Running head: EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK
EXCHANGE
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK
EXCHANGE
A Thesis
Presented to the Faculty
of Economics programme at ISM University of Management and Economics
in Partial Fulfillment of the Requirements for the Degree of
Bachelor of Economics
by
Gytis Štarolis
Advised by
Lect. Tomas Krakauskas
May 2015
Vilnius
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 2
Abstract
Štarolis, G., Evaluation of Passive Investment Strategies in Oslo Stock Exchange
[Manuscript]: bachelor thesis: Economics. Vilnius, ISM University of Management and
Economics, 2015.
The aim of this thesis was to evaluate and compare results of traditional passive investment strategy (market capitalization weighted portfolio) and alternative passive investment strategies (Smart Beta portfolios) in Oslo Stock Exchange in 2005-2014 period.
The situation analysis showed that Oslo Stock Exchange is a safe and attractive market for investors because of Norway‘s political and economic stability and strong performance of Oslo Stock Exchange in the recent decade. Also, alternative passive investment strategies were found to outperform traditional passive investment strategy in the
US market in the analyzed period.
Analysis revealed supporting evidence for the hypothesis that alternative Smart Beta portfolios outperform traditional market capitalization weighted portfolios. All 7 portfolios that were formed according to various Smart Beta portfolio formation rules outperformed market capitalization weighted portfolio and Oslo Stock Exchange Benchmark Index. Smart
Beta strategies showed significantly higher rates of annual returns that were from 2.2pp to
22.7pp higher than the ones of market capitalization weighted portfolio. Sharpe ratios of all
Smart Beta portfolios were also found to be higher than the ones of market capitalization weighted portfolio and Oslo Stock Exchange Benchmark Index.
Value portfolio, which consisted of shares with lowest price-to-book value ratios, was found to perform best in the analyzed period, as it showed the highest annual growth rate
(34.3%) and highest Sharpe ratio (1.09) of all portfolios.
Keywords: passive investment, Smart Beta strategies, Oslo Stock Exchange, value investing. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 3
Table of contents List of Figures ...... 6
List of Tables ...... 7
Situation analysis ...... 9
Overview of political situation in Norway ...... 10
Geopolitical risk...... 10
Corruption ...... 11
Conclusion on political environment in Norway...... 11
Overview of economic situation in Norway ...... 11
Nominal GDP ...... 11
Population and GDP per capita (PPP) ...... 12
Nominal GDP growth (%)...... 13
Inflation and unemployment...... 13
Interest rates...... 14
Overview of Oslo Stock Exchange ...... 15
Oslo Axess...... 15
Oslo Bors...... 15
Comparison to other stock exchanges...... 16
Oslo Bors by liquidity...... 18
Oslo Stock Exchange indices...... 18
Brokers...... 20
Performance of passive investment strategies ...... 22
Literature Review and Methodology ...... 24
Literature review ...... 24
Passive investment versus active investment...... 24
Asset pricing models...... 25
Smart Beta strategies ...... 26 EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 4
Equally-weighted portfolio...... 28
Low volatility investing ...... 30
Value investing and fundamental weighting...... 31
Growth investing...... 34
Momentum investing...... 35
Methodology ...... 36
Return...... 37
Volatility...... 38
Sharpe ratio...... 38
Analysis...... 39
Data selection ...... 39
Methodology for formation and evaluation of portfolios...... 40
OSEBX and Market Capitalization portfolio ...... 41
Formation of Market Capitalization portfolio...... 41
Performance of Market Capitalization portfolio...... 41
Equally-weighted portfolio ...... 43
Formation of Equally-weighted portfolio...... 43
Performance Equally-weighted portfolio...... 43
Low Volatility and High Volatility portfolios...... 44
Formation of Low Volatility and High Volatility portfolios...... 44
Performance of Low Volatility and High Volatility portfolios...... 45
Momentum and Contrarian portfolios ...... 47
Formation of Momentum and Contrarian portfolios...... 47
Performance of Momentum and Contrarian portfolios ...... 47
Growth portfolio ...... 48
Formation of Growth portfolio...... 48
Performance of Growth portfolio...... 49 EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 5
Value portfolio ...... 50
Formation of Value portfolio...... 50
Performance of Value portfolio...... 51
Comparison of performances of all portfolios ...... 53
Returns...... 53
Volatility...... 53
Sharpe Ratio...... 54
Implications on Smart Beta Investing versus Traditional Passive Investing ...... 55
Implications on Carhart‘s four-factor asset pricing model...... 56
Recommendation ...... 57
Conclusions ...... 58
Reference List ...... 62
Appendices ...... 68
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 6
List of Figures
Figure 1. Nominal annual GDP growth (%)...... 13
Figure 2. Norway‘s key policy rate (%)...... 14
Figure 3. Number of companies by sector in Oslo Stock Exchange...... 17
Figure 4. Market capitalization by sector in Oslo Stock Exchange...... 17
Figure 5. Oslo Bors major indices 2007-2015 ...... 19
Figure 6. OSEBX and world‘s major indices in 2005-2014...... 19
Figure 7. Oslo Stock Exchange sector indices 2009-2015...... 20
Figure 8. Norwegian krone to US dollar historical exchange rate...... 21
Figure 9. Performances of OAX10ENERGY, OSEBX Brent oil in 2005-2014...... 21
Figure 10. Performance of S&P 500 indexes (rebased at 100)...... 23
Figure 11. Returns of OSEBX and Market Capitalization portfolios...... 42
Figure 12. Returns of Equal Weight and Market Capitalization portfolios...... 43
Figure 13. Returns of Low Volatility, High Volatility and Market Capitalization portfolios. 45
Figure 14. Returns of Momentum, Contrarian and Market Capitalization portfolios...... 47
