112 127 147 135 144 215 207 Other receivables 100 73 59 80 67 91 144 138 Total current assets 100 106 116 157 142 159 221 222
Non-interest bearing debt Accounts payable 100 107 121 126 139 163 208 207 Deferred tax liabilities 100 104 130 196 168 191 231 238 Public duties payable 100 130 148 197 165 177 275 186 Pension liabilities 100 110 125 75 65 64 27 57 Taxes payable 100 22 123 519 423 117 421 440 Other short-term liabilities 100 130 152 205 180 146 193 261 Total non-interest-bearing debt 100 104 129 188 172 171 228 237
Operating working capital 100 108 101 120 107 145 211 205
Invested capital net operating assets 100 107 104 132 134 149 177 183
155 | P a g e
Lerøy Common-Size Analysis (Invested Capital) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Deferred tax asset 0,00 % 0,00 % 0,08 % 0,05 % 0,09 % 0,26 % 0,12 % 0,42 % 0,13 % Licences, rights and goodwill (immaterial assets) 51,44 % 50,41 % 51,73 % 52,92 % 52,60 % 48,31 % 40,91 % 42,01 % 48,79 % Buildings, land and operating assets 20,87 % 22,05 % 21,42 % 21,82 % 24,90 % 25,47 % 24,39 % 26,56 % 23,43 % Long-term receivables 0,01 % 0,11 % 0,21 % 0,11 % 0,11 % 0,10 % 0,27 % 0,32 % 0,16 % Shares in associated companies 5,26 % 4,73 % 4,77 % 4,66 % 4,46 % 4,03 % 7,54 % 5,62 % 5,13 % Total non-current assets 77,58 % 77,30 % 78,21 % 79,56 % 82,17 % 78,18 % 73,22 % 74,93 % 77,64 %
Current assets Biological assets 27,14 % 28,55 % 32,49 % 37,22 % 32,15 % 33,14 % 38,24 % 36,53 % 33,18 % Other inventories 4,81 % 3,80 % 4,13 % 3,99 % 4,45 % 3,97 % 3,68 % 5,21 % 4,25 % Pension assets 0,01 % 0,01 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % Accounts receivable 12,55 % 13,16 % 15,31 % 13,94 % 12,67 % 12,10 % 15,25 % 14,17 % 13,64 % Other receivables 3,99 % 2,72 % 2,29 % 2,42 % 2,01 % 2,42 % 3,24 % 3,00 % 2,76 % Total current assets 48,50 % 48,23 % 54,22 % 57,59 % 51,28 % 51,63 % 60,41 % 58,91 % 53,85 %
Non-interest bearing debt Accounts payable 9,23 % 9,28 % 10,77 % 8,78 % 9,56 % 10,05 % 10,87 % 10,45 % 9,87 % Deferred tax liabilities 11,69 % 11,40 % 14,59 % 17,33 % 14,69 % 14,96 % 15,26 % 15,19 % 14,39 % Public duties payable 0,69 % 0,83 % 0,97 % 1,02 % 0,85 % 0,81 % 1,06 % 0,70 % 0,87 % Pension liabilities 0,22 % 0,23 % 0,26 % 0,12 % 0,11 % 0,09 % 0,03 % 0,07 % 0,14 % Taxes payable 1,38 % 0,28 % 1,64 % 5,44 % 4,37 % 1,08 % 3,29 % 3,32 % 2,60 % Other short-term liabilities 2,87 % 3,51 % 4,20 % 4,46 % 3,87 % 2,80 % 3,13 % 4,10 % 3,62 % Total non-interest-bearing debt 26,08 % 25,53 % 32,43 % 37,14 % 33,45 % 29,81 % 33,64 % 33,83 % 31,49 %
Operating working capital 22,42 % 22,70 % 21,79 % 20,44 % 17,83 % 21,82 % 26,78 % 25,07 % 22,36 %
Invested capital net operating assets 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 %
156 | P a g e
Lerøy Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 99 000 104 000 116 000 127 300 136 672 153 403 144 784 158 258 Growth 5,05 % 11,54 % 9,74 % 7,36 % 12,24 % -5,62 % 9,31 %
Lerøy Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Deferred tax asset 0 % 0 % 4 % 3 % 5 % 14 % 8 % 27 % 8 % Licences, rights and goodwill (immaterial assets) 2861 % 2846 % 2551 % 3023 % 2838 % 2589 % 2754 % 2676 % 2767 % Buildings, land and operating assets 1161 % 1245 % 1056 % 1246 % 1344 % 1365 % 1642 % 1691 % 1344 % Long-term receivables 1 % 6 % 10 % 6 % 6 % 6 % 18 % 20 % 9 % Shares in associated companies 292 % 267 % 235 % 266 % 241 % 216 % 508 % 358 % 298 % Total non-current assets 4315 % 4364 % 3857 % 4544 % 4434 % 4190 % 4930 % 4772 % 4426 %
Current assets Biological assets 1509 % 1612 % 1602 % 2126 % 1735 % 1776 % 2574 % 2327 % 1908 % Other inventories 268 % 215 % 204 % 228 % 240 % 213 % 248 % 332 % 243 % Pension assets 1 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % Accounts receivable 698 % 743 % 755 % 796 % 684 % 649 % 1027 % 902 % 782 % Other receivables 222 % 154 % 113 % 138 % 109 % 130 % 218 % 191 % 159 % Total current assets 2697 % 2723 % 2674 % 3289 % 2767 % 2768 % 4067 % 3752 % 3092 %
Non-interest bearing debt Accounts payable 513 % 524 % 531 % 501 % 516 % 539 % 732 % 666 % 565 % Deferred tax liabilities 650 % 644 % 720 % 990 % 793 % 802 % 1027 % 968 % 824 % Public duties payable 38 % 47 % 48 % 58 % 46 % 44 % 72 % 44 % 50 % Pension liabilities 12 % 13 % 13 % 7 % 6 % 5 % 2 % 4 % 8 % Taxes payable 77 % 16 % 81 % 310 % 236 % 58 % 221 % 212 % 151 % Other short-term liabilities 160 % 198 % 207 % 254 % 209 % 150 % 211 % 261 % 206 % Total non-interest-bearing debt 1450 % 1441 % 1599 % 2122 % 1805 % 1598 % 2265 % 2155 % 1804 %
Operating working capital 1247 % 1282 % 1075 % 1168 % 962 % 1170 % 1803 % 1597 % 1288 %
Invested capital net operating assets 5562 % 5646 % 4932 % 5712 % 5396 % 5360 % 6732 % 6369 % 5713 %
