Valuation of A.P. Møller - Mærsk A/S - The impact of a conglomerate discount

Copenhagen Business School

Master Thesis

Authors: Simon Tjessem (AEF) and Henrik Tveiterås (AEF)

Supervisor: Tim Mondorf

Number of standard pages: 109

Number of characters: 160 446

Executive summary

Executive summary The primary objective of this thesis has been to estimate the theoretical share price of A.P. Møller – Mærsk A/S (APMM) through a sum-of-the-parts valuation of APMM as of 1st of April 2016. The stock of a company engaged in multiple unrelated business segments typically trades below the combined value of its separate entities – a phenomenon known as the conglomerate discount. The effects of being a conglomerate thus need to be accounted for when estimating the theoretical share price of the sum-of- the-parts.

APMM is a Danish business conglomerate founded in 1904 with a long and proud history, which operates in global trade, shipping, and energy. It employs some 89.000 employees and has activities in more than 130 countries. Its core business comprises eight business units; Maersk Line, APM Terminals, Maersk Oil, Maersk Drilling, Maersk Supply Services, Maersk Tankers, Svitzer, and Damco. In recent years, APMM has divested several companies such as Maersk FPSOs, Maersk LNG, Danish Supermarket, and most recently its share in Danske Bank, which makes the company significantly more focused than few years ago.

We valued each of the core business units using a fundamental analysis and discounted cash flow approach. Other assets and liabilities that were not a part of the eight reportable business segments were valued at book value, whereas eliminations and other unallocated activities were valued with a Gordon Growth model.

The sum-of-the-parts valuation yielded a theoretical share price of 10.700 DKK, above the trading price of 8.455 DKK. However, the sensitivity analysis revealed that the fundamental value of APMM is highly sensitive to external factors such as freight rates and the oil price.

By analyzing APMM through the lens of conglomerate diversification, we found it unlikely that the benefits of diversification outweigh the costs, and a conglomerate discount in the range of 5-15% is warranted. The exact number of the discount is, however, hard to pinpoint, illustrated by the wide range of supporting arguments from the empirical literature. Even amongst equity analysts, who have a significant influence on the actual trading price, there does not seem to be any consensus as into how and why a conglomerate discount should be applied.

In light of the likely presence of a conglomerate discount we recommend a hold position for APMM.

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Contents Executive summary ...... 1 1.0 Introduction ...... 5 1.1 Context and motivation ...... 5 1.2 Problem Formulation ...... 6 1.3 Methodology ...... 9 2.0 Theory of the Conglomerate Discount ...... 12 2.1 Conglomerate perspectives ...... 12 2.1.1 Three dominating rationales for the conglomerate structure ...... 13 2.1.2 Best owner perspective ...... 14 2.1.3 Costs of the conglomerate structure ...... 16 2.2 Is the conglomerate structure creating or destroying value? ...... 16 3.0 Theoretical Framework ...... 17 3.1 Strategic Analysis ...... 17 3.1.1 PESTEL ...... 17 3.1.2 Porter’s Five Forces ...... 18 3.1.3 VRIO ...... 18 3.1.4 SWOT ...... 19 3.2 Financial Analysis ...... 19 3.2.1 Credit analysis ...... 19 3.3 Cost of Capital ...... 20 3.3.1 Cost of Debt ...... 20 3.3.2 Cost of Equity ...... 21 3.3.3 Capital Structure ...... 22 3.4 Valuation ...... 23 3.4.1 Pro forma statements ...... 23 3.4.2 Discounted Cash Flow model ...... 23 3.4.3 Relative Valuation ...... 24 4.0 A.P. Møller - Maersk A/S ...... 26 4.1 History ...... 26 4.2 Historical performance ...... 27

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4.2.1 APMM’s financial performance ...... 27 4.2.2 Share price performance ...... 29 4.3 Economic factors affecting all business units ...... 31 4.4 Credit analysis ...... 33 4.5 Peer groups ...... 35 4.6 Estimating Cost of Capital ...... 36 4.6.1 Cost of Debt ...... 36 4.6.2 Cost of Equity ...... 36 4.6.3 Capital Structure ...... 37 4.6.4 WACC in each business unit ...... 38 5.0 Business Units Valuation ...... 42 5.1 Maersk Line ...... 42 5.1.1 Overview ...... 42 5.1.2 Strategic Analysis ...... 44 5.1.3 Forecasting ...... 50 5.1.4 Valuation ...... 52 5.2 Maersk Oil ...... 55 5.2.1 Overview ...... 55 5.2.2 Strategy ...... 56 5.2.4 Forecast ...... 60 5.2.5 Valuation ...... 62 5.3 APM Terminals ...... 64 5.3.1 Overview ...... 64 5.3.2 Strategy ...... 65 5.3.3 Financial analysis ...... 67 5.3.4 Forecasting ...... 68 5.3.6 Valuation ...... 70 5.4 Maersk Drilling ...... 72 5.4.1 Overview ...... 72 5.4.2 Strategy ...... 73 5.4.4 Forecast ...... 78 5.4.5 Valuation ...... 80

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5.5 APM Shipping Services ...... 82 5.5.1 Maersk Tankers ...... 82 5.5.2 Maersk Supply Service ...... 85 5.5.3 Damco ...... 88 5.5.4 Svitzer ...... 91 6.0 SWOT...... 95 7.0 Sum-of-the-parts ...... 96 7.1 Aggregated reportable segments ...... 96 7.2 Reportable segment adjustments ...... 97 7.3 Sum-of-the-parts value ...... 99 8.0 Conglomerate Discount Discussion...... 101 8.1 APMM in the perspective of conglomerate theory ...... 101 9.0 Conclusion ...... 107 10.0 Thesis in perspective ...... 108 11.0 References ...... 110 12.0 Appendix ...... 117

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1.0 Introduction

1.1 Context and motivation A.P. Møller - Maersk (APMM) is a conglomerate mainly focusing on shipping and energy headquartered in Copenhagen, Denmark with operations in some 130 countries. The group owns the world’s largest container carrier, Maersk Line, and is one of the world’s largest container terminal operators. It is furthermore active in oil exploration & production, tanker, drilling, offshore supply vessels and other shipping segments (APMM, 2015a).

APMM has a long history as a huge conglomerate but has now become more and more focused on a smaller group of core segments. The group has now defined its five core business units (BUs) as; Maersk Line, Maersk Oil, APM Terminals, Maersk Drilling and APM Shipping services, the latter which combines the four business units Maersk Supply Service, Svitzer, Maersk Tankers and Damco. For the rest of this thesis, we treat the eight business units independently.

Through APMM’s history equity analyst have used a wide range of conglomerate discounts, both over time and amongst themselves. APMM’s management argues they do not believe a discount should be present, and aim to be a premium conglomerate trading above the value of its parts. However, equity analysts still argue for a conglomerate discount.

The main goal of this thesis is to do a thorough sum-of-the-parts (SOTP) discounted cash flow (DCF) valuation of APMM to find its fundamental value. Does this fundamental value imply the presence of a conglomerate discount when compared to today’s trading price? Moreover, would such a discount be supported by current theory?

Our motivation for writing this thesis is based on numerous factors. We find a business valuation to be a good way of applying and further exploring theoretical knowledge acquired through our master studies. A multi-business, multi-national company is both challenging and exciting due to its complexity and to the broad range of activities. Furthermore, we find the concept of conglomerate discounts and the seemingly contradicting viewpoints by both theorists and practitioner as interesting.

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1.2 Problem Formulation The primary objective of this thesis is to determine the fundamental value of APMM, and further look for evidence of a conglomerate discount. We will seek to provide a thorough SOTP-valuation by doing a DCF analysis on each of the conglomerate’s business units. The problem statement will be covered in the following research question:

"What is the theoretical share price of APMM as of 1st of Apr 2016,

and are there indications of the stock trading at a conglomerate discount?"

In addition, we have identified specific sub-questions with the purpose of guiding for the primary research, as presented below.

Theory of the conglomerate discount We start with reviewing the theory of corporate diversification and why some theorists argue for a conglomerate discount.

● What is the rationale behind corporate diversification? ● What are the costs of being a conglomerate?

Theoretical Framework The SOTP-valuations requires a theoretical framework. We identify the relevant theories and briefly describe how they work. It should be noted several of the strategic frameworks are basic, but are used to assure all relevant factors have been covered. In our analysis, these models will often not be mentioned explicitly, but rather used indirectly to identify the factors discussed.

● What are the relevant theories necessary to determine the fundamental value of APMM?

APMM at a corporate level In order to understand APMM’s current situation as a conglomerate and how it is likely to develop, it is also a prerequisite to understand the company’s history, other market characteristics and the internal factors of the conglomerate.

● How has APMM developed and performed historically? ● What are the external and internal characteristics of APMM likely to affect performance?

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Valuation Each business unit of APMM will have a separate section where its fundamental value will be determined. A comprehensive analysis of external and internal factors affecting future cash flow will be performed, which will create the basis for the forecasted performance. Appropriate discount rates will be applied to determine the fundamental value of each BU.

● What are the main factors influencing future performance of each BU? ● What are the appropriate business unit’s discount rates representing the opportunity cost for investors? ● What is the fundamental value of each business unit and how sensitive is it to its input?

Sum-of-the-parts-valuation and SWOT In addition to the aggregated value of each reportable business unit, there are cost and revenue items related to corporate functions, which still are not accounted for. We will evaluate the aggregated performance, and identify the key strength, weaknesses, opportunities and threats (SWOT) for APMM.

● What adjustments are needed for the aggregate business units to represent APMM as a whole? ● What are the SWOT’s of APMM? ● How sensitive is our fundamental value to its input?

Conglomerate discussion In order to evaluate whether a conglomerate discount should be present we evaluate APMM in relation to the theory earlier identified.

 How does APMM fit into the theory of corporate diversification?  What is the conglomerate discount in the view of equity analysts?  What is the conglomerate discount in the view of APMM’s management?

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The sub-questions identified in the problem statement section make up for the structure of our thesis and is also shown graphically below in Figure 1.

Figure 1 - Structure of the thesis

Source: Compiled by authors.

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1.3 Methodology The following section seeks to explain the methodology and approaches applied in the thesis. A wide range of theories, models and sources has been used to evaluate APMM. The thesis is based on a post- positivistic mindset, meaning we are considering ourselves realists and as well as searching for causal explanations to derive APMMs fundamental value (Guba, 1990, pp.17–27). We acknowledge researchers and their methods imply inherent weaknesses and biases. We therefore try to correct or minimize some of these triangulating multiple data types and sources to settle upon APMMs fundamental value and how it is affected by conglomerate diversification (Tracy, 2013).

When answering the research- and sub-questions, a deductive method has been used, where theory has been contributing to the structure of the thesis, and data have been collected on the basis of the theory (Ghauri & Greønhaug, 2002). The theories conducted will vary in use within the different business units as well as on a corporate level, to be able to focus on the most important aspects.

Data collection and criticism of sources The theoretical foundation of this paper is based on academic literature from well-recognized sources. For the parts relating to the valuation process our most important theoretical sources have been Damodaran, Koller et al., and Petersen & Plenborg. The main conglomerate section sources are Koller et al. and Sudarsanam.

This thesis is written from an investor's perspective. In the process, only data from publicly available sources has been used, classified as secondary data, as the authors have not collected it (Bryman & Bell, 2011). This includes both quantitative data, e.g. annual reports and stock prices, and qualitative data, e.g. books, articles, investor presentations, press releases, news articles, and other official information on the internet. Since this data is public, we consider the credibility as high, as the companies are responsible for publishing correct information.

APMM’s annual reports have been prepared in accordance with International Financial Reporting Standards (IFRS), and thus the reported numbers should not be too misleading. However, even if we assume the information provided by APMM has a low degree of manipulation, the reported data from annual reports, investor presentations, etc. might be skewed in the direction of what the company wants to portray. E.g. choosing the numbers of years for an average, while another would have portrayed a more negative picture. Additionally, the data is not very transparent on business unit level, which has given some complications when using the data. As Maersk only started releasing accounting

Page 9 of 158 1.0 Introduction data on a segmented level five years ago, we have applied data from 2011-2015, unless otherwise stated.

A conglomerate's accounting can obscure the performance of the conglomerate's business units. The profitability measure ROIC stated by APMM will be used, even if this sometimes differ from own computations. This is due to the limited information to compute the adjusted and correct ROIC, where we assume APMM’s numbers to me more correct due to their extensively more detailed information. When assuming underlying net operating profit after tax is NOPAT fewer impairment losses/sales and reversal of impairment/sales, the difference between ROIC calculated by authors vs. APMM is smaller. We thus use APMM’s own ROIC in the historical period from 2011-2015.

While traditional financial statements do not separate operations and investments in operations from financing activities, APMM has done so in their segmented financial statements. Unfortunately, the disaggregated data on segment level which is publicly available is at a fairly aggregated level and is thus not ideal for analyzing on a deeper level, e.g. disaggregated cost segments. APMM does not distribute its long-term debt per business unit and we assume distributing net interest bearing debt according to the weighted share of invested capital.

The SOTP valuation is conducted by breaking down the company into individual businesses followed by valuing each business, as it is more likely to generate a more accurate estimate. A multi-business, multi- national company will often have segments with quite different economics. I.e. if a company with a fast growing segment has higher capital returns than a slower growing segment we will expect the corporate return on invested capital to increase as the weights of the different segments change. Valuing the entire company as a single entity will thus not provide an accurate estimate, and you will generate more insights by valuing each segment and adding them up to estimate the value of the entire company (Koller et al., 2015, pp.375).

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Furthermore, we have used analysis from financial analysis companies to verify our own. These companies have access to a lot of data and information through databases, advanced computer programs and often possess a lot of industry knowledge, which should make these sources credible.

The cut-off date for share price and information used in this thesis is set April 1st,2016. Hence, no information after this date will be considered. All market data such as stock prices and financial analysis of peers has been obtained from Bloomberg.

Due to the current downturn in several of APMM’s markets, some of the BU’s will have most of its present value from the terminal period. The underlying uncertainty in forecasting substantially many years ahead is however also significant, and the authors have chosen six years as a cut off as we do not believe that a longer forecasting period will provide any extra value. In our analysis, we have also assumed no major acquisitions or divestments.

If necessary, further assumptions and delimitations will be taken throughout the thesis. In general, it is assumed the reader is familiar with the common terminology of finance and economics. The glossary and abbreviations used in the thesis are presented in Appendix 1.

Page 11 of 158 2.0 Theory of the Conglomerate Discount

2.0 Theory of the Conglomerate Discount The debate whether conglomerates should be attributed a discount to its aggregated parts has kept on going for years. This section will investigate the theoretical rationale behind conglomerations and the opposing arguments for applying a discount.

History In the 1960s, the US experienced a significant increase in mergers and acquisitions (M&A) activity, known as the conglomerate wave. The M&As were mostly unrelated, aiming at achieving growth through diversification into new operating markets. Around twenty years later, a partial reversal of the conglomeration emerged, where firms started divesting and downsizing their business, moving focus to core operations and obtaining greater competitive advantages (Sudarsanam, 2003). During the conglomerate wave, a multi-divisional structure organization started, where daily operations were decentralized while strategic planning was kept centralized. The different business units were given much autonomy and were separated in terms of cost and profit, held responsible for their performance.

There exists vast empirical research on the effect of conglomerate diversification. The literature has been mainly negative in its assessment of conglomerations. Amongst the early ones, Berger & Ofek, (1995) documented that conglomerates exhibit a negative excess value of 10-15%. A conglomerate discount was also supported by research from Servaes (1996) and Lang & Stulz (1994). Campa and Kedia, (2002) and Villalonga, (2004) however found no evidence of the conglomerate discount when they accounted for the endogeneity which occurred when corporate diversification strategies were accounted for. McKinsey&Company, (2012) also found that average total returns to shareholder were lower for conglomerates, but more interestingly that the upside gains were limited as it is unlikely that all of a diverse conglomerate’s businesses will outperform at the same time. Conglomerates are unlikely to generate unexpected returns as it usually is made up of relatively mature businesses while the downside is not limited, as the performance of more mature businesses can fall a lot further than it can rise.

2.1 Conglomerate perspectives While most research has shown evidence of a conglomerate discount, economic and managerial theories offer several perspectives that might serve as explanations as to why companies might gain from having a conglomerate structure.

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2.1.1 Three dominating rationales for the conglomerate structure The economic perspective approaches an argument where diversified companies are better positioned to take advantage of different business cycles in different sectors. By cross-subsidizing, conglomerates can transfer funds from businesses at the top of their cycle to businesses in sectors at the bottom of their cycle, outcompeting single-business peers. In total, this will create value in diversification through increased market power. A drawback is said to be this strategy requires some capital market weakness to gain an advantage, and empirical evidence on the market power proposition is limited (Sudarsanam, 2003).

The resource-based perspective argues diversification can be a value-maximizing strategy even if specialization is generally efficient, as the diversifying acquirer redeploys excess of its resources and capabilities to its acquired target (Sudarsanam, 2003). These resources are tangible and intangible assets owned or controlled by the firm, while capabilities are organizational competencies allowing the company to make effective use of its resources (Sudarsanam, 2003). Opposing evidence shows firms who made diversifying acquisitions during the conglomerate wave in the 1960s achieved positive abnormal results when the management of the targeted company was retained (Matsusaka, 1993).

The third perspective is financial-based and may be split into two arguments. Firstly, diversifying reduces the variability of the combined income stream (Lewellen, 1971). The higher the volatility of income and earnings, the higher the risk of default and bankruptcy followed by an increased cost of borrowing, hence an increase in the cost of equity to the firm. The conglomerate can also raise its liabilities while maintaining the same risk profile. With increased borrowings, the firm can gain on the tax shield by reducing taxable income with increased interest expenses. However, when examining the S&P 500 companies between 1997 and 2007, Koller et al., (2010) never came across diversified companies systematically using more debt than their peers.

The second argument of the financial perspective is that the conglomerate serves as a replica of a diversified stock portfolio, where it benefits when transaction costs of investing in a diversified portfolio of stocks are larger than the transaction costs of assembling the conglomerate. However, with a developed financial market this argument is opposing economic theory due to the high transaction costs.

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2.1.2 Best owner perspective A guiding principle for portfolio decisions is that the owner who will create the most value can generate the greatest cash flows from a business. Koller et al., (2015) argues for five different sources of value creation that are dependent on owners. In the following section we identify these and look how the best owner may change over time.

The most direct source of value owners might add is by creating links between businesses within their portfolio. Such links can be made across the value chain, from research and development to manufacturing to distribution to sales. E.g. a company with an already existing distribution network can add value to a startup with no such existing distribution network.

Secondly, better owners may have distinctive functional or managerial skills from which the new business can benefit. Such a skill has to be a key driver of success in the industry, but may reside from anywhere in the business system (e.g. product development, manufacturing processes, and sales and marketing).

Better overall governance of a business is another way better owners can add value. Governance refers to the way the company’s owners, or representatives, interact with the management team to create maximum value in the long term. Kehoe & Heel (2005) studied 60 successful investments by 11 leading private-equity firms and found that in almost two-thirds of the transactions, the primary source of new value was improvement in performance through fruitful interaction between the owners and the management team.

Furthermore, companies acting on their insight into how a market and industry will evolve can be better owners by capitalizing on innovative ideas to expand existing business or develop new ones. Lastly, distinctive access to critical stakeholders such as talent, capital, government, suppliers and customers can benefit companies. However, this is mainly true in emerging markets where several factors complicate running companies such as relatively small pools of managerial talent, undeveloped capital markets, and governments heavily involved in business. In more developed markets, access to talent and capital are rarely an issue to the same extent.

Koller et al., (2015) further argue there exists no static definition of who the best owner is, as the circumstances of businesses change over time. E.g. through a lifecycle we can see founders coming up with the idea, a venture capital firm providing capital and professional management, and a large corporation accelerate the company’s growth through its global distribution capabilities.

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This implies executives must continually identify and develop or acquire companies where they could be the best owner, and divest businesses where they have less to contribute than another potential owner. A study by McKinsey of 200 large U.S. companies over a 10-year period showed companies with a passive portfolio approach, those who did not sell businesses or only sold poor businesses under pressure, underperformed relative to companies with an active portfolio approach (Brandimarte, Fallon, & McNish, 2001).

Marakon, (2011) analyzed S&P 500, distinguishing between pure plays and diversified companies. 25% of S&P 500 was considered diversified into multiple industries. Furthermore, total shareholder return between the two groups was compared (2001-2011). Pure play companies performed 2.2pp better (2001-2006) when growth was valued more than risk, while the diversified companies performed 1.5pp better (2006-2011), probably due to their reduced risk profile during the recession, pure play companies performed better. In total, diversified companies performed better, however only 0.1pp.

In the same report, market/book and forward P/E using 2012 estimates multiples yielded mixed results; diversified companies trade at a 10% higher market/book ratio and a 10% lower P/E ratio. The latter multiple is more sensitive to growth, making sense given the world economy recovery. In summary, the data did not show pure plays outperforming diversified companies over time. However, when conducting a cross-sectional analysis of S&P 500, Marakon (2011) found an average of 6% discount to SOTP of the diversified companies.

Conglomerates are usually significantly larger than pure play companies. When including business units with lower correlation to each other, volatility in earnings decreases. In total, Marakon, (2011) found the volatility being reduced by 50% over what it would be for each business as a stand-alone company. Hence, management can take more risk in one of its businesses and deploy more capital.

Research has shown the stock market consistently reacts positively to both sales and spin-offs (Mulherin & Boone, 2000), but some executives may be focused on empire building and feel like divestitures look like an admission of failure. Cusatis, Miles, & Woolridge, (1994) found research spun-off businesses tended to increase profit margins by one-third during the three years after the transactions were complete.

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2.1.3 Costs of the conglomerate structure While the benefits of diversification can be argued to be elusive, the costs are easy to identify. Substantially changing the portfolio of a business involves considerable transaction costs and disruption, and typically takes years to complete. In comparison, investors can diversify their portfolios at a much lower cost and can do so easily many times a year.

Diversified companies also often perform worse than those of its more focused peers, partly explained due to added complexity and bureaucracy. The acquisitions of a conglomerate might be a part of management’s empire building if the motives are driven by maximizing shareholder value or in order to obtain private benefits of control, respectively named incentive- and entrenchment effect (Bennedsen & Nielsen, 2010).

2.2 Is the conglomerate structure creating or destroying value? Koller et al., (2015) argue diversification is intrinsically neither good nor bad. If the company is the best owner for a set of diverse businesses in its portfolio, then its diversification is by definition value creating, and the reverse is also true. They find three ways high-performing conglomerates outperform. Firstly, high-performing conglomerates continually rebalance their portfolios by purchasing companies where they can improve performance. Secondly, they aggressively manage capital allocation across units at the corporate level in order to allocate it across current and new business or investment opportunities, based on their potential for growth and returns on invested capital. Finally, high- performing conglomerates operates with a lean corporate center that restricts its involvement in the management of business units to selecting leaders, allocating capital, vetting strategy, setting performance targets, and monitoring performance.

McKinsey&Company, (2012) argues many executives and boards in developed markets realize how difficult it is to add value to businesses in a conglomerate, and as a result, many pairings have largely disappeared. By the end of 2010, only 22 true conglomerates in the United States remained, and by 2012 three of them had announced they would split up too. Many of the conglomerates which remain obsessed with empire building sacrifice value for growth, or hang on to business that will never prosper (or would perform better in other hands) (Marakon, 2011).

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3.0 Theoretical Framework In this section we explain different theoretical perspectives used in the thesis. It should be noted that in our strategic analysis of the business units the theoretical frameworks will not be used explicitly, but rather used indirectly to identify the most important factors.

3.1 Strategic Analysis The strategic analysis aims to identify the factors affecting APMM’s key value drivers. These factors constitute the fundament for APMM’s profitability and growth prospects when forecasting future earnings.

3.1.1 PESTEL The PESTEL analysis covers political, economic, socio-cultural, technological, legal and environmental factors. It gives a bird’s eye view of the whole environment from many different angles. Covering these factors will achieve a thorough understanding of APMM’s environment (Pestleanalysis.com).

● What are the Political situations in countries where APMM operate and how can it affect the industry? These factors determine to which degree the government may influence the economy or a certain industry. ● What are the prevalent Economic factors? These factors are determinants of an economy’s performance directly impacting a company and have resonating long-term effects. ● How much importance do Social factors have in the market and what are its determinants? These factors examine the social environment of the market, determining factors like population, demographics, and cultural trends. ● What Technological innovations are likely to affect the market structure? These factors may affect the operations of the industry and the market favorably or unfavorably. ● What are the Environmental concerns for the different industries? These factors include all those influencing or are determined by the surrounding environment. ● Are there any current Legislations regulating the industry or can there be any change in the legislations for the industry? There are some laws affecting the business environment in a certain country while there are other policies companies maintain for themselves, e.g. consumer laws, labor laws and safety standards.

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3.1.2 Porter’s Five Forces In 1979, Michael Porter developed a framework to analyze the level of competition within an industry to reveal its profitability. The five forces are threat of new entry, threat from substitutes, bargaining power of suppliers, bargaining power of customers and competitive rivalry. The forces should be considered dynamic, as a change in one force most likely implies a change in another. Together they serve as a useful checklist to understand the main forces and cooperation opportunities within the different industries operated by APMM (HD Uddannelse, 2013).

Figure 2 - Porters Five Forces

Sources: Compiled by authors, HD Uddannelse, (2013)

3.1.3 VRIO VRIO is a useful tool in examining the internal competencies and competitive advantages of a company in order to develop an understanding of the company’s industry independent drivers and capabilities. VRIO is structured into four characteristics, which together determine the competitive potential of a resource or a capability. Each resource can be analyzed by answering the following four questions to each factor (Barney & Hesterly, 2012);

● Value: Does the resource enable APMM to exploit an opportunity and/or neutralize a threat? ● Rarity: Is the resource presently controlled by only a few competing firms? ● Imitability: Do firms without the resource face a cost disadvantage in obtaining or developing it? ● Organization: Are APMM´s other policies and procedures organized to support the production of its valuable, rare, and costly-to-imitate resources?

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3.1.4 SWOT The SWOT analysis summarizes the most important factors of the former internal and external analysis (Petersen & Plenborg, 2012). Internal factors are split into strengths and weaknesses internal to the organization, while external factors are opportunities and threats represented by the external environment. The SWOT analysis seeks to tie the analyses together to aggregate the net impact of the different strategic and financial factors affecting future key value drivers. This allows for a more comprehensive understanding of how APMM is positioned, and which possibilities and challenges the company is facing both on corporate and business unit level.

3.2 Financial Analysis The purpose of the financial analysis is to analyze the historical performance of the different business units by breaking down the components for further analysis. The financial analysis sections later in the thesis will focus on analyzing the historical figures of APMM’s business segments. This will provide invaluable insights to how the company has created value, and being able to understand the key value drivers will help us better forecast future cash flows.

As financing is coordinated at the group level we will also perform a short- and long-term liquidity risk analysis to understand APMM’s financial situation better. This will be important as several of APMM business segments now experience an industry downturn.

3.2.1 Credit analysis The credit analysis investigates a company’s ability to pay its financial obligations promptly, through an assessment of a firm’s financial health based on financial ratios (Petersen & Plenborg, 2012). The credit rating is an evaluation of the creditworthiness of the company. Low creditworthiness may e.g. reduce potential for profitable investment opportunities, increase financial expenses, or lead to a possible bankruptcy. The credit risk is influenced by the company’s ability to generate positive net cash flows, both short- and long-term (Petersen & Plenborg, 2012).

The ratios conducted for the credit analysis describe different aspects of a company’s profitability and risk. The Petersen & Plenborg, (2012) Table 11.3, “Ratings for non-financial corporations”, is used in the analysis in section 4.4.1. The threshold ratios show what is required for industrial firms to achieve a given rating. Ratings from AAA/Aaa to BBB/Baa correspond to an investment grade, where ratings below BBB/Baa correspond to a speculative grade.

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3.3 Cost of Capital In estimating APMM’s fundamental value by the discounted cash flow (DCF) method, it is important to identify the appropriate discount rate representing the opportunity costs of all investors. Shareholders as well as banks and equity investors who provides funds to risky projects are risk averse and want to be compensated for bearing risk. The weighted average cost of capital (WACC) represents the opportunity cost which investors face for investing their funds in one particular business instead of others with similar risk (Koller et al., 2015).

Equation 1 – WACC equation

Source: Compiled by authors, (Petersen & Plenborg, 2012, p. 246)

Each business unit should be valued at its cost of capital as the systematic risk of operating cash flow, and their ability to support debt (Koller et al., 2015). To determine the cost of capital of each business segment we need to know the unit’s target capital structure, its cost of equity, and its cost of borrowing. Finally, as APMM generate cash flow and issue debt in multiple currencies we face the dilemma of currencies with several inflation rates, risk-free rates and discount rates (Damodaran, 2009a).

3.3.1 Cost of Debt The cost of debt is computed by adding the default spread to the risk-free rate and adjusting for any tax benefits generated by interest expenses (Damodaran, 2008).

Equation 2 - Required return on debt

Source: Compiled by authors, (Petersen & Plenborg, 2012, p. 265)

Damodaran (2009, pp.18) raises three aspects when classifying the cost of debt for multinational firms. The first is the risk-free rate, a measure of how much an investor can earn without incurring any risk (Petersen & Plenborg, 2012). The expected return on a zero-beta portfolio will be the theoretically correct estimate, but due to problems with constructing such a portfolio, highly liquid, long-term government securities (10–30 years) are usually used. The risk-free rate can vary across the countries APMM borrows; however, the risk-free rate will always be in the currency of valuation, no matter what

Page 20 of 158 3.0 Theoretical Framework the currency of the actual borrowing is in (Damodaran, 2009, pp.18). The second issue relates to the default spread, which may vary across the different borrowings of the company. Since APMM has a rating, BBB+ by S&P and Baa1 by Moody’s, the rating can be used to compute the default spread (APMM, 2016g). The final issue is which tax rate to use. A solution is using the tax rate of the country where the company is incorporated; Denmark, or using the highest marginal tax rate where the company operates (Damodaran (2009)). The latter is arguably for tax reasons as the interest expenses will be directed to the country having the highest tax rate. However, Plenborg (2012, p265) differ from Damodaran (2009), stating the effective corporate tax rate should be used, being an average of the company’s different corporate taxes. The latter theory will be followed in our analysis later in the thesis.

3.3.2 Cost of Equity The most favored method to calculate the cost of equity is using the Capital Asset Pricing Model (CAPM), (Petersen & Plenborg, 2012):

Equation 3 - Required return on equity

Source: Compiled by authors, (Petersen & Plenborg, 2012, pp. 249)

Systematic risk on equity (Levered beta) According to CAPM, the investors only pay for the risk which cannot be diversified when holding a sufficiently broad portfolio. Beta (β) is a measure of the systematic risk of the stock, whereby the re increases when β increases (Petersen & Plenborg, 2012). By holding a sufficiently broad portfolio of shares, investors only pay for the risk being unable to diversify. Only the systematic risk beta (βe) is priced, illustrated by the equation below.

Equation 4 - Equity Beta

Source: Compiled by authors, (Petersen & Plenborg, 2012, pp.255)

Damodaran, (2009) argues sector betas adjusted for financial leverage are more precise than regression betas. As for a conglomerate at APMM’s size, business units grow at different rates, and a regression beta (reflecting the current mix of business units prior to change over time) will generate distortions in

Page 21 of 158 3.0 Theoretical Framework value. Damodaran, (2016a) has computed betas by sectors for a large range of industries, and we use these sector betas (βa) when computing the costs of equity for each BU. Assuming debt and interest will be paid, the security will carry no market risk and hence βd is assumed zero.

Market risk premium

The market portfolio’s risk premium (MRP) is the difference between market returns rm and returns from risk-free investments rf (Petersen & Plenborg, 2012). It is most often calculated ex-post based on historical excess returns on the stock market. Damodaran (2009a), argues the MRP should reflect the risk faced in each operating country, incorporated through weighting the different MRPs in each country/region by the respective portion of total operating income. Market risk premiums differ for different countries, and Damodaran, (2016b) has made an overview summarizing the latest bond ratings and appropriate default spreads for different countries. We use these when calculating the risk premium by computing the weighted average based on revenues or other measures of presence of the corresponding BU.