Figure 15. Returns of Growth and Market Capitalization portfolios...... 49
Figure 16. Returns of Value and Market Capitalization portfolios...... 51
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 7
List of Tables
Table 1. Nominal GDP of Norway in United States dollars (in billions) ...... 11
Table 2. Nominal GDP by sector in Scandinavian countries in 2014 (estimated) ...... 12
Table 3. Historical annual inflation (CPI) in Norway (%)...... 13
Table 4. Historical unemployment rate in Norway (% of total labor force) ...... 14
Table 5. Statistics of different liquidity groups in Oslo Bors stock exchange...... 18
Table 6. Indices representing passive investment strategies in US market...... 22
Table 7. Compounded annual growth rates of S&P indices (TR)...... 23
Table 8. Performances of OSEBX and Market Capitalization portfolio...... 42
Table 9. Performances of Equally-weighted and Market Capitalization portfolios...... 44
Table 10. Performances of Low Volatility, High Volatility and Market Capitalization portfolios...... 46
Table 11. Performances of Momentum, Contrarian and Market Capitalization portfolios. .... 48
Table 12. Performances of Growth and Market Capitalization portfolios...... 50
Table 13. Performances of Value and Market Capitalization portfolios...... 52
Table 14. Returns of all portfolios...... 53
Table 15 Volatilities of all portfolios...... 54
Table 16 Sharpe ratios of all portfolios...... 55
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 8
As short-term real interest rates in most European countries are below 0% level, more investors tend to switch to potentially more lucrative investments. Norwegian stock market or so called Oslo Stock Exchange is one of the possible destinations for such investments. Since
2005 Oslo Bors Benchmark index, that consists of 52 most liquid stocks of Oslo Bors stock exchange, has increased by more than 150% and has outperformed major World indices
(S&P500, FTSE100, Nikkei225) by more than double. Also, Norway is considered to be a country with low level of political and economic risks, which encourages investments in Oslo
Stock Exchange. High returns on the stock market, low yields on other classes of assets and safe investment environment in Norway make Oslo Stock Exchange an attractive stock market for investors.
In order to maximize returns from investments in Oslo Stock Exchange an in-depth analysis of outcomes of how different passive investment strategies perform in Oslo Stock
Exchange needs to be performed. The thesis will try to resolve the following problem: do alternative passive investment portfolios outperform traditional market capitalization weighted portfolio?
To solve the above-mentioned problem, the aim of the thesis was defined: to evaluate and compare different passive investment strategies in Oslo Stock Exchange in 2005-2014 period.
To reach the aim of the thesis, the following objectives were set:
1. To evaluate attractiveness of Oslo Stock Exchange by analyzing Norway‘s political
situation, economic situation and performance of the shares listed on Oslo Stock
Exchange.
2. To analyze the performance of different passive investment strategies in largest stock
exchanges. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 9
3. To form investment portfolios that would represent different passive investment
strategies using stocks listed on Oslo Stock Exchange.
4. To compare and evaluate previously-formed portfolios.
The following research methods will be used in this thesis: literature analysis to analyze the performance of strategies in various stock exchanges, fundamental analysis of the companies listed on Oslo Stock Exchange to form investment portfolios, statistical analysis of share prices and formed portfolios for evaluation of portfolios. The Microsoft Excel software will be used to explore and visualize data.
Thesis should be practically valuable for investors who are considering Oslo Stock
Exchange as an investment destination, as practical investment opportunities will be analyzed by taking into account transaction costs related to portfolio formation and its readjustments. It could also be valuable for everyone who is interested in passive investment strategies and investments in stock markets in general.
Situation analysis
Norway is an OECD country located in the Scandinavian Peninsula. The country is considered to be one of the most developed countries in the world. With literacy rate of
100%, expected lifespan of 81.5 years and infant deaths averaging 3.8 out of 1000, Norway is ahead of Europe‘s and world‘s averages. Norway is not a member of European Union, but is one of the founders of NATO and United Nations.
According to Euromoney, in the first half of 2014 Norway with a score of
90.86/100.00 was the country with the lowest country risk in the world, ranked just above
Switzerland and Singapore. This particular ranking consists of political risk (30%), economic performance (30%), structural assessment (10%), debt indicators (10%), credit ratings (10%) and access to bank finance/capital markets (10%). Norway being ranked at the first place suggests that country‘s political risk is low and economic performance is stable (Euromoney, EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 10
2014). It makes Norwegian assets, such as stocks on Oslo Bors, more appealing for investors who are looking for relatively safe and stable markets to invest in.
Overview of political situation in Norway
Kingdom of Norway is a constitutional monarchy. The political powers in Norway are split in the following way: executive power belongs to the Head of State (the King) and the
Council of State (the cabinet), legislative power is split between the government and the parliament (Storting), judicial power, which is independent from executive and legislative branches, belongs to courts and Supreme Court system. Effective distribution of powers suggests high level of democracy in the country.