Grieg Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Sales revenues 100 145 158 239 200 201 235 261 Other income 100 23 19 22 36 61 43 21 Income from associated companies 100 -37 -105 -400 -1 327 48 -118 -151 Net Income 100 140 152 231 196 195 228 251 Change in inventories of work in progress 100 25 77 -5 96 - - - Raw materials and consumables used 100 121 121 125 146 161 130 155 Salaries and personell expenses 100 121 142 175 175 203 222 249 Other operating expenses 100 169 209 301 307 326 343 393 Other gains and losses (2009) - - 100 -954 251 -66 983 79 769 Share of profit from associated companies and JV (2010) - - - 100 289 268 119 211 EBITDA 100 72 144 360 192 -16 252 251 Depreciation 100 146 163 160 189 217 184 187 Amortisation of licenses and other intangible assets 100 379 284 317 279 370 222 452 EBIT 100 23 130 481 193 -161 293 288 Tax on core operations 100 474 574 2 053 657 -728 855 1 004 NOPAT 100 -6 102 381 164 -125 258 242
157 | P a g e
Grieg Common-Size Analysis (Net Revenue) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Sales revenues 95,81 % 99,25 % 99,34 % 99,28 % 98,00 % 98,69 % 99,08 % 99,52 % 98,62 % Other income 4,36 % 0,70 % 0,54 % 0,41 % 0,79 % 1,36 % 0,83 % 0,37 % 1,17 % Income from associated companies -0,18 % 0,05 % 0,12 % 0,31 % 1,20 % -0,04 % 0,09 % 0,11 % 0,21 % Net Income 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % Change in inventories of work in progress 19,30 % 3,47 % 9,74 % -0,42 % 9,47 % 0,00 % 0,00 % 0,00 % 5,19 % Raw materials and consumables used -69,97 % -60,72 % -55,48 % -37,83 % -52,06 % -57,88 % -39,93 % -43,07 % -52,12 % Salaries and personell expenses -12,78 % -11,10 % -11,91 % -9,67 % -11,41 % -13,29 % -12,46 % -12,68 % -11,91 % Other operating expenses -18,45 % -22,35 % -25,29 % -24,05 % -28,90 % -30,92 % -27,82 % -28,92 % -25,84 % Other gains and losses 0,00 % 0,00 % 0,00 % -0,03 % 0,01 % 0,00 % 0,03 % 2,38 % 0,30 % Share of profit from associated companies and JV 0,00 % 0,00 % 0,00 % 0,19 % 0,66 % 0,61 % 0,23 % 0,37 % 0,26 % EBITDA 18,10 % 9,30 % 17,07 % 28,18 % 17,76 % -1,48 % 20,05 % 18,08 % 15,88 % Depreciation -6,80 % -7,13 % -7,29 % -4,70 % -6,56 % -7,56 % -5,50 % -5,06 % -6,32 % Amortisation of licenses and other intangible assets -0,11 % -0,29 % -0,20 % -0,15 % -0,15 % -0,21 % -0,11 % -0,19 % -0,18 % EBIT 11,20 % 1,87 % 9,58 % 23,33 % 11,05 % -9,25 % 14,45 % 12,83 % 9,38 % Tax on core operations -0,67 % -2,29 % -2,54 % -5,99 % -2,26 % 2,52 % -2,53 % -2,69 % -2,06 % NOPAT 10,53 % -0,42 % 7,04 % 17,34 % 8,79 % -6,73 % 11,91 % 10,14 % 7,33 %
Grieg Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 40 461 51 700 48 747 64 214 60 082 70 000 58 061 64 736 Growth 27,78 % -5,71 % 31,73 % -6,43 % 16,51 % -17,06 % 11,50 %
Grieg Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Sales revenues 2525 % 2857 % 3308 % 3810 % 3407 % 2929 % 4141 % 4117 % 3387 % Other income 115 % 20 % 18 % 16 % 28 % 40 % 35 % 15 % 36 % Income from associated companies -5 % 1 % 4 % 12 % 42 % -1 % 4 % 4 % 8 % Net Income 2636 % 2879 % 3330 % 3838 % 3476 % 2968 % 4179 % 4137 % 3430 % Change in inventories of work in progress 509 % 100 % 324 % -16 % 329 % 0 % 0 % 0 % 156 % Raw materials and consumables used -1844 % -1748 % -1847 % -1452 % -1810 % -1718 % -1669 % -1782 % -1734 % Salaries and personell expenses -337 % -319 % -397 % -371 % -397 % -394 % -521 % -525 % -408 % Other operating expenses -486 % -643 % -842 % -923 % -1005 % -918 % -1163 % -1196 % -897 % Other gains and losses 0 % 0 % 0 % -1 % 0 % 0 % 1 % 99 % 12 % Share of profit from associated companies and JV 0 % 0 % 0 % 7 % 23 % 18 % 10 % 15 % 9 % EBITDA 477 % 268 % 568 % 1082 % 617 % -44 % 838 % 748 % 569 % Depreciation -179 % -205 % -243 % -181 % -228 % -224 % -230 % -209 % -212 % Amortisation of licenses and other intangible assets -3 % -8 % -7 % -6 % -5 % -6 % -4 % -8 % -6 % EBIT 295 % 54 % 319 % 895 % 384 % -274 % 604 % 531 % 351 % Tax on core operations -18 % -66 % -85 % -230 % -79 % 75 % -106 % -111 % -77 % NOPAT 277 % -12 % 234 % 666 % 306 % -200 % 498 % 419 % 274 %
158 | P a g e
Grieg Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Goodwill 100 31 63 65 76 76 77 78 Licences, patents, etc 100 98 96 109 116 115 117 125 Property, plant & equipment 100 124 128 145 176 179 188 223 Loan to associated companies 100 83 66 119 34 35 35 2 Investmetns in associated companies and JV 100 106 125 308 344 453 379 385 Long-term receivables 100 17 - 19 3 1 2 - Other intangible assets (2008) - 100 68 39 56 46 55 140 Total non-current assets 100 88 124 162 163 142 181 196
Current assets Biological assets 100 101 128 147 132 123 165 173 Inventories 100 128 141 167 193 188 212 253 Account receivables 100 141 168 237 200 111 159 227 Other current receivables 100 57 67 51 69 61 64 68 Total current assets 100 102 128 149 135 119 160 173
Non-interest-bearing debt Deferred tax liabilities 100 74 118 189 173 152 198 199 Tax payable 100 - - - -69 - 16 539 Pension obligations 100 95 44 47 36 25 14 5 Accounts payable 100 109 118 128 154 125 161 152 Accured salary expense and public tax payable 100 158 161 291 261 229 252 151 Other current liabilites 100 93 283 163 189 211 214 429 Total non-interest-bearing debt 100 88 124 162 163 142 181 196
Operating working capital 100 111 130 140 116 104 145 157
Invested capital net operating assets 100 105 114 126 130 127 143 159
159 | P a g e