3.3.3 Capital Structure In companies where debt is consolidated at the company level, we have two choices (Damodaran, (2009a)). The first is using industry average debt ratio for publicly traded firms in the same corresponding businesses, where the debt ratio can vary between the different businesses of the same firm. However, with this approach the sum of debt across business units will not add up to the total debt outstanding for the company. Second is to assume that the debt ratio is the same across all businesses and using the company cost of debt as the cost for each division. This might lead to skewed estimates if a business unit has very different debt capacity. However, due to their capital intensity, it seems reasonable that most of the APMM business units will carry debt ratios similar to the overall company.

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3.4 Valuation

3.4.1 Pro forma statements The pro forma statement design can be used to apply strategic and financial value drivers to forecast and assure internal coherence of the different statements. The development of pro forma statements is crucial to financial statement analysis and assures pro forma statements articulate, e.g. the bookkeeping is performed properly (Petersen & Plenborg, 2012, pp.181). Financial value drivers are numbers that mirror the company’s underlying performance such as growth, margins and investments ratios. These forecasted drivers are often derived from strategic or operational initiatives that can be undertaken by a company to improve its strategic value drivers. The forecasting ties together the findings from the strategic and financial analysis to form realistic projections for the future, and thus analytical knowledge and accuracy are key components of forecasting. There are several pro forma statement designs, but the sales-driven forecasting approach ensures a good link between the level of activity in a company and the related expenses and investments (Petersen & Plenborg, 2012, pp.175), and is also the preferred design in this thesis.

Koller et al. (2015, pp.230) argues for a detailed 5-7 years forecast, referred to as the forecasting period, as well as a simplified forecast for the remaining years, referred to as the terminal period, in order to avoid the error of false precision. The terminal period assumes everything remains constant and should reflect a steady state environment, and often make up the majority of the estimated enterprise value. In the terminal period every forecast item grows by the same constant – the terminal growth (Koller et al., 2015, pp.177).

An evaluation of the estimates and pro forma statements is a crucial step in the forecasting process, in order to assure the performance the underlying assumptions are supporting is achievable. Comparing past to future performance through profitability measures such as ROIC can be valuable. Any scenario that deviates from historical performance should have compelling evidence. It is also recommended to perform a sensitivity analysis to explore how adjustments of key financial value drivers affect financial measures such as the free cash flow (FCFF) and ROIC (Plenborg, p. 198).

3.4.2 Discounted Cash Flow model The Discounted Cash Flow (DCF) analysis is an accurate and flexible method for valuing projects, divisions, and companies, especially useful when applied to a multi-business enterprise (Koller et al., 2015, pp. 139). There are two ways of conducting the DCF model; estimating the enterprise value of a company or estimating the equity value of a company. We have chosen the former for our Business

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Units of APMM, as the combined debt will be subtracted in the sum-of-the-parts section. According to the model, only the FCF and WACC affect the company’s market value. FCFF is considered a trustworthy measure, as it tracks the money left for investors, regardless of whether a cash outlet is counted as an expense or turned into an asset on the balance sheet. Changes in non-current liabilities are not considered to be part of NWC or CAPEX and therefore included as a separate element.

Equation 5 - FCFF

Source: Compiled by authors, Petersen & Plenborg, (2012)

Equation 6 - Enterprise value

Source: Compiled by authors, Petersen & Plenborg, (2012, pp.216)

Market value of equity is calculated by subtracting the value of net interest-bearing debt and the value of minority interest from the estimated enterprise value (Petersen & Plenborg, 2012).

3.4.3 Relative Valuation To reality check our discounted cash flow results we will also perform a relative valuation to the peer groups we have identified. The object of relative valuation is to value assets based upon how similar assets are currently priced in the market (Damodaran). The peer group of each business unit is chosen by collecting peers stated by both APMM and a large group of equity analysts.

Koller et al. (2010, pp.352) recommend using forward estimates of earnings as they have a much lower variation across peers, which leads to a narrower range of uncertainty of value. Liu et al. (2002) found empirical evidence on the one-year-forward P/E ratio having 1.6 times less the standard deviation of historical earnings-to-price ratios when individual companies were compared with their industry multiples (Koller et al., 2010). A key requirement for a successful analysis is to use the right multiples. Forward-looking multiples have been collected from the most relevant peers from Bloomberg, where the multiples price/book, EV/EBITDA and EV/sales have been collected. Deeper analysis of multiples such as Maersk Oil’s reserves will not be conducted. In Table 1, we have summarized the strengths and limitations of our forward-looking multiples.

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Table 1 – Strength and weaknesses of chosen multiples

Source: Compiled by authors, Koller et al., (2015), Petersen & Plenborg, (2012)

Koller et al., (2015, pp.389) argue one should eliminate outliers with multiples being out of line with their underlying economics, and instead where possible, estimate a median of close peers with similar returns and growth. Harmonic mean generates more accurate value estimates than multiples based on mean, median or a value weighted average as they are more stable regarding outliers (Petersen & Plenborg, 2012, pp.234). Harmonic mean is thus our preferred method for calculating the average multiple over the peer group.

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4.0 A.P. Møller - Maersk A/S This section will present an overview of APMM and the business units to provide a better understanding of the company. We present a short historical summary in addition to the development of the financial performance of APMM. Furthermore, the economic factors affecting all business units will be discussed and a credit analysis performed. Lastly, we will derive the BU’s own WACC and present their chosen peer groups.

4.1 History APMM has a long and proud history, which started in 1904 with the predecessor to Maersk Line, The Steamship Company Svendborg, founded by Captain Peter Mærsk-Møller and his son Arnold Peter Møller. The company built a shipyard in Odense in 1919, and in 1928 Maersk Line was established with six motor ships. Eleven years later, before WWII, Maersk Line was the second largest shipping company in Denmark with a total of 46 ships. Post-WWII the fleet was reduced to 21 ships, and the following years were spent rebuilding and increasing their fleet.

Shipping was the sole focus for many decades until 1962, when a license was granted to search for oil in the Danish part of the North Sea. A new era began, moving the company towards a conglomerate enterprise, a description still valid today, as a large share is within other businesses than the container business. In 1964 Dansk Supermarked A/S was founded, followed by Maersk Air in 1969, four years after Mærsk Mc-Kinney Møller took the helm after the death of his father, A.P. Møller. In 1973, Maersk Line added its first container ship to the fleet, and twenty years later it became the largest container line in the world. During the 90’s and 00’s the company made several acquisitions, with Sea-Land Corporation, a 70 vessels liner service in 1999 being the largest.

In recent years, APMM has gone from being a closed family conglomerate to a much more open company, becoming more and more focused on its core activities and divesting non-core, e.g. selling of Maersk Air in 2005. The company held it first capital markets day in 2012, a normal occurrence at other groups but quite revolutionary for the conglomerate (Financial Times, 2013). However, the Møller family still owns a controlling majority of the company, and financial information is still at a fairly limited level.

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Table 2 - Main shareholders APMM

Shareholders with more than 5% of share capital or votes Share capital Votes A.P. Møller Holding A/S 41,51% 51,09% A.P. Møller og Hustru Chastine McKinney Møllers Familiefond 8,37% 12,84%

Den A.P. Møllerske støttefond 2,94% 5,86% Source: Conducted by authors, APMM, (2015c)

4.2 Historical performance

4.2.1 APMM’s financial performance Maersk has lately made significant changes in its portfolio of businesses. During 2009-2014 APMM made divestments worth ~USD 11bn which proceeds were used to reinvest into other businesses and to reduce the high debt level. The period of divestment was followed up in 2015 with the USD 5bn divestment of its Danske Bank stake which proceeds were distributed through an extraordinary dividend with cash and shares. As a result, we also see net interest-bearing debt (NIBD) dropping in the period from 2011-2015 from a level of USD 15.3bn down to USD 7.8bn.

Table 3 - Financial highlights APMM

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Income statement Revenue 49.917 49.491 47.386 47.569 40.308 Profit for the year 3.377 4.038 3.777 5.195 925 Balance sheet Total assets 70.444 72.396 74.509 68.844 62.408 Total equity 36.190 39.324 42.513 42.225 35.739 Invested capital 51.753 53.814 54.630 49.927 43.509 Net interest-bearing debt 15.317 14.489 11.642 7.698 7.770 Investments in property, plant and equipment and intangible assets 10.901 7.826 7.087 9.368 7.647 Cash flow Cash flow from operating activities1 6.665 7.041 8.909 8.761 7.969 Cash flow used for capital expenditure1 -10.285 -5.822 -4.881 -6.173 -1.408 Financial ratios Return on invested capital after tax (ROIC) 8% 9% 8% 11% 3% 1 From continuing operations

Source: Compiled by authors,(APMM, 2016e)

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Figure 3 - Divestments

Source: Compiled by authors, APMM, (2015j)

APMM had in the same period relatively stable revenue and profit, but both fell significantly in 2015 mainly due to the oil price dropping to 50% on a year to year basis and container rates being at a historic low. Performance for the last five years has been below the targeted 10% ROIC APMM aims to achieve through the cycle.

Figure 4 – Revenue and NOPAT APMM 2015 per business unit

Source: Compiled by authors, APMM, (2015d)

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Figure 5 - Invested capital APMM 2015 per business unit

Source: Compiled by authors, STRATEGY

4.2.2 Share price performance APMM has underperformed relative to OMXC20 the last five years mainly due to the drop in 2015. An interesting aspect is to see how the market has reacted to Maersk’s recent divestments (see Table 4). The divestments are of differing size but the corresponding changes in stock price during the day of the announcements are clearly indicating the market is responding positively to APMM’s divestment announcements.

Figure 6 - APMM share price performance relative to OMXC20, 2011-2015

Source: Compiled by authors, Yahoo! Finance, (2016a, 2016b)

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Table 4 - Share price changes due to divestments

Date Event Return February 25, 2015 Value of ownership interest in Danske Bank A/S to be distributed as extraordinary cash dividend 9,47% January 7, 2014 Sale of shares in Dansk Supermarked A/S and F. Salling A/S 0,89% October 12, 2011 Sale of Maersk LNG A/S 4,19% May 27, 2010 Sale of Netto Foodstores Limited 4,78% December 17, 2009 Agreement on the sale of Norfolk Holdings B.V. -2,43% January 30, 2008 A.P. Møller - Mærsk A/S becomes a major shareholder in Höegh Autoliners 0,40% Source: Compiled by authors, APMM, (2016a)

Late 2013 a holding company was put between the AP Møller Foundation for General Purposes and A.P. Moller-Maersk. Previously all dividends received were to be used for donations to benefit the public in countries across the Nordic region but could after the change be used to boost the group’s financial flexibility through better control of cash flow (Reuters, 2013). Ane Mærsk-Mc-Kinney Uggla herself stated "With the establishment of the holding company the A.P. Moller Foundation wants to secure and strengthen its active ownership and provide financial flexibility and a financial buffer for the whole group," (Shippingwatch, 2013)

Dividends are APMM’s primary way of distributing capital to its shareholders, and the nominal dividend has increased steadily over the last decade. APMM’s objective is to increase the nominal dividend per share over time supported by underlying earnings growth (APMM, 2014e). Included in APMM’s financing strategy is a key ratio guideline to keep equity / total assets > 40% (APMM, 2016c).

Figure 7 - Historically ordinary dividend

Source: Compiled by authors, APMM, (2016d)

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4.3 Economic factors affecting all business units Numerous factors impact the value drivers of APMM’s business units and this section will focus on these most critical factors.

GDP Real gross domestic product (Real GDP), an inflation-adjusted measure of all goods and services produced within a year in a country, is an important indicator of the health of a country’s economy. The consensus is that a 2.5 – 3.5% growth in GDP is considered optimal, enough to create corporate profit and jobs without causing too high inflation (Khan, Nauman, Farooq, & Yahya, 2013). There are large variations worldwide considering the annual worldwide growth rate, especially in emerging markets where the annual disposable income per capita has increased significantly and is growing the worldwide consumption. Impact on individual business units will be elaborated in the respective business unit sections.

Currency APMM generates most of its revenues in USD, and a large share of its values is USD based (APMM, 2015c); hence the currency risk relates to the range of other currencies. The company hedges itself towards a change in USD against its main exposures, i.e. DKK, GBP, EUR, NOK, and SEK, reducing fluctuations in the total APMM profit. A change in USD will have a low impact on APMM revenue, value and share price, where 10% increase in the USD exchange rate estimated to impact APMM NOPAT negatively of $ -0.1bn, while the effect was estimated to $ -0.3bn in 2014 (APMM, 2015c).

Interest rates APMM has most of its debt in USD, but also in currencies such as EUR, DKK, GBP, SEK, NOK and JPY (APMM, 2015c). The company strives to maintain a combination of fixed and floating rates, reflecting risks and expectations. The hedging is mostly governed by interest rate swaps, with portfolio duration of 2.5 years in 2015. A one percentage point increase in the interest rate affect NOPAT by $120M, ceteris paribus (APMM, 2015j). The effect on an equal increase in the equity interest rate will impact APMM positive, estimated to $33M, ceteris paribus (APMM, 2015c).

Oil price A lower oil price as the past couple of years has shown, affects several of APMM’s operating industries. The most oil related businesses (Maersk Oil, Maersk Tankers, Maersk Supply Service and Maersk Drilling) are clearly long oil, meaning a higher oil price benefits the BUs. Predicting the impact of the remaining businesses (Maersk Line, APM Terminals, Damco, and Svitzer) is somewhat complicated.

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Amongst these, except for APM Terminals, the shipping related business units will receive large cost savings of a lower oil price due to the bunker fuel price having a 0.98 correlation with the price of Brent (United Nations, 2010).

The question is whether the savings of the shipping segments outweigh the loss of profit from the oil related activities of APMM. Maersk Oil’s entitlement production in 2015 was 315,000 boepd (APMM, 2015c) and had an effective production tax rate around 60% (APMM, 2015h) which means around 125,600 boepd filters through the bottom line. In 2014, Maersk Line’s bunker consumption equaled 8.8m tonnes (APMM, 2015h), equivalent to around 153,000 boepd. There is some marginal taxation in the country based sales organization, but otherwise no tax impact due to the tonnage tax system.

Whether the two business units combined are net long or short is then rather a question of how much of Maersk Line’s bunker savings is passed on to its customers. With the back of the envelope calculations above the two business units will become break even when 18% of savings is passed on to customers. Some argue up to 70-80% is passed on to customers in the longer term, due to competition in both shipping and other transportation markets (APMM, 2015h). Concluded, it seems clear APMM is net long oil.

A regression of the APMM share price vs. Brent since 2000 supports this conclusion with a significant relationship; a 1% increase in the oil price leads to an increase in the APMM share of 0.23%.

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Figure 8 - Share price vs. oil price regression

SUMMARY OUTPUT Regression Statistics Multiple R 0,194042517 R Square 0,037652499 Adjusted R Square 0,037419597 Standard Error 0,027024689 Observations 4134

ANOVA df SS MS F Significance F Regression 1 0,118071098 0,118071098 161,6673019 2,32833E-36 Residual 4132 3,017739348 0,000730334 Total 4133 3,135810447

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 0,000607983 0,000420378 1,4462754 0,14817582 -0,000216185 0,001432151 X Variable 1 0,234128645 0,018413801 12,71484573 0,00 0,198027682 0,270229607

Source: Compiled by authors, Yahoo! Finance, (2016a), U.S. Energy Information Administration, (2016)

4.4 Credit analysis The purpose of the credit ratings is to provide investors with a simple system of gradation by which future relative creditworthiness of securities may be gauged. Moody’s and S&P already have conducted analyses of APMM as of February 2016 (APMM, 2016g), which will be the foundation of this section.

S&P rates APMM BBB+; adequate capacity to meet financial commitments, but more subject to adverse economic conditions (Petersen & Plenborg, 2012). However, they estimate a negative outlook with the possibility of a downgrade within 2016. The assessment of Maersk's creditworthiness will incorporate developments in oil prices and container freight rates in the second half of 2016. A deterioration of the business risk profile, either in the form of a weaker competitive position or reduced diversification, to the lower spectrum of the satisfactory category could also put the ratings under pressure.

The Moody’s report yields the equivalent rating, Baa1, but with a stable outlook. Moody’s have used their industry rating corresponding to each BU, as well as a peer comparison, to estimate credit quality for each business unit as well as assessing Maersk against a number of qualitative factors, positioning Maersk in the Baa2 rating category. However, APMM’s level of business diversification, as well as the score on qualitative factors, justified an uplift to Baa1.

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Table 5 contains some of the most used and most applicable key ratios within credit rating, calculated by the authors to provide an examination of APMM in terms of credit analysis, where both solidity and profitability is measured. Calculations have been made on business unit level as well as for APMM at a corporate level, both looking at historical and estimated future numbers.

Table 5 - Credit analysis 2013-2015 Aa A Baa Line Oil APMT Drilling Supply Tankers Damco Svitzer ALL BUs Debt/EBITDA 1,00 1,70 2,40 1,94 1,39 2,22 2,24 1,71 1,71 -5,41 1,91 1,53 CAPEX/Dep Exp 1,40 1,30 1,20 1,13 1,74 2,05 1,84 0,43 0,43 -0,09 1,35 Operating margin 17,0% 13,8% 12,6% 5,8% -9,9% 17,8% 26,8% 24,2% 24,2% -3,5% 17,9% 5,4% EBIT interest cover 10,10 6,10 3,70 11,34 23,93 19,41 13,24 13,63 13,63 -15,23 10,37 13,42 Average rating Baa Baa Aa Aa A A

2016-2018 Aa A Baa Line Oil APMT Drilling Supply Tankers Damco Svitzer ALL BUs Debt/EBITDA 1,00 1,70 2,40 1,39 3,07 2,80 4,39 2,47 2,23 17,46 2,38 2,60 CAPEX/Dep Exp 1,40 1,30 1,20 1,74 1,37 2,40 0,72 0,58 0,52 0,82 1,43 1,50 Operating margin 17,0% 13,8% 12,6% -9,9% 5,2% 14,9% 9,0% 17,0% 13,1% 0,5% 12,2% 5,2% EBIT interest cover 10,10 6,10 3,70 23,93 11,91 14,66 2,24 6,39 10,96 6,10 11,06 7,01 Average rating Baa Baa A

The credit analysis is based on year-end figures, and the two tables consist of three years median for 2013-2015 and 2016-2019 respectively, based on Petersen & Plenborg, (2012, pp. 277). The color coding in the table is based on the following:  Green if the number is A or better  Blue if the number is A-Aa  Black if the number is Baa-A  Red if the number is worse than Baa

On an aggregated level, the 2013-2015 rating was more promising than the 2016-2018 rating. The latter rating estimates the same result as Moody’s and S&P, and the negative S&P outlook can be argued for (see Appendix 2 -9 for full calculations). On a business unit level, there are indications of APM Terminals having a higher credit-worthiness, meaning they could suffer from the conglomerate structure in terms of having a higher credit spread than if being a separate company. Damco, Supply Service Maersk Drilling seem to profit from being a part of a conglomerate in terms of credit spread, as they are very unlikely to receive a Baa rating as a separate company. A drawback from the calculations might be the debt structure as each business unit is given debt relatively to invested capital. I.e. the Debt/EBITDA might be a skewed measure, meaning some BUs, in reality, have a different ratio and hence deserve a better credit rating. This drawback will not affect APMM at a corporate level.

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4.5 Peer groups The following table illustrates the chosen peer group of each business unit. The peers are operating in the same industry as the respective BU; however, they are less comparable considering APMM is operating in several industries. We assume the chosen peers conducted by APMM information and equity analysts comparable to the business unit of APMM. According to APMM reports, Svitzer does not have any sufficient comparable peers for historical performance, as relevant peer data is unavailable due to industry consolidation. Hence relative valuation is not included in the Svitzer section later (APMM, 2015h).

Table 6 - Peer groups APMM business units

Maersk Line Maersk Oil Maersk Drilling CSCL Canadian Natural Resources Atwood Evergreen Chesapeake Diamond Offshore Drilling Hanjin Devon Ensco PLC K Line DNO Fred Olsen Energy MOL Hess Noble Corporation Orient Overseas Marathon Oil ProSafe Yyang Ming Marine Transport Murphy Oil Rowan APM Terminals Noble Energy Seadrill CSL OXY Songa Offshore DP World Petroleo Brasileira Transocean Hamburger Hafen Statoil Damco ICTSI Maersk Supply Services Deutsche Post Maersk Tankers Deep Sea Supply Expeditors Teekay Farstad Shipping Panalpina Welttransport Frontline Solstad Offshore Source: Compiled by authors

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4.6 Estimating Cost of Capital

4.6.1 Cost of Debt The cash flows of the business units of APMM are mainly in USD (APMM, 2015c); hence the risk-free rate should be a US long-term government bond. The US holds an AA+-rating from S&P, the second highest category, with very low default risk. As of April 1st, 2016, the ten years US Treasury Bill was 1.79%, hence our estimate for risk-free rate is 1.79%. As explained in section 4.4, APMM is given the credit rating BBB+ and Baa1 by S&P and Moody’s respectively. The credit rating implies a default spread of 1.77% (Damodaran, 2016b). The marginal tax rate varies across countries and we assume the average effective tax rate for each business unit. Given the calculations above, the Cost of Debt for each business unit is (1.79+1.77)*(1-t), where t is each BU’s marginal tax percentage.

4.6.2 Cost of Equity The business units of APMM will be classified in four segments amongst Damodaran’s unlevered sector beta (βa) calculation, illustrated in Table 7 (Damodaran, 2016a)). Table 8 illustrates the market risk premium of the business units. As each region/country has its own risk premium MRP is calculated as the weighted average of their presence each region/country. Given these calculations above, the Cost of Equity for each business unit is 1.79+Levered Beta*MRP.

Table 7 - Unlevered beta

Number D/E Unlevered Industry Name of firms Beta Ratio Tax rate beta Oil/Gas (Production and Exploration) 1029 1,87 78,82% 3,22% 1,06 Oil/Gas Distribution 207 1,55 95,54% 9,57% 0,83 Shipbuilding & Marine 337 1,21 86,07% 12,41% 0,69 Transportation 222 1,15 51,08% 20,48% 0,82 Source: Compiled by authors, Damodaran, (2016a)

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Table 8 - Average of Market Risk Premium

Average of MRP Regions Line Oil APMT Drilling SvitzerSupply Tankers Damco Africa 12% 15% - 4% - 1% - 20% 8% Asia 10% 15% - 58% 5% 2% 5% 17% 22% Australia & New Zealand 8% 5% - 2% - 20% - 0% 1% Caribbean 11% 0% - 0% - 0% - 0% 0% Central and South America 11% 14% - 6% - 15% - 0% 15% Eastern Europe & Russia 10% 8% - 4% - 0% - 0% 5% Middle East 8% 17% 15% 6% - 10% - 30% 13% North America 6% 15% - 8% - 2% - 15% 14% Western Europe 8% 11% - 13% - 50% - 17% 22% Scandinavia 6% - 26% - 65% - 65% - -

Countries UK 6% - 16% ------Brazil 13% - 1% - 5% - 5% - - Kazakhstan 10% - 1% - 5% - 5% - - Qatar 8% - 41% - 10% - 10% - - Egypt 13% - - - 5% - 5% - - Azerbaijan 10% - - - 5% - 5% - - Uruguay 9% ------Ghana 8% ------USA 6% ------Sum = Total MRP (weighted average) 9,36% 7,23% 9,26% 7,62% 8,62% 7,62% 8,83% 9,13% Source: Compiled by authors, APMM 2011-2016

4.6.3 Capital Structure The following table shows the estimated capital structure of APMM units 2016 going forward. All business units have the same capital structure based on the previously mentioned assumption that all net interest bearing debt is spread out to the BU’s based on their share of invested capital.

Table 9 - Capital structure APMM

Ratio 2016E 2017E 2018E 2019E 2020E 2021E(TP) E/EV 0,74 0,74 0,74 0,75 0,78 0,85 D/EV 0,26 0,26 0,26 0,25 0,22 0,15 NIBD/E 0,35 0,35 0,35 0,34 0,29 0,18 Source: Compiled by authors

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4.6.4 WACC in each business unit

Maersk Line Maersk Line MRP is computed by distributing the revenue split to the different regions disclosed in APMM reports, as seen in Table 8. As Maersk Line operates in every corner of the world the Market Risk Premium is the highest among the other business units: 9.36% in total. Maersk Line is considered to be in the transportation segment with an unlevered beta of 0.82 implied from Damodaran’s calculations. Taxes are assumed to be in line with the average 2011-2015; 3.4%.

Table 10 - WACC Maersk Line

Maersk Line 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 0,82 0,82 0,82 0,82 0,82 0,82 Levered B 1,10 1,10 1,11 1,10 1,05 0,97 CoE 12,09% 12,10% 12,16% 12,04% 11,63% 10,83% Marg. tax 3,4% 3,4% 3,4% 3,4% 3,4% 3,4% CoD 3,44% 3,44% 3,44% 3,44% 3,44% 3,44% WACC 9,87% 9,87% 9,87% 9,86% 9,81% 9,70% Source: Compiled by authors

Maersk Oil Maersk Oil’s market risk premium is estimated based on the entitlement production in its respective production countries. Algeria has no risk premium by Damodaran; hence the Middle East is used. Total computed market risk premium is at 7.23%. Maersk Oil is assumed included in Damodaran’s “Oil/Gas production and exploration” segment, hence an unlevered beta of 1.06. Taxes are assumed to be 60% (APMM, 2015h).

Table 11 - WACC Maersk Oil

Maersk Oil 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 1,06 1,06 1,06 1,06 1,06 1,06 Levered B 1,42 1,43 1,43 1,42 1,36 1,25 CoE 12,08% 12,10% 12,15% 12,04% 11,63% 10,83% Marg. tax 60,0% 60,0% 60,0% 60,0% 60,0% 60,0% CoD 1,42% 1,42% 1,42% 1,42% 1,42% 1,42% WACC 9,35% 9,35% 9,35% 9,35% 9,36% 9,38% Source: Compiled by authors

Page 38 of 158 4.0 A.P. Møller - Maersk A/S

APM Terminals MRP of APM Terminals is estimated based on a weighted average of income in the operating countries of APM Terminals, as seen in Table 8. Asia accounts for the largest share with 57.5% of revenue followed by Western Europe at 13.2% leaving a relatively high market risk premium of 9.26%. We categorize APM Terminals in the shipbuilding and marine segment, which implies an unlevered beta of 0.69. Taxes are assumed to be in line with the average 2011-2015; 15.2%.

Table 12 - WACC APM Terminals

APMT 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 0,69 0,69 0,69 0,69 0,69 0,69 Levered B 0,93 0,93 0,93 0,92 0,89 0,81 CoE 10,37% 10,38% 10,43% 10,33% 9,99% 9,32% Marg. tax 15,2% 15,2% 15,2% 15,2% 15,2% 15,2% CoD 3,02% 3,02% 3,02% 3,02% 3,02% 3,02% WACC 8,48% 8,49% 8,49% 8,48% 8,44% 8,36% Source: Compiled by authors

Maersk Drilling MRP of Maersk Drilling is estimated based on the location of each rig, as seen in Table 8, which is mainly located in Scandinavia implying a relatively low market risk premium of 7.62%. We categorize Maersk Drilling the oil/gas (production and exploration) segment, which implies an unlevered beta of 0.82. Taxes are assumed to be in line with the average 2011-2015; 20%.

Table 13 - WACC Maersk Drilling

Maersk Drilling 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 1,06 1,06 1,06 1,06 1,06 1,06 Levered B 1,42 1,43 1,43 1,42 1,36 1,25 CoE 12,65% 12,66% 12,72% 12,60% 12,17% 11,32% Marg. tax 19,8% 19,8% 19,8% 19,8% 19,8% 19,8% CoD 2,85% 2,85% 2,85% 2,85% 2,85% 2,85% WACC 10,13% 10,13% 10,14% 10,13% 10,10% 10,02% Source: Compiled by authors

Page 39 of 158 4.0 A.P. Møller - Maersk A/S

Maersk Supply Services As Maersk Supply Services has a focus on deep-water operations we assume the 7.62% MRP of Maersk Drilling is representative also for the Maersk Supply Service with related activities, as seen in Table 8. Maersk Supply Service fits the oil/gas transportation sector of Damodaran (unlevered beta of 1.02) and taxes are assumed to be in line with the average 2011-2015; 7.0%.

Table 14 - Maersk Supply Services

Supply Services 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 1,06 1,06 1,06 1,06 1,06 1,06 Levered B 1,42 1,43 1,43 1,42 1,36 1,25 CoE 12,65% 12,66% 12,72% 12,60% 12,17% 11,32% Marg. tax 7,0% 7,0% 7,0% 7,0% 7,0% 7,0% CoD 3,31% 3,31% 3,31% 3,31% 3,31% 3,31% WACC 10,25% 10,25% 10,26% 10,25% 10,20% 10,09% Source: Compiled by authors

Maersk Tankers The market risk premium of Maersk Tankers has been calculated as a weighted average of the market risk premiums of the regions between Maersk Tankers’ main trading routes, as seen in Table 8, implying a 8,83% market risk premium. Maersk Tankers fit the oil/gas transportation sector of Damodaran (unlevered beta of 0.83), and effective taxes are assumed to be 0%.

Table 15 - WACC Maersk Tankers

Maersk Tankers 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 0,83 0,83 0,83 0,83 0,83 0,83 Levered B 1,12 1,12 1,13 1,12 1,07 0,98 CoE 11,68% 11,69% 11,74% 11,63% 11,24% 10,47% Marg. tax 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% CoD 3,56% 3,56% 3,56% 3,56% 3,56% 3,56% WACC 9,59% 9,59% 9,60% 9,59% 9,53% 9,41% Source: Compiled by authors

Page 40 of 158 4.0 A.P. Møller - Maersk A/S

Damco The market risk premium of Damco is a weighted average of the author’s estimations of Damco’s activity based on the number of offices in various regions around the world (Damco, 2016). Asia and Western Europe have the largest shares, and the implied market risk premium is 9.13%. We apply an unlevered beta of 0.82 as we categorize Damco to be in Damodaran’s transportation segment. Taxes are assumed to be in line with the average 2011-2015; 16.3%.

Table 16 - WACC Damco

Damco 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 0,82 0,82 0,82 0,82 0,82 0,82 Levered B 1,10 1,10 1,11 1,10 1,05 0,97 CoE 11,83% 11,84% 11,90% 11,79% 11,39% 10,61% Marg. tax 16,3% 16,3% 16,3% 16,3% 16,3% 16,3% CoD 2,98% 2,98% 2,98% 2,98% 2,98% 2,98% WACC 9,56% 9,56% 9,57% 9,56% 9,52% 9,44% Source: Compiled by authors

Svitzer The MRP is calculated as a weighted average of Svitzer’s operations based on authors’ own estimations of activity around the world (Svitzer, 2016c). Western Europe and Australia have the largest share, followed by Asia and Latin/Central America, which in total implies a market risk premium of 8.62%. We include Svitzer in the shipbuilding and marine segment, implying an unlevered beta of 0.69. Taxes are assumed to be in line with the average 2011-2015: 23.2%.

Table 17- WACC Svitzer

Svitzer 2016E 2017E 2018E 2019E 2020E 2021E(TP) Unlevered B 0,69 0,69 0,69 0,69 0,69 0,69 Levered B 0,93 0,93 0,93 0,92 0,89 0,81 CoE 9,78% 9,79% 9,83% 9,74% 9,43% 8,80% Marg. tax 23,2% 23,2% 23,2% 23,2% 23,2% 23,2% CoD 2,74% 2,74% 2,74% 2,74% 2,74% 2,74% WACC 7,97% 7,97% 7,98% 7,97% 7,94% 7,87% Source: Compiled by authors

Page 41 of 158 5.0 Business Units Valuation

5.0 Business Units Valuation

5.1 Maersk Line

5.1.1 Overview Maersk Line is APMM’s cornerstone and the world’s largest container shipping company with a market share of more than 15% (Alphaliner, 2016). Maersk Line has some 32.750 employees and a fleet of 266 owned (1,78M TEU1) and 332 (1,25M TEU) chartered vessels (Alphaliner, 2016). It also had 30 ordered vessels (0,4M TEU) as of March 2016. In 2015, Maersk Line had revenues of $23.41B and a NOPAT of $1.3B (Maersk, 2015b). The figures below illustrate Maersk Line presence in the world by market share by trade.