In 2013 Norway was ranked at no. 12 in Political Stability and Absence of
Violence/Terrorism. This index shows how likely the government is to be conquered in cruel or unconstitutional ways. Highly democratic election system, low level of corruption and outstanding economic performance in Norway positively influences most of the indicators taken into consideration that are used in computing Political Stability and Absence of
Violence/Index (The World Bank, 2014a).
Geopolitical risk. Geopolitical risk to a great extent depends on how politically and economically interrelated the countries or regions are. Even though Norway is a neighbor of
Russia, which itself is considered as one of the biggest geopolitical risks in the world in 2015,
Norway‘s geopolitical risk is at a minimum level. Firstly, countries have had a stable diplomatic relationship. Secondly, the biggest realistic threat from Russia is not a war threat, but various bans on imports exports. Assuming Russia imposes bans on exports and imports to and from Norway (which is highly unlikely), Norway would not be devastated, because imports from Russia amounts to only 1.6% of total Norwegian import (Observatory of economic complexity). Norway is a highly self-sufficient country that maintains its self- sufficiency by producing most of the needed energy resources itself. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 11
Corruption. According to Corruption Perception Index (CPI), Norway is the 5th least corrupted country in the world, that scored 86/100 in CPI rankings in the first half of 2014.
On one hand, the score is well above EU-28 average (64.2) and world average (43.2), and it represents high level of transparency in the country. On the other hand, other Scandinavian countries were even more transparent – Sweden had a score of 87, Denmark a score of 92 – which leaves some room for improvement for Norway (Transparency International).
Conclusion on political environment in Norway. All of the above-mentioned indicators are highly interrelated in their determinants, which makes indicators of Norway‘s political situation biased. One positively evaluated indicator influences other indicators in a positive way and may offset particular disadvantages of Norway‘s political situation when added together. This way the downsides of political environment of Norway may not be noticed and objectively analyzed and the optimism on political situation of Norway might be overly exaggerated.
However, it is safe to say that political situation in Norway is stable and positive.
Norway is among leaders in the world in most of criterias that define positive and stable political situation in the country.
Overview of economic situation in Norway
Nominal GDP. Nominal GDP in Norway has been steadily growing since 2007 except for year 2009 when financial crisis struck Europe (see Table 1).
Table 1.
Nominal GDP of Norway in United States dollars (in billions)
Year 2007 2008 2009 2010 2011 2012 2013
GDP 393.479 453.885 378.849 420.945 490.807 500.030 512.580
Source: The World Bank EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 12
Norway is a relatively industrial country. Compared to industry sectors as a percentage of GDP in other Scandinavian countries, Norway‘s industry sector as a percentage of GDP is 8.4% higher than Sweden‘s and 20.6% higher than Denmark‘s (see Table 2).
Table 2.
Nominal GDP by sector in Scandinavian countries in 2014 (estimated)
Country Norway Sweden Denmark
Agriculture 1.7% 1.8% 1.3%
Industry 41.8% 33.4% 21.2%
Services 56.5% 64.8% 77.5%
Source: Central Intelligence Agency
In 2014 40.95% of Norway‘s GDP was created by private consumption, 21.84% by government expenditures, 28.78% by fixed capital formation and 8.43% by net exports. GDP calculation using expenditure approach suggests similar compositions by type of expenditures in all 3 compared Scandinavian countries (OECD, 2015).
Population and GDP per capita (PPP). From 2005 to 2013 the population of Norway grew on average by 1.2% annually. As nominal GDP was growing faster than the population, nominal GDP per capita was increasing – on average by 5.4% per year. In 2013, Norway had the second highest nominal GDP per capita in the world – 100,898.4$. Norway’s GDP per capita is 66% higher than Sweden’s, 68% percent higher than Denmark’s and 184% higher than average of EU-28.
The noticeable difference between Norway and other compared countries mainly relies in the industrial sector. Given that in 2013 the same share Norway’s GDP was created by industry sector as in 2012, 20.2% of Norwegian workers created 42.3% of GDP, which equals 209,406$ per capita in the industry sector – at least 3 times more than workers in industry sector in Sweden or Denmark, or EU-28 created. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 13
In 2013 Norway had 6th largest GDP per capita PPP, equal to 65,500 USD. It was more than 40% higher than GDP per capita PPP in Sweden and Denmark. It is also 85% higher than average EU-28 GDP per capita PPP and more than 3.5 times higher than the world’s average (The World Bank, 2014c).
Nominal GDP growth (%). Since 2007 Norway‘s annual nominal GDP has been growing by 6% on average. Norway‘s GDP growth was even higher than European Union‘s (2.4%) and world‘s (5.8%) growth rates, which is impressive because Norway is a highly developed country and GDP growth rates in more developed countries tend to be lower than the ones in less developed or developing countries (see Figure 1).
20.00%
10.00% Norway 0.00% EU-28 2007 2008 2009 2010 2011 2012 2013 World -10.00%
-20.00%
Figure 1. Nominal annual GDP growth (%). Source: World Bank
Inflation and unemployment. The aim of Norway‘s monetary policy is low and stable inflation, with annual consumer price inflation of approximately 2.5% over time (Norges
Bank). The average annual CPI inflation in 2005-2014 period was 1.94% (0.56% below target level) (see Table 3).