Grieg Common-Size Analysis (Invested Capital) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Goodwill 5,72 % 1,71 % 3,18 % 2,96 % 3,33 % 3,41 % 3,09 % 2,81 % 3,28 % Licences, patents, etc 35,06 % 32,56 % 29,72 % 30,27 % 31,24 % 31,70 % 28,64 % 27,60 % 30,85 % Property, plant & equipment 26,37 % 31,09 % 29,74 % 30,18 % 35,64 % 37,04 % 34,69 % 36,88 % 32,70 % Loan to associated companies 0,12 % 0,09 % 0,07 % 0,11 % 0,03 % 0,03 % 0,03 % 0,00 % 0,06 % Investmetns in associated companies and JV 0,45 % 0,45 % 0,49 % 1,09 % 1,18 % 1,60 % 1,19 % 1,09 % 0,94 % Long-term receivables 0,42 % 0,07 % 0,00 % 0,06 % 0,01 % 0,00 % 0,01 % 0,00 % 0,07 % Other intangible assets 0,00 % 0,32 % 0,20 % 0,10 % 0,15 % 0,12 % 0,13 % 0,30 % 0,17 % Total non-current assets 68,14 % 66,30 % 63,41 % 64,79 % 71,59 % 73,90 % 67,78 % 68,68 % 68,07 %
Current assets Biological assets 44,04 % 42,01 % 49,64 % 51,12 % 44,44 % 42,52 % 50,89 % 47,74 % 46,55 % Inventories 1,44 % 1,75 % 1,79 % 1,91 % 2,13 % 2,13 % 2,13 % 2,28 % 1,95 % Account receivables 4,62 % 6,18 % 6,83 % 8,67 % 7,08 % 4,05 % 5,12 % 6,58 % 6,14 % Other current receivables 3,49 % 1,90 % 2,07 % 1,41 % 1,84 % 1,66 % 1,56 % 1,48 % 1,93 % Total current assets 53,59 % 51,83 % 60,33 % 63,11 % 55,49 % 50,36 % 59,70 % 58,08 % 56,56 %
Non-interest-bearing debt Deferred tax liabilities 11,60 % 8,10 % 12,06 % 17,37 % 15,40 % 13,85 % 16,06 % 14,48 % 13,62 % Tax payable 0,39 % 0,00 % 0,00 % 0,00 % -0,20 % 0,00 % 0,04 % 1,31 % 0,19 % Pension obligations 0,18 % 0,16 % 0,07 % 0,07 % 0,05 % 0,04 % 0,02 % 0,01 % 0,07 % Accounts payable 8,14 % 8,40 % 8,48 % 8,28 % 9,59 % 7,99 % 9,15 % 7,78 % 8,48 % Accured salary expense and public tax payable 0,36 % 0,53 % 0,50 % 0,82 % 0,71 % 0,64 % 0,63 % 0,34 % 0,57 % Other current liabilites 1,06 % 0,93 % 2,63 % 1,36 % 1,53 % 1,75 % 1,58 % 2,84 % 1,71 % Total non-interest-bearing debt 21,73 % 18,13 % 23,74 % 27,90 % 27,08 % 24,27 % 27,47 % 26,76 % 24,63 %
Operating working capital 31,86 % 33,70 % 36,59 % 35,21 % 28,41 % 26,10 % 32,22 % 31,32 % 31,93 %
Invested capital net operating assets 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 %
160 | P a g e
Grieg Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 Tons 40 461 51 700 48 747 64 214 60 082 70 000 58 061 64 736 Growth 27,78 % -5,71 % 31,73 % -6,43 % 16,51 % -17,06 % 11,50 %
Grieg Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Goodwill 3,43 0,84 1,80 1,41 1,75 1,50 1,85 1,68 178 % Licences, patents, etc 21,00 16,09 16,79 14,42 16,44 13,95 17,12 16,47 1654 % Property, plant & equipment 15,80 15,36 16,80 14,38 18,75 16,30 20,74 22,01 1752 % Loan to associated companies 0,07 0,05 0,04 0,05 0,02 0,01 0,02 0,00 3 % Investmetns in associated companies and JV 0,27 0,22 0,28 0,52 0,62 0,70 0,71 0,65 50 % Long-term receivables 0,25 0,03 0,00 0,03 0,01 0,00 0,00 0,00 4 % Other intangible assets 0,00 0,16 0,11 0,05 0,08 0,05 0,08 0,18 9 % Total non-current assets 40,82 32,76 35,82 30,87 37,66 32,53 40,52 40,98 3650 %
Current assets Biological assets 26,39 20,76 28,04 24,36 23,38 18,72 30,42 28,49 2507 % Inventories 0,86 0,86 1,01 0,91 1,12 0,94 1,27 1,36 104 % Account receivables 2,77 3,05 3,86 4,13 3,72 1,78 3,06 3,92 329 % Other current receivables 2,09 0,94 1,17 0,67 0,97 0,73 0,93 0,88 105 % Total current assets 32,10 25,62 34,08 30,07 29,20 22,17 35,69 34,66 3045 %
Non-interest-bearing debt Deferred tax liabilities 6,95 4,00 6,81 8,28 8,10 6,10 9,60 8,64 731 % Tax payable 0,23 0,00 0,00 0,00 -0,11 0,00 0,03 0,78 12 % Pension obligations 0,11 0,08 0,04 0,03 0,03 0,02 0,01 0,00 4 % Accounts payable 4,88 4,15 4,79 3,94 5,05 3,52 5,47 4,64 456 % Accured salary expense and public tax payable 0,21 0,26 0,28 0,39 0,37 0,28 0,37 0,20 30 % Other current liabilites 0,63 0,46 1,49 0,65 0,81 0,77 0,94 1,70 93 % Total non-interest-bearing debt 13,02 8,96 13,41 13,29 14,25 10,68 16,43 15,97 1325 %
Operating working capital 19,09 16,66 20,67 16,78 14,95 11,49 19,26 18,69 1720 %
Invested capital net operating assets 59,91 49,42 56,49 47,65 52,61 44,02 59,78 59,67 5369 %
NRS Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Operating revenue 100 117 139 174 150 151 226 226 Other revenue 100 ------Income from associates 100 -191 109 350 -30 185 510 480 Net revenue 100 115 138 174 149 151 226 226 Change in inventory and cost of material 100 114 133 158 140 139 193 196 Gross profit 100 134 234 493 330 387 892 815 Personel expenses 100 146 204 285 364 431 514 627 Other operating expenses 100 163 226 310 319 427 541 721 EBITDA 100 103 263 788 313 323 1 444 1 027 Depreciation and write-downs 100 396 803 2 021 1 676 1 959 2 170 2 665 EBIT 100 80 222 695 210 199 1 389 903 Tax core operations 100 225 -175 907 41 282 1 553 488 NOPAT 100 53 296 655 242 183 1 358 981
161 | P a g e