Figure 9 - Maersk Line capacity market share by trade FY2015

Source: APMM, (2015c)

Maersk Line has continually increased its transported volume from 2011 to 2015; however, revenue has declined in the same period due to the decreasing freight rates. Unit cost in the same period has also fallen significantly, mainly due to lower fuel price, which accounts for 13-20% of total costs2, and cost

1 Twenty-foot Equivalent Unit, a measure of cargo capacity

2 The percentage depends on the current fuel price. In 2015, bunker fuel accounted for 13% of total costs, according to APMM, (2015c)

Page 42 of 158 5.0 Business Units Valuation saving initiatives as previously mentioned. The average financial performance of Maersk Line, as seen through the underlying ROIC, has not been satisfactory in regards to meeting the goal of a 10%

Table 18 - Financial Highlights Maersk Line

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 25.108 27.117 26.196 27.351 23.729 Operating costs -24.099 -24.938 -22.883 -23.139 -20.405 EBITDA 1.009 2.179 3.313 4.212 3.324 Depreciation & amortisation 1.559 1.697 1.789 1.870 1.915 EBIT -482 525 1.571 2.504 1.431 EBIT-margin -1,9% 1,9% 6,0% 9,2% 6,0% Tax 71 64 61 163 128 NOPAT -553 461 1.510 2.341 1.303 Underlying NOPAT 1.463 2.199 1.287 Invested capital 18.502 20.648 20.046 20.084 20.054 Underlying ROIC (APMM) -3,1% 2,3% 7,3% 10,9% 6,4% Transported volumes (000 FFE) 8.111 8.493 8.839 9.442 9.522 Average freight rate (USD FFE) 2.828 2.881 2.674 2.630 2.209 Unit cost (USD/FFE) -2.916 -2.854 -2.529 -2.386 -2.087 Source: Compiled by authors, APMM, (2016e)

Figure 10 - Volume and freight rates 2011-2015 Figure 11 - Unit cost and fuel price 2011-2015

Source: Compiled by authors, APMM, (2015c) Source: Compiled by authors, APMM, (2015c)

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5.1.2 Strategic Analysis

External factors This section will examine the container line shipping industry (CLSI) and its main revenue drivers. The revenue of Maersk Line is a product of container volumes and freight rates, driven by the supply/demand balance.

Container volumes have grown strongly over the past decades, mostly due to the growing world GDP, an increase in global trade and an increased containerization (goods being shipped in containers instead of as a break-bulk). There is a fairly strong correlation between container volume growth and world GDP growth. Between 1981 and 2014 container volumes at ports have grown on average 2.6x faster than world GDP (Carnegie, 2014). However, the container volume multiplier has been decreasing rapidly since the beginning of the 21st century, as shown in Figure 12. BCG expects the container volume multiplier to be 1.3 over the next upcoming years (Boston Consulting Group, 2015).

Figure 12 - GDP and container demand growth and corresponding multiplier

Source: Compiled by authors, Alphaliner, Statista.com, Boston Consulting Group

There are several reasons for the declining multiple. Global trade in 2000–2007 far outpaced GDP growth as supply chains were being globalized following the IT revolution in the 1990s and early 2000s, resulting in more goods being shipped back and forth. While globalization is hardly over it seems it will continue to increase at a slower pace. E.g. where commodities often have been produced in China and

Page 44 of 158 5.0 Business Units Valuation shipped to Europe afterward, the intra-region trade is now increasing, thus decreasing the demand for shipping relatively to world GDP growth. Also, the container shipping industry is also somewhat vulnerable to technological innovations such as 3D printing which will decrease the need for shipping services.

Another reason for the slowing container volume growth to GDP growth multiple is the declining growth in the containerization rate. The share of ports who have adopted containerization increased from 50% in 1980 to 85% in 2010 (Carnegie, 2014). The upper limit has not been reached yet, especially not in emerging markets, but containerization will contribute less to the multiplier than it has in the past.

While container volume growth has slowed capacity continues to increase. Container liner industry capacity increased with 70% percentage in the period from 2006-2009 while demand only grew 13%. Some of the gap was offset in 2010, but supply has continued to increase faster than demand since. One of the reasons for the continuing increase in capacity is the fuel cost savings of more efficient newer vessels. Capacity on order books accounted for 11% of the global liner fleet over the period 2004-2014, and for as much as 20% today (Alphaliner, 2016). Alphaliner thus expects capacity to further outweigh demand growth with an increase of 9% in 2016 and by 5% in 2017, and the supply/demand imbalance is expected to further deteriorate.

Figure 13 - Supply/Demand Container Line Shipping Industry

Source: Compiled by authors, Alphaliner, APMM, (2015c)

Page 45 of 158 5.0 Business Units Valuation

Freight rates have a fairly low transparency as they are agreed in bilateral contracts or via brokers. The China Containerized Freight Index (CCFI) is amongst the useful indicators, which cover the east-west routes from Asia to Europe and the US, which also account for 24% of total Maersk Line volume (Wolf Street, 2016b). The graph below shows the CCFI development since 2008 and the relationship with the Maersk Line freight rates. Container rates are now at an all-time low. The relationship between the two measures is strong (illustrated by the correlation in the figure), and the decline in CCFI rates 1st quarter in 2016 is one of the arguments of a decreasing forecasted Maersk Line freight rate. As seen in Table 19 Maersk Line rates had a premium of 40% to CCFI in 2008-2011, which significantly decreased in the period 2012-2015. This is due to several reasons, e.g. Maersk Line has started doing more back-haul (i.e. transporting containers back to their origin, often empty), which commands lower rates. It also increased its share of intra-regional trade, which comes with lower rates because of the shorter distances. However, the correlation between CCFI and Maersk Line freight rates remains significant.

Figure 14 - Maersk Line vs. CCFI

Source: Compiled by authors, APMM annual reports 2008-2015, Wolf Street, (2016a)

Table 19 - Freight rate premium

2008 2009 2010 2011 2012 2013 2014 2015 Yearly premium Maersk Line/CCFI 49% 34% 40% 42% 29% 29% 23% 23%

Source: Compiled by authors, APMM annual reports 2008-2015, Wolf Street, (2016a)

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Trade conditions also highly influence a multinational enterprise such as APMM, especially considering the large share of activities in remote parts of the world. E.g. China is rather protectionist when it comes to national shipping companies, which also affects the trade conditions for Maersk Line. As an example, the planned P3 alliance between Maersk Line, MSC and CMA CGM was rejected by the Ministry of Commerce of the People’s Republic of China (MOFCOM), arguing the alliance would outcompete domestic shipping companies in a pressed market (HG.org, 2014). Another example is the World Trade Organization (WTO) who continuously works to reduce international trade costs, tariff and non-tariff through the WTO Trade Facilitation Agreement. WTO estimates international trade costs to account for around 12.5%-17.5% of total shipping costs (OECD, 2015).

The International Maritime Organization (IMO) focuses on the prevention of pollution within maritime operations, and starting 1st of January 2015 ships trading in designated emission control areas (the Baltic Sea, the North Sea, the North American area and the US Caribbean Sea areas) will have to use on board fuel oil with a Sulphur content of no more than 0.10% (International Maritime Organizations, 2014). Outside the emission control areas, the current limit for Sulphur content of fuel oil is 3.5%. Sulphur fuel is up to 40% more expensive, and APMM estimates bunker costs to increase by USD 200m, which of it will try to pass on to customers through tariffs (APMM, 2014c).

EU is currently targeting carbon emission savings in the shipping industry which rules may apply in the next couple of years (European Commision, 2016). APMM’s CO2 emissions are huge and was in 2008 estimated to be at the same size as Denmark, 40-50 million tons of CO2 (Ingeniøren, 2008). APMM has done several actions to reduce this, targeting a 30% reduction within 2020 with 2010 as the baseline. By the end of 2015, 23% was received (APMM, 2015l).

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Internal factors Maersk Line’s EBIT margin has been above EBIT-margin of its peer group since the 1st half of 2012 (APMM, 2014c), however, several competitors have started targeting the more profitable routes and Maersk’s profit margin is under pressure. There are big differences on the respective routes, e.g. the North-South route has yielded an EBIT of 7% while the east-west route has yielded a 2% EBIT (APMM, 2014d). With the increased competition cost-cutting has been crucial, as will be explained below, there are three ways Maersk Line has focused on cutting cost; merging routes, slow steaming and having larger ships.

Figure 15 - Maersk Line EBIT gap to peers

Source: Compiled by authors, Danske Bank, (2015)

The 2M alliance together with Mediterranean Shipping Company (MSC), the second-largest player in the industry, implies efficiency gains through increased utilization of its fleet through merging routes and reducing bunker consumption and port expenses (APMM, 2014c). The vessel-sharing agreement started April 2015 with a duration of ten years. This organizational factor is an important aspect when evaluating the strength of Maersk Line in the industry competition. There are four mega-alliances including 2M, CKYHE, G6 and Ocean Three, comprising 16 of the top-20 largest container liners, which combined control almost all capacity on the Far East-Europe trade lanes, as well as on the Far East-North America trade lanes.

Page 48 of 158 5.0 Business Units Valuation

Figure 16 - Fleet capacity per alliance

Source: Compiled by authors, Alphaliner, (2016)

The logic behind the 2M alliance is cost saving due to the fleet compositions of the two companies. On the Asia-Europe route, Maersk Line and MSC respectively have a 21% and 13% market share. However, MSC will have excess capacity due to larger vessels. Thus, Maersk Line can reduce its cost per shipped unit by sending some of its goods with MSC’s large ships and possibly redeploy its smaller ships to other shorter routes. MSC’s gain will thus be higher utilization. APMM targets cost savings at $350m per annum (APMM, 2014d).

The second main cost-cutting strategy is increasing the average vessel size. According to APMM, a doubling in vessel size reduces unit cost by 25% (APMM, 2015d). This is mainly due the more or less fixed crew and to maintenance, berthing and building cost not increasing proportionally with its volume. As for Maersk Line, the Triple-E vessels are good examples of Maersk investing in large vessels to reduce unit cost.

Slow steaming is another cost-cutting strategy in which sailing at lower speeds yields significant reductions in fuel consumptions which is estimated to 40% when speed reduces by 20%, according to APMM (2010). CO2 emissions are also lower; APMM (2010) estimates the 20% speed reduction will reduce CO2 emissions per container by 7%.

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5.1.3 Forecasting

Revenue Maersk Line expects the global container shipping demand to grow by 1-3% in 2016 (APMM, 2016d). The market imbalance is expected to further deteriorate, which is expected to lead to continuing pressure on prices (APMM, 2015j), a 10% decrease in 2016 compared to 2015, estimated by the authors. Our estimates assume price pressure reflecting lower bunker costs and price competition on Asia- Europe trade lanes. Volume is estimated to grow 2% in 2016. For 2017 and going forward both freight rates and volume numbers are expected to rise, as illustrated in Table 20. However, we do not expect freight rates crossing the 2015 average until 2020. Table 20 below shows estimated freight rates going forward. The numbers are highly dependent on the largest economies in the world. In particular, a continuation of the slowing BRIC economies will affect the supply/demand balance (APMM, 2015j). In the 1st quarter of 2016, Maersk Line average was at 1988 USD/FFE, a 36% premium relative to CCFI average rates of 1460 USD/FFE, close to the 35% premium in December 2015. “Other revenue” is expected to be in line with the average of 2011-2015; $2.519mn.

Table 20 - Estimated freight rates, USD/FFE

2016E 2017E 2018E 2019E 2020E 2021(TP) Volume ('000 FFE) 9.712 10.004 10.304 10.716 11.145 11.591 Volume growth 2% 3% 3% 4% 4% 4% Freight rates 1.988 2.028 2.068 2.151 2.237 2.327 Freight rates growth -10% 2% 2% 4% 4% 4%

Source: Compiled by authors

Cost Over the next two years, Maersk Line aims to lower SG&A costs by USD 250m with an estimated impact of USD 150m in 2016. This due to the organizational transformation and ongoing automation and digitalization, expected to lead to a reduction in the global land-based headcount of 4,000, or 17% (Shippingwatch, 2015b). The 2M vessel sharing agreement includes $0.35B cost savings p.a. Also, the low bunker price is a direct result of the low oil price, estimated around $0.2B in 20163. Higher fuel efficiency will also decrease cost, and there have been calculations of a forecasted 5% p.a. improve compared to 2015 levels (Jefferies, 2015). Due to these factors, we estimate a total of 6% decrease in unit cost relative to 2015; which is also somewhat in line with the 2015 Q4 unit cost. After the 2016 unit

3 The oil price itself will be elaborated when forecasting Maersk Oil.

Page 50 of 158 5.0 Business Units Valuation cost reduction, prices will be somewhat stable in 2017 and 2018. 2019 going forward we forecast the unit cost increase in line with GDP, at 2.5% each year, as e.g. the oil price will increase. The forecasted depreciations will be estimated somewhat in line with the 2015 level. Below is a table of the forecasted unit cost USD/FFE, included and the estimated unit cost excluded depreciation & amortization.

Table 21 – Estimated unit cost Maersk Line

2016E 2017E 2018E 2019E 2020E 2021 (TP) Unit cost incl. D&A -1.079 -1.083 -1.093 -1.117 -1.141 -1.163 Unit cost excl. D&A -981 -981 -991 -1.015 -1.041 -1.067 Source: Compiled by authors

Our estimate for the 2016 bottom line is thus a result of $418m, which is in line with Maersk Line guidance for significantly lower underlying result for 2016 compared to 2015 (USD 1.3bn) (APMM, 2016d).

Capex Maersk Line is guiding for continuing elevated capex levels of $3.0bn on average per annum until 2020, due to scrapping and increased volume, (APMM, 2015j). As an example, the Triple-E vessels are estimated to cost $160mn each. Maersk Line’s strategy focuses on maintaining capacity market share and currently has almost 400,000 TEU of new capacity on its order book for delivery during 2017-2019, almost 15% of its current fleet (Alphaliner, 2016). The terminal period “Property plant and equipment” is assumed in line with 2020, yielding a capex each year of $2.2bn.

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Forecasting summary Given the forecasts elaborated above, as seen in Figure 17, the future estimated ROIC will increase after a decrease in 2016. Figure 18 illustrates the development in revenue and EBIT-margin.

Figure 17 - Future ROIC Maersk Line Figure 18 - Revenue and EBIT-margin Maersk Line

Source: Compiled by authors Source: Compiled by authors

5.1.4 Valuation

DCF Through forecasting the key value drivers the future estimated FCFFs of Maersk Line is shown as seen below. The enterprise value of $16.599bn will be added to the sum-of-the-parts section later.

Figure 19 - DCF Maersk Line

Maersk Line DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF -1.441 -298 -150 541 861 2.026 WACC 9,87% 9,87% 9,87% 9,86% 9,81% 9,81% Discount factor 0,91 0,83 0,75 0,69 0,63 Discounted FCFF -1.312 -247 -113 371 539

Valuation PV of FCFF in forecast horizon -762 PV Terminal period FCFF 17.361 Terminal period - % of total value 105% Terminal period - FCFF growth 2,5% Enterprise Value 16.599 Source: Compiled by authors

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Relative Valuation Table 22 - Relative Valuation Maersk Line

P/B Maersk Line 2016E 2017E CSCL 0,70 0,68 Evergreen 0,75 0,76 Hanjin 0,94 1,12 K Line 0,45 0,45 MOL 0,95 0,94 Orient Overseas 0,48 0,46 Yyang Ming Marine Transport 1,05 1,23 Harmonic mean 0,69 0,70 Maersk Line 0,68 0,64 Source: Compiled by authors, Bloomberg

Table 22 illustrates the 2016 and 2017 multiples of the chosen Maersk Line peer group. As the Price/Book multiple illustrates how the market value the assets of the company, which mainly includes vessels, it gives a good view of the Maersk Line value relative to its peers. Since most container liners suffer from poor profitability, earnings multiples are less meaningful. As the assumed Maersk Line NIBD is subtracted from the EV a plausible market value of equity estimation error must be taken into account. The 2016 and 2017 P/B estimates for Maersk Line are in line with the harmonic mean of its peers. The strong market position and healthy cost cuts of Maersk Line are amongst the arguments for a stronger multiple relative to peers. Hence, the business unit might have an upside.

Sensitivity Analysis We have constructed a sensitivity analysis to enable the reader to make own assumptions about the most critical assumptions, and to highlight the variability in estimated values. This process will illustrate the potential up- or downside as a result of changing market conditions or internal factors.

Our sensitivity analysis Table 23 examines the change in enterprise value (in billion USD) when terminal period growth (top-down) and cost of capital (left-right) changes. Table 24 examines the share price impact of an isolated Maersk Line change. As Maersk Line holds a significant share of total APMM value, a change in Maersk Line values has a powerful impact of the share price.

Page 53 of 158 5.0 Business Units Valuation

Table 23 - Sensitivity analysis enterprise value Maersk Line Table 24 – Share price changes

Terminal WACC change Terminal WACC change growth 2pp 1pp 0 -1pp -2ppgrowth 2pp 1pp 0 -1pp -2pp 3,50% 13.158 15.812 19.350 24.276 31.5593,50% 9.688 10.482 11.540 13.013 15.190 3,00% 12.366 14.750 17.874 22.123 28.2033,00% 9.451 10.164 11.098 12.369 14.187 2,50% 11.659 13.815 16.599 20.311 25.4792,50% 9.240 9.884 10.717 11.827 13.372 2,00% 11.024 12.987 15.488 18.765 23.2242,00% 9.050 9.637 10.385 11.365 12.698 1,50% 10.451 12.248 14.510 17.431 21.3271,50% 8.878 9.416 10.092 10.966 12.131

Source: Compiled by authors Source: Compiled by authors

It is important to state the impact of a change of freight rates. Our own calculations find with a 1pp increase in freight rates for all forecasted years, ceteris paribus, will increase Maersk Line EV by 20.05%, equivalent to a share price increase of 1000 DKK. The corresponding calculations when increasing transported volume 1pp is a Maersk Line EV increase of 1.725%, or a 72 DKK share price increase ceteris paribus (e.g. unit cost/FFE).

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5.2 Maersk Oil

5.2.1 Overview Maersk Oil is a mid-size exploration and production company established in 1962 with roots in the North Sea. The successful development of the tight Danish reservoirs enabled Maersk Oil to expand geographically and take on Qatar’s Al Shaheen field in 1992. Maersk Oil now produces oil from the Danish and UK sections of the North Sea, Qatar, Kazakhstan, the US Gulf of Mexico and Algeria, and has about 3100 employees. It conducts exploration and development activities in the aforementioned countries and Angola, Norway, Kenya, Ethiopia, Greenland, Brazil, and Kurdistan Region of Iraq (Maersk Oil, 2016).

Figure 20 - Maersk Oil entitlement production

Source: Compiled by authors, APMM, (2015c)

Maersk Oil has an operated production of over 500,000 barrels of oil equivalents per day (boepd) with an entitlement production of 312,000 boepd. APMM announced a target in 2012 of increasing entitled production to 400,000 boepd by 2020 while maintaining a return on invested capital of at least 10% across the cycle. This is a goal that is looking increasingly challenging with license renewal risk in Qatar,

Page 55 of 158 5.0 Business Units Valuation limited reserves, and few new development projects which are also challenged in the current low price environment.

Table 25 - Financial highlights Maersk Oil 2011-2015

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 12.616 9.623 10.444 9.607 7.662 Operating cost 1.611 1.910 2.233 2.856 2.468 Exploration cost 990 1.088 1.149 765 423 EBITDA 10.015 7.156 5.760 5.116 2.748 Depreciation & amortisation 2.146 1.866 1.570 1.441 1.593 Tax 5.730 2.884 3.004 2.327 175 NOPAT 2.112 2.444 1.046 -861 -2.146 Underlying NOPAT 1.083 1.035 435 Invested capital 6.427 6.920 6.478 5.282 3.450 Underlying ROIC (APMM) 37,2% 35,7% 16,2% -15,2% -38,6% Entitlement production (boepd) 333 257 235 251 312 Avg. Crude oil price (USD/barrel) 111 112 109 99 52 Capital Expenditure -3.788 -1.959 -1.800 -2.198 -2.017 Source: Compiled by authors, APMM, (2016e)

Maersk Oil realized an average 30% over the period 2011-2013 significantly higher to the level of its closest peers, but partly a reflection of relatively lower development capex. The sharp drop in oil prices has now taken its toll on Maersk Oil’s profit. As Maersk Oil sells its production at spot price the oil price has a direct impact on both its top and bottom line. Revenues in 2015 fell 35% due to the average oil price dropping 47% from 2014 to 2015, partly offset by an increase in entitled production. The drop in oil price also caused Maersk Oil to take large impairment losses the two last years, and guidance from Maersk now is a break-even level reached in the range of USD 44-55 per barrel.

5.2.2 Strategy The strategy section will cover the key value drivers of Maersk Oil; the Brent crude oil price, oil & gas production, and reserve levels.

Oil price There is great uncertainty to where the oil price will head, mainly due to factors such as China’s oil demand, the strength of US unconventional and OPEC’s strategic response. EIA’s monthly Short-Term Energy Outlook in March 2016 forecast an average of $34/b in 2016 and $40/b in 2017 for Brent (U.S. Energy Information Administration (EIA), 2016). However, uncertainty even in these short-term numbers is high, as indicated from current futures and options contracts. For example, WTI, which is

Page 56 of 158 5.0 Business Units Valuation expected to have the same average price as Brent, has a 95% confidence interval from $24/b to $58/b as close as in June 2016 (U.S. Energy Information Administration (EIA), 2016). The Brent Crude forward price has the advantage that it comes with a built-in mechanism for hedging against commodity prices (Damodaran, 2009b), and we assume the oil price to be in line with these forward prices in our forecast period.

Table 26 - Oil price assumptions – Brent crude forward prices

Oil price assumptions 2016E 2017E 2018E 2019E 2020E Brent Crude forward prices ($/barrel) 41,65 46,08 49,06 51,42 53,33

Source: Compiled by authors, Barchart.com, (2016)

Oil and gas production The decision by Qatar Petroleum regarding who will get to operate the Al Shaheen field will be another crucial oil-related key factor in 2016. Maersk Oil has been the operator for more than two decades, but the contract will expire in the summer of 2017. The field accounted for around 125,000 boepd in 2015, the equivalent of 40% of total entitlement production for Maersk Oil.

The Qataris set the contract up for tender last year where presumably the Qataris felt they needed to get the most out of the field and their suppliers in the wake of the falling oil price (Carnegie, 2016). Maersk Oil expects to be challenged by terms and conditions but thinks it is well positioned for extension beyond 2017 based on its technical experience and understanding of the field (APMM, 2015g).

Reserve levels Maersk Oil is also struggling with a declining level of reserves. The 1p reserves replacement ratio4 for Maersk Oil in 2014 (2015 numbers are yet to be released) was 29% based on proven reserves and production, significantly below the 100% needed for the company to stay in business long-term.

Table 27 - Maersk Oil reserves and resources (million boe)

4 The reserve-replacement ratio measures the amount of proved reserves added to a company's reserve base during the year relative to the amount of oil and gas produced. During stable demand condition environments a company's reserve

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2010 2011 2012 2013 2014 Proved reserves (1P) 515 443 410 392 327 Probable reserves (2P - incremental) 209 207 183 Proved and Probable reserves (2P) 515 443 619 599 510 Contingent resources (2C) 740 874 801 Reserves & resources (2P + 2C) 1.237 1.384 1.359 1.473 1.311 Production (million boe) 122 94 86 92 1P reserves replacement ratio (%) 41% 65% 79% 29% Source: Compiled by authors, APMM, (2015g)5

Jefferies (2015) furthermore estimated Maersk Oil’s reserves to be among the lowest in the European oil & gas exploration & production industry, with remaining life of reserves being less than 10 years6.

Figure 21 – Remaining reserve life (years) European E&P sector

Source: Compiled by authors, (Jefferies, 2015)

Another project which is causing uncertainty to Maersk Oil’s goal of 400,000 boepd is the Chissonga project outside of Angola’s coast. Production was estimated to be around 60,000 boepd (Capital market day of 2014, Maersk), but due to the current low oil price this project is now currently put on hold.

5 Proved Reserves: quantities of oil and gas estimated with reasonable certainty to be commercially recoverable. Probable Reserves: additional reserves, which analysis of geoscience and engineering data indicate are more likely than not to be commercially recoverable. Contingent Resources: quantities of oil and gas estimated, as of a given date, to be potentially recoverable from known accumulations, but which are not yet considered mature enough for commercial development due conditions that are not fulfilled.

6 Included in the estimation was a 75% probability Maersk’s license in Qatar would be renewed.

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Two other largest projects, Johan Sverdrup in Norway and Culzean in the UK, recently became sanctioned adding up a total of 300 mmboe in additional reserves. Plateau entitlement production for these projects is estimated to 29,000 and 30-45,000 boepd respectively, both with first production in 2019. Maersk Oil’s key projects are illustrated below.

Table 28 - Sanctioned development projects

Net Capex Plateau Production Project First Production Working Interest (USD Billion) (Entitlement, boepd) Operator Flyndre & Cawdor (UK/Norway) 2017 73,7% & 60,6% ~0,5 8.000 Maersk Oil Johan Sverdrup Phase 1 (Norway) Late 2019 8,44% 1,8 29000* Statoil Culzean (UK) 2019 49,99% 2,3 30-45,000 Maersk Oil * Capex and production estimates are for Phase 1 only Source: Compiled by authors. APMM, (2015c)

Table 29 – Major discoveries under evaluation (Pre-sanctioned projects)

Net Capex Estimate Plateau Prodcution Estimate Project* First Production Estimate Working Interest (USD Billion) (Entitlement, boepd) Chissonga (Angola) TBD 65% TBD TBD Buckskin (USA)** 2019 20% TBD TBD Lokichar (Kenya) 2021 25% TBD TBD * Significant uncertainties about time frames, net capex estimatesn and production forecast ** Buckskin being re-evaluated following operator Chevrons decision to exit Source: Compiled by authors, APMM, (2015c)

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5.2.4 Forecast

Oil price The Brent crude oil price is assumed to be in line with current forward rates to incorporate the market’s expectation of future rates. The million (billion) dollar question of where the long-term oil price is heading is obviously not a trivial question. OPEC has lost significantly market power due to the increased shale oil production, and with less coordination within and we assume 65$/barrel to be a fair assumption for a new pricing environment. This input obviously has a significant on Maersk Oil’s enterprise value and will be further elaborated as seen in the sensitivity analysis.

Production Maersk Oil is guiding for a production level of 315,000 for 2016, which we also factor in in our forecast. In the coming years, the production from the legacy assets in Denmark and Qatar will continue to decrease, but will likely be more than offset by the new fields coming in. In view of license renewal risk in Qatar and relatively limited remaining oil reserves of <10 years we see Maersk Oil’s production target of 400,000 boepd by 2020 as challenging. Furthermore, with the current low oil price environment, we see it likely that more projects can be put on hold. We thus factor in a gradual increase in production of 4% per annum, which takes production to a level of 369,000 boepd by 2020, below management’s 400,000 boepd target.

Lifting costs/opex At the capital market day of 2015 Maersk Oil guided to lower operating costs down 10% from the 2014 level in 2015, and further down for a total of 20% in 2016. For the financial year of 2015 opex was down by 13.6%, and we factor in the 20% opex cut as likely. We see this cost reduction as a sustainable reduction, and factor in the implied lifting cost/bbl for opex guidance for our forecasted period as well.

Tax rate Maersk Oil indicates an effective tax rate on production for 60% (APMM, 2015h), which is also what we factor in.

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Historical exploration costs Exploration costs are provided, but identifying specific drivers for these or the large chunk of other operating costs is difficult. Exploration cost for 2015 was also down 45% from the 2014 level. In the current climate and with the recent disappointing exploration results, Maersk Oil has decided to shift its focus to M&A growth (APMM, 2015g). Exploration in the long term will be critical to replace reserves. Guidance by APMM for 2016 exploration cost is for the same amount as in 2015. With our forecasted oil level, we assume this amount adjusted for inflation to be representable for the forecasted period.

Capex During the capital market days of September 2015 Maersk Oil guided for a target capex/year in the range of 2-4 billion per year. Due to our oil price assumptions, we assume capex will be in the lower range of this guidance for 2016 and 2017 with several delayed projects. With Johan Sverdrup Phase 1 and Culzean expected in 2019 we factor in 3 billion in 2018 and 3.5 billion in 2019. As Maersk Oil’s reserves are amongst the lowest in the European oil and gas exploration and production industry we assume capex to be higher than depreciation in our terminal period. We thus factor in property, plant and equipment growth of 3% in our terminal period.

Forecasting summary Given the forecasts elaborated above we implicitly assume ROIC to fall until 2017 before gradually increasing to around 9% for the terminal period.

Figure 22 - ROIC Maersk Oil Figure 23 - Revenue & EBITDA-margin Maersk Oil

Source: Compiled by authors Source: Compiled by authors

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5.2.5 Valuation In total our estimated enterprise value of Maersk Oil is $5.507b.

Figure 24 - DCF Maersk Oil

Maersk Oil DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF -2.737 102 -509 -607 572 902 WACC 9,35% 9,35% 9,35% 9,35% 9,36% 9,38% Discount factor 0,91 0,84 0,76 0,70 0,64 Discounted FCFF -2.503 85 -390 -424 366

Valuation PV of FCFF in forecast horizon -2.866 PV Terminal period FCFF 8.373 Terminal period - FCFF growth 2,5% Terminal period - % of total value 152% Enterprise value at YE(2015) 5.507 Source: Compiled by authors

Relative valuation Table 30 - Relative valuation Maersk Oil

P/B MAERSK OIL 2016E 2017E Anadarko 1,80 1,99 Canadian Natural Resources 1,46 1,42 Chesapeake 1,36 1,38 Devon 1,87 1,83 DNO 1,55 1,15 Hess 0,82 0,86 Marathon Oil 0,41 0,44 Murphy Oil 0,87 0,91 Noble Energy 1,40 1,50 OXY 2,38 2,58 Petroleo Brasileira 0,44 0,43 Statoil 1,19 1,18 Harmonic mean 0,98 0,99 Maersk Oil 0,84 0,80 Source: Compiled by authors, Bloomberg

Table 30 illustrates the P/B peer group multiples of Maersk Oil. P/B is chosen over the other available multiples due to volatile earnings and revenue in the industry. Maersk Oil is slightly undervalued relative to peers, meaning the fundamental analysis regards the business unit’s value lower than it would have been using a relative valuation, which also is in line with what we have seen in our strategic analysis.

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Sensitivity analysis Table 31 - Sensitivity analysis Maersk Oil Table 32 – Share price impact Maersk Oil

Terminal WACC change Terminal WACC change growth 2pp 1pp 0 -1pp -2pp growth 2pp 1pp 0 -1pp -2pp 3,50% 3.872 5.165 6.930 9.459 13.345 3,50% 10.228 10.615 11.142 13.545 14.707 3,00% 3.474 4.624 6.163 8.312 11.490 3,00% 10.109 10.453 10.913 11.556 12.506 2,50% 3.121 4.151 5.507 7.359 10.014 2,50% 10.003 10.311 10.717 11.271 12.064 2,00% 2.805 3.734 4.940 6.556 8.812 2,00% 9.909 10.187 10.547 11.031 11.705 1,50% 2.521 3.364 4.445 5.870 7.814 1,50% 9.824 10.076 10.399 10.825 11.407 Source: Compiled by authors Source: Compiled by authors

The terminal period forecasted oil price has a large impact of the EV of Maersk Oil. Table 33 illustrates our own estimates of the EV given the different oil price scenarios (USD/BBL). Ceteris paribus a $10 TP oil price increase implies a 900 DKK share price increase. It is important noticing an oil price change will not only affect Maersk Oil. However, these business units are not as directly affected as for Maersk Oil.