Table 3.
Historical annual inflation (CPI) in Norway (%)
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Inflation 1.85 2.24 2.78 2.13 2.01 2.76 0.15 1.38 2.04 2.07
Source: Worldwide Inflation Data
Average unemployment rate from 2005 to 2013 was 3.3% and remained low and stable during crisis (see Table 4). Norway‘s average unemployment rate in 2005-2013 was EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 14 lowest in Europe and was much lower than average EU-28 unemployment rate (8.98%)
(Eurostat, 2014).
Table 4.
Historical unemployment rate in Norway (% of total labor force)
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013
Unempl. rate 4.5 3.4 2.5 2.5 3.2 3.6 3.3 3.2 3.5
Source: Eurostat
Interest rates. Currently the base Norwegian interest rate is 1.25%. In July, 2008 Norway‘s key policy rate was at the highest level of recent decade - 5.75%. Since May, 2011, when the base interest rate was increased to 2.25%, Norway‘s central bank has been gradually lowering the interest rate to 1.75%, 1.5% and to a current rate of 1.25%. In March, 2015, Norway‘s central bank was expected to continue its program of economic stimulation and to lower the interest rate to 1%. However, unexpectedly, the key policy rate remained at 1.25% (see
Figure 2).
7
6
5
4
3 Key policy rate 2
1
0
May-… May-… May-… May-… May-…
Jan-05 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15
Sep-07 Sep-09 Sep-11 Sep-13 Sep-05 Figure 2. Norway‘s key policy rate (%). Source: Norges Bank
Conclusion on economic environment in Norway. Norway is an economically strong and stable country. Norway has the second highest GDP per capita in the world, Norway‘s unemployment rate is the lowest in Europe. The country managed to maintain relatively high EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 15
GDP growth throughout the last 10 years and recovered from crisis quickly. Also, Norway‘s central bank managed to maintain low and stable inflation rate, which is close to a target inflation level of 2.5%, by reducing base interest rates to the lowest decade in recent decade –
1.25%.
Overview of Oslo Stock Exchange
There are 2 separately functioning exchanges in Oslo Stock Exchange – Oslo Axess and Oslo
Bors.
Oslo Axess. Oslo Axess is Norway‘s regulated stock market in which small capitalization companies that do not meet the criteria to be listed on Oslo Bors are listed. In order to be listed on Oslo Axess, the company also has to satisfy Oslo Axess listing requirements. For example, the company has to have at least 100 shareholders each holding shares with a value of at least 10,000 NOK. Also, minimum market capitalization of the company has to be at least 8 million NOK. As of 31st December, 2014, there are 33 small market capitalization companies listed in Oslo Axess. Total Oslo Axess market cap is 17.7 billion NOK, which is approximately 2.37 billion USD. In 2014, there was a total of 304.5 thousand transactions made in Oslo Axess, that made up 1.46 billion shares traded, that were worth 9.9 billion NOK
(1.3 billion USD) or 55.74% of Oslo Axess market capitalization (Oslo Bors, 2015).
Oslo Bors. Oslo Bors is Norway‘s regulated stock market in which mostly medium capitalization and large capitalization companies are listed. In order to be listed on Oslo
Bors, the company has to satisfy Oslo Bors listing requirements. Firstly, the company has to have 500 shareholders, each of whom should hold shares with a value of at least 10,000
NOK. 3 year history of the company and its business activities has to be provided. Also, the minimum market capitalization of the company has to be at least 300 million NOK. As of 31st
December, 2014, there are 164 listed companies. Total Oslo Bors market capitalization is 1.8 EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 16 trillion NOK (240 billion USD). Market capitalization of Oslo Bors is around 100 times larger than Oslo Axess. (Oslo Bors, 2015).
Comparison to other stock exchanges. According to World Bank, at the end of 2012 Oslo
Stock Exchange had a market capitalization of 252.95 billion USD and was the 28th largest stock exchange in the world. Oslo Stock Exchange‘s market capitalization was equal to
0.476% of the total World‘s market capitalization. Size of Oslo Stock Exchange was the most similar to Colombia‘s stock exchange (262 billion USD). Compared to other Scandinavian countries, Norway had a little bigger stock exchange than Denmark (225 billion USD), but more than twice smaller than Sweden (561 billion USD) (The World Bank, 2014d).
The number of domestic companies listed on Norway‘s stock exchange at the end of
2012 was 184. From this perspective, the Oslo Stock Exchange was the most similar to
Croatia‘s stock exchange (184) and Kuwait‘s stock exchange (192). There were more companies listed on Oslo Stock Exchange than on Copenhagen stock exchange (174), but much less than on Stockholm stock exchange (332) (The World Bank, 2014e).
In 2012 Norway‘s market capitalization was equal to 50.6% of Norway‘s GDP, which suggests a possible undervaluation of Oslo Stock Exchange. From this perspective, Saudi
Arabia and Peru have the most similar stock exchanges. Both Denmark (69.8%) and Sweden
(103.1%) had higher market capitalization to GDP ratios. There were only 14 OECD countries that had lower market capitalization to GDP ratio, most of which are still much less economically developed than Norway (The World Bank, 2014f).
Oslo Stock Exchange by sector. The companies on Oslo Axess and Oslo Bors are divided into 10 different sectors, according to the company‘s business activity. On Oslo Axess two sectors with largest market capitalization are Energy (57.49%) and IT (21.00%).