NRS Common-Size Analysis (Net Revenue) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Operating revenue 99,05 % 100,81 % 99,62 % 99,02 % 100,10 % 99,40 % 98,90 % 98,97 % 99,48 % Other revenue 0,46 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,06 % Income from associates 0,49 % -0,81 % 0,38 % 0,98 % -0,10 % 0,60 % 1,10 % 1,03 % 0,46 % Net revenue 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % Change in inventory and cost of material -95,23 % -94,45 % -91,93 % -86,49 % -89,43 % -87,78 % -81,21 % -82,81 % -88,67 % Gross profit 4,77 % 5,55 % 8,07 % 13,51 % 10,57 % 12,22 % 18,79 % 17,19 % 11,33 % Personel expenses -1,43 % -1,82 % -2,11 % -2,35 % -3,50 % -4,09 % -3,25 % -3,98 % -2,82 % Other operating expenses -1,44 % -2,04 % -2,35 % -2,56 % -3,08 % -4,07 % -3,43 % -4,59 % -2,94 % EBITDA 1,90 % 1,69 % 3,60 % 8,60 % 3,99 % 4,06 % 12,10 % 8,63 % 5,57 % Depreciation and write-downs -0,13 % -0,46 % -0,78 % -1,55 % -1,50 % -1,74 % -1,28 % -1,58 % -1,13 % EBIT 1,76 % 1,23 % 2,83 % 7,05 % 2,49 % 2,33 % 10,82 % 7,05 % 4,44 % Tax core operations -0,28 % -0,55 % 0,35 % -1,45 % -0,08 % -0,52 % -1,91 % -0,60 % -0,63 % NOPAT 1,48 % 0,69 % 3,18 % 5,60 % 2,41 % 1,80 % 8,91 % 6,45 % 3,81 %
NRS Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 NRS Farming 4 400 5 195 6 828 10 667 18 781 21 162 25 191 22 356 External volumes 35 100 39 500 40 700 39 000 32 000 36 500 37 000 36 754 Tons 39 500 44 695 47 528 49 667 50 781 57 662 62 191 59 110 Growth 13,15 % 6,34 % 4,50 % 2,24 % 13,55 % 7,85 % -4,95 %
NRS Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Operating revenue 2917 % 3019 % 3372 % 4031 % 3415 % 3025 % 4187 % 4398 % 3545 % Other revenue 14 % 0 % 0 % 0 % 0 % 0 % 0 % 0 % 2 % Income from associates 14 % -24 % 13 % 40 % -3 % 18 % 46 % 46 % 19 % Net revenue 2945 % 2995 % 3385 % 4071 % 3411 % 3043 % 4233 % 4444 % 3566 % Change in inventory and cost of material -2805 % -2828 % -3112 % -3521 % -3051 % -2671 % -3438 % -3680 % -3138 % Gross profit 140 % 166 % 273 % 550 % 361 % 372 % 795 % 764 % 428 % Personel expenses -42 % -54 % -71 % -96 % -119 % -124 % -138 % -177 % -103 % Other operating expenses -42 % -61 % -80 % -104 % -105 % -124 % -145 % -204 % -108 % EBITDA 56 % 51 % 122 % 350 % 136 % 124 % 512 % 383 % 217 % Depreciation and write-downs -4 % -14 % -26 % -63 % -51 % -53 % -54 % -70 % -42 % EBIT 52 % 37 % 96 % 287 % 85 % 71 % 458 % 313 % 175 % Tax core operations -8 % -16 % 12 % -59 % -3 % -16 % -81 % -27 % -25 % NOPAT 44 % 21 % 108 % 228 % 82 % 55 % 377 % 287 % 150 %
162 | P a g e
NRS Index Analysis (2007) 2007 2008 2009 2010 2011 2012 2013 2014 CORE OPERATIONS Non-current assets Licenses 100 257 292 366 369 369 369 476 Property, plant and equipment 100 401 499 963 1498 1512 1779 2443 Investments in associated 100 90 94 102 86 99 119 134 Other long-term receivables 100 121 208 73 73 90 60 58 Loans to associated companies 100 12 ------Total non-current assets 100 185 209 267 285 292 311 399
Current assets Inventory 100 247 160 253 314 347 450 671 Biological assets 100 172 352 531 534 723 879 1113 Short-term receivables 100 103 141 177 163 192 289 359 Total current assets 100 127 204 284 277 353 469 590
Non-interest-bearing debt Deferred tax liabilities 100 216 219 354 314 331 473 557 Pension liabilities 100 107 106 101 111 118 135 245 Accounts payable 100 109 193 272 235 313 409 455 Tax payable 100 - - 38 - 26 278 68 Other current liabilities 100 396 201 218 181 340 520 2050 Total non-interest-bearing debt 100 153 194 282 246 305 418 548
Operating working capital 100 76 224 289 336 447 565 671
Invested capital net operating assets 100 160 213 272 297 328 370 463
NRS Common-Size Analysis (Invested Capital) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses 38,18 % 61,56 % 52,33 % 51,28 % 47,40 % 42,96 % 38,05 % 39,29 % 46,38 % Property, plant and equipment 3,32 % 8,34 % 7,78 % 11,73 % 16,71 % 15,28 % 15,93 % 17,50 % 12,07 % Investments in associated 31,29 % 17,68 % 13,82 % 11,75 % 9,06 % 9,47 % 10,05 % 9,09 % 14,03 % Other long-term receivables 1,45 % 1,10 % 1,42 % 0,39 % 0,35 % 0,40 % 0,24 % 0,18 % 0,69 % Loans to associated companies 2,37 % 0,18 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,00 % 0,32 % Total non-current assets 76,60 % 88,85 % 75,35 % 75,14 % 73,52 % 68,12 % 64,27 % 66,07 % 73,49 %
Current assets Inventory 1,68 % 2,60 % 1,27 % 1,57 % 1,78 % 1,78 % 2,05 % 2,44 % 1,89 % Biological assets 20,36 % 21,97 % 33,72 % 39,72 % 36,56 % 44,92 % 48,37 % 48,97 % 36,82 % Short-term receivables 46,55 % 30,03 % 30,79 % 30,33 % 25,53 % 27,21 % 36,39 % 36,09 % 32,87 % Total current assets 68,59 % 54,60 % 65,77 % 71,62 % 63,87 % 73,90 % 86,81 % 87,50 % 71,58 %
Non-interest-bearing debt Deferred tax liabilities 13,73 % 18,54 % 14,13 % 17,87 % 14,49 % 13,84 % 17,53 % 16,52 % 15,83 % Pension liabilities 2,15 % 1,44 % 1,07 % 0,79 % 0,80 % 0,77 % 0,78 % 1,13 % 1,12 % Accounts payable 26,23 % 17,88 % 23,79 % 26,17 % 20,72 % 25,00 % 28,98 % 25,82 % 24,32 % Tax payable 0,84 % 0,00 % 0,00 % 0,12 % 0,00 % 0,07 % 0,63 % 0,12 % 0,22 % Other current liabilities 2,25 % 5,59 % 2,13 % 1,80 % 1,37 % 2,34 % 3,16 % 9,98 % 3,58 % Total non-interest-bearing debt 45,19 % 43,45 % 41,12 % 46,75 % 37,39 % 42,02 % 51,08 % 53,57 % 45,07 %
Operating working capital 23,40 % 11,15 % 24,65 % 24,86 % 26,48 % 31,88 % 35,73 % 33,93 % 26,51 %
Invested capital net operating assets 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 % 100,00 %
163 | P a g e