Table 33 – Maersk Oil sensitivity to long-term oil price

Oil price Terminal Period, USD/bbl 100 95 90 85 80 75 70 65 60 55 50 45 Enterprise value 26.692 23.665 20.638 17.612 14.585 11.559 8.533 5.507 2.482 -544 -3.569 -6.594 Source: Compiled by authors

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5.3 APM Terminals

5.3.1 Overview APM Terminals (APMT) is an international container terminal operating company with around 21,100 employees, headquartered in The Hague, Netherlands. Total revenue in 2015 was $4.24 billion with a TEU throughput of 36 million. It is one of the world’s leading port developers and operators and provides inland infrastructure. In 2015, it had a market share of 5.5%, as the third largest operator in the market (Port Technology, 2014). APMT operates a global terminal network with interests in 72 operating ports in 40 countries. It also has significant immediate growth potential as it has ten ongoing expansions and seven greenfield building projects driving revenue and earnings in the coming years (APMM, 2015d). The operating ports and greenfield projects are visualized in Figure 25.

Figure 25 – Operating port and greenfield project locations APMT

Source: Compiled by authors, APMM, (2015c)

APMT was established within APMM in 2001; however, the history began in 1958 with the first APMM facility opened in Brooklyn to handle general cargoes. Up until 2006 APMT was an integrated part of Maersk Line acting as its terminal arm. APMT has been a cash cow for APMM, considering it’s relatively high and stable NOPAT yielding an average ROIC of 12.7% since 2011. In 2015 APMT had the highest ROIC amongst the business units (10.9%).

The three sources of revenue in APMT are port revenue, inland revenue, and construction revenue. Port revenue covers revenue for lifting containers off ships and onto trucks or trains and accounts for approximately three quarters of total revenue. Inland revenue stems from the forwarding of the containers from port to the final destination and accounts for around 20%. Construction revenue is fairly

Page 64 of 158 5.0 Business Units Valuation small (5%), and captures income from the construction of a new terminal or port facility, or expansion of a current one (APMM, 2013).

5.3.2 Strategy Being highly dependent on the container shipping industry, APMT and its peers benefit from the same main drivers as the container line shipping industry. The world population growth, as well as a growing middle class in emerging markets, leads to an increase in consumer demand. The growth in consumer demand from emerging markets is supported by urbanization and increased participation in global trade, as well as a growing containerization, which has been at very low levels in emerging markets.

There are two key drivers for port revenue. The first and most important one is the container throughput, the number of crane lifts made. It depends on the number of terminals and lifts per terminal, which is influenced by factors such as global trade and GDP. Figure 26 illustrates the global container output in addition to APMM estimates of future growth; global container output is still expected to increase, but at a lower rate than the previous years. E.g. in the period of 2012-2015 average annual growth was 4.6%, driven by the growth of 5.5% in emerging markets and 1.9% in mature markets (APMM, 2015j). APMT expects total global container throughput to increase by around 4-5% per annum.

Figure 26 - Global container throughput and Y/Y growth

Source: Compiled by authors, APMM, (2015e)

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Figure 27 - Terminals and crane lifts APMT

Source: Compiled by authors, APMM, (2015e)

The second driver of revenue is the average income per lift made. Table 34 illustrates the development in APMT port revenue per lift. As shown, there has been a steady increase over time; however, the increase has flattened the past years. This is mainly due to an increased share of terminals in emerging markets, where revenue is lower. However, this does not necessarily have a negative impact of the business, as the relatively lower costs in emerging markets increase EBITDA margin relative to developed markets.

Table 34 - Revenue per lift APMT (USD)

2006 2007 2008 2009 2010 2011 2012 2013 Revenue per lift 78 81 96 100 100 110 109 111 Source: Compiled by authors, APMM, (2014c)

The terminal port industry is also protected by high entry barriers, due to the relatively high capital intensity, limited availability of long-term port concessions at attractive locations as well as the ability for current players to build up a global network of terminals. The relatively low competition in the industry explains the relatively healthy double-digit returns on invested capital.

As APMT gets a major part of its revenue from Maersk Line the revenue is more stable and easier to predict. Compared to Maersk Line, having volatile freight rates, APMT operates in a more stable pricing environment; hence, it does not suffer from the same volatility in earnings. The internal volume share is however decreasing. Volumes from external customers have increased gradually since the separation of the two. APMT says it continues to pursue an independent course in seeking carriers’ business(JOC,

Page 66 of 158 5.0 Business Units Valuation n.d.). As shown in the graph below, the share of external volumes was right above 30% in 2007, increasing to 50% in 2013.

Figure 28 - External volume in APMT as share of total volume

Source: Compiled by authors, Carnegie, (2014)

APMT has a significant presence in emerging markets, pt. around 50% of the revenue and as much as 80% of the EBITDA is generated in emerging markets (Port Finance International, 2014). In addition, both expansion and construction of new terminals are ongoing in e.g. China, Mexico, Turkey and Costa Rica. The number of terminals has constantly been increasing, and the 7 billion DKK acquisition of Grup Maritim TCB March 2016 added 8 terminals to APMT.

A large share of the cost of running a terminal is fixed or semi-variable, 58% in 2014 according to Maersk (APMM, 2015j). These categories mostly consist of wages, rent and capital costs, periodical fees, maintenance etc. Variable cost includes operational planning and execution, as well as continuous improvement. In 2014 APMT announced a NOPAT target of $1 billion by 2016 (APMM, 2014c), which implies a significant improvement from the 2015 level ($654 million).

5.3.3 Financial analysis Table 35 shows the financial highlights the past five years. Revenue is somewhat stable, dropping a little in 2015 due to divestitures (63 terminals YE2015 and 64 YE2014) and torpid global trade, particularly in West Africa, Russia and Brazil, only partly offset to revenue improvement (JOC, 2015) (APMM, 2015c). Cost saving initiatives reduce operating costs, giving a ROIC above the WACC target. There is not much of a trend in the ROIC measure.

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Table 35 - Financial highlights APMT 2011-2015

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 4.682 4.206 4.332 4.455 4.240 Operating costs 3.623 3.335 3.440 3.445 3.395 EBITDA 1.059 871 892 1.010 845 Depreciation & amortisation 369 283 297 302 309 Tax 121 163 56 234 106 NOPAT 648 701 770 900 654 Underlying NOPAT 709 849 626 Invested capital 5.124 5.495 6.177 5.933 6.177 Underlying ROIC (APMM) 13,1% 15,2% 13,5% 14,7% 10,9% Containers handled (million TEU) 33,5 35,5 36,3 38,3 36,0 Source: Compiled by authors, APMM, (2016e)

5.3.4 Forecasting A significant change in 2016 is the Grup Maritim TCB acquisition of 8 container terminals in Spain and Latin America for 2016Q1. The estimated annual container volume is an additional 3.5m TEUs, close to 10% of the current APMT volume (APM Terminals, 2016). APMT estimates an organic container throughput growth of 4-5% p.a. (Figure 26, upper bound). We assume a slightly more bearish estimate of 3% p.a. in our forecasted period. Revenue growth per lift is estimated at 1% p.a., implying a total organic growth of 4% p.a.

We expect an increase in the number of terminals the coming years; we, however, assume no large acquisitions. Due to the Grup Maritim TCB acquisition, the inorganic growth in 2016 and also 2017 is estimated at approximately 8% and 5% respectively, as well as a modest 2% for greenfield projects and acquisitions of 1-2 terminals per year. This implies total revenue growth as shown below.

Table 36 - Revenue growth APMT

2016E 2017E 2018E 2019E 2020E 2021(TP) Organic growth 4,0% 4,0% 4,0% 4,0% 4,0% 4,0% Inorganic growth 8,0% 5,0% 2,0% 2,0% 2,0% 2,0% Total growth 12,3% 9,2% 6,1% 6,1% 6,1% 6,1% Source: Compiled by authors

In our cost estimation, we assume the cost level to be proportional to the number of ports. We factor only a slightly increasing cost per terminal going forward, considering the normal inflation pressure. The opening of new terminals in emerging markets, where costs are lower, will somewhat offset inflationary pressure in more mature markets. These factors combined make the estimated EBITDA margin at 2015

Page 68 of 158 5.0 Business Units Valuation level. In 2015, the cost per terminal was about $53 million. A small increase of cost multiplied with the 2016 average number of terminals implies a cost of about $3.8B million, hence an EBITDA-margin of 20%. These assumptions combined are implying APMT will not reach its $1 billion target NOPAT in the forecasted period.

APMT has estimated capex approximately $1 billion p.a., due to acquisitions and other investments, where the Grup Maritim TCB acquisition investment of USD 400m over the next five years is included (APMM, 2015i).

Forecasting Summary Figure 29 - ROIC AMPT Figure 30 - Revenue & EBITDA-margin APMT

Source: Compiled by authors Source: Compiled by authors

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5.3.6 Valuation

DCF The implied enterprise value of APMT is thus $11.076bn.

Figure 31 - DCF APMT

APM Terminals DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF 75 211 278 356 436 884 WACC 8,48% 8,49% 8,49% 8,48% 8,44% 8,36% Discount factor 0,92 0,85 0,78 0,72 0,67 Discounted FCFF 69 180 218 257 291

Valuation PV of FCFF in forecast horizon 1.014 PV Terminal period FCFF 10.062 Terminal period - % of total value 91% Terminal period - FCFF growth 2,5% Enterprise value at YE(2015) 11.076

Source: Compiled by authors

Sensitivity analysis Our sensitivity analysis table examines the change in enterprise value (in billion USD) when terminal period growth (top-down) and cost of capital (left-right) changes. Table 38 examines the share price impact of an isolated APMT change. The share price is somewhat volatile to APMT changes.

Table 37 - APMT sensitivity analysis Table 38 – Share price

Source: Compiled by authors Source: Compiled by authors

APMT costs are largely fixed, so the gross contribution from another lift is significant. Our own calculations expect a 1.49% change in APMT EV when revenue changes 1pp in 2016 and going forward. Cost initiatives might increase EBITDA-margin, where a 1pp decrease in EBITDA-margin increases APMT EV with 7.39%.

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Relative Valuation Due to the relatively stable earnings in the industry we use the EV/EBITDA multiple to sanity check our DCF with our comparable peers. The harmonic mean of APMT is above the harmonic mean of its peers. This could mean the fundamental analysis overvalues APMT, or the relatively better performance of the APMM business unit underpins its higher relative EV/EBITDA. However, APMT is in line with DP World, as Hamburger Hafen lowers the peer average.

Table 39 - Relative valuation APMT

EV/EBITDA APM Terminals 2016E 2017E CSL 7,34 7,00 DP World 10,54 9,63 Hamburger Hafen 4,79 4,41 ICTSI 9,49 8,85 Harmonic mean 7,34 6,82 APM Terminals 11,67 10,69

Source: Compiled by authors, Bloomberg

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5.4 Maersk Drilling

5.4.1 Overview Maersk Drilling is a medium-size provider of offshore drilling services to the upstream segment of the oil and gas industry. It was established in 1972, just as Maersk Oil had commenced operations at its first oil field. As the world’s demand for oil has grown, so has Maersk Drilling’s expansion continued with a focus on harsh conditions and deep waters. Today Maersk Drilling employs almost 4000 people and its fleet consists of 22 rigs; 14 jack-ups (and one under construction), four semisubmersibles, and four drillships. The figure below illustrates the drilling locations, end of 2015.

Figure 32 - Maersk Drilling Rig fleet overview

Source: APMM, (2015j)

Despite the current market conditions, Maersk Drilling made a historically high NOPAT of $751M in 2015. The overall high financial performance of 2015 has been mainly due to good contract coverage, fleet growth, cost savings and fewer yard stays (APMM, 2015d). Maersk Drilling has also been investing in several new rigs the last couple of years, almost doubling invested capital from 2011 to 2015, while ROIC has been in the range of 7.1-12.5%.

Maersk Drilling has seen its sales significantly increase the last couple of years, mainly due to the $4.5 billion investment in the recent fleet expansion program. 2015 was a record year where NOPAT reached $751m increased 57% from 2014 to 2015 mainly driven by seven new rigs under contract and lower start-up costs related to the nearly completed fleet expansion, partly offset by two rigs off contract.

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Table 40 - Financial Highlights Maersk Drilling 2011-2015

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 1.878 1.683 1.972 2.102 2.517 Operating costs 1.016 1.045 1.109 1.199 1.121 EBITDA 862 638 863 903 1.396 Depreciation & amortisation 242 197 239 313 519 Tax 130 94 119 123 163 NOPAT 488 347 528 478 751 Underlying NOPAT 524 471 732 Invested capital 4.102 4.283 5.320 7.623 7.978 Underlying ROIC (APMM) 12,5% 8,8% 10,8% 7,1% 9,3%

Source: Compiled by authors, APMM, (2016e)

Drilling costs consist primarily of operating expenses related to the rigs, where the crew, maintenance, and capital costs are the major components, which are relatively fixed. The drilling industry, therefore, offers great leverage in its business model; when utilization and day rates are high the business is vastly profitable. Unfortunately, leverage works both ways and idle rigs with relatively high fixed costs can be a significant drag.

5.4.2 Strategy This section will discuss the main value driving strategic factors affecting Maersk Drilling.

External factors Revenue in Maersk Drilling is the product of the number of rigs employed, the day rates they command and the operational uptime. We, therefore, look into the factors involved in affecting the outcome of these variables. The figure below illustrates the development in day rates for both ultra-deepwater floaters and premium jack-up day rates for the past 9 years. It is worth noting these are averages and include quite some variation in regards to conditions such as water depth, vessel technology, and duration of contract. Due to the durations of varying contracts, Maersk Drilling’s revenue is affected by a certain lag as we see changes in the prevailing day rates.

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Table 41 - Day rates (USD) drilling market 2007-2015 Figure 33- Supply/Demand and utilization in the drilling market

Source: Compiled by authors, APMM, (2015c), ABG Source: Compiled by authors, Sparebank 1

Sunndal Collier, (2015) Markets, (2016)

The utilization rate in the global market has declined about 10% percentage points over the two last years due to the increased gap between supply and demand. Half of the floater fleet will come off contract before YE2016 and utilization is thus likely continued to drop, with a trough likely to be seen at the 50% mark (Sparebank 1 Markets, 2016). These highly unfavorable market conditions will make day rates lean toward opex, and for some short-term work also even drop below opex. Global rig utilization is decreasing as supply outpaces demand, and nothing indicates this will turn around quickly in the short-term.

Exploration and production (E&P) of oil companies is one of the main drivers behind the demand for drilling services. The current oil price is causing oil companies to back down on their exploration and production capital expenditures. Headcounts at oil companies are being reduced, and several existing offshore field developments are either postponed or outright canceled. Based on guidance from a large number of oil companies, E&P spending in 2016 is expected to decline about 16% following the record- high cut of 22% in 2015, which without a large amounts of scrapping will cause an even larger deviation between supply and demand (Sparebank 1 Markets, 2016).

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Figure 34 - Capital expenditures by oil companies 2010-2016

Source: Compiled by authors, APMM, (2015c)

The rig market has seen a solid increase in supply over the past few years, as shown in the graph below. Between 2010 and 2015, the rig fleet grew by around 40%. Order books have been at record levels and a continued oversupply is expected for the upcoming years. We expect the process of restoring market balance to be a lengthy and painful exercise for the industry.

Figure 35 - Global rig fleet

Source: Compiled by authors, Carnegie, (2014)

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Drilling companies have done a good job preserving cash flow by reducing cost. For many companies with steep negative cash flows and high debt levels it is essential to preserve cash in order to stay within debt covenants, and thus, avoid restructuring and/or equity injections. (Sparebank 1 Markets, 2016) notes this could turn out to be challenging as contract re-negotiations and terminations are likely to surface. The NIBD/EBITDA ratio in the industry has rapidly increased the past 10 years and it is therefore likely a number of drillers will be in need for debt restructuring and/or equity need starting this year. Thus, in the current market players are not only dependent on a new rig fleet but also good balance sheet strength in what seems to be a game of survival. If the conglomerate structure of APMM is able to support Maersk Drilling financially in this downturn of the cycle Maersk Drilling should have a sustainable competitive advantage relative to its peers.

Figure 36 - NIBD/EBITDA

Source: Compiled by authors, Sparebank 1 Markets, (2016)

Internal factors Maersk Drilling has a young and modern fleet compared to its competitors and should be amongst the first in line for new contracts. However, this could also impose a threat if the down turn in the industry is sustaining and Maersk Drilling would need to scrap newer rigs and face higher impairments with its relatively new and more valuable assets.

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Table 42 - Average years jack-up fleet Table 43 - Average year floater fleet

Source: Compiled by authors, Infield.com, (2016) Source: Compiled by authors, Infield.com, (2016)

An oversupply of rigs has caused the rig market to collapse in 2015, but Maersk Drilling has not been hit too hard due to good contract coverage. However, in December 2015 Maersk Drilling stacked one old rig and is warm-stacking another two newer ones, showing not even Maersk Drilling is immune to the market downturn. Eight out of Maersk Drilling’s 23 rigs are facing contract expiry in 2016 and imposes a big risk on earnings.

Figure 37 - Contract coverage Maersk Drilling Figure 38 - Revenue backlog $B per year

Source: Compiled by authors, APMM, (2015c) Source: Compiled by authors, APMM, (2015c)

The market situation now requires another cost level, and Maersk Drilling and other industry players have launched cost reduction and performance enhancement programs. Maersk Drilling aims for 10% savings from its 2014 level to 2016 and claims to have cut the cost of 8% through optimizing yard stays, vendor renegotiations, reduced organization in the head office, a salary freeze and changes to and

Page 77 of 158 5.0 Business Units Valuation optimization of Maersk Drilling’s operation (Maersk Drilling, Annual Magazine). However, some of these industry savings could also be related to postponement of non-critical maintenance and reduction of stacking cost (SBR markets). This would eventually bite back either in the form of higher than expected re-activation cost – or significantly reduced long-term earnings capacity.

5.4.4 Forecast

Revenue To forecast revenue we have modeled Maersk Drilling’s income as a function of rates for current contracts and assumed future rates and utilization. The day rates for the current contracts (Carnegie, 2016) have been used as input for the length of the total current contracts. Day rates beyond have been based on the Sparebank 1 Market day rates assumptions for the industry for 2016-2018. Beyond this, we assume day rates grow by 4% annually between in line with the argument of a recovering oil price, and an implied increase spend on E&P activity and demand for rigs (see Appendix 10-12 for full calculations). Operational uptime is assumed to be the equivalent of the average uptime for the last five years (96% according to APMM, (2015c)). For our terminal period, we try to represent long-term normalized earnings and factor in historical average prices for the period 2007-2015 for premium jack ups and ultra-deepwater rigs (160 and 442 thousand per day respectively).

Operating costs Operating expenses is assumed to be at the same level as 2015 in line with the nearly completed fleet expansion program and the dampening lower start-up costs related to the new rigs, offset by the expected recurring of maintenance and stacking cost. These costs are adjusted for the increase in contracted days which are proxied by the average number of operational rigs in each corresponding year. We furthermore assume the operational cost for warm stacked rigs to remain at a full level.

Utilization We assume utilization to both be affected by whether it is under contract and whether a yard stay is necessary. Yard stays are highly dependent on both cost and duration on numerous factors such as age and type of vessel. Maersk guides for a duration of 14-100 days with the cost of USD 5m - 100m (Maersk Drilling, 2014). We assume all rigs will undergo a yard stay every five year with a length of 30 days, mainly due to the fleet’s young age, thus implying on an average year 1.64% of all available days during the year are used for yard stays. Contract coverage is assumed to fall to a bottom of 80% during 2018, before gradually increasing to 92% for 2020.

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Capex The fleet expansion program has nearly been completed, with only one rig still outstanding for delivery Q1 2016. We thus assume cash flow for capital expenditure to dampen off to 0.7bn for 2016, before going back to the 2012 level of 0.4bn for the rest of our forecasted period as we assume the Maersk Drilling with its new fleet will restrain from new rig investments in light of our assumed oil price.

Forecasting summary We expect Maersk Drilling to have a revenue drop in 2016 and 2017, affecting ROIC. Throughout the forecasting period, ROIC will be low, due to the market conditions. In the terminal period we expect the market conditions to improve, hence the increased ROIC.

Figure 39 - Future ROIC Maersk Drilling Figure 40 - Revenue & EBITDA-margin Maersk Drilling

Source: Compiled by authors Source: Compiled by authors

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5.4.5 Valuation Through forecasting the key value drivers, the future estimated FCFFs of Maersk Drilling is shown below.

Table 44 - DCF Maersk Drilling

Maersk Drilling DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF 147 100 136 190 161 493 WACC 10,13% 10,13% 10,14% 10,13% 10,10% 10,02% Discount factor 0,91 0,82 0,75 0,68 0,62 Discounted FCFF 134 83 101 129 100

Valuation PV of FCFF in forecast horizon 546 PV Terminal period FCFF 4.054 Terminal period - % of total value 88% Terminal period - FCFF growth 2,5% Estimated Enterprise Value 4.600 Source: Compiled by authors

Relative valuation Table 45 - Relative valuation Maersk Drilling

P/B MAERSK DRILLING 2016E 2017E Atwood 0,19 0,19 Diamond Offshore Drilling 0,70 0,69 Ensco PLC 0,34 0,33 Fred Olsen Energy 0,20 0,24 Noble Corporation 0,36 0,37 ProSafe 0,17 0,15 Rowan 0,39 0,39 Seadrill 0,15 0,15 Songa Offshore 0,05 0,04 Transocean 0,23 0,23 Harmonic mean 0,17 0,16 Maersk Drilling 0,41 0,41 Sources: Compiled by authors, Bloomberg

Table 45 illustrates the 2016 and 2017 P/B multiples of the chosen Maersk Drilling peer group. Maersk Drilling has a multiple above the harmonic mean but in line with some of the top trading multiples, which seems plausible due to Maersk Drilling relatively new fleet.

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Sensitivity Analysis Our sensitivity analysis examines the change in Enterprise Value (USD billion) when Terminal Period growth (top-down) and cost of capital (left-right) changes. Table 47 examines the share price impact of an isolated Maersk Drilling change. Relatively to the other business units the share price is not very volatile to Maersk Drilling.

Table 46 - Sensitivity analysis Maersk Drilling Enterprise Value Table 47 – Share price sensitivity

Terminal WACC change Terminal WACC change growth 2pp 1pp 0 -1pp -2pp growth 2pp 1pp 0 -1pp -2pp 3,50% 3.788 4.406 5.221 6.340 7.966 3,50% 10.474 10.659 10.903 11.237 11.723 3,00% 3.607 4.165 4.888 5.861 7.231 3,00% 10.420 10.587 10.803 11.094 11.504 2,50% 3.445 3.952 4.600 5.454 6.628 2,50% 10.371 10.523 10.717 10.972 11.323 2,00% 10.328 10.466 10.641 10.868 11.173 2,00% 3.299 3.762 4.347 5.106 6.126 1,50% 10.288 10.416 10.575 10.778 11.046 1,50% 3.167 3.593 4.124 4.804 5.701 Source: Compiled by authors Source: Compiled by authors

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5.5 APM Shipping Services The APM Shipping Services group was established in 2014 and comprises four business units; Maersk Tankers, Maersk Supply Service, Damco and Svitzer. In 2015, the business unit had some 18300 employees, representing 13% of the APMM revenue and 12% of the invested capital. APM Shipping Services stated a goal to reach a NOPAT of USD 500M by 2016 (APMM, 2014c). These four business units will be valued in the following four sections.

Figure 41 - Invested capital APMM, 2015 Figure 42 - Revenue & EBITDA APM Shipping Services, 2015

Source: Compiled by authors, APMM, (2015b) Source: Compiled by authors, APMM, (2015b)

5.5.1 Maersk Tankers Maersk Tankers is amongst the largest product tanker companies in the world (Shippingwatch, 2015c). Its main trading routes are from the production areas in the Arabian Gulf and West Africa to Asia, Europe and the USA (Maersk Tankers, 2016). Financial performance was unsatisfactory for years partly due to industry overcapacity in the tanker industry. Outlooks did not seem to improve and Maersk decided to divest its gas (2013) and crude segment tanker fleet (2014), now focusing solely on product tankers. The sales of these segments combined with impairments and depreciation significantly lowered invested capital from $3.6bn in 2012 to $1.6bn in 2014. After a longer period of unsatisfactory returns NOPAT grew in 2015 and increased ROIC to slightly below 10%.

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Table 48 - Financial highlights 2011-2015 Maersk Tankers

Financial highlights (USDn) 2011 2012 2013 2014 2015 Revenue 1.299 1.977 1.625 1.175 1.058 Operating costs 1.191 1.763 1.604 904 761 EBITDA 108 214 21 271 297 Depreciation & amortisation 228 268 195 132 140 Tax 11 2 2 1 1 NOPAT -175 -315 -321 130 160 Underlying NOPAT -172 139 156 Invested capital 3.774 3.633 2.335 1.583 1.644 Underlying ROIC (APMM) -4,3% -8,2% -10,4% 6,8% 9,9%

Source: Compiled by authors, APMM, (2016e)

Strategic overview According to external consultancies (APMM, 2014c) expected annual market growth for the product tanker market is expected to be 3-4% through 2014-2019. This is driven by expected refinery closures in Europe resulting in an increased need for transportation of refined products over longer distances from production centers in Asia and the Middle East to Europe (ICIS, 2015). Maersk introduced its “Taking Lead” strategy for Maersk Tankers focusing on improving profitability and relative performance within cost leadership, active position taking based on data and analytics, and third-party services. In 2015, $21m in profit was contributed to this initiative and Maersk estimates “Taking Lead” to contribute 2-3% to ROIC over the next years (APMM, 2015e).

Morten Engelstoft, CEO of Maersk Tankers, stated: “We're not going to be bigger than we are today. We are going to phase out the oldest part of our fleet as we take delivery of new ships. Right now the rates are strong, but this is still a very volatile industry with long periods of high and low levels. The key thing now is to improve our results,” (Shippingwatch, 2015a). Maersk Tankers now aim to cut operating expenses by 12% by FY19E, amongst other things by slow steaming7. However, these addressable operational expenses do not include, among other, time charter and bareboat hire costs and depreciations (APMM, 2014c).

7 Slow steaming refers to the practice of operating transoceanic cargo ships, especially container ships, at significantly less than their maximum speed

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Forecast We believe product tanker growth will be in the lower end of APMM’s expectations of 3-4% annual growth in line with our oil price assumptions of a slowly increasing oil price. We thus factor in a 3% growth until 2019, before flattening growth flattens out to 2.5%. The EBITDA forecast is based on the recent years after the restructuring, and we factor in a slight increase in the years due to the cost cutting initiatives.

Due to the assets held for sale in 2012-2014, net working capital was abnormally high for these years. We do not expect more assets to be held for sale in our forecasted period, and thus, use the historical average of NWC/sales subtracted assets held for sale. We do not expect any impairment losses and assume tax/EBIT to be in line with its historical average. As old ships will be phased out as new come in, we assume property, plant and equipment for Maersk Tankers to stay stable for the forecasted period.

The forecasted numbers lead to the following development in ROIC, revenue, and EBITDA-margin. Our forecast thus sees ROIC maintaining the current level after the restructuring with a gradual increase due to the cost initiatives, but we do not expect Maersk Tankers to fully reach the stated goal of a 2-3% increase.

Figure 43 - ROIC & WACC Maersk Tankers Figure 44 - Revenue and EBITDA-margin Maersk Tankers

Source: Compiled by authors Source: Compiled by authors

Valuation

By discounting with the corresponding calculated WACC we end up with an estimated enterprise value of $2.422 million (see Appendix 30-32 for full pro forma statement).

Page 84 of 158 5.0 Business Units Valuation

Figure 45 - DCF Maersk Tankers

Maersk Tankers DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF 103 147 168 183 193 203 WACC 9,59% 9,59% 9,60% 9,59% 9,53% 9,41% Discount factor 0,91 0,83 0,76 0,69 0,63 Discounted FCFF 94 123 128 127 122

Valuation PV of FCFF in forecast horizon 593 PV Terminal period FCFF 1.866 Terminal period - % of total value 76% Terminal period - FCFF growth 2,5% Estimated Enterprise Value 2.459 Source: Compiled by authors

Table 49 - Sensitivity analysis Maersk Tankers Table 50 - EV/EBITDA multiple Maersk Tankers

Terminal WACC change growth 2pp 1pp 0 -1pp -2pp 3,50% 2.050 2.360 2.775 3.360 4.245

3,00% 1.961 2.239 2.605 3.106 3.834 2,50% 1.883 2.134 2.459 2.894 3.508 2,00% 1.813 2.042 2.333 2.716 3.242 1,50% 1.749 1.960 2.223 2.564 3.021 Source: Compiled by authors Source: Compiled by authors

Table 49 and illustrates the enterprise value sensitivity of changes in terminal growth as well as WACC. Due to the relatively low impact, there will be no share price table for Maersk Tankers nor the three other business units of APM Shipping Services. The Maersk Tankers EV/EBITDA multiple in Table 50 overvalues Maersk Tankers relative to peers.

5.5.2 Maersk Supply Service Maersk Supply Service is a provider of global offshore marine services with a focus on deep-water services with a fleet of more than 50 vessels with over 1,900 crew members supported by around 250 onshore staff (Maersk Supply Service, 2016). It has a leading 17% market share in the anchor handling tug supply segment, responsible for towing of oil rigs and handling of anchors with its 44 vessels (Jefferies, 2015), and a 2% market share in the offshore supply vessel market (6 vessels). In terms of invested capital Maersk Shipping Services was the largest unit of APM Shipping Services (37%) in 2015. Revenue has continually decreased since 2011 and dropped significantly in 2015, mainly due to lower rates and utilization in the context of the market decline of the offshore industry.

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Table 51 - Financial highlights Maersk Supply Service 2011-2015

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 942 877 772 778 613 Operating costs 526 558 423 430 345 EBITDA 416 319 349 348 268 Depreciation & amortisation 167 166 146 142 141 Tax 9 10 20 18 10 NOPAT 243 132 187 201 147 Underlying NOPAT 182 189 117 Invested capital 2.146 2.206 1.699 1.704 1.769 Underlying ROIC (APMM) 11,2% 6,1% 10,7% 11,9% 8,5% Source: Compiled by authors, APMM, (2016e)

Strategy According to APMM the main demand driver for APM Shipping Services is existing and sanctioned reservoirs (APMM, 2014c). Market conditions in the offshore supply vessel industry have deteriorated due to increase pressure on the offshore segment, initially from an increasing focus on capital discipline and more recently from increasing project delays in the current low oil price environment. Revenues fell 21,2% from 2014 and 2015, which was in line with the record cut high in E&P spending in 2015 (22%). According to a survey done by Barclays of 225 upstream oil and gas companies, E&P spending is expected to decline by 15% in 2016 (Oil & Gas Journal, 2016), and short-term outlook for Maersk Supply Services does thus not look to promising.

To better handle this downturn Maersk initiated a cost efficiency project in Q2 2015, Winning in the storm, with a goal of reaching annual savings of USD 40m by 2016 (Maersk Supply Service, 2015).

Forecast We assume the expected cut in E&P for 2016 to have a similar impact for APM Shipping Services as the E&P spending cut in 2015 and factor in a 15% revenue decline in 2016. In line with our slowly increasing oil price assumption we assume the market for offshore marine services to get better as E&P spending increase and more projects get sanctioned, and factor in a 3% growth in the remaining forecast period. Furthermore, we assume EBITDA margin to slightly increase over the forecasted period due to the cost efficiency program. We see ROIC stabilizing on a level below its targeted 10% for our forecasted period.

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Figure 46 - ROIC Maersk Supply Services Figure 47 -Revenue and EBITDA Maersk Supply Services

Source: Compiled by authors Source: Compiled by authors

Valuation By discounting with the corresponding calculated WACC we end up with an estimated enterprise value of USD 1.321bn (see Appendix 33-35 for full pro forma statement).

Figure 48 - DCF Maersk Supply Services

Maersk Supply Service DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF 56 91 98 105 112 121 WACC 10,25% 10,25% 10,26% 10,25% 10,20% 10,09% Discount factor 0,91 0,82 0,75 0,68 0,62 Discounted FCFF 50 75 73 71 69

Valuation PV of FCFF in forecast horizon 339 PV Terminal period FCFF 982 Terminal period - % of total value 74% Terminal period - FCFF growth 2,5% Estimated Enterprise Value 1.321 Source: Compiled by authors

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Table 52 - Sensitivity analysis Maersk Supply Services EV Table 53 - Multiple Maersk Supply Service

Source: Compiled by authors Source: Compiled by authors

Table 52 illustrates the sensitivity of changes in terminal growth as well as WACC. Table 53 illustrates the EV/EBITDA multiple of Maersk Supply Services relative to peers. The Maersk Supply Services EV/EBITDA multiple in Table 53 overvalues Maersk Tankers relative to peers.