On Oslo Bors, the sectors with highest number of companies are Energy (54 of 164 companies) and Industrials (33/164). In terms of market capitalization, the three largest EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 17 sectors are Energy (32.27% of total Oslo Bors market capitalization), Consumer
Discretionary (10.33%) and Material (10.30%).
Both exchanges together, the sectors with highest number of companies are Energy and Industrials (see Figure 3).
Figure 3. Number of companies by sector in Oslo Stock Exchange. Source: OsloBors.no
The sectors with largest market capitalization as percentage of total market capitalization of Oslo Stock Exchange are Energy (32.47%) and Finance (18.20%). (0.25%)
(see Figure 4).
Figure 4. Market capitalization by sector in Oslo Stock Exchange. Source: OsloBors.no EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 18
Oslo Bors by liquidity. The stocks on Oslo Bors are divided into 5 groups, according to their liquidity level (Oslo Bors).
OBX: Shares in OBX index
OB Match: average of minimum 10 trades per day or shares with liquidity provider
scheme
OB Standard: Shares with fewer than 10 trades per day on average and without
liquidity provider scheme
OB New: Recently listed shares
OB Equity Certificates: Listed ECs
OBX group is by far the largest and 25 companies that are in the OBX index add up to
78.70% of entire Oslo Bors market capitalization (see Table 5).
Table 5.
Statistics of different liquidity groups in Oslo Bors stock exchange.
Group OBX OBX Match OB Standard & New OB Equity Certificates Number of 25 122 31 19 companies % of market 78.70% 19.06% 0.90% 1.34% capitalization Source: Oslobors
Oslo Stock Exchange indices. There are three most commonly used indices on Oslo Bors
(Oslo Bors).
OBX. It consists of 25 most traded shares on Oslo Bors, based on six months
turnover. OBX is revised semi-annually.
Benchmark index (OSEBX). Index which comprises the most traded shares listed on
Oslo Bors. OSEBX is also revised semi-annually.
OSEAX. The index that consists of all the shares listed on Oslo Bors. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 19
All 3 indices in 2007-2015 period were changing similarly. OBX increased most and outperformed both OSEBX and OSEAX, while OSEBX outperformed OSEAX. This pattern suggests that the most traded shares grew more than least traded shares in 2007-2015 (see
Figure 5).
Figure 5. Oslo Bors major indices 2007-2015. Source: Euroinvest
Compared to the world‘s most used indices, Oslo Bors benchmark index (OSEBX) grew faster than major world indices (S&P500, FTSE100, NIKKEI225) in 2005-2014. Even though OSEBX was mostly affected by financial crisis, it managed to recover faster and in total in 2005-2014 period grew by more than 140% (see Figure 6).
Figure 6. OSEBX and world‘s major indices in 2005-2014. Source: Yahoo Finance EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 20
There are also 9 indices representing different sectors of Oslo Stock Exchange traded on the Oslo Stock Exchange. Since July, 2009 when all 9 indices were introduced, Consumer
Discretionary and Telecommunication sectors that grew by 507% and 298% respectively were the fastest growing sectors. Telecommunication sector index is composed of only 2 companies, one of which, Telenor, has more than 2500 times higher market capitalization than the other of 2 companies – Telio ASA. The fact that Telecommunication sector has been the second fastest growing one basically means that Telenor managed to outperform all sectors except for Consumer Discretionary in 2009-2015 period. While Telecommunication and Consumer Discretionary were thriving, Utilities and Energy grew by only 32% and 34% respectively (see Figure 7).
Figure 7. Oslo Stock Exchange sector indices 2009-2015. Source: Euroinvestor
Brokers. In 2014 in Oslo Axess there were 610 thousand transactions made by 38 brokers that added up to 19,786 million NOK. Local banks accounted for 62% of number of transactions that made up 80% of total turnover.
In 2014 in Oslo Bors there were 47.2 million transactions made by 44 brokers that added up to 2.2 billion NOK. Foreign banks traded much more actively on Oslo Bors than on
Oslo Axess. 3 out of 5 largest brokers were non-Norwegian banks. In total, all local banks accounted only for 38.8%% of transactions and 43.8% percent of total turnover. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 21
Risks. Norway has its own independent currency – Norwegian krone. As a result of it, foreign investors who invest to Oslo stock are exposed to currency risk. Currency risk has been especially significant recently, because in the last year Norwegian krone weakened by more than 20% (see Figure 8).
0.2 0.18 0.16 0.14 NOK/USD 0.12 0.1
Figure 8. Norwegian krone to US dollar historical exchange rate. Source: Investing.com
Another major risk that investors are exposed to in Oslo Stock Exchange is oil price risk. Energy sector is the biggest sector in Oslo Stock Exchange (33% of total Oslo Stock
Exchange market capitalization). Because of high share of total Oslo Stock Exchange market capitalization, prices of the shares of the companies in the Energy sector are very influential on major investable indices. Most of the Energy sector companies are oil producers or oil refineries, so their results are directly related to the world‘s oil price (see Figure 9).