NRS Harvest Volume 2007 2008 2009 2010 2011 2012 2013 2014 NRS Farming 4 400 5 195 6 828 10 667 18 781 21 162 25 191 22 356 External volumes 35 100 39 500 40 700 39 000 32 000 36 500 37 000 36 754 Tons 39 500 44 695 47 528 49 667 50 781 57 662 62 191 59 110 Growth 13,15 % 6,34 % 4,50 % 2,24 % 13,55 % 7,85 % -4,95 %
NRS Common-Size Analysis (Kilograms) 2007 2008 2009 2010 2011 2012 2013 2014 Average CORE OPERATIONS Non-current assets Licenses 3097 % 6750 % 5822 % 4671 % 2678 % 2376 % 1996 % 2903 % 3787 % Property, plant and equipment 269 % 914 % 865 % 1068 % 944 % 845 % 836 % 1293 % 879 % Investments in associated 2538 % 1939 % 1538 % 1070 % 512 % 524 % 527 % 672 % 1165 % Other long-term receivables 118 % 120 % 158 % 35 % 20 % 22 % 12 % 13 % 62 % Loans to associated companies 192 % 19 % 0 % 0 % 0 % 0 % 0 % 0 % 26 % Total non-current assets 6214 % 9743 % 8383 % 6845 % 4153 % 3768 % 3372 % 4881 % 5920 %
Current assets Inventory 136 % 285 % 141 % 143 % 100 % 98 % 107 % 180 % 149 % Biological assets 1652 % 2410 % 3751 % 3618 % 2065 % 2484 % 2538 % 3617 % 2767 % Short-term receivables 3776 % 3293 % 3426 % 2763 % 1443 % 1505 % 1909 % 2666 % 2598 % Total current assets 5565 % 5987 % 7318 % 6524 % 3608 % 4088 % 4554 % 6463 % 5513 %
Non-interest-bearing debt Deferred tax liabilities 1114 % 2033 % 1572 % 1628 % 819 % 765 % 920 % 1220 % 1259 % Pension liabilities 174 % 158 % 119 % 72 % 45 % 43 % 41 % 84 % 92 % Accounts payable 2128 % 1961 % 2647 % 2384 % 1171 % 1383 % 1520 % 1907 % 1888 % Tax payable 68 % 0 % 0 % 11 % 0 % 4 % 33 % 9 % 16 % Other current liabilities 183 % 613 % 237 % 164 % 78 % 129 % 166 % 737 % 288 % Total non-interest-bearing debt 3666 % 4765 % 4575 % 4259 % 2112 % 2324 % 2680 % 3957 % 3542 %
Operating working capital 1898 % 1223 % 2743 % 2265 % 1496 % 1763 % 1874 % 2506 % 1971 %
Invested capital net operating assets 8113 % 10965 % 11126 % 9110 % 5649 % 5531 % 5246 % 7387 % 7891 %
Appendix 11 – SalMar credit analysis
Adj. Key Industrial Financial Ratios AAA AA A BBB BB B CCC EBIT interest coverage ratio 21,4 10,1 6,1 3,7 2,1 0,8 0,1 EBITDA interest coverage ratio 26,5 12,9 9,1 5,8 3,4 1,8 1,3 Free operating Cash flow/total debt 84,2 25,2 15 8,5 2,6 -3,2 -12,9 FFO/Total debt 128,8 55,4 43,2 38,8 18,8 7,8 1,6 Return on capital 34,9 21,7 19,4 13,6 11,6 6,6 1 Operating income/revenue 24,7 22,1 18,6 15,4 15,9 11,9 11,9 Long-term debt/capital 13,3 28,2 33,9 42,5 57,2 69,7 68,8 Total debt/Capital 22,9 37,7 42,5 48,2 62,6 74,8 87,7
Adj. Key Industrial Financial Ratios 2007 2008 2009 2010 2011 2012 2013 2014 EBIT interest coverage ratio 9,78 4,97 20,00 23,26 7,28 2,89 8,43 15,90 EBITDA interest coverage ratio 10,85 5,74 22,44 25,19 8,63 4,03 9,78 18,14 Free operating Cash flow/total debt 21,45 % 14,73 % 25,73 % 26,19 % 13,41 % 7,65 % 25,52 % 29,44 % FFO/Total debt 19,17 % 6,48 % 21,22 % 25,64 % 0,36 % 6,68 % 34,44 % 18,79 % Return on capital 15,84 % 11,24 % 19,18 % 20,58 % 11,29 % 6,23 % 18,19 % 19,74 % Operating income/revenue 26,95 % 20,79 % 26,36 % 32,26 % 18,32 % 10,11 % 22,13 % 27,12 % Long-term debt/capital 57,72 % 57,04 % 53,11 % 62,08 % 60,40 % 54,17 % 53,36 % 46,44 % Total debt/Capital 73,86 % 76,28 % 74,54 % 78,56 % 84,23 % 81,51 % 71,28 % 67,05 % 164 | P a g e
Adj. Key Industrial Financial Ratios 2007 2008 2009 2010 2011 2012 2013 2014 EBIT interest coverage ratio A BBB AA AAA A BB A AA EBITDA interest coverage ratio A BB AA AA BBB BB BBB AA Free operating Cash flow/total debt A BBB AA AA BBB BB AA AA FFO/Total debt BB B BB BB CCC CCC BB BB Return on capital BBB B AA AA B CCC BBB AA Operating income/revenue AA A AA AAA BBB CCC AA AAA Long-term debt/capital BB BB BB BB BBB BB BB BB Total debt/Capital BB B BB B B B BB BB
Adj. Key Industrial Financial Ratios 2007 2008 2009 2010 2011 2012 2013 2014 EBIT interest coverage ratio 2 3 1 0 2 4 2 1 EBITDA interest coverage ratio 2 4 1 1 3 4 3 1 Free operating Cash flow/total debt 2 3 1 1 3 4 2 1 FFO/Total debt 4 5 4 4 6 6 4 4 Return on capital 3 5 1 1 5 6 3 1 Operating income/revenue 1 2 1 0 3 6 1 0 Long-term debt/capital 4 4 4 4 3 4 4 4 Total debt/Capital 4 5 4 5 5 5 4 4 Average rating 2,75 3,875 2,125 2 3,75 4,875 2,875 2 Rating A BBB A A BBB BB A A Risk-free rate 4,78 % 4,47 % 4,00 % 3,52 % 3,12 % 2,10 % 2,58 % 2,52 % Spread 2,95 % 4,35 % 1,08 % 0,80 % 3,90 % 10,20 % 3,33 % 0,80 % Cost of debt 5,57 % 6,35 % 3,65 % 3,11 % 5,05 % 8,86 % 4,31 % 2,42 % Average 4,92 %
Number Rating Score Rating High Low 0 AAA 0,99 AAA 1,9 0,6 1 AA 1,99 AA 2,4 0,7 2 A 2,99 A 3,6 0,8 3 BBB 3,99 BBB 4,7 1,3 4 BB 4,99 BB 11,2 2,6 5 B 5,99 B 13,1 3,2 6 CCC 6,99
165 | P a g e
Appendix 12 – SalMar pro forma financial statements