5.5.3 Damco

Overview Damco is a freight forwarder managing a global logistics network and providing customers with supply chain services. In 2015, Damco managed 2.9 million TEU of ocean freight and supply chain management volumes, and air freighted 180,000 tons. Damco has been one of the worst-performing business units of APMM, suffering a deficit which can be traced all way back from the separation from Maersk Line in 2009 (Shippingwatch, 2014).

Damco is headquartered in The Hauge, the Netherlands, and provides services across about 100 countries with some 11,000 employees in 300+ locations worldwide (Damco, 2015). The “One Damco” restructuring program restructured the number of operations offices to 50, in addition to 250 sales offices (APMM, 2016f). Damco’s origin goes back to 1905 when C.W.H. van Dam & Co was established (Damco, 2015). The company became a part of APMM in 2005, combined with the other freight forwarding operations of Maersk Logistics, and rebranded to Damco in 2009.

Strategic analysis Damco relies on many of the same value drivers as Maersk Line, e.g. the demand of freighted goods and containerization. The “One Damco” restructuring program targeted annual cost savings of $35 million (APMM, 2014c) by focusing on improving collaboration through the consolidation of eight geographic regions into four (Americas, Europe+Russia, Africa+ME and Asia Pacific).

According to APMM, the container shipping market is expected to grow 3-5% (APMM, 2015e) over the next years which mean there is room for top line growth also for Damco. It has to improve its

Page 88 of 158 5.0 Business Units Valuation profitability in order to be in line with APMM’s other BU’s, which seems to be a tough turnaround. A divestment of Damco has already been mentioned, and should not be ruled out (Maritime Executive, 2015).

Financial analysis The global restructuring program that was initiated and expected to end in 2013 took its toll on the bottom line as expected in 2013, but dragged out and also significantly impacted the result in 2014. Top priorities are growing ocean and air profitability and improving margins. In 2015, Damco was able to show a positive result again, but revenue dropped 13% mainly due to the rate of exchange movements and a drop in ocean freight volumes in order to de-select less profitable business. The transformation phase from 2013-2014 has started to show some of the planned benefits, mainly due productivity improvements, overhead cost reductions, and growth in supply chain management activities.

Table 54 - Financial highlights Damco 2011-2015, million USD

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 2.752 3.229 3.212 3.164 2.740 Operating costs 2.632 3.138 3.277 3.312 2.686 EBITDA 120 91 -65 -148 54 Depreciation & amortisation 24 23 28 34 29 Tax 35 36 22 52 21 NOPAT 63 55 -111 -293 19 Underlying NOPAT -107 -225 15 Invested capital 317 512 412 321 203 Underlying ROIC (APMM) 24% 13% -22% -63% 7% Source: Compiled by authors, APMM, (2016e)

Forecasting APMM has revealed very limited amounts of financial information on Damco, which leaves fewer inputs to our forecast. APMM expects market growth of 3-5% over the next years (APMM, 2014b), but no supporting arguments make us factor in an annual growth of 3% in the forecasted period. APMM still expects to see improvements from its turnaround program, but also admitted it “definitely faces a number of challenges” during its capital market day of 2015. As for EBITDA-margin we see no strong arguments for expecting a different level than of 2015 for the coming years. Depreciation and other items are expected to be in line with its historical average.

Failure to improve DAMCO’s profitability might lead to the decision to divest the company due to the relatively limited synergies between freight forwarding and shipping, illustrated by a wave of recent

Page 89 of 158 5.0 Business Units Valuation divestments of logistics operations by the shipping lines (Jefferies, 2015). However, we do not factor in a divestment of Damco in our forecast.

The forecasted numbers lead to the following development in ROIC, revenue, and EBITDA-margin.

Figure 49 - ROIC Damco Figure 50 - Revenue and EBITDA Damco

Source: Compiled by authors Source: Compiled by authors

Valuation The future estimated FCFFs of Damco is shown below which implies and Enterprise Value of $404M added to the sum-of-the-parts section later.

Figure 51 - DCF Damco

Maersk Damco DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF -96 7 3 3 4 41 WACC 8,38% 8,38% 8,39% 8,38% 8,34% 8,26% Discount factor 0,92 0,85 0,79 0,72 0,67 Discounted FCFF -88,2 5,8 2,2 2,4 2,6

Valuation PV of FCFF in forecast horizon -75,2 PV Terminal period FCFF 479,6 Terminal period - % of total value 119% Terminal period - FCFF growth 2,5% Enterprise value at YE(2015) 404 Source: Compiled by authors

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Table 55 - Sensitivity analysis Damco enterprise value Table 56 - Relative valuation Damco

Terminal WACC change EV/EBITDA growth 2pp 1pp 0 -1pp -2pp Damco 2016E 2017E 3,50% 299 383 505 694 1.022 Deutsche Post 6,25 5,87 Expeditors 10,72 10,15 3,00% 273 347 450 604 854 Panalpina Welttransport 11,27 9,30 2,50% 250 315 404 532 730 Harmonic mean 8,77 7,97 2,00% 231 289 366 474 636 Damco 9,74 9,46 1,50% 213 265 333 427 561 Source: Compiled by authors, Bloomberg Source: Compiled by authors

Table 55 examines the change in enterprise value (USD million) when terminal period growth (top- down) and cost of capital (left-right) changes. In Table 56 we see the EV/EBITDA value of Damco is lower than the harmonic mean of its peer group. This can be argued due to the poor performance of the business unit.

5.5.4 Svitzer Svitzer is a towage operator with revenues of $669m in FY15, accounting for 1.6% of total revenues in APMM. NOPAT amounted to $120m with an underlying ROIC of 10.9%. It was established already in 1833 as a pioneering salvage company and entered the towing business in 1870. In 1979 APMM acquired Svitzer. Today, Svitzer operates in more than 40 countries worldwide with a fleet of more than 430 vessels and around 4000 employees (Svitzer, 2016a).

Svitzer’s activities can be divided into harbor towage, terminal towage, and salvage & emergency response. Harbor towage is towage of large vessels in regular ports and accounted for approximately two thirds of Svitzer EBITDA in 2013 (APMM, 2014c). Terminal towage is towage at LNG, oil & mining terminals and accounted for approximately one third of total EBITDA. Salvage & emergency response is vessel emergency prevention and response as well as vessel wreck removal, from where EBITDA only accounted for a couple of percent of 2013 (APMM, 2014c). This segment was merged with Crowley Maritime’s Titan Salvage in 2015 to form the largest player in the field, Ardent, which covers approximately one third of the market for emergency response.

Strategic Analysis Within the harbor towage segment each port is a market and the contracts with vessel operators are priced by the individual job. The harbor towage market is highly competitive due to overcapacity in mature markets of Europe and Australia. Svitzer’s strategy focuses on increasing asset utilization and establishing multi-port and performance-related contracts while capitalizing on reliability and providing

Page 91 of 158 5.0 Business Units Valuation value through its coverage of ports worldwide. Improvement of productivity in the market is heavily reliant on collaborating unions in order to find more flexible working arrangements. It further focuses on leveraging the current relationship with global clients to increase investments outside of Europe and Australia in emerging markets (APMM, 2015e). In 2015, Svitzer acquired a Brazilian towage operator (Svitzer, 2015), another one in the Caribbean (Svitzer, 2016b), and established a joint venture with SVR Marine Services to enter the Malaysian market (LNG World News, 2015).

Terminal towage, on the other hand, is under long-term contracts, typically 15-25 years, with competition through tendering. For example, Svitzer is currently engaged on some large LNG projects, including Angola LNG, Ras Laffan in Qatar and Gorgon LNG and Wheatstone LNG both in Australia under long-term contracts. The difficult outlook for the commodity exports and for shipping and offshore in general will likely impact Svitzer’s growth potential negatively in the coming years. Like Damco, Svitzer is in the periphery of APMM’s core operations, and some analysts see a divestment in the near future as likely (Shippingwatch, 2016).

Financial Analysis Svitzer has in recent years on average performed below the 10% ROIC goal. The results for 2012 and 2014 were significantly impacted by impairments, the latter on goodwill related to the 2007 Adsteam acquisition in Australia which is negatively impacted by industry overcapacity, a high industrial cost structure and a general slowdown of bulk activities (APMM, 2014a). Revenue in 2015 dropped by USD 143m due to a stronger USD relatively to the Euro and Australian dollar, but also as salvage revenue was excluded from revenues after the merge with Titan Salvage (USD 80m). EBITDA margin saw significant improvement to 28.4% (20.9%) through pricing, productivity and cost saving initiatives which were initiated in 2014 (APMM, 2014a, 2015c).

Table 57 - Financial highlights Svitzer 2011-2015

Financial highlights (USDmn) 2011 2012 2013 2014 2015 Revenue 873 820 831 812 669 Operating costs 636 597 614 642 479 EBITDA 237 223 217 170 190 Depreciation & amortisation 109 92 85 93 84 Tax 30 38 21 20 6 NOPAT 102 7 156 -270 120 Underlying NOPAT 134 82 116 Invested capital 1.589 1.495 1.363 1.069 1.132 Underlying ROIC (APMM) 6,4% 0,5% 10,8% -19,2% 10,9% Source: Compiled by authors, APMM, (2016e)

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Forecasting We assume a slight increase in property, plant, and equipment for 2016 and 2017 in line with Svitzer’s strategy of further expanding operations outside of Europe and Australia. We expect revenue to grow in line with the growth in operations and inflation but slightly offset due to tough market conditions. EBITDA margin is assumed to be in line with the historical average, as well as depreciation and other items. We assume no investments in joint ventures in the forecasted period and do not take into account any possible divestment. The forecasted numbers lead to the following development in ROIC, revenue, and EBITDA-margin.

Figure 52 - Future ROIC Svitzer Figure 53 - Revenue & EBITDA-margin Svitzer

Source: Compiled by authors Source: Compiled by authors

Valuation The future estimated FCFFs of Damco is shown below which implies and Enterprise Value of $1.554bn which will be added to the sum-of-the-parts section later.

Page 93 of 158 5.0 Business Units Valuation

Figure 54 - DCF Svitzer

Svitzer DCF 2016E 2017E 2018E 2019E 2020E 2021(TP) FCFF 82 47 92 95 98 97 WACC 7,97% 7,97% 7,98% 7,97% 7,94% 7,87% Discount factor 0,93 0,86 0,79 0,74 0,68 Discounted FCFF 76 40 73 70 67

Valuation PV of FCFF in forecast horizon 325 PV Terminal period FCFF 1.229 Terminal period - % of total value 79% Terminal period - FCFF growth 2,5% Enterprise Value 1.554 Source: Compiled by authors

Our Table 58 sensitivity analysis of Svitzer examines the change in enterprise value (USD billion) when terminal period growth (top-down) and cost of capital (left-right) changes.

Table 58 - Sensitivity analysis Svitzer enterprise value

Terminal WACC change growth 2pp 1pp 0 -1pp -2pp 3,50% 1.253 1.490 1.835 2.385 3.399 3,00% 1.184 1.390 1.680 2.121 2.868 2,50% 1.125 1.306 1.554 1.916 2.494 2,00% 1.073 1.234 1.449 1.754 2.216 1,50% 1.027 1.171 1.361 1.622 2.002 Source: Compiled by authors

Page 94 of 158 6.0 SWOT

6.0 SWOT To summarize our analysis we have conducted a SWOT matrix combining the factors to visualize what are the strengths, weaknesses, opportunities and threats of APMM and its business units.

Strengths Weaknesses  Distribution and sales networks (APMM)  High volatility and seasonality in earnings  Strong balance sheet implying significant (APMM) access to capital (APMM)  Underpricing due to conglomerate discount  Strong global brand name and reputation (APMM) (APMM, Maersk Line in specific)  Somewhat bureaucratic  Market share and cost leadership in container shipping (Maersk Line)  Best in class drilling assets (Drilling)  Global footprint in port management (APMT)  Barriers to market entry (APMT)

Opportunities Threats  Freight rates and oil price increase (APMM)  Sustained low freight rates and oil price  Growing economy (APMM) (APMM)  M&A and divestments (APMM)  Economic slowdown (APMM)  2M alliance synergies, e.g. cost savings  Large vessel disasters (APMM) (Maersk Line)  Major cyber-attack (APMM)  Regulation changes (APMM)  Future credit downgrade (APMM)

 Developments in the digital economy and its long-term effect on shipping  Lower global trade multiple vs GDP growth (Maersk Line & APMT)  Qatar contract at risk (Maersk Oil)  Oil spill (Maersk Oil)

Page 95 of 158 7.0 Sum-of-the-parts

7.0 Sum-of-the-parts

7.1 Aggregated reportable segments To see the bigger picture of APMM’s core performance we have added the reportable segments to an aggregated pro forma of Maersk’s reportable segments (see Appendix 42-44). This helps us understand the development of critical factors such as revenue growth, earnings, debt, cash flows, debt and invested capital.

We see APMM’s revenue fall further into 2016 before gradually increasing to the 2011 level by 2020. As for NOPAT we see an improvement already in 2016, mainly due to the large impairment losses in Maersk Oil for 2015. We expect NOPAT to increase gradually back to and above the 2012-2013 level, which helps increase ROIC to a 8.3% level for our terminal period.

Figure 55- APMM historical and estimated ROIC Figure 56 - APMM revenue and NOPAT

Source: Compiled by authors Source: Compiled by authors In our model, the surplus/deficit of each business units is assumed transferred to the corporate level where both dividends and net interest-bearing debt are set. We assume APMM will stick to its objective of increasing the nominal dividend per share over time and adjust the debt level accordingly. The debt level will thus increase significantly in 2016 and lower the equity ratio, but the ratio is well above the guidance to stay above a level of 40%.

Page 96 of 158 7.0 Sum-of-the-parts

Figure 57 - Dividends

Source: Compiled by authors, APMM, (2016c)

7.2 Reportable segment adjustments The reportable segments add up as the majority of Maersk’s core operation. However, the aggregated reportable segments do not account for the full income statement and balance sheet of Maersk Group’s, and hence, several adjustments are necessary to account for all of APMM’s activities.

Income statement adjustments

NOPAT from reportable segments does not aggregate to the consolidated income statement of APMM. The annual reports accounts for the adjustments from reportable segments to APMM profit (see Appendix 45), and includes other businesses, net financial items, unallocated tax, other unallocated items, and eliminations.

Other businesses include, amongst others, Maersk Container Industry and Maersk Training, as well as investments in the associated companies Danske Bank (sold in 2014) and Höegh Autoliners. Information on other businesses is limited to aggregated revenue and profit for the year, and as the underlying businesses vary highly from year to year (e.g. sales of the share of Danske Bank and Esvagt) the other businesses segment is thus unsuitable for DCF-valuations. Relative to the strictly limited availability of information on these other businesses we consider book value to be a fair assumption for the value of these other businesses and associated companies.

Page 97 of 158 7.0 Sum-of-the-parts

We have spread APMM’s net interest debt to the reportable segments based on the corresponding weight of invested capital, and net financial items have thus been covered in our reportable segments valuation.

Unallocated activities and eliminations are necessary to adjust for in order to make sure our all of APMM’s activities are properly accounted for. Unallocated activities comprise activities which are not attributable to reportable segments, including financial items as well as centralized purchasing and resale of a bunker and lubricating oil to companies. It is not specified by APMM, but we assume that these activities also include headquarters which is not directly attributable to any one segment. Revenue between segments is limited except for terminal activities and Damco, where a large part of the services is delivered to the Group’s container shipping activities. Eliminations are made due to transactions with associated companies, and joint arrangements are also eliminated in proportion to the APMM’s ownership share.

In order to account for the value effect of unallocated activities and eliminations, we value the cash flow of these unallocated activities and eliminations with a Gordon Growth Model. We assume a Danish corporate tax rate of 22%, cost of capital 9.65% (weighted average of the business units) and a growth rate of 2.5% (see Appendix 45)

Balance sheet adjustments

To account for all assets and liabilities, it is necessary to compare the aggregated reportable segments with the consolidated balance sheet. We have created an aggregated reportable segment pro forma (see Appendix 46) and differences in assets and liabilities have been identified (see Appendix 46). Significant differences exist with items such as non-interest bearing liabilities, other current and non- current assets, investments in associated companies, and property, plant, and equipment. We value all of these at book value in our sum of the parts calculations, implicitly other businesses at their book value.

Page 98 of 158 7.0 Sum-of-the-parts

7.3 Sum-of-the-parts value The sum-of-the-parts add up the contributing value from the business units, as well as the other factors, which cannot be traced to a business unit. To adjust the enterprise value to share price we adjust for the number of shares (21.891.500, Børsen.dk, (2016)) as well as the exchange rate from USD to DKK at the 1st of April (USD/DKK 6.546, ExchangeRates.org.uk, (2016)). Consequently, the sum of the parts valuation ultimately results in a theoretical share price of DKK 10.717, implying a 21.1% discount compared to the corresponding market price of 8,455 as of April 1st, 2016 (Yahoo! Finance, 2016a).

Figure 58 - Sum-of-the-parts

Sum-of-the-parts valuation

A.P. Moeller Maersk EV (USDm) Value/share (DKK) Methodology Reportable segments Maersk Line 16.599 4.963 DCF Maersk Oil 5.507 1.647 DCF APM Terminals 11.076 3.312 DCF Maersk Drilling 4.600 1.375 DCF Maersk Tankers 2.459 735 DCF Damco 404 121 DCF Svitzer 1.554 465 DCF Maersk Supply Service 1.321 395 DCF

Non-reportable segments* Assets Property, plant and equipment 530 158 1 x BV Investments in associated companies 347 104 1 x BV Other current assets 4.819 1.441 1 x BV Other non-current assets 1.412 422 1 x BV Liabilities Non-interest-bearing liabilities -6.006 -1.796 1 x BV NIBD -7.770 -2.323 1 x BV

Unallocated activities Unallocated activities and eliminations -1.013 -303 DCF

Theoretical share price (DKK) 10.717

USD/DKK 01.04 6,546 # shares (MM) 21,9

Closing price, 1. April 8.455 Implied discount 21,1%

*Assets and liabilities are calculated as the difference between total reportable segments and group balance sheet. Source: Compiled by authors

Page 99 of 158

Figure 58 illustrates the different BU’s impact of the total EV. When comparing to invested capital, Maersk Line and Maersk Drilling have an EV 9 pp lower than invested capital, meaning it contributes less to the total value relative to the amount of invested capital. Vice versa, the EV of APM terminal is 10pp above invested capital. Maersk Oil is 5pp above while APM Shipping Services combined is 2pp above. The sensitivity analysis reveals increasing WACC by 0.75% or decreasing the estimated terminal period growth by 1% will leave the theoretical share price slightly below the actual closing price of April 1st.

Figure 59 - Enterprise value reportable segments Table 59 - Sensitivity analysis reportable segments

TP growth WACC change #REF! 1.5pp 0.75pp 0 -0.75pp -1.5pp 3,50% 8.970 10.741 12.985 15.909 19.866 3,00% 8.234 9.804 11.762 14.263 17.560 2,50% 7.586 8.990 10.717 12.886 15.684 2,00% 7.011 8.276 9.814 11.718 14.129 1,50% 6.498 7.646 9.027 10.714 12.818

Source: Compiled by authors

Source: Compiled by authors

Page 100 of 158 8.0 Conglomerate Discount Discussion

8.0 Conglomerate Discount Discussion Our section on the theory of the conglomerate discount established the relevance of the phenomenon by covering the perspectives and predicted effects of corporate diversification. Our valuation shows evidence of a perception gap between the fundamental values of each business unit relative to the market price, trading at a discount of 21.1%.

A conglomerate discount has been applied by a number of equity analysts, but there seems to be no consensus on what the appropriate discount for APMM should be. Applying the theory about the benefits and costs of conglomeration should help indicate to which degree such a discount is justified. The following section will also discuss APMM and the conglomerate discount in relation to the view of APMM’s management and the market.

8.1 APMM in the perspective of conglomerate theory As Koller et al., (2015) argues the best owner of a company is changing over time, and high-performing conglomerates rebalance their portfolio by buying the ones they can improve performance and sell off the ones where someone else can provide extra value. In recent years, we have seen APMM selling several of its assets, but we still see some of the business units such as DAMCO struggling to reach the goal of being a top quartile performer. The change over time of best owner is perhaps even more frequent in today’s rapidly changing environment; especially in volatile industries such as the ones that APMM operate in. Over time, we expect APMM’s portfolio to be frequently subject to change and thus consider the transaction cost and disruption involved in these processes to be a big cost of diversification for APMM. Any investor can do this far more efficient and cheaply by adjusting his or her portfolio of stocks.

Another costly aspect of diversified companies is the lower performance that is often present due to added complexity and bureaucracy. Nils Smedegaard Andersen stated in 2011 he thought he stepped into a very bureaucratic company when he took over as CEO in 2007 (Børsen.dk, 2011). Much might have changed since then, but the culture and processes of such a large and historically rich company is not changed overnight. The authors feel confident in assuming the complexity and bureaucracy in a company like APMM should be significantly higher than its pure-play peers. In total, the benefits of the conglomerate structure should be quite large to outweigh the costs.

The main benefit for APMM as a conglomerate is arguably the unique links between its business units. Through its vertical integration, APMM should be able to harvest on improved insight and foresight

Page 101 of 158 8.0 Conglomerate Discount Discussion through the value chain, which allows for strategic planning and optimization opportunities in its long- term investments. If a company can embody activities along the supply chain, then it should be able to gain a competitive advantage towards the other players in the market. APMM’s supply chain is unique in its reach into ancillary shipping businesses. From its activities such as oil extraction, container development, and development of ports APMM is invested in both downstream and upstream businesses related to its core shipping business. Other examples include freight forwarding and supply chain management services under DAMCO and additional logistics service provider Svitzer, even though these are more peripheral to the core activities. However, after Nils Smedegaard Andersen took over as a CEO the company chose to take a step away from its vertical integration policy. E.g. by encouraging APM Terminals to increase its external revenue and APMM’s logistic operations were told to be a neutral player when choosing which shipping line to use. "We are moving away from this vertical integration in order to simplify our business and make sure every business we are involved in is competitive", Mr. Andersen said in an interview with Financial Times, (2008).

After several divestments of non-core businesses APMM seems to have a more aligned portfolio of businesses. There is, however, a downside to a more aligned business portfolio in that their returns often are more correlated which both increases earning volatility and limits the possibilities of optimizing capital allocation in periods where several of the businesses are experiencing a downturn. Neither the argument of being able to sustain a higher debt to take advantage of the tax shield seems to apply for APMM who in recent years has significantly decreased its debt.

The Conglomerate Discount in the view of APMM’s Management CEO Nils Smedegaard Andersen stated in an interview with Børsen (1. June 2015) he has a goal of eliminating the conglomerate discount and aims at being a part of the group of conglomerates trading at a premium, such as Siemens, ABB and General Electrics (Børsen.dk, 2015). He furthermore said “For an investor who is interested in oil, oil service and transportation, it should make good sense to invest in us, as we can maximize the value of the investment, and build up and invest when the market is in a downturn”, an argument in line with the theoretical economic perspective of diversification.

Late 2013 Andersen also gave an interview with the Financial Times where he briefly talked about the conglomerate structure in a way that is familiar in the best owner perspective of superior insight (Financial Times, 2013): “Being in all of the businesses at the same time gives us a lot of additional insight into the industries. And given that insight I think we can make superior capital allocations

Page 102 of 158 8.0 Conglomerate Discount Discussion compared to the external market and definitely compared to people who only work in one or two of these [sectors]”.

Michael Pram Rasmussen, chairman of the board, also stated during the general annual meeting of 2015 the strength of the conglomerate structure is the opportunity of risk diversification, both geographically and industrial, and thus a reduction of the volatility in total earnings, which is in line with the theoretical financial-based perspective of diversification. He furthermore stated the last eight years’ volatility in total earnings for the four largest business areas implied a risk reduction of 31% due to APMM’s conglomerate structure, and he believed this robustness to be of value in a changing world where important earnings parameters cannot be affected (APMM, 2016b).

A low/negative correlation between the business units will underpin the risk reduction statement of the chairman. After looking at the results of its four main business units over 25 quarters through 2007- 2013, APMM presented the correlation matrix illustrated in Table 60 below. The test yielded a risk reduction of 34% relative to the business unit as a stand-alone company where the units largely uncorrelated, besides Maersk Drilling and Maersk Oil with a slight positive correlation. The negative correlation of Maersk Line and APMT is somewhat surprising considering the two business units are somewhat vertically integrated into the same supply chain. In total, this serves to support the argument in which the structure of APMM reduces volatility.

Table 60 - Correlation matrix APMM business units 2007-2013

Maersk Line APMT Maersk Oil Drilling Maersk Line 100% APMT -6% 100% Maersk Oil 5% 0% 100% Drilling -13% 11% 23% 100% Source: Compiled by authors, (APMM, 2014f)

Page 103 of 158 8.0 Conglomerate Discount Discussion

The Conglomerate Discount in the View of Equity Analysts Early in 2015 in preparation for APMM’s annual general meeting, APMM interviewed its analyst regarding the conglomerate discount and estimated the conglomerate discount had dropped from 11 percent in 2013 to 6 percent in 2014 (Børsen.dk, 2015). During the annual general meeting of 2016 feedback from analyst was yet to be received, but the chairman of the board, Michael Pram Rasmussen, stated he did not believe the discount had fallen any further from 2014 to 2015. He furthermore elaborated the decline from 2013 to 2014 mainly came due to the sale of the Danske Bank shares, and with no such divestments and resistance in several of APMM’s businesses in 2015 he did not expect the conglomerate discount to have fallen any further (Business.dk, 2016).

The discounts we have gathered from the reports we have available is illustrated in Table 61. None of the analysts give any supporting arguments for their chosen conglomerate discount in their reports, and the wide range of discounts indicate there does not seem to be any consensus regarding what the conglomerate discount should be.

Table 61 - Conglomerate discount by equity analysts (numbers in DKK)

Share price at Conglomerate Target Year Date Analyst valuation date Discount price 2003 17.des ABG Sundal 8.300 15% 8.000 2013 06.jun Jefferies 8.448 20% 6.000 2013 28.feb Credit Suisse 9.080 0% 8.540 2014 17.nov Carnegie 12.430 0% 11.000 2014 17.dec Handelsbanken 11.290 10% 15.800 2015 11.feb ABN Amro 7.875 15% 8.600 2015 15.jul Jefferies 11.900 20% 14.250 2015 06.nov Danske Bank 10.510 0% 12.500 2016 15.jan SEB 8.125 10% 8.800 2016 10.feb Deutsche Bank 8.165 0% 10.050 2016 12.feb Nomura 7.410 5% 10.500 2016 29.mar Equita 8.825 0% 8.600 Source: Compiled by authors, Equity analyst research *Assumed 0% when no information of conglomerate discount in report

Kim Korsgaard Nielsen, portfolio manager at Carnegie Asset Management, says a large conglomerate discount is warranted due to the underperformance of the APMM share relative to the C20-index the last ten years, and to the many uncertainties regarding future earnings. He believes the discount to lie between 10 to 20% (Børsen.dk, 2015). He mainly points to the uncertainties of the oil business as the

Page 104 of 158 8.0 Conglomerate Discount Discussion biggest obstacle for removing the conglomerate discount. "One might fear that APMM Oil is going into a long period of significantly lower and maybe non-satisfactory returns on its invested capital, due to the low oil price and increasing costs. The risk in the oil business is significantly higher going forward than it has been historically, and the returns significantly lower. Not a good combination". The general underperformance and uncertainty in regards to future earning are neither argument supported for a conglomerate discount by the literature, but rather a general sign of a lower enterprise value. With no elaborations in their reports, we do not see any indications of consensus amongst analysts as of why there should be a conglomerate discount, in addition to the varying range of conglomerate discounts applied.

Potential divestments in APMM An interesting aspect of the conglomerate discount is the development of APMM’s business portfolio. After Mr. Andersen took over as CEO APMM announced it would sell off some of its assets, but insisted the supermarket investment and stake in Danske Bank would be kept (Financial Times, 2008). Several years later a lot of non-core assets have been sold off, including the aforementioned assets. Matthew O’Keeffe of Berenberg Equity Research stated the divestment of the Danske Bank Holding suggested: “nothing is sacred within the Maersk portfolio and that a sum-of-the-parts valuation for this group is no longer merely a theoretical exercise” (Bloomberg, 2015).

Even though most of the most obvious items have been sold and APMM is refraining from commenting on future potential divestments, analysts are speculating in which divestments is most likely next in line. The most obvious candidate is DAMCO which has had below top quartile performance for several years (Maritime Executive, 2015) for which it is questionable whether APMM is the best owner for the company. The global logistic industry is recognized as fragmented and consolidation is expected by many (APMM, 2015b, 2015d), and it stands out as the most likely next divestment target for APMM as there are no real synergies for owning the company. Jacob Pedersen from Sydbank, however, deems it likely that before a divestment can take place a turnaround is necessary (Maritime Executive, 2015). According to Mergemarkets trend report for 2016 Svitzer is also one of the most likely candidates for divestment (Shippingwatch, 2016). As Ricky Steen Rasmussen, senior analyst at Nykredit Markets, stated it: "It was reflected with Dansk Supermarked and Danske Bank that regardless of what was said, Maersk's "non-core" companies are for sale if a different and better owner shows up - and this is where Damco and Svitzer are the most obvious candidates" (Shippingwatch, 2016). Even Maersk Oil and Maersk Drilling have been mentioned as reasonable divestments targets if the oil prices remain

Page 105 of 158 8.0 Conglomerate Discount Discussion low(TheLoadStar.co.uk, 2015). It seems clear the business portfolio of APMM is getting more aligned, and it's getting harder to define what is non-core in the conglomerate.

In summary, we cannot see the benefits of conglomeration outweighing the costs for APMM, and other things equal we expect to see APMM trading at a discount. We do however not believe the full 21.1% is justifiable as a conglomerate discount, especially taken into consideration the recent broad history of divestment and market expectations of further divestments. However, we cannot say this premium to the trading price is significant and thus recommend a hold position

Page 106 of 158 9.0 Conclusion

9.0 Conclusion The primary objective of this thesis has been to provide an estimate of the theoretical share price of APMM as of April 1st, 2016 in the light of a possible conglomerate discount. After doing a thorough sum- of-the-parts valuation we found the fundamental value to imply a share price of 10.717 DKK, 21.1% above the corresponding trading price of 8.500 DKK. We do however not recommend a buy in light of the likely presence of a conglomerate discount in the range of 5-15%, and therefore recommend a hold position.

To reach this conclusion we have searched for answers using several related sub-questions.

We started out looking at the theory of the conglomerate structure to build a fundamental understanding of the theoretical arguments for and against the presence of a conglomerate discount. Through analyzing the historical performance and strategic factors for each of the eight business unit we forecasted the value drivers of each business in the pro forma statements, which we aggregated to a total for reportable segments. Maersk Line is the largest of the business units, accounting for 38% of the SOTP. Maersk Line also accounts for 47% of the invested capital. APM Terminals also has a significant share, accounting for 25% of the SOTP, only claiming 15% of the invested capital in APMM. The corresponding SOTP enterprise value was adjusted for other items not reported on a more disaggregated level, which in total yielded our sum-of-the-parts.

The fundamental share price of APMM is very sensitive to changes in the underlying inputs of the authors, confirming APMM is highly sensitive to its external factors. As an example, our sensitivity analysis for the aggregated business units revealed a WACC increase of 1 percentage point would imply a share price in line with the current traded price. Freight rates and the oil price for the terminal period were amongst the crucial inputs, which significantly changed the share price value. E.g. ceteris paribus a 10 $/barrel change in the terminal period changes the share price approximately 900 DKK while a 1% increase in freight rates for all forecasted years including terminal period increase the share price of around 1.000 DKK.

By analyzing APMM through the lens of conglomerate diversification, we found it unlikely that the benefits of diversifications outweigh the costs, even after APMM has become a more focused company after several divestments. However, the exact number of this discount is hard to pinpoint, also illustrated by the wide range of discounts applied in practice. Even amongst equity analysts, who have a

Page 107 of 158 10.0 Thesis in perspective major influence on the actual trading price, there does not seem to be any transparency as into how and why a conglomerate discount is used, which could also be an interesting topic for further research.