250 200 150 OAX10ENERGY 100 Brent oil price 50 OSEBX 0
Figure 9. Performances of OAX10ENERGY, OSEBX Brent oil in 2005-2014. Source: Euroinvestor EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 22
Figure 9 shows high interdependency between OAX10ENERGY index, which includes all energy sector companies, Benchmark Index (OSEBX) and Brent oil price. In
2005-2014 correlation coefficient between OAX10ENERGY and OSEBX was 0.895, between OAX10ENERGY and Brent oil price – 0.577, between Brent oil price and OSEBX –
0.399.
Performance of passive investment strategies
Various passive investment strategies are represented by different indexes created for companies included in the S&P 500. The returns of the following indexes are compared:
Table 6.
Indices representing passive investment strategies in US market.
S&P 500 The share of a particular stock in the index is equal to company‘s free-float capitalization to S&P 500 free-float capitalization ratio S&P 500 Equal Each of 500 companies is allocated a fixed weight of 0.2% of the Weight Index index total
S&P 500 High Measures the performance of 100 companies that belong to S&P Beta Index 500 and are most affected by changes in market returns
S&P 500 Low Tracks the performance of 100 least volatile stocks in the S&P 500 Volatility Index S&P 500 Measures the performance of S&P 500 companies that have Dividend increased dividends every year for at least 25 years Aristocrats S&P 500 Pure Tracks the performance of 33% of most undervalued S&P 500 Value Index companies. The most undervalued companies are chosen according to the value score, which includes 3 factors: book value to price ratio, earnings to price ratio, sales to price ratio
S&P 500 Pure Tracks the performance of 33% fastest growing companies. The Growth Index growth is determined by three factors: three-year change in earnings per share over price per share, three-year sales per share growth rate and momentum (12-Month % price changes)
Source: S&P Indices
In the last ten years traditional free-float capitalization weighted S&P 500 index was outperformed by each of the above-mentioned indices, except for S&P 500 High Beta index, EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 23 which was harmed by the financial crisis mostly and underperformed in a highly volatile period (see Figure 10).
300
250
200 S&P 500 150 S&P 500 Equal Weight S&P 500 Pure Growth 100 S&P 500 Pure Value 50 S&P 500 Low Volatility S&P 500 High Beta 0 S&P 500 Dividend Aristocrats
Figure 10. Performance of S&P 500 indexes (rebased at 100). Source: Euroinvestor.com
Pure Growth and Dividend Aristocrats indices had more than 3% higher compounded annual growth rate (CAGR) than free-float capitalization weighted S&P 500. Equal Weight,
Low Volatility and Pure Value indices outperformed S&P 500 by a margin which is close to
2pp on annual basis (see Table 7).
Table 7.
Compounded annual growth rates of S&P indices (TR).
Index S&P 500 Equal High Low Dividends Pure Pure weight Beta volatility Aristocrats value growth index index index index index index CAGR 8.1% 10.0% 3.5% 10.0% 11.4% 10.1% 11.7% Source: S&P Indices
Higher returns in Equal Weight, Low Volatility, Dividend Aristocrats, Pure Growth and Pure
Value indices suggest that various passive investment strategies can be expected to bring higher returns than traditional investments in market capitalization based indexes. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 24
Literature Review and Methodology
Literature review
Passive investment versus active investment. The main difference between passive investment and active investment is the goal passive or active investors seek to reach. Passive investors seek to replicate the returns of various indices, such as S&P 500, while active investors try to outperform these indices. It is possible because of the assumed market inefficiency (Baird’s Advisory Services Research, 2012).
Passive managers assume that all market participants have equal information and, thus, markets are efficient and there is no need to pay additionally for the costs of active management. Passive portfolios have to be transparent and systematically implemented, meaning that portfolios are constructed according to pre-determined and well-defined strategy and the funds have to fully implement such strategy. Passive managers usually take positions in long-term investments and do not change the assets of the portfolio for long periods of time. Oppositely, active managers actively trade their assets trying to outperform the indices. Active managers look for better market-timing or stock-picking opportunities to reach their goal, because they believe markets are inefficient and there are investment strategies that consistently outperform market portfolio. As a result of this, active investors are involved in more trades (Swedroe, 2014).
Compared to active investment, the main advantages of passive investment are market risk diversification, liquidity and lower trading fees. However, the passive investor also faces few main disadvantages: the companies that compose the portfolio are predetermined, investors also have to accept the predetermined weighting of each company in the portfolio, weighting, which is usually based on market capitalization of each company and which increases the exposure to large market capitalization companies (Whitehead). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 25
Asset pricing models. The asset pricing has been always widely discussed topic in the realm of Finance. Since 1964, plenty of different models explaining asset pricing were created. The core model is the Capital Asset Pricing Model (CAPM), created by Sharpe in 1964. The model states expected returns are explained by one factor - “beta“, which shows the sensitivity of an asset‘s price to changes in the market price (Market factor) (Sharpe, 1964).
rit-rft =αi+βimkt(rmt-rft)+εit,
where rit-rft is excess return to a risk-free rate of an asset i, αi is excess return of an
asset due to market inefficiencies, βimkt is asset‘s sensitivity to changes in market
portfolio return, (rmt-rft) is market portfolio‘s excess return to a risk-free rate and εit is
random error term.