Short-Term Medium-Term Long-Term Pro Forma Income Statement (NOK 1000) E2015 E2016 E2017 E2018 E2019 Terminal CORE OPERATIONS Sales revenue 8 016 514 7 876 640 7 770 810 7 912 572 8 229 075 8 394 456 Other operating revenues 31 730 32 841 33 990 35 248 36 658 37 394 Income from associated companies 139 464 144 345 149 397 154 925 161 122 164 360 Net revenue 8 187 708 8 053 826 7 954 197 8 102 744 8 426 854 8 596 210 Change in stock of goods in progress and finished goods 169 414 175 344 181 481 188 196 195 724 199 657 Cost of goods sold -3 811 126 -4 028 230 -4 169 218 -4 323 479 -4 496 418 -4 586 783 Gross profit 4 545 996 4 200 940 3 966 460 3 967 461 4 126 160 4 209 084 Salaries and payroll expenses -742 399 -768 383 -795 277 -824 702 -857 690 -874 927 Other operating expenses -1 356 152 -1 487 331 -1 539 388 -1 596 345 -1 660 199 -1 693 564 EBITDA 2 447 445 1 945 225 1 631 796 1 546 414 1 608 271 1 640 592 Depreciation of PP&E -277 325 -287 032 -297 078 -308 070 -320 393 -326 832 Write down of PP&E and other intangible assets -2 413 -2 497 -2 584 -2 680 -2 787 -2 843 EBIT 2 167 707 1 655 696 1 332 133 1 235 664 1 285 091 1 310 917 Tax core operations -498 217 -380 539 -306 172 -284 000 -295 360 -301 296 NOPAT 1 669 490 1 275 158 1 025 961 951 664 989 731 1 009 621
NON-CORE OPERATIONS Other interest income 7 346 8 935 9 248 9 571 9 925 10 322 Other financial income 80 781 98 248 101 686 105 245 109 139 113 505 Interest expenses 119 957 145 895 151 001 156 286 162 069 168 551 Other financial expenses -18 768 -22 826 -23 625 -24 452 -25 356 -26 371 Net financial profit/loss 189 316 230 251 238 310 246 651 255 777 266 008 Net non-core operations 189 316 230 251 238 310 246 651 255 777 266 008 Corporate tax rate (Norway) 0,27 0,27 0,27 0,27 0,27 0,27 Tax non-core operating items (tax shield) -51 115 -62 168 -64 344 -66 596 -69 060 -71 822 Net Income 1 807 690 1 443 241 1 199 927 1 131 719 1 176 448 1 203 807
166 | P a g e
Short-Term Medium-Term Long-Term Pro Forma Balance Sheet (NOK 1000) E2015 E2016 E2017 E2018 E2019 Terminal CORE OPERATIONS Non-current assets Licenses, patents, etc. 2 436 134 2 521 398 2 609 647 2 706 204 2 814 453 2 871 015 Goodwill 502 232 519 810 538 004 557 910 580 226 591 887 Property, plant and equipment 1 600 006 1 656 007 1 713 967 1 777 384 1 848 479 1 885 628 Investments in associated companies and joint ventures 931 070 963 657 997 385 1 034 288 1 075 660 1 097 277 Other long-term receivables 14 748 15 265 15 799 16 383 17 039 17 381 Total non-current assets 5 484 190 5 676 137 5 874 802 6 092 170 6 335 856 6 463 189
Current assets Biological assets (unfinished products) 2 774 268 2 871 367 2 971 865 3 081 824 3 205 097 3 269 510 Pension fund assets 4 309 4 460 4 616 4 787 4 979 5 079 Inventories (raw materials and finished products) 262 022 271 193 280 685 291 070 302 713 308 796 Accounts receivable 690 619 714 791 739 809 767 181 797 869 813 904 Receviable from parent company 246 254 263 273 284 289 Other current receivables 226 271 234 191 242 388 251 356 261 410 266 664 Total current assets 3 957 735 4 096 256 4 239 625 4 396 491 4 572 351 4 664 242
Non-interest-bearing debt Deferred tax liabilities 1 278 050 1 322 782 1 369 079 1 419 735 1 476 525 1 506 199 Accounts payable 564 221 583 969 604 408 626 771 651 842 664 942 Pension liabilities 4 774 4 942 5 115 5 304 5 516 5 627 Tax payable 179 487 185 769 192 271 199 385 207 361 211 528 Public duties payable 81 807 84 671 87 634 90 876 94 512 96 411 Other current liabilities 202 948 210 051 217 403 225 447 234 465 239 177 Total non-interest-bearing debt 2 311 289 2 392 184 2 475 910 2 567 519 2 670 220 2 723 883
Operating working capital 1 646 447 1 704 072 1 763 715 1 828 972 1 902 131 1 940 359
Invested capital net operating assets 7 130 637 7 380 209 7 638 517 7 921 142 8 237 987 8 403 548
Equity primo 5 137 277 4 332 402 4 484 036 4 640 977 4 812 693 5 005 201 Net income 1 807 690 1 443 241 1 199 927 1 131 719 1 176 448 1 203 807 Dividends -2 612 566 -1 291 607 -1 042 986 -960 003 -983 940 -1 103 217 Equity ultimo 4 332 402 4 484 036 4 640 977 4 812 693 5 005 201 5 105 791 Net interest-bearing debt 2 798 235 2 896 173 2 997 539 3 108 448 3 232 786 3 297 756 Invested capital net financial assets 7 130 637 7 380 209 7 638 517 7 921 142 8 237 987 8 403 548
Short-Term Medium-Term Long-Term Capital Expenditures (CAPEX) (NOK 1000) E2015 E2016 E2017 E2018 E2019 Terminal Total non-current assets primo -5 453 332 -5 484 190 -5 676 137 -5 874 802 -6 092 170 -6 335 856 Depreciation of PP&E 277 325 287 032 297 078 308 070 320 393 326 832 Write down of PP&E and other intangible assets (impairment losses)2 413 2 497 2 584 2 680 2 787 2 843 Total non-current assets ultimo 5 484 190 5 676 137 5 874 802 6 092 170 6 335 856 6 463 189 CAPEX 310 596 481 476 498 327 528 118 566 867 457 008
167 | P a g e
Short-Term Medium-Term Long-Term Pro Forma Cash Flow Statement (NOK 1000) E2015 E2016 E2017 E2018 E2019 Terminal NOPAT 1 669 490 1 275 158 1 025 961 951 664 989 731 1 009 621 Depreciation of PP&E 277 325 287 032 297 078 308 070 320 393 326 832 Write down of PP&E and other intangible assets (impairment losses)2 413 2 497 2 584 2 680 2 787 2 843 Change in net operating working capital 338 245 -57 626 -59 643 -65 257 -73 159 -38 227 CAPEX -310 596 -481 476 -498 327 -528 118 -566 867 -457 008 Free cash flow to firm (FCFF) 1 976 877 1 025 585 767 654 669 039 672 885 844 061 Change in net interest-bearing debt 497 488 97 938 101 366 110 909 124 338 64 970 Net financial profit/loss 189 316 230 251 238 310 246 651 255 777 266 008 Tax non-core operations (tax shield) -51 115 -62 168 -64 344 -66 596 -69 060 -71 822 Free cash flow to equity (FCFE) 2 612 566 1 291 607 1 042 986 960 003 983 940 1 103 217 Dividends -2 612 566 -1 291 607 -1 042 986 -960 003 -983 940 -1 103 217 Cash surplus 0 0 0 0 0 0