10.0 Thesis in perspective In relation to the chosen methods and research design, there are several points which deserve to be discussed.

Firstly, the DCF model can be criticized for being sensitive to assumptions being made in the terminal period. As many of APMM’s industries are now facing downturns, the present values of the terminal periods constitute a majority of the value for several of the business units. With cyclical companies whose value is determined to a great extent a few macroeconomic variables, probabilistic approaches work well, such as scenario analysis and simulations (Damodaran, 2009b). The authors view this as outside of the scope of this thesis and expect some of the uncertainty to be reduced due to our sum-of- the-parts model is the sum of eight somewhat uncorrelated business units.

The authors could furthermore have conducted an even more in-depth analysis of the value drivers of each business segment, as some of the assumptions might be simplified compared to valuations of pure play companies. I.e. we have assumed the opex level of Maersk Drilling to grow proportionally with the number of rigs, where an alternative would be to look at the specific cost level of each vessel. We have not been able to obtain such information, but this could have been found through interviews with industry professionals. In general, access to more detailed industry information would have been beneficiary for an even more accurate forecasting.

Potential divestment targets, such as DAMCO and Svitzer, could be of higher value than the fundamental valued implied by our DCF-value obtained if a better owner were willing to buy at a premium. One approach would be to look at alternative owners and value potential synergies in an M&A perspective. However, this would have required a profound analysis of potential buyers, and lies outside the scope of the original problem statement. An alternative could have been to look at the value of e.g. Svitzer’s assets through a liquidation approach where the vessels are sold in the second-hand market.

Several other methods for valuing the equity value of a company could have been used, i.e. a more comprehensive relative valuation, net asset value or economic value analysis. Valuing Maersk Oil through a relative valuation with multiples of proved and probable reserve levels to comparable peers

Page 108 of 158 11.0 References would have been a viable alternative to our fundamental valuation. Another interesting approach could be to use real options to value Maersk Oil in relation to expanding and ceasing projects dependent on the oil price. However, the authors view the other approaches as outside of the scope of this thesis and have chosen to be consistent in our valuation method of the different business units.

In relation to the results, the authors find it rather surprisingly there does not seem to be any consensus amongst financial analysts about why and how to incorporate the conglomerate discount. Some simply state they do not include any subjective discount/premiums to their sum of the parts while others say it should be a given amount without stating why, or in other cases for reasons not supported by theory. The lack of common practice regarding the conglomerate discount phenomenon reveals there should be investment opportunities associated with conglomerate companies, and further research is encouraged.

Other methodical approaches for analyzing the conglomerate discount could have been used. Empirical research often measures total shareholder returns for a group of conglomerates against the general market for a longer period of time to see whether they over or underperform. Another viable approach would have been to contact equity analysts of APMM and gather their historical sum-of-the-parts estimations (excl. any conglomerate discount estimations) and the corresponding trading prices. If we could assume the market to be represented by the average analyst we should expect to see stronger evidence of the conglomerate discount through a time-series rather than for a cross-sectional analysis.

Page 109 of 158 11.0 References

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12.0 Appendix

Appendix 1 – Glossary and Abbrevations

Beta – A measure of systematic risk, where βu denotes the unlevered beta, whereas βe denotes the levered beta CAPEX – Capital Expenditures CoC – Cost of Capital CoE – Cost of Equity D - Debt D&A – Depreciations & Amortizations DKK – Danske kroner DCF – Discounted Cash Flow E – Equity EBIT – Earnings before Interest and Tax EBITDA – Earnings before Interest, Tax, Depreciations and Amortizations EV – Enterprise Value FCFF – Free Cash Flow to the Firm MRP – Market Risk Premium NIBD – Net Interest Bearing Debt NOPAT – Net Operating Profit after Tax NWC – Net Working Capital PV – Present Value Rd – Cost of Debt Re – Required return of Equity

Rf – Risk-free rate

Ri – Return on a given asset, i Rm – Market required return ROE – Return on Equity ROIC – Return on Invested Capital  NOPAT / Invested Capital SOTP – Sum-of-the-parts SWOT – Strengths, Weaknesses, Opportunities and Threats T – Corporate tax rate USD – US dollar VRIO – Valuable, Rare, Inimitable, Organization WACC – Weighted Average Cost of Capital

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Appendix 2 – Credit Analysis Maersk Line

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 5.571 5.622 3.836 1.774 1.642 4.340 4.538 4.807 4.647 3.911 2.069 Non-interest 4.608 4.786 4.440 4.511 4.803 3.915 4.091 4.275 4.587 4.924 5.289 CASH 3.428 3.788 2.951 2.739 2.771 2.645 2.763 2.887 3.098 3.326 3.572 NIBD 6.751 6.620 5.325 3.546 3.674 5.610 5.866 6.195 6.135 5.509 3.785 DEBT 10.179 10.408 8.276 6.285 6.445 8.255 8.629 9.082 9.233 8.835 7.358 EQUITY 11.751 14.028 14.721 16.538 16.380 16.242 16.901 17.477 18.068 19.270 20.881 TOT ASSETS 21.930 24.436 22.997 22.823 22.825 24.497 25.530 26.559 27.301 28.105 28.239 EK% 53,6% 57,4% 64,0% 72,5% 71,8% 66,3% 66,2% 65,8% 66,2% 68,6% 73,9% Debt/Book Capital 46,4% 42,6% 36,0% 27,5% 28,2% 33,7% 33,8% 34,2% 33,8% 31,4% 26,1% 28% 34% Financial Leverage D/E 0,87 0,74 0,56 0,38 0,39 0,51 0,51 0,52 0,51 0,46 0,35 Debt/EBITDA 10,09 4,78 2,50 1,49 1,94 3,70 3,29 3,20 2,87 2,42 1,78 1,94 3,29 CAPEX/Dep Exp 2,15 0,93 1,13 1,13 1,54 1,48 1,45 1,29 1,31 1,00 1,13 1,48 Operating margin -2,2% 1,7% 5,8% 8,6% 5,5% 1,6% 2,7% 3,2% 4,2% 5,2% 6,5% 5,8% 3% EBIT interest cover 2,18 6,67 13,21 11,34 2,83 3,19 3,74 5,03 6,81 10,10 11,34 3,19

Source: Compiled by authors, (APMM, 2016e)

Appendix 3 – Credit Analysis Maersk Oil

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 3.296 4.217 2.512 957 -762 4.294 4.149 4.753 5.522 5.244 4.454 Non-interest 4.525 4.761 5.466 5.510 5.231 2.694 3.124 3.477 3.805 4.117 5.061 CASH 1.394 2.058 1.500 1.185 1.019 717 831 925 1.012 1.095 1.346 NIBD 6.427 6.920 6.478 5.282 3.450 6.271 6.442 7.305 8.315 8.266 8.169 DEBT 7.821 8.978 7.978 6.467 4.469 6.988 7.273 8.230 9.327 9.361 9.515 EQUITY 4.082 4.701 4.757 4.349 2.818 4.661 4.782 5.394 6.207 6.428 6.915 TOT ASSETS 11.903 13.679 12.735 10.816 7.287 11.649 12.055 13.624 15.534 15.790 16.430 EK% 34,3% 34,4% 37,4% 40,2% 38,7% 40,0% 39,7% 39,6% 40,0% 40,7% 42,1% Debt/Book Capital 65,7% 65,6% 62,6% 59,8% 61,3% 60,0% 60,3% 60,4% 60,0% 59,3% 57,9% 61% 60% Financial Leverage D/E 1,92 1,91 1,68 1,49 1,59 1,50 1,52 1,53 1,50 1,46 1,38 Debt/EBITDA 0,78 1,25 1,39 1,26 1,63 3,87 3,07 2,95 2,96 2,69 2,22 1,39 3,07 CAPEX/Dep Exp 1,05 1,59 1,95 1,74 1,37 1,29 1,59 1,58 1,08 1,26 1,74 1,37 Operating margin 16,7% 24,1% 11,4% -9,9% -38,1% 1,9% 5,2% 6,1% 6,3% 7,6% 9,5% -9,9% 5% EBIT interest cover 63,82 51,28 23,93 -59,37 9,33 11,91 14,97 14,80 17,43 30,74 23,93 11,91

Source: Compiled by authors, (APMM, 2016e)

Appendix 4 – Credit Analysis APM Terminals

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 1.778 1.371 1.520 846 836 1.469 1.595 1.745 1.785 1.604 985 Non-interest 1.150 1.080 1.155 1.060 1.039 1.192 1.302 1.381 1.465 1.554 1.649 CASH 1.058 689 1.034 858 743 911 995 1.055 1.120 1.188 1.260 NIBD 1.870 1.762 1.641 1.048 1.132 1.751 1.902 2.071 2.131 1.971 1.374 DEBT 2.928 2.451 2.675 1.906 1.875 2.662 2.897 3.126 3.251 3.159 2.634 EQUITY 3.254 3.733 4.536 4.885 5.045 5.069 5.481 5.842 6.275 6.895 7.580 TOT ASSETS 6.182 6.184 7.211 6.791 6.920 7.730 8.378 8.969 9.526 10.054 10.214 EK% 52,6% 60,4% 62,9% 71,9% 72,9% 65,6% 65,4% 65,1% 65,9% 68,6% 74,2% Debt/Book Capital 47,4% 39,6% 37,1% 28,1% 27,1% 34,4% 34,6% 34,9% 34,1% 31,4% 25,8% 28% 35% Financial Leverage D/E 0,90 0,66 0,59 0,39 0,37 0,53 0,53 0,54 0,52 0,46 0,35 Debt/EBITDA 2,76 2,81 3,00 1,89 2,22 2,80 2,80 2,84 2,79 2,55 2,01 2,22 2,80 CAPEX/Dep Exp 3,37 2,39 0,55 2,05 2,66 2,40 2,19 2,02 1,90 1,20 2,05 2,40 Operating margin 13,8% 16,7% 17,8% 20,2% 15,4% 15,1% 14,9% 14,7% 14,5% 14,4% 14,8% 17,8% 15% EBIT interest cover 12,98 13,17 19,41 20,38 20,98 14,66 14,08 13,58 13,93 16,33 19,41 14,66

Source: Compiled by authors, (APMM, 2016e)

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Appendix 5 – Credit Analysis Maersk Drilling

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 1.345 1.298 1.030 1.320 1.443 1.962 1.992 2.029 1.960 1.708 1.116 Non-interest 687 608 899 713 712 694 565 537 551 540 672 CASH 535 533 516 687 693 563 459 436 447 438 545 NIBD 1.497 1.373 1.413 1.346 1.462 2.092 2.098 2.130 2.064 1.810 1.243 DEBT 2.032 1.906 1.929 2.033 2.155 2.655 2.557 2.566 2.511 2.248 1.788 EQUITY 2.605 2.910 3.907 6.277 6.516 6.057 6.044 6.010 6.078 6.331 6.854 TOT ASSETS 4.637 4.816 5.836 8.310 8.671 8.712 8.601 8.577 8.589 8.579 8.642 EK% 56,2% 60,4% 66,9% 75,5% 75,1% 69,5% 70,3% 70,1% 70,8% 73,8% 79,3% Debt/Book Capital 43,8% 39,6% 33,1% 24,5% 24,9% 30,5% 29,7% 29,9% 29,2% 26,2% 20,7% 25% 30% Financial Leverage D/E 0,78 0,66 0,49 0,32 0,33 0,44 0,42 0,43 0,41 0,36 0,26 Debt/EBITDA 2,36 2,99 2,24 2,25 1,54 3,26 4,79 4,39 3,84 3,64 1,83 2,24 4,39 CAPEX/Dep Exp 0,47 1,84 2,54 0,64 0,86 0,72 0,70 0,64 0,67 0,41 1,84 0,72 Operating margin 26,0% 20,6% 26,8% 22,7% 29,8% 16,5% 6,0% 9,0% 12,5% 10,7% 24,1% 26,8% 9% EBIT interest cover 8,28 13,24 11,95 19,08 7,62 1,57 2,24 3,14 2,72 8,69 13,24 2,24

Source: Compiled by authors, (APMM, 2016e)

Appendix 6 – Credit Analysis Maersk Supply Service

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 796 722 413 259 266 443 444 451 435 379 253 Non-interest 221 234 230 237 191 148 152 156 161 166 171 CASH 234 249 192 195 133 130 134 138 142 146 149 NIBD 783 707 451 301 324 460 462 469 454 398 275 DEBT 1.017 956 643 496 457 590 596 607 597 545 424 EQUITY 1.363 1.499 1.248 1.403 1.445 1.333 1.331 1.323 1.338 1.393 1.515 TOT ASSETS 2.380 2.455 1.891 1.899 1.902 1.923 1.927 1.930 1.934 1.938 1.939 EK% 57,3% 61,0% 66,0% 73,9% 76,0% 69,3% 69,1% 68,5% 69,2% 71,9% 78,1% Debt/Book Capital 42,7% 39,0% 34,0% 26,1% 24,0% 30,7% 30,9% 31,5% 30,8% 28,1% 21,9% 26% 31% Financial Leverage D/E 0,75 0,64 0,52 0,35 0,32 0,44 0,45 0,46 0,45 0,39 0,28 Debt/EBITDA 2,44 3,00 1,84 1,42 1,71 2,58 2,47 2,44 2,33 2,06 1,56 1,71 2,47 CAPEX/Dep Exp 0,72 -0,88 0,43 0,83 0,55 0,60 0,58 0,56 0,55 0,53 0,43 0,58 Operating margin 25,8% 15,1% 24,2% 25,8% 24,0% 15,3% 17,0% 17,7% 18,4% 19,1% 19,7% 24,2% 17% EBIT interest cover 5,09 8,22 13,63 14,66 7,42 5,97 6,39 6,73 7,43 9,03 13,63 6,39

Source: Compiled by authors, (APMM, 2016e)

Appendix 7 – Credit Analysis Maersk Tankers

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 1.390 1.747 1.501 411 298 412 413 419 405 352 Non-interest 359 331 480 234 198 245 253 260 268 276 CASH 372 913 1.361 365 195 229 236 243 250 257 NIBD 1.377 1.165 620 280 301 428 430 437 423 371 DEBT 1.749 2.078 1.981 645 496 657 665 679 673 628 EQUITY 2.397 2.468 1.715 1.303 1.343 1.240 1.239 1.232 1.245 1.297 TOT ASSETS 4.146 4.546 3.696 1.948 1.839 1.897 1.904 1.911 1.918 1.925 EK% 57,8% 54,3% 46,4% 66,9% 73,0% 65,4% 65,0% 64,5% 64,9% 67,4% Debt/Book Capital 42,2% 45,7% 53,6% 33,1% 27,0% 34,6% 35,0% 35,5% 35,1% 32,6% 44,8% 33% 35% Financial Leverage D/E 0,73 0,84 1,16 0,49 0,37 0,53 0,54 0,55 0,54 0,48 Debt/EBITDA 16,19 9,71 94,34 2,38 1,67 2,36 2,23 2,13 2,02 1,83 2,40 2,38 2,23 CAPEX/Dep Exp -0,81 -59,48 0,49 1,13 0,69 0,52 0,49 0,46 0,45 1,20 0,49 0,52 Operating margin -13,5% -15,9% -19,8% 11,1% 15,1% 11,7% 13,1% 14,5% 15,3% 15,7% 12,6% 11,1% 13% EBIT interest cover -6,39 -7,69 5,93 16,18 11,88 9,64 10,96 11,74 12,79 3,70 5,93 10,96

Source: Compiled by authors, (APMM, 2016e)

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Appendix 8 – Credit Analysis Maersk Damco

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med16-18 Financial liabilities 154 307 163 108 3 124 127 134 137 131 93 Non-interest 630 662 749 693 549 601 619 650 683 717 753 CASH 668 805 803 744 515 645 664 697 732 769 795 NIBD 116 164 109 57 37 80 82 87 87 79 51 DEBT 784 969 912 801 552 725 746 784 819 848 846 EQUITY 201 348 303 264 166 232 237 244 257 278 283 TOT ASSETS 985 1.317 1.215 1.065 718 957 983 1.028 1.076 1.126 1.129 EK% 20,4% 26,4% 24,9% 24,8% 23,1% 24,2% 24,1% 23,8% 23,8% 24,7% 25,1% Debt/Book Capital 79,6% 73,6% 75,1% 75,2% 76,9% 75,8% 75,9% 76,2% 76,2% 75,3% 74,9% 75% 76% Financial Leverage D/E 3,89 2,79 3,02 3,03 3,33 3,13 3,15 3,21 3,19 3,05 2,99 Debt/EBITDA 6,53 10,65 -14,04 -5,41 10,23 17,46 17,46 17,46 17,38 17,14 16,28 -5,41 17,46 CAPEX/Dep Exp 1,26 -0,35 -0,09 -0,07 1,37 0,75 0,82 0,81 0,80 0,33 -0,09 0,82 Operating margin 2,3% 1,7% -3,5% -9,3% 0,7% 0,5% 0,5% 0,5% 0,5% 0,5% 0,5% -3,5% 0% EBIT interest cover 22,10 -15,23 -61,86 19,82 11,93 5,81 6,10 6,22 6,64 7,81 -15,23 6,10

Source: Compiled by authors, (APMM, 2016e)

Appendix 9 – Credit Analysis Maersk Svitzer

Credit and liquidity analysis 11 12 13 14 15 16E 17E 18E 19E 20E 21(TP) Med13-15 Med13-15 Financial liabilities 664 599 512 271 282 380 395 402 394 359 279 Non-interest 71 57 43 54 56 49 51 52 53 54 55 CASH 155 177 193 136 131 138 143 146 149 152 154 NIBD 580 479 362 189 207 291 303 308 298 261 180 DEBT 735 656 555 325 338 429 446 454 447 413 334 EQUITY 1.009 1.016 1.001 880 925 844 873 868 878 914 994 TOT ASSETS 1.744 1.672 1.556 1.205 1.263 1.273 1.320 1.322 1.324 1.327 1.328 EK% 57,9% 60,7% 64,3% 73,1% 73,2% 66,3% 66,2% 65,7% 66,3% 68,9% 74,8% Debt/Book Capital 42,1% 39,3% 35,7% 26,9% 26,8% 33,7% 33,8% 34,3% 33,7% 31,1% 25,2% 27% 34% Financial Leverage D/E 0,73 0,65 0,55 0,37 0,37 0,51 0,51 0,52 0,51 0,45 0,34 Debt/EBITDA 3,10 2,94 2,56 1,91 1,78 2,38 2,38 2,37 2,29 2,07 1,64 1,91 2,38 CAPEX/Dep Exp 1,00 -0,69 1,56 1,35 1,43 1,54 1,01 1,01 1,01 1,01 1,35 1,43 Operating margin 11,7% 0,9% 18,8% -33,3% 17,9% 12,2% 12,2% 12,4% 12,5% 12,7% 12,2% 17,9% 12% EBIT interest cover 2,18 10,37 -19,40 18,75 14,94 11,06 11,00 11,20 11,95 13,36 10,37 11,06

Source: Compiled by authors, (APMM, 2016e)

Page 120 of 158 12.0 Appendix

Appendix 10 - Maersk Drilling rate assumptions – part 1 Maersk Voyager Maersk Venturer Maersk Valiant Maersk Viking Drillships Heydar Aliyev Maersk Discoverer Maersk Deliverer Maersk Developer Semisubmersibles XL Enhanced 4 Jack-Ups Under Construction Maersk Convincer Maersk Completer Maersk Resilient Maersk Resolve Maersk Resolute Maersk Reacher Maersk Guardian Maersk Giant Maersk Gallant Maersk Integrator Maersk Interceptor Maersk Intrepid Maersk Insipirer Maersk Innovator Jack-Ups USD thousand Year 2015 2014 2014 2014 2003 2009 2010 2009 2016 2008 2007 2008 2009 2008 2009 1986 1986 1993 2015 2014 2014 2004 2003 Annual revenue Annual contractAverage coverage time Non-yard uptime Average revenue Quarterly Days Start mar-16 maj-14 nov-14 nov-12 nov-15 maj-07 sep-12 sep-11 sep-16 feb-16 dec-14 aug-14 feb-10 jun-14 jun-12 apr-17 okt-15 jun-14 jun-15 jul-15 jul-12 End no no contract no contract maj-21 nov-16 mar-16 dec-18 aug-17 aug-19 feb-17 sep-16 sep-21 aug-16 dec-19 sep-18 dec-16 jun-17 apr-22 okt-18 okt-18 apr-16 jun-19 jun-18 jul-16 Day rate 100,5 195,0 376,7 475 366 634 557 400 475 530 425 163 205 304 106 389 397 377 275 275 78 - - jan 475 366 634 557 400 475 530 163 100 195 205 304 106 389 397 377 377 275 275 31 595.378 feb Q1 475 366 634 557 400 475 530 163 100 195 205 304 106 389 397 377 377 275 275 28 mar 475 366 634 557 400 475 530 163 100 195 205 304 150 389 397 377 377 275 275 31 apr 475 366 634 557 400 475 530 163 100 195 205 304 150 389 397 377 377 275 275 30 596.993 may Q2 475 366 634 557 400 475 530 163 100 195 304 150 389 397 377 377 275 275 31 80 jun 1.921.177 475 366 634 557 400 475 530 163 100 195 304 150 389 397 377 377 275 275 30 80 2016 90% 97% 96% jul 475 366 634 557 400 475 530 163 195 304 150 389 397 377 377 275 275 31 80 576.717 aug Q3 475 240 634 557 400 475 530 163 100 195 304 150 150 397 377 377 275 275 31 80 sep 475 240 634 557 400 475 530 163 100 195 304 150 150 397 377 377 275 275 30 80 78 oct 475 240 634 557 400 475 530 163 100 195 150 150 150 397 377 377 275 275 31 80 78 511.194 nov Q4 240 240 240 557 400 475 530 163 100 195 150 150 150 397 377 377 275 275 30 80 78 dec 240 240 240 557 400 475 220 163 100 195 150 150 150 397 377 377 275 275 31 80 78 jan 240 240 240 557 400 475 220 220 163 100 195 150 150 150 397 377 377 175 275 31 80 80 78 476.942 feb Q1 240 240 240 557 400 475 220 220 163 100 195 150 150 150 397 377 377 175 275 28 80 80 78 mar 240 240 240 557 400 475 220 220 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78 apr 240 240 240 557 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 30 80 80 80 78 514.056 may Q2 240 240 240 557 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78 jun 1.565.128 240 240 240 557 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 30 80 80 80 78 2017 85% 97% 96% jul 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78 490.541 aug Q3 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78 sep 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 30 80 80 80 78 oct 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78 490.541 nov Q4 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 30 80 80 80 78 dec 240 240 240 240 400 475 220 220 425 163 100 150 150 150 397 377 377 175 275 31 80 80 80 78

Source: Compiled by authors, dayrates e-mailed 2016-04-09 from Carnegie

Page 121 of 158 12.0 Appendix

Appendix 11 - Maersk Drilling rate assumptions – part 2

2018 2019 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 jan feb mar apr may jun jul aug sep oct nov dec jan feb mar apr may jun jul aug sep oct nov dec

275 275 275 275 275 275 193 193 193 193 193 193 194 194 194 196 196 196 197 197 197 199 199 199 193 193 193 193 193 193 193 193 193 193 193 193 194 194 194 196 196 196 197 197 197 199 199 199 377 377 377 377 377 377 377 377 377 193 193 193 194 194 194 196 196 196 197 197 197 199 199 199 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 377 397 397 397 397 397 397 397 397 397 397 397 397 397 397 397 397 397 397 197 197 197 199 199 199 165 165 165 165 165 165 165 165 165 165 165 165 166 166 166 167 167 167 169 169 169 170 170 170 165 165 165 165 165 165 165 165 165 165 165 165 166 166 166 167 167 167 169 169 169 170 170 170 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 165 165 165 165 165 165 165 165 165 165 165 165 166 166 166 167 167 167 169 169 169 170 170 170 88 88 88 88 88 88 88 88 88 88 88 88 89 89 89 89 89 89 90 90 90 91 91 91 88 88 88 88 88 88 88 88 88 88 88 88 89 89 89 89 89 89 90 90 90 91 91 91 100 100 100 100 100 100 100 100 100 100 88 88 89 89 89 89 89 89 90 90 90 91 91 91 163 163 163 163 163 163 163 163 163 163 88 88 89 89 89 89 89 89 90 90 90 91 91 91 88 88 88 88 88 88 88 88 88 88 88 88 89 89 89 89 89 89 90 90 90 91 91 91

425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425 425

242 242 242 242 242 242 242 242 242 242 242 242 244 244 244 246 246 246 247 247 247 249 249 249 242 242 242 242 242 242 242 242 242 242 242 242 244 244 244 246 246 246 247 247 247 249 249 249 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 475 247 249 249 249 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400 400

264 264 264 264 264 264 264 264 264 264 264 264 266 266 266 268 268 268 270 270 270 272 272 272 264 264 264 264 264 264 264 264 264 264 264 264 266 266 266 268 268 268 270 270 270 272 272 272 264 264 264 264 264 264 264 264 264 264 264 264 266 266 266 268 268 268 270 270 270 272 272 272 264 264 264 264 264 264 264 264 264 264 264 264 266 266 266 268 268 268 270 270 270 272 272 272 31 28 31 30 31 30 31 31 30 31 30 31 31 28 31 30 31 30 31 31 30 31 30 31 500.307 505.866 503.881 481.645 470.561 477.866 460.035 448.360 96% 96% 97% 97% 80% 88% 1.487.717 1.525.668

Source: Compiled by authors

Page 122 of 158 12.0 Appendix

Appendix 12 - Maersk Drilling rate assumptions – part 3

2020 2021(TP) Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 jan feb mar apr may jun jul aug sep oct nov dec jan feb mar apr may jun jul aug sep oct nov dec

200 200 200 202 202 202 203 203 203 205 205 205 160 160 160 160 160 160 160 160 160 160 160 160 200 200 200 202 202 202 203 203 203 205 205 205 160 160 160 160 160 160 160 160 160 160 160 160 200 200 200 202 202 202 203 203 203 205 205 205 160 160 160 160 160 160 160 160 160 160 160 160 200 200 200 202 202 202 203 203 203 205 205 205 160 160 160 160 160 160 160 160 160 160 160 160 200 200 200 202 202 202 203 203 203 205 205 205 160 160 160 160 160 160 160 160 160 160 160 160 171 171 171 172 172 172 174 174 174 175 175 175 160 160 160 160 160 160 160 160 160 160 160 160 171 171 171 172 172 172 174 174 174 175 175 175 160 160 160 160 160 160 160 160 160 160 160 160 78 78 78 78 78 78 78 78 78 78 78 78 160 160 160 160 160 160 160 160 160 160 160 160 171 171 171 172 172 172 174 174 174 175 175 175 160 160 160 160 160 160 160 160 160 160 160 160 91 91 91 92 92 92 93 93 93 93 93 93 160 160 160 160 160 160 160 160 160 160 160 160 91 91 91 92 92 92 93 93 93 93 93 93 160 160 160 160 160 160 160 160 160 160 160 160 91 91 91 92 92 92 93 93 93 93 93 93 160 160 160 160 160 160 160 160 160 160 160 160 91 91 91 92 92 92 93 93 93 93 93 93 160 160 160 160 160 160 160 160 160 160 160 160 91 91 91 92 92 92 93 93 93 93 93 93 160 160 160 160 160 160 160 160 160 160 160 160

425 425 425 425 425 425 425 425 425 425 425 425 160 160 160 160 160 160 160 160 160 160 160 160

251 251 251 253 253 253 255 255 255 257 257 257 442 442 442 442 442 442 442 442 442 442 442 442 251 251 251 253 253 253 255 255 255 257 257 257 442 442 442 442 442 442 442 442 442 442 442 442 251 251 251 253 253 253 255 255 255 257 257 257 442 442 442 442 442 442 442 442 442 442 442 442 400 400 400 400 400 400 400 400 400 400 400 400 442 442 442 442 442 442 442 442 442 442 442 442

274 274 274 276 276 276 278 278 278 280 280 280 442 442 442 442 442 442 442 442 442 442 442 442 274 274 274 276 276 276 278 278 278 280 280 280 442 442 442 442 442 442 442 442 442 442 442 442 274 274 274 276 276 276 278 278 278 280 280 280 442 442 442 442 442 442 442 442 442 442 442 442 274 274 274 276 276 276 278 278 278 280 280 280 442 442 442 442 442 442 442 442 442 442 442 442 31 28 31 30 31 30 31 31 30 31 30 31 31 28 31 30 31 30 31 31 30 31 30 31 425.106 432.408 439.786 442.432 534.240 540.176 546.112 546.112 96% 96% 97% 97% 92% 92% 1.494.434 1.861.150

Source: Compiled by authors

Page 123 of 158 12.0 Appendix

Appendix 13 – Fleet Status Report – Maersk Drilling (1st of April 2016)

Rig name Year (ft) Customer Start End Country Comments Jack-Ups Maersk Innovator 2003 492 ConocoPhillips feb-10 jun-18 Norway 1 x 1 year option Maersk Insipirer 2004 492 Statoil (Volve) maj-07 dec-16 Norway Maersk Intrepid 2014 492 Total aug-14 sep-18 Norway 4 x 1 year options Maersk Interceptor 2014 492 Det norske dec-14 dec-19 Norway Up to 2 years options Maersk Integrator 2015 492 Statoil jun-15 jun-19 Norway 2 x 1 year options Maersk Gallant 1993 394 Total feb-16 aug-16 Norway Total E&P Norge A/S takes over Maersk Gallant from Statoil Maersk Giant 1986 350 DONG nov-15 mar-16 Denmark Maersk Guardian 1986 350 Maersk Oil sep-16 sep-21 Denmark Accomodation contract with 2 x 1 year options Maersk Reacher 2009 350 BP sep-11 sep-16 Norway Maersk Resolute 2008 350 Hess nov-12 apr-16 Denmark Maersk Resolve 2009 350 DONG jun-14 feb-17 Denmark 2 x 1 well options - will not be exercised Maersk Resilient 2008 350 Maersk Oil okt-15 okt-18 Denmark Maersk Completer 2007 375 BSP nov-14 okt-18 Brunei 3 x 1 year options Maersk Convincer 2008 375 Available

Jack-Ups Under Construction XL Enhanced 4 2016 492 BP apr-17 apr-22 Norway 5 x 1 year options

Semisubmersibles Maersk Developer 2009 10000 Available Maersk Deliverer 2010 10000 Chevron jun-12 nov-16 Angola Maersk Discoverer 2009 10000 BP jul-12 aug-19 Egypt Heydar Aliyev 2003 3280 BP sep-12 maj-21 Azerbaijan

Drillships Maersk Viking 2014 12000 ExxonMobil maj-14 jun-17 USA Maersk Valiant 2014 12000 ConocoPhillips/Marathonjun-14 aug-17 USA Maersk Venturer 2014 12000 Total mar-16 jul-16 Uruguay Maersk Voyager 2015 12000 Eni jul-15 dec-18 Ghana

Source: Compiled by authors, Maersk Drilling, (2016)

Page 124 of 158 12.0 Appendix

Appendix 14 - Maersk Drilling rig categorization

MODU Year Ft Sub Type Rig Sub Type Country Rig Model Corresponding SpareBank 1 Market category Jack-Ups Maersk Innovator 2003 492 Independent Leg Cantilever High-Specification Norway CJ70-150MC Norway, CJ-70 Maersk Insipirer 2004 492 Independent Leg Cantilever High-Specification Norway CJ70-150MC Norway, CJ-70 Maersk Intrepid 2014 492 Independent Leg Cantilever High-Specification Norway CJ70-X150MD Norway, CJ-70 Maersk Interceptor 2014 492 Independent Leg Cantilever High-Specification Norway CJ70-X150MD Norway, CJ-70 Maersk Integrator 2015 492 Independent Leg Cantilever High-Specification Norway CJ70-X150MD Norway, CJ-70 Maersk Gallant 1993 394 Independent Leg Cantilever Premium Norway CJ62-120-S Norway, other Maersk Giant 1986 350 Independent Leg Cantilever Premium Norway Ultra Harsh Enviroment Jack Up Norway, other Maersk Guardian 1986 350 Norway, other Maersk Reacher 2009 350 Independent Leg Cantilever Premium Norway CJ50-X100MC Norway, other Maersk Resolute 2008 350 Independent Leg Cantilever Premium Denmark CJ50-X100MC NW Europe >300ft. Maersk Resolve 2009 350 Independent Leg Cantilever Premium Denmark CJ50-X100MC NW Europe >300ft. Maersk Resilient 2008 350 Independent Leg Cantilever Premium Denmark CJ50-X100MC NW Europe >300ft. Maersk Completer 2007 375 NW Europe >300ft. Maersk Convincer 2008 375 NW Europe >300ft.