In the last 20 years models that explain bigger part of asset’s price were created. In 1992
Fama-French found that returns of the assets could be better explained by the three-factor model. Aside from the above mentioned market beta, Fama and French found that excess returns of the assets can be partially explained by value and size of companies. Small size companies and companies with high book value to price ratios had historically higher returns
(Fama & French, 1992).
rit-rft =αi+βimkt(rmt-rft)+βivalVALt+βisizeSIZEt+εit,
Where βival shows how exposed an asset i is exposed to value risk factor, VAL
measures historic excess returns of value stocks over growth stocks, βisize measures
how exposed an asset i is to size risk factor and SIZE measures historic excess returns
of small stocks over large stocks.
In 1997 Carhart extended three-factor model to a four-factor model by including
“momentum” factor to a model. Momentum factor states that stocks that were appreciating in previous period are expected to have higher expected returns in future than the stocks that were depreciating in previous period (Carhart, 1997). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 26
rit-rft =αi+βimkt(rmt-rft)+βivalVALt+βisizeSIZEt+βimomMOMt+εit,
Where βimom shows how exposed an asset i is to momentum factor and MOM
measures historic excess returns of appreciating stocks over depreciating stocks
Recently, Fama and French extended their previously-mentioned three-factor model to a five-factor model. The fourth factor they found to be significant is higher profitability. Higher profitability, measured as operating profitability minus interest expense to book value ratio, suggests that expected returns will be higher. The fifth significant factor is the investment factor. Companies that invest conservatively are expected to have higher future returns than the companies that invest aggressively (Fama & French, 2014).
rit-rft =αi+βimkt(rmt-rft)+βivalVALt+βisizeSIZEt+βiproPRO+βiinvINV+εit ,
where βipro shows how exposed an asset i is to profitability factor, PRO measures
historic excess returns of highly profitable companies‘ stocks over less profitable
companies‘ stocks, βiinv shows how exposed an asset i is to investment factor and INV
measures excess returns of the stocks of the companies that invest conservatively over
stocks of the companies that invest aggressively.
However, Fama and French found that Value factor in the five-factor model is explained by other factors, which makes the Value factor redundant. Essentially, there are only four factors included in the five-factor model.
rit-rft =αi+βimkt(rmt-rft)+βisizeSIZEt+βiproPRO+βiinvINV+εit. (Atlas Capital Advisors)
Smart Beta strategies. Traditionally, the weights of shares in the indices and index ETFs are determined by their market capitalizations. Above mentioned-studies found that cap-weighted portfolios are less exposed to Size and Value factors than equally- or fundamentally- weighted portfolios. Market capitalization weighted portfolios hold big positions in large and overvalued companies and small positions in small and undervalued companies because of the way they are composed. This is inefficient, since small companies and companies with EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 27 high book value to price ratio are expected to have higher returns according to asset pricing models.
To mitigate this inefficiency and to capitalize more gains, Smart Beta strategies were created. A strategy is a Smart Beta investment strategy, which breaks the link between stock‘s price and stock‘s weight in the portfolio. Different Smart Beta strategies are used to form the portfolios, but what is in common of all of them – the share price and market capitalization are not used as criteria for weights of the shares in the portfolio.
One type of indices that are formed according to Smart Beta strategies are fundamental indices. Fundamental indices are weighted according to different fundamental criteria, such as book value or gross sales, and they outperform traditional market capitalization based indices, because, relatively to market cap indices, fundamental indices overweigh most feared stocks - small cap and with high book value to price ratio - and underweight most liked - large cap and low value - stocks (Kalesnik, 2014).
Traditional market capitalization indices were found to be outperformed by
Fundamental indices in the US market in the long run (1962-2004 period) (Arnott, Hsu, &
Moore, 2005). Also, in 1987-2009 period market capitalization based MSCI world index was outperformed by all Smart Beta investment strategies, including minimum variance and equal weighting strategies (Chow , Hsu, Kalesnik, & Little, 2011).
Polychronopolous in 2014 concluded, that Momentum, which is a type of Smart beta strategy, also managed to outperform market capitalization based strategy in 1967-2013 period (Polychronopoulos, 2014). Smart Beta portfolios are said to outperform market cap based portfolios by 2% in efficient markets and by even more in inefficient markets
(Research Affiliates, 2013).
According to Research Affiliates definition, Smart Beta strategies are somewhere in between of passive and active investment strategies, because Smart Beta strategies combine EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 28 the benefits of both passive and active strategies – they have strict set of investments rules, low fees, but also do not create the link between share price and its weight in the portfolio.
However, the author of this thesis consider Smart Beta strategies to be passive, because Smart
Beta uses a predetermined set of investment rules and excludes market timing and stock picking strategies, thus, Smart Beta strategies are very similar to passive investment strategies.
There are two types of Smart Beta strategies: optimized and heuristic. Optimized strategies seek to minimize or maximize particular setting of the portfolio as a whole, for example, minimum variance strategy seeks to minimize variance of the portfolio. Heuristic- based Smart Beta strategies are rules-based weighting strategies that usually combine individual assets that are superior to other assets in the desired setting. For example, low volatility strategy combines a certain number of assets that are least volatile individually and weighs them according to the predetermined weighting rules.