Appendix 13 – Forecasted cost of capital SalMar 13.1 – Regression beta summary statistics
SalMar Regression Summary REGRESSION STATISTICS Multiple R 0,4566 R Square 0,2085 Adjusted R Square 0,2000 Standard Error 0,0796 Observations 95
ANOVA df SS MS F Significance F Regression 1 0,1553 0,1553 24,5005 0,0000033 Residual 93 0,5895 0,0063 Total 94 0,7448
CoefficientsStandard Error t Stat P-value Lower 95% Upper 95% Intercept 0,0154 0,0082 1,8862 0,0624 -0,0008 0,0317 X Variable 1 0,6192 0,1251 4,9498 0,0000 0,3708 0,8676
168 | P a g e
13.2 – Fundamental beta analysis
SalMar Fundamental Beta Analysis Risk Level SalMar´s Ability To Manage Risk OPERATING RISK External risk Biological conditions Medium Medium ability to influence sanitary conditions, high emergency response harvest capacity Legislations Medium Highly regulated industry, yet some influence can be exercised regarding legislation
Strategic risk Rivalery amongst competitors High Few large players controling the industry, high pressure on margins Suppliers power High Low ability to manage risks related costs of input factors such as feed (55-60% of production costs) Customer power High Homogenous product which can easily be bough from competitors at low switching cost Market growth Low Stagnating growth due to governmental constraints Substitute products High High number of substituting products at lower prices (poultry, swine, beef) Threat of entry Low High finacial and legal barriers
Operational risk Exploiting production facilities Low Industry leading production facilities Quality management Medium Homogenous product, salmon enjoys high quality image, harvest alert Choice of cost structure Medium Cost leader
Total assesment of operating risk High Cost side hard to predict and influence, good strategic position, operational excellence . FINANCIAL RISK Salmon Price High Solely dependend on salmon price, low inflence, 46% sold on fixed-price contracts in 2014 Feed prices High Financial leverage Low Historical debt ratio of ~25% Access to capital Easy borrowing due to low debt ratio and macro environment. But no bonds in the market Variable interest rate Low Interest-bearing debt on floating rates subject to fluctuations, but stable and low rates Short term to maturity Low Sufficient liquidity to handle short-term debt Currency Low Most revenue,costs and debt in NOK
Total assesment of financial risk Low Low debt ratio, high liquidity, insignificant currency issues
Total risk Neutral High operating risk and low financial risk implies a neutral beta of 0.85 - 1.15
169 | P a g e
13.2 – WACC forecast
Short-Term Medium-Term Long-Term SalMar Cost of Capital (NOK 1000) E2015 E2016 E2017 E2018 E2019 Terminal Equity Unlevered beta 0,60 0,60 0,60 0,60 0,60 0,60 Levered beta 0,88 0,88 0,88 0,88 0,88 0,88 Risk-free rate 1,65 % 1,65 % 1,65 % 1,65 % 1,65 % 3,39 % Market risk premium 5,75 % 5,75 % 5,75 % 5,75 % 5,75 % 5,75 % Liquidity risk premium N/A N/A N/A N/A N/A N/A Cost of equity (Re) 6,70 % 6,70 % 6,70 % 6,70 % 6,70 % 8,44 %
Debt Interest rate according to credit rating 4,92 % 4,92 % 4,92 % 4,92 % 4,92 % 4,92 % Interest rate historical average 5,51 % 5,51 % 5,51 % 5,51 % 5,51 % 5,51 % Rd (average of credit rating and historical) 5,21 % 5,21 % 5,21 % 5,21 % 5,21 % 5,21 %
Capital structure Pro forma book value of equity 4 332 402 4 484 036 4 640 977 4 812 693 5 005 201 5 105 791 Pro forma book value of debt 2 798 235 2 896 173 2 997 539 3 108 448 3 232 786 3 297 756 Pro forma book value of enterprise 7 130 637 7 380 209 7 638 517 7 921 142 8 237 987 8 403 548 Equity ratio 60,76 % 60,76 % 60,76 % 60,76 % 60,76 % 60,76 % Debt ratio 39,24 % 39,24 % 39,24 % 39,24 % 39,24 % 39,24 % Debt/Equity 64,59 % 64,59 % 64,59 % 64,59 % 64,59 % 64,59 %
Corporate tax rate 27,00 % 27,00 % 27,00 % 27,00 % 27,00 % 27,00 %
Weighted average cost of capital (WACC) 5,56 % 5,56 % 5,56 % 5,56 % 5,56 % 6,62 %
170 | P a g e
Appendix 14 – Monte Carlo simulation 14.1 Full simulation
Crystal Ball-rapport - fullstendig Simuleringen startet den 26.06.2015 klokken 00:57 Simuleringen stoppet den 26.06.2015 klokken 01:00
Kjørepreferanser: Antall prøver som er kjørt 100 000 Monte Carlo Tilfeldig seed Presisjonskontroll på Konfidensnivå 95,00 %
Kjøretidsstatistikk: Total kjøretid (sek) 184,71 Prøver per sekund (gjennomsnitt) 541 Tilfeldige tall per sek 18 949
Crystal Ball-data: Forutsetninger 35 Korrelasjoner 0 Korrelasjonsmatriser 0 Beslutningsvariabler 0 Prognoser 1
Prognose r
Prognose: Share price 1/5/2015 Celle: C49
Sammendrag: Hele området er fra -44,68 til 792,09 Basistilfellet er 145,62 Etter 100 000 prøver er standardfeilen for gjennomsnittet 0,18
171 | P a g e
Statistikk: Prognoseverdier Prøver 100 000 Basistilfelle 145,62 Gjennomsnitt 150,75 Median 145,72 Modus --- Standardavvik 57,27 Varians 3 279,53 Skjevhet 0,8071 Kurtose 5,16 Varianskoeffisient 0,3799 Minimum -44,68 Maksimum 792,09 Områdebredde 836,76 Gjennomsnittlig standardfeil 0,18