Jack-Ups Under Construction XL Enhanced 4 2016 492 Norway, CJ-70

Semisubmersibles Maersk Developer 2009 10000 5th gen. - 7,500-10,000ft. Maersk Deliverer 2010 10000 5th gen. - 7,500-10,000ft. Maersk Discoverer 2009 10000 5th gen. - 7,500-10,000ft. Heydar Aliyev 2003 3280 5th gen. - 7,500-10,000ft.

Drillships Maersk Viking 2014 12000 Ultradeep water USA 6th gen. - 10,000ft+ Maersk Valiant 2014 12000 6th gen. - 10,000ft+ Maersk Venturer 2014 12000 6th gen. - 10,000ft+ Maersk Voyager 2015 12000 6th gen. - 10,000ft+

Source: Compiled by authors, Infield.com, (2016)

Page 125 of 158 12.0 Appendix

Appendix 15 - Jack-up day rate assumptions 2016-2018

SpareBank 1 markets - assumptions Authors - assumptions Y/y growth 3% 3% 3% 2016 2017 2018 2019 2020 TP Jack-ups Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Harsh Enviornment Norway, CJ-70 175 175 175 175 175 175 175 175 193 193 193 193 194 196 197 199 200 202 203 205 206 208 209 211 Norway, other 150 150 150 150 150 150 150 150 165 165 165 165 166 167 169 170 171 172 174 175 176 178 179 180 NW Europe, High-Spec 100 100 100 100 100 100 100 100 110 110 110 110 111 112 112 113 114 115 116 117 118 118 119 120 NW Europe >300ft. 80 80 80 80 80 80 80 80 88 88 88 88 89 89 90 91 91 92 93 93 94 95 95 96 NW Europe <300ft. 60 60 60 60 60 60 60 60 66 66 66 66 66 67 67 68 68 69 70 70 71 71 72 72 400ft.+ IC 88 88 88 88 88 88 88 88 97 97 97 97 98 98 99 100 101 101 102 103 104 104 105 106 US Gulf of Mexico 80 80 80 80 80 80 80 80 88 88 88 88 89 89 90 91 91 92 93 93 94 95 95 96 Mexico 90 90 90 90 90 90 90 90 99 99 99 99 100 100 101 102 103 103 104 105 106 107 107 108 Middle East 90 90 90 90 90 90 90 90 99 99 99 99 100 100 101 102 103 103 104 105 106 107 107 108 South East Asia 90 90 90 90 90 90 90 90 99 99 99 99 100 100 101 102 103 103 104 105 106 107 107 108 Rest of the World 90 90 90 90 90 90 90 90 99 99 99 99 100 100 101 102 103 103 104 105 106 107 107 108 361-400 IC 84 84 84 84 84 84 84 84 93 93 93 93 94 94 95 96 97 97 98 99 99 100 101 102 US Gulf of Mexico 80 80 80 80 80 80 80 80 88 88 88 88 89 89 90 91 91 92 93 93 94 95 95 96 Mexico 85 85 85 85 85 85 85 85 94 94 94 94 95 95 96 97 98 98 99 100 100 101 102 103 Middle East 85 85 85 85 85 85 85 85 94 94 94 94 95 95 96 97 98 98 99 100 100 101 102 103 South East Asia 85 85 85 85 85 85 85 85 94 94 94 94 95 95 96 97 98 98 99 100 100 101 102 103 Rest of the World 85 85 85 85 85 85 85 85 94 94 94 94 95 95 96 97 98 98 99 100 100 101 102 103 301-360 IC, Premium 79 79 79 79 79 79 79 79 88 88 88 88 89 89 90 91 91 92 93 93 94 95 95 96 US Gulf of Mexico 75 75 75 75 75 75 75 75 83 83 83 83 84 84 85 85 86 87 87 88 89 89 90 91 Mexico 80 80 80 80 80 80 80 80 89 89 89 89 90 90 91 92 92 93 94 94 95 96 97 97 Middle East Gulf 80 80 80 80 80 80 80 80 89 89 89 89 90 90 91 92 92 93 94 94 95 96 97 97 South East Asia 80 80 80 80 80 80 80 80 89 89 89 89 90 90 91 92 92 93 94 94 95 96 97 97 Rest of the World 80 80 80 80 80 80 80 80 89 89 89 89 90 90 91 92 92 93 94 94 95 96 97 97 301-360 IC, Conventional 70 70 70 70 70 70 70 70 74 74 74 74 75 75 76 76 77 77 78 79 79 80 80 81 US Gulf of Mexico 70 70 70 70 70 70 70 70 67 67 67 67 67 68 69 69 70 70 71 71 72 72 73 73 Mexico 70 70 70 70 70 70 70 70 67 67 67 67 67 68 69 69 70 70 71 71 72 72 73 73 Middle East Gulf 70 70 70 70 70 70 70 70 79 79 79 79 80 80 81 81 82 83 83 84 84 85 86 86 South East Asia 70 70 70 70 70 70 70 70 79 79 79 79 80 80 81 81 82 83 83 84 84 85 86 86 Rest of the World 70 70 70 70 70 70 70 70 79 79 79 79 80 80 81 81 82 83 83 84 84 85 86 86 300 IC, Conventional 56 56 56 56 56 56 56 56 60 60 60 60 60 61 61 62 62 63 63 64 64 65 65 66 US Gulf of Mexico 60 60 60 60 60 60 60 60 57 57 57 57 57 58 58 59 59 60 60 60 61 61 62 62 Mexico 55 55 55 55 55 55 55 55 52 52 52 52 52 53 53 54 54 54 55 55 56 56 56 57 Middle East Gulf 55 55 55 55 55 55 55 55 64 64 64 64 64 65 65 66 66 67 67 68 68 69 69 70 South East Asia 55 55 55 55 55 55 55 55 64 64 64 64 64 65 65 66 66 67 67 68 68 69 69 70 Rest of the World 55 55 55 55 55 55 55 55 64 64 64 64 64 65 65 66 66 67 67 68 68 69 69 70 150-300ft, commodity 300 IS 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 250 IC 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 250 IS 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 250 MC 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 250 MS 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 54 200 MC 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 <200 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45

Source: Compiled by authors, Sparebank 1 Markets, (2016)

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Appendix 16 - Floater day rate assumptions 2016-2018

2016 2017 2018 2019 2020 TP SpareBank 1 markets - assumptions Authors - assumptions Y/y growth 3% 3% 3% Floaters Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Norway/Harsh Environment 6th gen. - 10,000ft+ 240 240 240 240 240 240 240 240 264 264 264 264 266 268 270 272 274 276 278 280 282 284 286 288 5th gen. - 7,500-10,000ft. 220 220 220 220 220 220 220 220 242 242 242 242 244 246 247 249 251 253 255 257 259 261 262 264 4th gen. - 5,000-7,500ft. 210 210 210 210 210 210 210 210 231 231 231 231 233 234 236 238 240 241 243 245 247 249 251 252 4rd gen. - >= 3000ft. 200 200 200 200 200 200 200 200 220 220 220 220 222 223 225 227 228 230 232 233 235 237 239 240 2nd gen. - >= 3000ft. 190 190 190 190 190 190 190 190 209 209 209 209 211 212 214 215 217 218 220 222 223 225 227 228 High-Spec 6G 225 225 225 225 225 225 225 225 250 250 250 250 252 254 256 258 259 261 263 265 267 269 271 273 High 250 250 250 250 250 250 250 250 275 275 275 275 277 279 281 283 285 287 290 292 294 296 298 300 Low 200 200 200 200 200 200 200 200 225 225 225 225 227 228 230 232 233 235 237 239 240 242 244 246 Low-Spec 6G/high-spec 5G - DP 205 205 205 205 205 205 205 205 230 230 230 230 232 233 235 237 239 240 242 244 246 248 249 251 High 230 230 230 230 230 230 230 230 255 255 255 255 257 259 261 263 265 267 269 271 273 275 277 279 Low 180 180 180 180 180 180 180 180 205 205 205 205 207 208 210 211 213 214 216 217 219 221 222 224 5G - M 190 190 190 190 190 190 190 190 215 215 215 215 217 218 220 221 223 225 226 228 230 231 233 235 High 210 210 210 210 210 210 210 210 235 235 235 235 237 238 240 242 244 246 247 249 251 253 255 257 Low 170 170 170 170 170 170 170 170 195 195 195 195 196 198 199 201 202 204 205 207 208 210 212 213 4G - DP - 5,000-7,500ft. 178 178 178 178 178 178 178 178 203 203 203 203 205 206 208 209 211 212 214 215 217 219 220 222 High 190 190 190 190 190 190 190 190 215 215 215 215 217 218 220 221 223 225 226 228 230 231 233 235 Low 165 165 165 165 165 165 165 165 190 190 190 190 191 193 194 196 197 199 200 202 203 205 206 208 4G - M - 5,000-7,5000 ft. 168 168 168 168 168 168 168 168 184 184 184 184 185 187 188 190 191 192 194 195 197 198 200 201 High 180 180 180 180 180 180 180 180 198 198 198 198 199 201 202 204 205 207 209 210 212 213 215 216 Low 155 155 155 155 155 155 155 155 171 171 171 171 172 174 175 176 177 179 180 181 183 184 185 187 3G 145 145 145 145 145 145 145 145 160 160 160 160 161 162 164 165 166 167 168 170 171 172 174 175 High 160 160 160 160 160 160 160 160 176 176 176 176 177 179 180 181 183 184 185 187 188 189 191 192 Low 130 130 130 130 130 130 130 130 143 143 143 143 144 145 146 147 148 149 151 152 153 154 155 156 2G 120 120 120 120 120 120 120 120 132 132 132 132 133 134 135 136 137 138 139 140 141 142 143 144 High 140 140 140 140 140 140 140 140 154 154 154 154 155 156 157 159 160 161 162 163 165 166 167 168 Low 100 100 100 100 100 100 100 100 110 110 110 110 111 112 112 113 114 115 116 117 118 118 119 120

Source: Compiled by authors, Sparebank 1 Markets, (2016)

Appendix 17 – Oil Forecast Revenue

Maersk oil Revenue and cost drivers 2011 2012 2013 2014 2015 2016E 2017E 2018E 2019E 2020E 2021 (TP) Total production 333 257 235 251 312 315 328 341 354 369 369 Avg oil price 111 112 109 99 52 41,7 46,1 49,1 51,4 53,3 65 Yearly production 121.545 93.805 85.775 91.615 113.880 114.975 119.574 124.357 129.331 134.504 134.685

Line items assumptions 2011 2012 2013 2014 2015 2016E 2017E 2018E 2019E 2020E 2021 (TP) Revenue 12.616 10.154 9.142 8.737 5.639 4.514 5.236 5.827 6.376 6.898 8.480 Opex 1.611 1.910 2.233 2.856 2.468 2.285 2.436 2.596 2.768 2.950 3.028 Exploration costs 990 1.088 1.149 765 423 423 434 444 456 467 479 EBITDA 1.807 2.366 2.786 3.153 3.481 4.973 Capex 2.000 2.000 3.000 4.000 3.000 3.000

Source: Compiled by authors

Page 127 of 158 12.0 Appendix

Appendix 18 - Maersk Line value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in ass. Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share assets/sales non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin expenseoperating Total Y/Y change expenses, Other (USD perFFE) Unitcost growth revenue Total revenue Other (USD perrate FFE) freight Average volumesin '000) Transported (FFE Value drives - Balance sheet - drives Balance Value - Income drivers statementValue -14,7% 2011 2011 18,4% 12,5% 11,5% -4,7% -7,7% 1,1% 0,2% 0,0% 0,0% 0,1% 0,0% 0,0% 0,5% 0,0% 0,2% 7,9% 4,0% 110,0% 2012 2012 17,6% 14,0% 12,2% -0,4% 55,3% 22,1% -3,7% -2,1% 0,0% 0,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,1% 0,3% 7,9% 8,0% 3,5% 8,0% 1,9% 4,7% -23,6% -11,4% 2013 2013 16,9% 11,3% 99,3% 12,6% -0,1% -5,7% -8,2% -3,4% -3,3% -7,2% 0,0% 0,4% 0,0% 0,0% 0,0% 3,9% 0,0% 0,0% 0,1% 0,0% 8,4% 4,1% 101,3% 2014 2014 16,5% 10,0% 15,4% -0,3% 14,7% -6,5% -5,6% -1,6% -1,6% 0,0% 0,6% 0,0% 0,0% 0,0% 6,5% 0,0% 0,0% 0,3% 0,0% 8,6% 1,1% 4,4% 6,8% 100,7% -11,8% -12,6% -12,5% -13,2% -16,0% 2015 2015 20,2% 11,5% 14,0% -8,6% 0,2% 1,0% 0,0% 0,0% 0,0% 8,9% 0,0% 0,0% 0,2% 0,0% 0,1% 8,8% 7,0% 0,8% Hist avg Hist avg Hist 102,8% 17,9% 11,8% 10,8% -5,8% -0,1% -3,9% -7,9% -1,1% -5,7% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,1% 8,3% 8,4% 6,0% 4,1% 2016E 2016E 105,3% -10,0% 17,9% 11,8% 10,2% -5,8% -3,9% -6,0% -8,0% -6,5% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 2,5% 2,0% 2017E 2017E 104,2% 17,9% 11,8% 11,5% -5,8% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 3,0% 2,5% 0,0% 4,5% 2,0% 3,0% 0% 2018E 2018E 104,0% 17,9% 11,8% 11,9% -5,8% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 4,0% 2,5% 1,0% 4,5% 2,0% 3,0% 0% 2019E 2019E 102,5% 17,9% 11,8% 12,6% -5,8% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 6,5% 2,5% 2,5% 7,3% 4,0% 4,0% 0% 2020E 2020E 102,6% 17,9% 11,8% 13,3% -5,8% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 6,5% 2,5% 2,5% 7,4% 4,0% 4,0% 0% TP TP 100,0% 17,9% 11,8% 14,0% -5,8% 0,3% 0,5% 0,0% 0,0% 0,0% 3,4% 0,0% 0,0% 0,2% 0,0% 0,0% 8,5% 6,5% 2,5% 2,5% 7,4% 4,0% 4,0% 0%

Source: Compiled by authors

Page 128 of 158 12.0 Appendix

Appendix 19 - Maersk Line pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax EBIT-margin companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation EBITDA-margin expenses Other expenseunit Total D&A (USD FFE), excluded per Unitcost (USD FFE) per Unitcost revenue Other revenueSum freight-related (USD FFE) per rate freight Average in '000) (FFE volumes Transported USD million Net earnings NOPAT EBIT EBITDA Total operating expenses Total revenue Pro formaPro income statement -24.099 -23.650 25.108 2011 -2.916 -3.108 22.938 -1,9% 1.009 2.828 8.111 1.559 2.170 4,0% -553 -553 -482 -449 128 71 58 -2 0 0 0 -24.938 -24.241 27.117 2012 -2.854 -3.054 24.468 2.179 2.881 8.493 1.697 2.649 1,9% 8,0% -100 -697 250 461 525 240 29 64 23 81 1 0 -22.883 -22.350 26.196 2013 -2.529 -2.731 23.635 12,6% 1.283 1.510 1.571 3.313 2.674 8.839 1.789 2.561 6,0% -533 236 -19 61 38 10 9 0 0 -23.139 -22.528 27.351 2014 -2.386 -2.584 24.832 15,4% 2.164 2.341 2.504 4.212 2.630 9.442 1.870 2.519 9,2% -611 190 163 -72 12 89 1 0 0 -20.405 -19.871 23.729 2015 -2.087 -2.288 21.034 14,0% 1.188 1.303 1.431 3.324 2.209 9.522 1.915 2.695 6,0% -534 126 128 11 40 17 -1 0 0 2016E -19.600 -19.053 21.828 -1.962 -2.159 19.309 10,2% 2.228 1.988 9.712 1.912 2.519 1,7% -547 231 357 370 131 12 54 4 0 0 0 0 2017E -20.185 -19.624 22.805 10.004 -1.962 -2.165 20.286 11,5% 2.620 2.028 2.038 2.519 2,8% -561 424 617 638 200 21 56 7 0 0 0 0 2018E -20.990 -20.415 23.831 10.304 -1.981 -2.187 21.313 11,9% 2.842 2.068 2.120 2.519 3,3% -575 553 754 781 209 26 59 7 0 0 0 0 2019E -22.352 -21.762 25.571 10.716 -2.031 -2.234 23.052 12,6% 1.072 1.109 3.219 2.151 2.173 2.519 4,3% -589 859 221 37 63 7 0 0 0 0 2020E -23.803 -23.199 27.452 11.145 -2.082 -2.282 24.933 13,3% 1.225 1.436 1.486 3.649 2.237 2.230 2.519 5,4% -604 218 50 68 7 0 0 0 0 TP -25.349 -24.730 29.486 11.591 -2.134 -2.326 26.968 14,0% 1.724 1.914 1.980 4.137 2.327 2.230 2.519 6,7% -619 196 67 73 7 0 0 0 0

Source: Compiled by authors, APMM, (2016)

Page 129 of 158 12.0 Appendix

Appendix 20 - Maersk Line pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT USD million (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and USD million Control flowcash Free to equity (FCFE) flowcash Free to the firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 18.502 11.751 18.502 19.604 19.682 -1.180 -1.441 6.751 4.608 3.146 2011 -2.949 1.936 1.912 282 -761 59 15 368 368 126 357 4 0 0 2017E 20.648 14.028 20.648 21.567 21.646 6.620 4.786 3.788 2012 -3.010 -998 2.038 -298 -235 -235 73 193 256 617 0 3 0 3 57 0 2018E 20.046 14.721 20.046 21.421 21.535 -1.489 5.325 4.440 2.951 2013 -3.084 2.120 -150 111 202 329 754 -23 -23 0 2 0 1 60 0 2019E 20.084 16.538 20.084 21.693 21.856 -1.772 3.546 4.511 2.726 2014 -2.805 2.173 1.072 161 541 13 268 268 213 101 -60 1 0 1 0 2020E 20.054 16.380 20.054 21.845 22.086 -2.032 3.674 4.803 2.721 2015 -2.915 2.230 1.436 239 -626 861 50 211 109 1 0 1 23 23 0 TP 2016E 21.852 16.242 21.852 16.380 23.007 23.123 -1.271 5.610 3.915 2.584 -1.723 -2.236 2.026 2.230 1.914 368 231 110 60 113 113 190 118 2 0 4 0 2017E 22.767 16.901 22.767 16.242 23.973 24.094 -1.328 5.866 4.091 2.700 -235 424 115 63 2 0 4 2018E 23.671 17.477 23.671 16.901 24.932 25.059 -1.387 6.195 4.275 2.822 553 120 -23 66 2 0 4 2019E 24.203 18.068 24.203 17.477 25.556 25.691 -1.489 6.135 4.587 3.027 268 859 129 71 2 0 4 2020E 24.779 19.270 24.779 18.068 26.231 26.377 -1.598 5.509 1.225 4.924 3.250 139 23 76 2 0 5 TP 24.666 20.881 24.666 19.270 26.231 26.382 -1.716 3.785 1.724 5.289 3.491 113 149 81 3 0 0

Source: Compiled by authors, APMM, (2016)

Page 130 of 158 12.0 Appendix

Appendix 21 - Maersk Oil value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share net/sales etc., assets, non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Explorationcosts/sales Operatingcosts/sales Revenuegrowth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue -24,8% 2011 2011 73,1% 24,2% 79,4% 12,8% 0,0% 0,0% 0,0% 0,0% 0,2% 7,8% 36% 11% 25% 0% 5% 1% 0% -26,6% -19,5% 2012 2012 54,1% 21,0% 70,5% -0,4% 10,7% 18,8% 101% 0,0% 1,1% 0,0% 0,3% 47% 20% 31% 0% 5% 2% 0% -43,4% -10,0% 2013 2013 74,2% 16,3% 63,0% -0,5% 12,6% 24,4% 114% 0,0% 0,0% 0,0% 1,1% 60% 16% 34% 0% 7% 2% 0% -49,5% ##### 2014 2014 25,3% 16,0% 58,6% -0,1% 32,7% -4,4% 115% 0,0% 0,0% 0,0% 8,8% 63% 14% 17% 0% 7% 0% 0% -74,7% -35,5% 2015 2015 55,5% 23,8% 48,7% -8,9% 43,8% 0,0% 0,0% 0,1% 0,0% 7,5% 93% 18% 17% 84% 0% 0% 0% 7% Hist avg Hist avg Hist 103% -44% -17% 60% 16% 23% 70% 16% 20% 64% 26% 0% 8% 1% 0% 0% 0% 0% 0% 9% 2016E 2016E 120% -44% -20% 60% 16% 60% 20% 40% 51% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 9% 2017E 2017E 105% -44% 60% 16% 60% 20% 45% 47% 16% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 8% 2018E 2018E 113% -44% 60% 16% 60% 20% 48% 45% 11% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 8% 2019E 2019E 113% -44% 60% 16% 60% 20% 49% 43% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 7% 9% 2020E 2020E 101% -44% 60% 16% 60% 20% 50% 43% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 7% 8% TP TP 103% -44% 60% 16% 60% 20% 50% 43% 23% 0% 8% 0% 0% 7% 0% 0% 0% 0% 0% 7%

Source: Compiled by authors, APMM, (2016)

Page 131 of 158 12.0 Appendix

Appendix 22 - Maersk Oil pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Explorationcost Operatingcost Revenue Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 10.015 2011 12.616 2.112 2.112 7.842 5.730 2.146 1.611 990 25 -4 0 0 2 0 2012 10.154 2.406 2.444 5.328 7.156 2.884 1.866 1.088 1.910 109 -42 45 83 29 0 0 2013 1.026 1.046 4.050 5.760 3.004 1.570 1.149 2.233 9.142 -42 59 79 98 0 0 0 2014 1.466 5.116 2.327 2.209 1.441 2.856 8.737 -825 -861 765 97 61 -5 -1 0 4 -2.182 -2.146 -1.971 2015 2.748 3.131 1.593 2.468 5.639 175 423 33 -3 0 0 5 0 2016E 1.807 1.597 2.285 4.514 210 126 423 75 84 14 23 0 0 0 0 0 2017E 2.366 1.684 2.436 5.236 250 273 683 410 434 34 57 0 0 0 0 0 2018E 2.786 1.901 2.596 5.827 330 354 885 531 444 35 59 0 0 0 0 0 2019E 1.007 3.153 2.145 2.768 6.376 376 403 604 456 41 68 0 0 0 0 0 2020E 1.308 3.481 2.173 2.950 6.898 493 523 785 467 45 75 0 0 0 0 0 TP 2.011 4.279 1.207 2.268 3.627 8.480 778 804 574 39 65 0 0 0 0 0

Source: Compiled by authors, APMM, (2016)

Page 132 of 158 12.0 Appendix

Appendix 23 - Maersk Oil pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E -3.131 6.427 4.082 6.427 -2.737 2.345 4.525 1.394 5.692 3.165 9.558 2011 -1.768 -1.768 -2.183 -2.235 1.597 577 124 978 0 0 84 0 9 2017E -2.703 6.920 4.701 6.920 2.219 4.761 2.058 5.752 3.146 9.623 2012 -2.170 1.684 528 197 102 129 129 316 273 0 0 23 50 0 10.444 2018E -3.966 6.478 4.757 6.478 1.721 5.466 1.500 6.548 3.096 2013 -3.023 1.901 -509 603 197 -281 -281 252 259 354 0 0 24 0 2019E -4.325 5.282 4.349 5.282 5.510 1.185 7.525 1.482 9.607 2014 -3.395 2.145 -607 933 600 -438 -438 196 241 403 0 0 0 27 0 2020E -4.212 3.450 2.818 3.450 5.231 6.308 7.662 2015 -2.353 2.173 632 999 960 394 -270 572 20 272 272 229 523 0 0 30 0 TP -1.768 -1.977 2016E 6.271 4.661 6.271 1.610 2.818 2.694 7.570 8.249 -2.864 2.268 713 364 315 -584 902 75 292 292 693 804 3 0 0 26 0 -2.293 2017E 6.442 4.782 6.442 1.660 4.661 3.124 7.948 8.735 129 250 827 422 366 4 0 0 -2.552 2018E 7.305 5.394 7.305 1.912 4.782 3.477 8.981 9.858 -281 330 921 469 407 4 0 0 10.149 11.108 -2.793 2019E 8.315 6.207 8.315 2.108 5.394 3.805 1.007 -438 376 513 445 5 0 0 10.250 11.288 -3.022 2020E 8.266 6.428 8.266 1.838 6.207 4.117 1.090 272 493 555 482 5 0 0 10.608 11.883 -3.715 TP 8.169 6.915 8.169 1.254 6.428 5.061 1.340 292 778 683 593 6 0 0

Source: Compiled by authors, APMM, (2016)

Page 133 of 158 12.0 Appendix

Appendix 24 - APM Terminals value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share net/sales etc., assets, non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth Inorganicgrowth Organicgrowth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue 2011 2011 15,7% 22,6% -2,0% 1,1% 0,0% 0,6% 0,0% 0,0% 8,2% 25% 16% 10% 21% 7% 6% 0% -10,2% 2012 2012 18,9% 20,7% -9,3% 1,4% 2,4% 2,8% 0,0% 0,0% 8,1% 26% 15% 11% 41% 74% 22% 1% 4% 2013 2013 20,6% -2,8% 109% 6,8% 1,6% 2,1% 1,6% 0,0% 0,0% 7,6% 3,0% 27% 20% 11% 39% 25% 4% 4% 2014 2014 20,6% 22,7% -0,3% -4,5% 102% 2,1% 8,4% 0,0% 0,6% 7,5% 2,8% 24% 18% 11% 33% 26% 1% 3% 2015 2015 13,9% 19,9% -0,3% -7,0% -4,8% 104% 2,0% 2,7% 0,3% 0,0% 7,1% 25% 17% 13% 35% 32% 0% 3% Hist avg Hist avg Hist 25% 17% 11% 35% 97% 25% 15% 21% -5% -2% 3% 4% 2% 1% 3% 0% 0% 8% 2016E 2016E 124% 25% 17% 11% 31% 25% 15% 20% 12% -5% 2% 4% 2% 1% 3% 0% 0% 8% 8% 4% 2017E 2017E 113% 25% 17% 10% 28% 25% 15% 20% -5% 2% 4% 2% 1% 3% 0% 0% 8% 9% 5% 4% 2018E 2018E 111% 25% 17% 10% 27% 25% 15% 20% -5% 2% 4% 2% 1% 3% 0% 0% 8% 6% 2% 4% 2019E 2019E 109% 25% 17% 25% 25% 15% 20% -5% 2% 4% 9% 2% 1% 3% 0% 0% 8% 6% 2% 4% 2020E 2020E 108% 25% 17% 24% 25% 15% 20% -5% 2% 4% 9% 2% 1% 3% 0% 0% 8% 6% 2% 4% TP TP 100% 25% 17% 22% 25% 15% 20% -5% 2% 4% 8% 2% 1% 3% 0% 0% 8% 6% 2% 4%

Source: Compiled by authors, APMM, (2016)

Appendix 25 - APM Terminals pro forma income statement

Page 134 of 158 12.0 Appendix Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 2011 1.059 3.623 4.682 648 648 769 121 369 50 28 -1 0 0 0 2012 3.335 4.206 647 701 864 871 163 100 117 283 13 67 59 0 0 2013 3.440 4.332 712 770 826 892 297 63 56 68 93 70 4 0 0 2014 1.134 1.010 3.445 4.455 854 900 234 374 302 -14 12 58 93 27 0 2015 3.395 4.240 622 654 760 845 106 114 309 -14 37 85 11 5 0 2016E 3.813 4.762 683 717 845 949 128 130 377 40 77 66 6 0 0 2017E 1.036 4.164 5.201 722 775 914 139 142 421 62 85 72 9 0 0 2018E 1.099 4.417 5.517 751 809 954 145 151 462 10 68 90 76 0 0 2019E 1.001 1.166 4.686 5.852 787 849 152 160 501 11 74 95 81 0 0 2020E 1.057 1.237 4.971 6.208 832 896 161 101 169 537 12 76 86 0 0 TP 1.146 1.312 5.273 6.585 912 972 174 107 180 544 11 70 91 0 0

Source: Compiled by authors, APMM, (2016)

Page 135 of 158 12.0 Appendix

Appendix 26 - APM Terminals pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 5.124 3.254 5.124 1.870 1.150 3.512 5.216 2011 -1.005 746 312 259 458 987 -92 659 659 619 377 717 -15 75 0 34 0 2017E 5.495 3.733 5.495 1.762 1.080 1.730 2.582 5.886 2012 -1.010 -391 632 171 478 925 211 57 310 310 152 421 775 53 26 0 2018E 6.177 4.536 6.177 1.641 1.155 1.708 2.812 1.098 6.298 2013 -1.012 -121 845 189 188 492 278 389 389 169 462 809 57 19 0 2019E 5.933 4.885 5.933 1.048 1.060 1.476 2.862 1.156 6.135 2014 -1.014 -202 800 137 504 356 58 353 353 501 849 63 60 20 0 2020E 6.177 5.045 6.177 1.132 1.039 1.476 2.976 1.350 6.473 2015 -1.018 -296 731 130 541 -160 436 12 212 212 537 896 64 21 0 TP 2016E 6.819 5.069 6.819 1.751 5.045 1.192 1.476 3.690 1.202 7.101 -281 659 683 816 191 541 -597 -655 884 95 227 227 544 972 60 22 0 2017E 7.383 5.481 7.383 1.902 5.069 1.302 1.476 4.152 1.313 7.690 -307 310 722 891 104 209 541 2018E 7.913 5.842 7.913 2.071 5.481 1.381 1.476 4.608 1.392 8.239 -326 389 751 945 110 222 541 2019E 8.406 6.275 8.406 2.131 5.842 1.465 1.003 1.476 5.023 1.477 8.752 -346 353 787 117 235 541 2020E 8.866 6.895 8.866 1.971 6.275 1.554 1.064 1.476 5.400 1.567 9.233 -367 212 832 124 249 541 TP 8.954 7.580 8.954 1.374 6.895 1.649 1.128 1.476 5.400 1.662 9.343 -389 227 912 132 264 541

Source: Compiled by authors, APMM, (2016)

Page 136 of 158 12.0 Appendix

Appendix 27 - Maersk Drilling value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share assets/sales non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue 2011 2011 21,0% 45,9% -1,0% -8,1% 0,0% 0,0% 0,0% 1,1% 5,7% 37% 28% 0% 2% 0% 0% 0% -10,4% 2012 2012 21,3% 37,9% -4,5% 0,0% 0,0% 0,0% 0,0% 0,0% 4,7% 36% 32% 99% 0% 2% 0% 9% 0% -19,4% 2013 2013 18,4% 43,8% 17,2% 131% 0,0% 1,0% 0,2% 0,0% 0,0% 4,4% 46% 26% 0% 3% 0% 8% 1% 2014 2014 20,5% 43,0% -1,7% -1,2% 137% 0,0% 3,9% 0,0% 1,7% 4,2% 6,6% 34% 33% 0% 2% 0% 6% 2% 17,83% 2015 2015 55,5% 19,7% -0,8% 105% 0,0% 0,7% 1,8% 0,0% 1,1% 6,6% 28% 28% 0% 1% 0% 5% 1% Hist avg Hist avg Hist 117,8% 29,3% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 45% -7% 0% 0% 1% 0% 1% 5% 8% 2016E 2016E 29,3% 104% -24% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 42% -7% 0% 0% 0% 0% 0% 5% 2017E 2017E 29,3% 100% -19% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 34% -7% 0% 0% 0% 0% 0% 5% 2018E 2018E 29,3% 100% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 39% -7% -5% 0% 0% 0% 0% 0% 5% 2019E 2019E 29,3% 100% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 43% -7% 0% 0% 0% 0% 0% 5% 3% 2020E 2020E 29,3% 100% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 41% -7% -2% 0% 0% 0% 0% 0% 5% TP TP 29,3% 100% 0,1% 2,1% 0,0% 5,7% 0,8% 36% 20% 52% 25% -7% 0% 0% 0% 0% 0% 5%