Prognose: Share price 1/5/2015 (forts.) Ce lle : C49
Persentiler: Prognoseverdier 0% -44,68 10% 83,53 20% 103,90 30% 119,08 40% 132,71 50% 145,72 60% 159,16 70% 174,05 80% 193,22 90% 222,71 100% 792,09
Slutt på prognoser
172 | P a g e
Forutse tninge r
Regneark: [Masterblaster MC.xlsx]Forecast
Forutse tning: E2015 Celle: K346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
Forutse tning: E2016 Ce lle : L346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
Forutse tning: E2017 Celle: M346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
Forutse tning: E2018 Celle: N346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
173 | P a g e
Forutse tning: E2019 Celle: O346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
Forutse tning: K330 Celle: K330
Triangulær fordeling med parametre: Minimum 158 266 Mest sannsynlig 161 766 Maksimum 165 266
Forutse tning: K342 Celle: K342
Triangulær fordeling med parametre: Minimum 44,60 Mest sannsynlig 49,56 Maksimum 54,51
Forutse tning: K347 Celle: K347
Triangulær fordeling med parametre: Minimum -25,92 Mest sannsynlig -23,56 Maksimum -21,20
174 | P a g e
Forutse tning: K348 Celle: K348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
Forutse tning: K349 Celle: K349
Triangulær fordeling med parametre: Minimum -9,22 Mest sannsynlig -8,38 Maksimum -7,55
Forutse tning: L330 Ce lle : L330
Triangulær fordeling med parametre: Minimum 163 928 Mest sannsynlig 167 428 Maksimum 170 928
Forutse tning: L342 Ce lle : L342
Triangulær fordeling med parametre: Minimum 42,34 Mest sannsynlig 47,04 Maksimum 51,75
175 | P a g e
Forutse tning: L347 Ce lle : L347
Triangulær fordeling med parametre: Minimum -26,47 Mest sannsynlig -24,06 Maksimum -21,65
Forutse tning: L348 Ce lle : L348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
Forutse tning: L349 Ce lle : L349
Triangulær fordeling med parametre: Minimum -9,77 Mest sannsynlig -8,88 Maksimum -8,00
Forutse tning: M330 Celle: M330
Triangulær fordeling med parametre: Minimum 169 788 Mest sannsynlig 173 288 Maksimum 176 788
176 | P a g e
Forutse tning: M342 Celle: M342
Triangulær fordeling med parametre: Minimum 40,36 Mest sannsynlig 44,84 Maksimum 49,33
Forutse tning: M347 Celle: M347
Triangulær fordeling med parametre: Minimum -26,47 Mest sannsynlig -24,06 Maksimum -21,65
Forutse tning: M348 Celle: M348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
Forutse tning: M349 Celle: M349
Triangulær fordeling med parametre: Minimum -9,77 Mest sannsynlig -8,88 Maksimum -8,00
177 | P a g e
Forutse tning: N330 Celle: N330
Triangulær fordeling med parametre: Minimum 176 199 Mest sannsynlig 179 699 (=N330) Maksimum 183 199
Forutse tning: N342 Celle: N342
Triangulær fordeling med parametre: Minimum 39,63 Mest sannsynlig 44,03 Maksimum 48,44
Forutse tning: N347 Celle: N347
Triangulær fordeling med parametre: Minimum -26,47 Mest sannsynlig -24,06 Maksimum -21,65
Forutse tning: N348 Celle: N348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
178 | P a g e
Forutse tning: N349 Celle: N349
Triangulær fordeling med parametre: Minimum -9,77 Mest sannsynlig -8,88 Maksimum -8,00
Forutse tning: O330 Celle: O330
Triangulær fordeling med parametre: Minimum 183 387 Mest sannsynlig 186 887 Maksimum 190 387
Forutse tning: O342 Celle: O342
Triangulær fordeling med parametre: Minimum 39,63 Mest sannsynlig 44,03 Maksimum 48,44
Forutse tning: O347 Celle: O347
Triangulær fordeling med parametre: Minimum -26,47 Mest sannsynlig -24,06 Maksimum -21,65
179 | P a g e
Forutse tning: O348 Celle: O348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
Forutse tning: O349 Celle: O349
Triangulær fordeling med parametre: Minimum -9,77 Mest sannsynlig -8,88 Maksimum -8,00
Forutse tning: P330 Celle: P330
Triangulær fordeling med parametre: Minimum 187 143 Mest sannsynlig 190 643 Maksimum 194 143
Forutse tning: P347 Celle: P347
Triangulær fordeling med parametre: Minimum -26,47 Mest sannsynlig -24,06 Maksimum -21,65
180 | P a g e
Forutse tning: P348 Celle: P348
Triangulær fordeling med parametre: Minimum -5,05 Mest sannsynlig -4,59 Maksimum -4,13
Forutse tning: P349 Celle: P349
Triangulær fordeling med parametre: Minimum -9,77 Mest sannsynlig -8,88 Maksimum -8,00
Forutse tning: T e rmina l Celle: P346
Triangulær fordeling med parametre: Minimum 0,94 Mest sannsynlig 1,05 Maksimum 1,15
181 | P a g e
14.2 – Probability for share price over NOK 112.50
Prognose : Sha re price 1/5/2015 Ce lle : C49
Sammendrag: Sikkerhetsnivået er 74,522 % Sikkerhetsområdet er fra 112,50 til INF Hele området er fra -44,68 til 792,09 Basistilfellet er 145,62 Etter 100 000 prøver er standardfeilen for gjennomsnittet 0,18
182 | P a g e
14.3 – Probability for share price between NOK 130 and 160
Prognose : Sha re price 1/5/2015 Ce lle : C49
Sammendrag: Sikkerhetsnivået er 22,644 % Sikkerhetsområdet er fra 130,00 til 160,00 Hele området er fra -44,68 til 792,09 Basistilfellet er 145,62 Etter 100 000 prøver er standardfeilen for gjennomsnittet 0,18
183 | P a g e