Source: Compiled by authors, APMM, (2016)

Page 137 of 158 12.0 Appendix

Appendix 28 - Maersk Drilling pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue Net earnings NOPAT EBIT EBITDA USD million Pro formaPro income statement 2011 1.016 1.878 488 488 618 862 130 242 -18 20 0 0 0 0 2012 1.045 1.683 305 347 441 638 197 11 53 94 0 0 0 0 0 2013 1.109 1.972 488 528 647 863 119 239 49 19 9 0 4 0 0 2014 1.199 2.102 438 478 601 903 123 313 -36 10 50 82 35 0 0 2015 1.396 1.121 2.517 712 751 914 163 519 48 18 46 27 9 0 0 2016E 1.108 1.921 276 318 396 813 417 10 52 79 0 0 0 0 0 2017E 1.031 1.565 117 534 417 34 94 15 74 23 0 0 0 0 0 2018E 1.488 134 167 584 417 904 74 15 75 33 0 0 0 0 0 2019E 1.526 130 191 238 655 417 871 15 76 47 0 0 0 0 0 2020E 1.494 101 160 200 617 417 878 15 73 40 0 0 0 0 0 TP 1.861 397 449 560 977 111 417 884 13 64 0 0 0 0 0

Source: Compiled by authors, APMM, (2016)

Page 138 of 158 12.0 Appendix

Appendix 29 - Maersk Drilling pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 4.102 2.605 4.102 1.497 4.214 4.254 2011 -152 687 530 -699 147 40 736 736 630 112 417 318 5 0 0 0 42 0 2017E 4.283 2.910 4.283 1.373 4.158 4.358 2012 608 533 159 -75 -386 100 41 417 -24 0 0 0 46 46 60 94 0 6 2018E 5.320 3.907 5.320 1.413 5.459 5.703 2013 -383 899 516 159 -410 136 66 19 108 108 417 134 0 0 60 33 -5 0 2019E 7.623 6.277 7.623 1.346 7.463 7.649 2014 713 687 118 -26 -420 190 33 35 417 191 -67 0 0 63 63 61 0 3 2020E 7.978 6.516 7.978 1.462 7.802 7.997 2015 712 693 136 -19 -152 -152 -254 -414 161 22 37 417 160 0 0 59 -2 0 TP 8.149 6.057 8.149 2016E 2.092 8.114 8.279 -131 694 562 110 -126 -126 -567 -398 493 40 16 417 449 1 0 52 25 0 8.142 6.044 8.142 2017E 2.098 6.057 8.114 8.249 -106 565 458 46 34 32 89 13 1 0 8.141 6.010 8.141 2018E 2.130 6.044 8.114 8.242 -101 108 537 435 74 31 85 12 1 0 8.142 6.078 8.142 2019E 2.064 6.010 8.114 8.245 -104 130 551 446 63 32 87 13 1 0 8.141 6.331 8.141 2020E 1.810 6.078 8.114 8.243 -152 -102 101 540 437 31 85 12 1 0 8.097 6.854 8.097 TP 1.243 6.331 8.114 8.224 -126 -127 397 672 544 39 56 15 1 0

Source: Compiled by authors, APMM, (2016)

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Appendix 30 - Maersk Tankers value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share net/sales etc., assets, non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue 2011 2011 -6,7% 0,0% 0,0% 0,5% 0,0% 3,8% 6,1% 8,3% 1,0% 28% 29% 0% 0% 0% 0% 0% 2012 2012 13,6% 10,8% 29,4% -0,6% 52,2% 0,0% 0,1% 0,4% 0,0% 8,8% 17% 23% 24% 81% 0% 0% 0% 0% -17,8% 2013 2013 14,2% 13,5% 54,2% -0,6% -4,7% 0,0% 0,0% 0,5% 1,3% 30% 23% 60% 47% 0% 0% 0% 0% -27,7% 2014 2014 23,1% 11,1% -0,3% 101% 0,8% 0,0% 0,0% 0,0% 0,3% 9,1% 20% 16% 15% 0% 0% 0% 0% -10,0% 2015 2015 28,1% -0,3% 114% 0,6% 0,0% 0,0% 0,5% 0,0% 0,1% 8,5% 19% 15% 4% 0% 0% 0% 0% Hist avg Hist avg Hist -1,3% 23% 21% 21% 86% 19% 14% -1% -1% 0% 0% 0% 0% 0% 0% 0% 6% 9% 2016E 2016E 102% 23% 21% 26% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3% 2017E 2017E 100% 23% 21% 27% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3% 2018E 2018E 100% 23% 21% 28% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3% 2019E 2019E 100% 23% 21% 28% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3% 2020E 2020E 100% 23% 21% 28% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3% TP TP 100% 23% 21% 28% -2% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 9% 3%

Source: Compiled by authors, APMM, (2016)

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Appendix 31 - Maersk Tankers pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue USD million Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 2011 1.191 1.299 -175 -175 -164 108 228 11 50 0 0 0 6 0 2012 1.763 1.977 -364 -315 -313 214 268 268 49 0 2 0 1 8 0 2013 1.604 1.625 -363 -321 -319 230 195 -77 21 41 0 2 0 0 8 2014 1.175 108 130 131 271 132 904 22 -4 0 1 0 0 0 4 2015 1.058 150 160 161 297 140 761 10 0 1 0 0 5 0 1 2016E 1.090 117 127 127 279 155 811 11 0 0 0 0 3 0 0 2017E 1.122 132 147 147 298 155 824 15 0 0 0 0 3 0 0 2018E 1.156 152 168 168 319 155 837 15 0 0 0 0 3 0 0 2019E 1.191 167 182 182 333 155 857 16 0 0 0 0 4 0 0 2020E 1.227 178 193 193 343 155 883 15 0 0 0 0 4 0 0 TP 1.263 187 200 200 354 155 910 13 0 0 0 0 1 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 32 - Maersk Tankers pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 3.774 2.397 3.774 1.377 3.745 3.761 2011 359 372 -193 103 13 219 219 127 155 127 0 5 6 0 5 11 14 0 2017E 3.562 2.397 3.633 1.165 3.036 3.051 2012 331 446 467 582 -155 147 134 134 155 147 1 6 1 7 15 0 1 0 2018E 3.017 2.397 2.335 1.440 1.454 2013 620 480 381 980 881 -155 168 159 159 155 168 0 5 4 5 15 0 7 1 2019E 2.677 2.397 1.583 1.448 1.452 2014 280 234 185 180 131 -155 183 153 153 155 182 -14 0 1 1 2 16 0 1 2020E 2.698 2.397 1.644 1.645 1.647 2015 301 198 154 -155 193 41 126 126 155 193 -3 -52 0 0 0 2 15 0 1 TP 2016E 2.723 2.295 1.669 2.397 1.678 1.685 428 219 117 245 229 -17 -115 -152 203 155 200 0 1 3 1 3 75 75 13 0 1 2017E 2.723 2.293 1.668 2.295 1.678 1.685 430 134 132 253 236 -17 0 1 3 1 3 2018E 2.722 2.286 1.668 2.293 1.678 1.686 437 159 152 260 243 -18 0 1 3 1 3 2019E 2.722 2.299 1.668 2.286 1.678 1.686 423 153 167 268 250 -18 0 1 3 1 3 2020E 2.722 2.351 1.668 2.299 1.678 1.686 371 126 178 276 257 -19 0 1 3 1 3 TP 2.719 2.463 1.664 2.351 1.678 1.684 255 187 284 265 -19 75 0 1 1 0 4

Source: Compiled by authors, APMM, (2016)

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Appendix 33 - Maersk Supply Service value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share assets/sales non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue 2011 2011 44,2% 3,6% 0,0% 0,0% 0,3% 0,0% 0,0% 7,8% 1,4% 23% 25% 0% 0% 0% 0% 0% 2012 2012 36,4% -0,5% -6,9% 103% 7,0% 0,0% 0,0% 0,0% 0,8% 7,6% 1,7% 27% 28% 0% 0% 0% 0% 0% -12,0% 2013 2013 45,2% -0,1% -4,9% 9,7% 0,0% 0,6% 0,0% 0,0% 8,4% 30% 25% 79% 0% 1% 0% 0% 1% 2014 2014 44,7% -5,4% 100% 8,2% 0,0% 0,1% 1,5% 0,0% 0,0% 8,1% 0,8% 30% 23% 2% 0% 0% 0% 1% -21,2% 2015 2015 43,7% -9,5% 104% 6,4% 0,0% 0,0% 4,9% 0,0% 0,0% 7,7% 31% 22% 0% 1% 0% 0% 3% Hist avg Hist avg Hist -10% 28% 24% 97% 43% -3% 1% 1% 0% 0% 1% 7% 0% 0% 1% 0% 0% 8% 2016E 2016E 100% -15% 28% 24% 44% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 2017E 2017E 100% 28% 24% 45% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 3% 2018E 2018E 100% 28% 24% 45% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 3% 2019E 2019E 100% 28% 24% 45% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 3% 2020E 2020E 100% 28% 24% 45% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 3% TP TP 100% 28% 24% 45% -3% 1% 1% 0% 0% 1% 7% 0% 0% 0% 0% 0% 8% 3%

Source: Compiled by authors, APMM, (2016)

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Appendix 34 - Maersk Supply Service income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue USD million Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 2011 243 243 252 416 167 526 942 0 9 0 0 3 0 0 2012 106 132 142 319 166 558 877 28 10 -4 2 0 0 0 7 2013 164 187 207 349 146 423 772 25 20 -1 2 0 5 0 0 2014 186 201 219 348 142 430 778 16 18 12 1 0 1 0 0 2015 137 147 157 268 141 345 613 11 10 30 1 0 0 0 0 2016E 229 144 292 521 69 80 86 12 1 6 0 0 0 0 0 2017E 242 144 295 537 76 91 98 16 1 7 0 0 0 0 0 2018E 105 249 144 304 553 82 98 16 1 7 0 0 0 0 0 2019E 105 112 256 144 313 569 89 17 1 8 0 0 0 0 0 2020E 112 120 264 144 323 586 97 16 1 8 0 0 0 0 0 TP 106 119 128 272 144 332 604 14 1 9 0 0 0 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 35 - Maersk Supply Service pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 2.146 1.363 2.146 2.128 2.133 2011 783 221 234 -127 13 181 181 136 144 -41 56 0 4 1 0 0 11 80 0 2017E 2.206 1.499 2.206 2.186 2.191 2012 707 234 245 -144 15 144 91 4 4 0 0 1 78 78 15 91 0 2 1 2018E 1.699 1.248 1.699 1.727 1.737 2013 451 230 192 -38 -144 144 98 0 4 0 0 6 90 90 15 98 0 7 1 2019E 1.704 1.403 1.704 1.734 1.746 2014 301 237 179 -42 -144 105 16 144 105 -15 3 0 0 9 75 75 16 0 1 2020E 1.769 1.445 1.769 1.802 1.827 2015 324 191 133 -58 -144 112 19 144 112 -56 0 6 0 0 41 41 15 0 1 TP 2016E 1.793 1.333 1.793 1.445 1.802 1.810 460 181 148 128 -17 -123 -144 121 69 144 119 -15 -15 3 3 0 0 5 13 0 2 2017E 1.793 1.331 1.793 1.333 1.802 1.811 462 152 131 -18 78 76 3 3 0 0 6 2018E 1.792 1.323 1.792 1.331 1.802 1.811 469 156 135 -18 90 82 3 3 0 0 6 2019E 1.792 1.338 1.792 1.323 1.802 1.811 454 161 139 -19 75 89 3 3 0 0 6 2020E 1.792 1.393 1.792 1.338 1.802 1.811 398 166 144 -20 41 97 3 3 0 0 6 TP 1.790 1.515 1.790 1.393 1.802 1.812 275 106 171 148 -15 -22 1 3 0 0 6

Source: Compiled by authors, APMM, (2016)

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Appendix 36 - Damco value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share /sales assets, non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue 2011 2011 35,7% 0,0% 0,0% 0,0% 0,0% 0,0% 9,9% 4,4% 1,4% 23% 23% 1% 1% 0% 0% 5% 2012 2012 39,6% 17,3% 0,0% 0,2% 0,6% 0,0% 0,1% 7,6% 2,8% 4,4% 21% 25% 89% 0% 1% 0% 1% 6% -24,7% 2013 2013 -2,0% -0,5% 0,0% 0,2% 0,1% 0,0% 0,2% 9,9% 1,7% 23% 25% 95% 0% 1% 0% 1% 6% -21,6% 2014 2014 16,7% -4,7% -1,5% 0,0% 0,3% 0,0% 0,0% 2,1% 1,6% 22% 23% 97% 0% 1% 0% 1% 4% -13,4% 2015 2015 52,5% 16,2% -1,2% 0,0% 0,4% 0,2% 0,0% 0,0% 2,0% 20% 19% 87% 0% 1% 0% 1% 4% Hist avg Hist avg Hist 22% 23% 92% 16% 12% 0% 1% 0% 1% 5% 2% 0% 0% 0% 0% 0% 0% 0% 2016E 2016E 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 1,0% 22% 23% 0% 1% 0% 1% 5% 2017E 2017E 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 3,0% 22% 23% 0% 1% 0% 1% 5% 2018E 2018E 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 5,0% 22% 23% 0% 1% 0% 1% 5% 2019E 2019E 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 5,0% 22% 23% 0% 1% 0% 1% 5% 2020E 2020E 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 5,0% 22% 23% 0% 1% 0% 1% 5% TP TP 16,3% 12,1% 100% 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,5% 5,0% 22% 23% 0% 1% 0% 1% 5%

Source: Compiled by authors, APMM, (2016)

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Appendix 37 - Damco pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue USD million Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 2011 2.632 2.752 120 63 63 98 35 24 -1 0 0 0 1 0 2012 3.138 3.229 53 55 91 91 36 19 23 2 4 0 6 0 2 2013 3.277 3.212 -118 -111 -89 -65 22 28 -1 6 0 8 2 0 6 2014 3.312 3.164 -298 -293 -241 -148 52 68 34 -1 4 0 9 0 0 2015 2.686 2.740 18 19 40 54 21 10 29 1 2 0 5 0 0 2016E 2.726 2.767 12 13 16 42 26 0 1 3 0 0 0 0 0 2017E 2.808 2.850 11 14 17 43 26 0 3 3 0 0 0 0 0 2018E 2.948 2.993 12 15 18 45 27 0 3 3 0 0 0 0 0 2019E 3.095 3.143 13 16 19 47 28 1 3 3 0 0 0 0 0 2020E 3.250 3.300 15 17 21 49 29 1 3 3 0 0 0 0 0 TP 3.413 3.465 16 18 22 52 30 0 3 4 0 0 0 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 38- Damco pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 2011 317 201 317 116 630 630 107 136 279 -96 38 38 36 -54 -54 -57 -78 0 0 43 26 13 0 1 2017E 2012 512 348 512 164 662 801 143 207 369 41 26 95 -32 4 0 26 14 -1 7 0 7 7 2 2 2018E 2013 412 303 412 109 749 798 193 358 54 46 29 90 -37 5 0 27 15 -2 3 0 5 5 2 4 2019E 2014 321 264 321 693 738 117 270 57 51 38 28 87 -38 6 0 28 16 -2 3 0 1 1 3 1 2020E 2015 203 166 203 549 515 103 237 -34 37 32 26 76 -40 0 0 29 17 -6 -6 -8 -2 4 0 3 TP 2016E 312 232 312 166 601 635 137 268 -54 80 12 10 44 35 20 76 -28 -17 41 0 11 11 10 30 18 0 2 2017E 319 237 319 232 619 654 141 274 82 11 11 45 36 20 76 7 0 2018E 331 244 331 237 650 686 149 284 87 12 11 47 38 21 76 5 0 2019E 344 257 344 244 683 721 156 294 87 13 12 49 40 22 76 1 0 2020E 357 278 357 257 717 757 164 305 79 15 12 52 42 23 76 -6 0 TP 334 283 334 278 753 795 172 293 51 11 16 42 44 76 0 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 39 - Svitzer value drivers Non-interest-bearing liabilities Non-interest-bearing revenue% of as assets current Other revenue% of as sale heldfor Assets revenue% of as assets non-current Other revenue% companies of as in associated Investments revenue% of as inventures jointInvestments year equipmentandlast % plant of as Property, revenue% of as Intangiblesassets NWC/sales Tax/EBIT companies/sales in associated profit/loss of Share inventures/sales jointprofit/loss of Share assets,/sales non-current Gain/loss of sale on impairment/salesReversal of Impairmentlosses/sales Depreciation/tangibleintangibleand assets EBIDTAmargin Growth USD million Value drives - Balance sheet - drives Balance Value - Income drivers statementValue -13,2% 2011 2011 22,7% 27,1% 0,0% 0,0% 0,5% 0,0% 0,0% 6,7% 31% 18% 60% 0% 8% 0% 0% -12,2% 2012 2012 84,4% 13,3% 27,2% -6,1% 0,0% 2,3% 0,5% 0,0% 6,3% 34% 21% 93% 52% 1% 7% 0% 9% 2013 2013 11,9% 26,1% -9,9% 0,0% 2,6% 3,5% 0,0% 0,7% 6,4% 1,3% 33% 23% 94% 44% 0% 5% 0% 8% 2014 2014 44,1% 20,9% -8,0% -0,4% -9,0% -2,3% 104% 0,0% 2,8% 0,6% 9,1% 26% 17% 0% 7% 0% 8% 2% -17,6% 2015 2015 28,4% -5,8% 101% 4,8% 0,0% 2,2% 0,7% 0,0% 0,0% 8,1% 25% 20% 13% 0% 8% 0% 2% Hist avg Hist avg Hist -10% 7,3% 30% 20% 98% 32% 23% 12% 26% -6% 0% 7% 0% 8% 0% 2% 1% 0% 2016E 2016E 104% -10% 7,3% 30% 20% 12% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 4% 2017E 2017E 104% -10% 7,3% 30% 20% 12% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 4% 2018E 2018E 100% -10% 7,3% 30% 20% 11% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 2% 2019E 2019E 100% -10% 7,3% 30% 20% 11% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 2% 2020E 2020E 100% -10% 7,3% 30% 20% 11% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 2% TP TP 100% -10% 7,3% 30% 20% 11% 23% 26% 0% 7% 0% 2% 0% 0% 1% 0% 0% 2%

Source: Compiled by authors, APMM, (2016)

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Appendix 40 - Svitzer pro forma income statement Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue USD million Net earnings NOPAT EBIT EBITDA Pro formaPro income statement 2011 102 102 132 237 109 636 873 30 0 0 0 4 0 0 2012 223 109 597 820 45 17 21 38 19 92 4 7 0 4 0 2013 141 156 177 217 614 831 17 21 22 29 85 2 0 0 6 2014 -284 -270 -250 170 358 642 812 13 20 23 93 -1 -3 0 5 2015 114 120 126 190 479 669 15 84 0 7 6 0 5 0 0 2016E 110 181 515 696 79 85 26 78 2 7 0 0 8 0 0 2017E 115 188 536 724 80 88 10 27 81 2 0 0 8 0 0 2018E 119 192 546 738 83 91 11 27 81 2 0 0 9 0 0 2019E 123 195 557 753 86 94 11 28 81 3 0 0 9 0 0 2020E 127 199 569 768 89 97 11 29 81 2 0 0 9 0 0 TP 124 203 580 783 88 95 29 81 2 9 0 0 2 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 41 - Svitzer pro forma balance sheet and cash flow statement - Cash surplus to corporate surplus Cash to - tax after expenses financial Net liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT (NIBD) debt interest-bearing Net level) Dividendscorporate (see earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and USD million Control flowcash Free to equity (FCFE) flowcash Free to fthe firm (FCFF) Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro cash flow statement formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 2016E 1.589 1.009 1.589 1.108 1.704 2011 -115 580 270 155 525 -112 71 160 160 82 0 0 0 84 31 78 85 0 6 2017E 1.495 1.016 1.495 1.035 1.595 2012 -100 479 277 171 427 -126 57 76 47 6 0 51 51 12 81 88 0 8 3 2018E 1.363 1.001 1.363 1.445 2013 362 275 193 969 367 -82 43 66 -82 92 0 0 88 88 81 91 0 8 5 1 2019E 1.069 1.069 1.008 1.142 2014 880 189 209 136 -73 54 65 15 -10 -83 95 0 0 77 77 81 94 0 8 1 2020E 1.132 1.132 1.015 1.171 2015 925 207 170 131 -39 56 84 16 -37 -83 98 0 0 53 53 81 97 0 8 2 TP 2016E 1.135 1.135 1.056 1.205 844 291 160 925 207 137 -70 79 49 84 16 -81 -83 97 1 0 81 95 0 8 8 7 2 2017E 1.176 1.176 1.098 1.249 873 303 844 216 142 -72 51 80 51 84 16 1 0 2018E 1.176 1.176 1.098 1.250 868 308 873 220 145 -74 88 83 52 84 16 1 0 2019E 1.176 1.176 1.098 1.251 878 298 868 224 148 -75 77 86 53 84 16 1 0 2020E 1.175 1.175 1.098 1.252 914 261 878 229 151 -77 53 89 54 84 16 1 0 TP 1.174 1.174 1.098 1.253 994 180 914 233 154 -79 88 55 84 16 8 0 0

Source: Compiled by authors, APMM, (2016)

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Appendix 42 - Pro forma APMM all reportable segments Tax shield Tax beginningNIBD expenses, financialyear Net of Tax companies in associated profit/loss of Share inventures jointprofit/loss of Share net etc., assets, non-current Gain/loss of sale on impairmentReversal of Impairmentlosses &Depreciationamortisation Operatingexpenses Revenue USD million Net earnings NOPAT EBIT EBITDA Pro formaPro income statement -12.864 13.826 50.150 2.928 2.928 9.065 6.137 4.844 2011 172 153 -20 44 0 0 0 -12.592 11.691 50.063 3.406 3.832 7.123 3.291 4.592 2012 -100 119 545 126 276 496 18 -10.183 11.350 48.082 3.333 3.765 7.070 3.305 4.349 2013 516 141 156 350 -96 84 26 -10.351 11.882 48.574 2.343 2.626 5.564 2.938 2.701 4.327 2014 132 414 562 -17 -76 89 41.205 -9.150 1.008 1.618 9.122 3.176 4.730 2015 758 274 610 157 147 -14 24 84 2016E 38.100 -8.050 1.541 1.781 2.160 6.527 4.705 277 379 195 37 77 66 0 0 2017E 40.039 -8.091 1.729 2.098 2.728 7.327 4.965 439 629 210 69 84 72 0 0 2018E 42.102 -8.437 2.038 2.423 3.195 8.115 5.307 456 773 221 72 90 76 0 0 2019E 44.980 -9.204 2.506 2.912 3.792 9.025 5.643 484 880 235 79 95 81 0 0 2020E 47.933 -9.979 3.030 3.435 4.511 9.840 1.076 5.766 488 101 250 83 86 0 0 -10.330 11.587 52.528 4.209 4.572 6.172 1.600 5.868 436 107 256 TP 73 91 0 0

iSource: Compiled by authors, APMM, (2016)

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Appendix 43 - Pro forma APMM all reportable segments Net interest-bearing debt (NIBD) debt interest-bearing Net Dividends earnings Net beginning Equity, period of working Net capital Intangibletangibleassets and USD million Invested capital (equity and NIBD) Equity, end of period Invested capital (net operating assets) Pro formaPro balance sheet Non-interest-bearing liabilities Non-interest-bearing assets current Other from corporate BUscash Surplus/deficit to saleheldfor Assets assets non-current Other companies in associated Investments inventures jointInvestments equipmentand plant Property, Intangiblesassets 41.981 26.664 41.981 15.317 12.450 40.110 46.587 -4.606 7.207 1.051 4.833 2011 637 593 0 45.121 30.632 45.192 14.489 12.739 40.411 48.719 -3.527 8.674 1.992 4.716 2012 538 916 684 44.512 32.870 43.830 11.642 13.694 40.466 48.974 -5.144 7.376 1.174 1.061 1.966 4.785 2013 696 44.693 36.995 43.599 13.167 43.820 49.857 -6.258 7.698 6.636 1.026 1.688 2.817 2014 273 506 43.461 35.691 42.407 12.893 43.469 49.100 -6.693 7.770 6.077 1.445 1.722 1.922 2015 123 542 48.778 36.455 48.000 12.323 35.691 46.993 51.720 -3.720 1.265 9.697 5.803 1.690 1.699 2016E 268 174 793 545 50.469 37.666 49.690 12.803 36.455 10.322 48.841 53.787 -4.097 1.037 1.729 6.039 1.670 1.861 2017E 186 869 546 52.777 39.169 51.999 13.608 37.666 10.957 51.290 56.428 -4.429 1.070 2.038 6.332 1.667 1.989 2018E 196 936 546 54.823 41.123 54.045 13.700 39.169 11.744 53.495 58.839 -4.794 1.104 2.506 6.742 1.006 1.670 2.121 2019E 209 546 55.822 43.585 55.044 12.237 41.123 12.522 54.649 60.195 -5.151 1.137 3.030 7.149 1.075 1.670 2.255 2020E 222 546 55.627 47.209 54.848 43.585 14.112 55.007 60.874 -6.025 8.418 1.170 4.209 7.865 1.239 1.616 2.468 222 544 TP

Source: Compiled by authors, APMM, (2016)

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Appendix 44 - Pro forma APMM all reportable segments ImpliedWACC FCFF per share (DKK) Dividend ratio Equity Dividends - tax after expenses financial Net from surplus/deficit BUs Cash other liabilitiesfinancial net New assets) (non-current investments Net - workinginChange Net capital - +amortisationandDepreciation NOPAT USD million Aggregated discounted FCFF Control flowcash Free to equity (FCFE) flowcash Free to the firm (FCFF) Reportable segments DCF Equity formaPro cash flow statement 2016E -3.481 -3.812 2016E 2016E -3.812 -7.325 -2.973 9,51% 4.553 4.705 1.781 -234 0,76 268 268 240 80 0 2017E 2017E 2017E -7.033 8,82% 344 1.037 1.037 4.965 2.098 0,76 408 408 310 369 518 480 377 0 2018E 2018E 2018E -7.947 7,50% 1.070 1.070 5.307 2.423 0,75 92 114 114 320 384 535 805 332 0 2019E 2019E 2019E -8.054 9,46% 603 1.104 1.104 5.643 2.912 0,76 866 866 330 406 552 364 92 0 2020E 1.556 2020E 2020E -1.463 -7.122 9,38% 2.436 2.436 1.137 1.137 5.766 3.435 0,79 340 405 569 357 0 TP -3.819 -6.548 9,35% 4.767 4.767 1.170 1.170 5.868 4.572 0,86 350 363 585 874 TP TP 0

Source: Compiled by authors, APMM, (2016)

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Appendix 45 - Income statement difference

From reportable segments to total revenue Revenue 2013 2014 2015 Adjustments 2013 2014 2015 Reportable segments 48.082 48.574 41.205 Other unallocated items -144 -105 -65 Other businesses 1.475 1.480 1.185 Eliminations -13 41 19 Unallocated activities (Maersk Oil Trading) 441 236 257 EBIT effect non-reportable items -157 -64 -46 Elminations -2.612 -2.721 -2.339 Tax (22%) 35 14 10 Total revenue 47.386 47.569 40.308 FCFF -122 -50 -36

Profit 2013 2014 2015 NPV of adjustments NOPAT reportable segments 3.769 2.628 1.008 Average FCFF last three years -69 Other businesses 400 408 316 WACC 9,35% Financial items, net -716 -606 -423 Growth 2,5% Unallocated tax 87 27 -70 NPV (Gordon growth formula) -1.013 Other unallocated items -144 105 65 *Assume Danish corporate tax Eliminations -13 41 19 Total continuing operations 3.383 2.339 925 Discountinued operations, after eliminations 394 2.856 0 Total profit 3.777 5.195 925

Source: Compiled by authors, APMM, (2014, 2015)

Appendix 46 - Balance sheet difference 2015

From reportable segments to total balance sheet

Reportable segments Total balance sheet Diff Intangible and tangible assets 49.100 51.390 2.290 Intangibles assets 1.922 1.922 - Property, plant and equipment 43.469 43.999 530 Investments in joint ventures 1.722 1.723 1 Investments in associated companies 542 889 347 Other non-current assets 1.445 2.857 1.412 Net working capital -6.693 -7.881 -1.188 Assets held for sale 123 122 -1 Other current assets 6.077 10.896 4.819 Non-interest-bearing liabilities 12.893 18.899 6.006 Invested capital (net operating assets) 42.407 43.509 1.102

Equity, end of period 35.691 35.739 -48 Net interest-bearing debt (NIBD) 7.770 7.770 0 Invested capital (equity and NIBD) 43.461 43.509 48 * diff from investments in joint ventures and assets held for sale stem from rounding errors

Source: Compiled by authors, APMM, (2016)

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Appendix 47 - Distribution of NIBD

Distribution of Net Interest Bearing Debt 2011 2012 2013 2014 2015 2016E 2017E 2018E 2019E 2020E TP Invested capital 41.981 45.192 43.830 43.599 42.407 48.000 49.691 51.999 54.045 55.044 54.850 Maersk Line 18.502 20.648 20.046 20.084 20.054 21.852 22.767 23.671 24.203 24.779 24.666 Maersk Oil 6.427 6.920 6.478 5.282 3.450 6.271 6.442 7.305 8.315 8.266 8.169 APM Terminals 5.124 5.495 6.177 5.933 6.177 6.819 7.383 7.913 8.406 8.866 8.954 Maersk Drilling 4.102 4.283 5.320 7.623 7.978 8.149 8.142 8.141 8.142 8.141 8.097 Maersk Tankers 3.774 3.633 2.335 1.583 1.644 1.669 1.668 1.668 1.668 1.668 1.664 Maersk Supply Service 2.146 2.206 1.699 1.704 1.769 1.793 1.793 1.793 1.792 1.792 1.792 Svitzer 1.589 1.495 1.363 1.069 1.132 1.135 1.176 1.176 1.176 1.175 1.174 Damco 317 512 412 321 203 312 319 331 344 357 334

APMM NIBD, % 15.317 14.489 11.642 7.698 7.770 12.323 12.803 13.608 13.700 12.237 8.418 Maersk Line 44% 46% 46% 46% 47% 46% 46% 46% 45% 45% 45% Maersk Oil 15% 15% 15% 12% 8% 13% 13% 14% 15% 15% 15% APM Terminals 12% 12% 14% 14% 15% 14% 15% 15% 16% 16% 16% Maersk Drilling 10% 9% 12% 17% 19% 17% 16% 16% 15% 15% 15% Maersk Tankers 9% 8% 5% 4% 4% 3% 3% 3% 3% 3% 3% Maersk Supply Service 5% 5% 4% 4% 4% 4% 4% 3% 3% 3% 3% Svitzer 4% 3% 3% 2% 3% 2% 2% 2% 2% 2% 2% Damco 1% 1% 1% 1% 0% 1% 1% 1% 1% 1% 1% Other businesses 23% 19% 24% 14% 2% 2% 2% 2% 2% 2% 2%

APMM NIBD, USDm 36% 32% 27% 18% 18% 26% 26% 26% 25% 22% 15% Maersk Line 6.751 6.620 5.325 3.546 3.674 5.610 5.866 6.195 6.135 5.509 3.785 Maersk Oil 2.345 2.219 1.721 933 632 1.610 1.660 1.912 2.108 1.838 1.254 APM Terminals 1.870 1.762 1.641 1.048 1.132 1.751 1.902 2.071 2.131 1.971 1.374 Maersk Drilling 1.497 1.373 1.413 1.346 1.462 2.092 2.098 2.130 2.064 1.810 1.243 Maersk Tankers 1.377 1.165 620 280 301 428 430 437 423 371 255 Maersk Supply Service 783 707 451 301 324 460 462 469 454 398 275 Svitzer 580 479 362 189 207 291 303 308 298 261 180 Damco 116 164 109 57 37 80 82 87 87 79 51 Other businesses 3.565 2.764 2.754 1.105 158 221 222 225 218 191 132

Source: Compiled by authors, APMM, (2016)

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