Even though the Smart Beta strategies tend to bring higher returns, they still have downsides. First of all, Smart Beta requires periodic rebalancing which results in higher transaction costs compared to market capitalization index, which does not require periodic rebalancing (Lenhard, 2014). The Smart Beta strategies are also considered to reduce liquidity, because non market capitalization weighted portfolios usually allocate higher share of the investment in smaller and less liquid companies. Because of that, Smart Beta strategies are also usually more dependent on the performance small capitalization stocks (Amenc,
Goltz, & Martellini, 2013). Different passive investment strategies are also exposed to strategy specific risks that will be discussed later.
Equally-weighted portfolio. In equally-weighted portfolio stocks of different companies constitute for the same share of the portfolio. The size of each company‘s share is determined by formula 1/n, where n is the number of companies in the portfolio. In order to maintain EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 29 equal weights of stocks in the portfolio, it has to be periodically readjusted, otherwise appreciating stocks eventually would become overrepresented and depreciating stocks would become underrepresented. Equally-weighted portfolio is not as biased towards large capitalization companies as cap-weighted portfolio is, because small and medium size companies represent higher share of the equally-weighted portfolio compared to market cap- weighted portfolio (Carlisle, 2012).
Plyakha, Uppal, Vilkov in 2012 found that monthly adjusted equally-weighted portfolios outperformed value- and market cap- weighted portfolios in US in 1967-2009 period. The better performance partially came from higher systematic risk, beta, and partially from higher alpha, so called active return of the investment. Alpha was responsible for 42% of the equally-weighted portfolio‘s excess return over value-weighted portfolio and systematic component accounted for 58%. However, compared to price-weighted portfolio, systematic component accounted for only 4% of the excess return of equally-weighted portfolio and alpha accounted for 96%. The excess systematic return of equally-weighted portfolio was explained by higher positive exposure to Market, Size and Value factors. The excess alpha was contributed to monthly rebalancing of the portfolio and not to the equal- weighting itself (Plyakha, Uppal, & Vilkov, 2012).
Oppositely, Urban and Ormos in 2012 found that even though equally-weighted portfolios outperformed cap-weighted portfolios in US in 1975-2008 period, the excess returns cannot be attributed to Value, Size or Momentum factors. Also, equally-weighted portfolios were found not to outperform market cap-weighted portfolio in Budapest stock exchange (BUX). However, there are only 48 companies listed on Budapest stock exchange and its total market capitalization is only 12 billion Euros, so it is neither a good comparison to the U.S. market nor a good representative of the world market (Urban & Ormos, 2012). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 30
Kose and Moroz (2014) acknowledged that equally-weighted portfolios are easy to understand and that they outperform cap-weighted portfolios. However, they found that equally-weight portfolio is outperformed by fundamentally-weighted portfolio in the long run before accounting for costs in 10 markets in North America and Europe. The reason for it is the fact that equally-weighted portfolios are usually composed by using just a part of all stocks of the market, for example 100 largest stocks. This way some of the overvalued stocks are taken into the portfolio that is why fundamentally-weighted portfolio performs better. The implementation costs of equally-weighted portfolio are also higher, because equally-weighted portfolio requires more rebalancing which results in higher turnover and higher fees. Another disadvantage of equally-weighted portfolio is lower liquidity of its assets. It comes from the fact that equally-weighted portfolios, contrary to fundamentally-weighted portfolios, do not take sizes of companies into portfolio formation and take disproportionate positions in small companies. Kose and Moroz also argue that higher diversification of equally-weighted portfolio is not itself an advantage and the important risk factors and only marginally better in equally-weighted portfolios compared to fundamentally-weighted portfolios. (Kose & Moroz,
2014).
Low volatility investing. The low volatility strategy seeks to minimize the risk of the portfolio. Low volatility strategies can be either heuristic (low volatility, low-beta) or optimized (minimum variance). The low volatility strategies underperform the cap-weighted strategies in bull market. However, this underperformance is more than offset by a superior performance of low volatility strategies in down-trending markets, for example, during financial crisis. Chow, Hsu, Kuo and Li showed that low volatility strategies over extended periods of time not only had higher Sharpe ratio, but also showed higher returns (Chow, Hsu,
Kuo, & Li, 2014). The fact that low volatility portfolio outperforms cap-weighted portfolio is explained by French-Fama three-factor model and its extensions. Haugen and Heins found EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 31 that in 1926-1971 in U.S. Stock Market and U.S. Bond Market risk and returns were negatively correlated, meaning that stocks (bonds) with lower risk had higher returns than stocks (bonds) with higher risk (Haugen & Heins, 1972). Ang, Hodrick, Xing and Zhang by analyzing 23 developed markets and controlling for size and value confirmed that higher idiosyncratic volatility itself results in lower returns (Ang, Hodrick, Xing, & Zhang, 2008).
Finally, Frazzini and Pedersen extended three-factor model by adding betting-against-beta factor and empirically proved that by choosing lower-beta assets investors are expected to have higher returns (Frazzini & Pedersen, 2013).
Chow, Hsu, Kuo & Li (2014) compared different low volatility strategies – minimum variance, equally-weighted low volatility (low-beta) and inverse-volatility (inverse-beta), in which higher weights were assigned to stocks with lower volatility (lower beta). All these strategies consistently had higher returns, lower volatility and, thus, higher Sharpe ratio than cap-weighted strategies in U.S., Global and Emerging markets. However, none of the low volatility strategies were statistically proved to be better than others, which is explained by the fact that low volatility stocks also tend to be low-beta stocks and thus portfolios are rather similar. The difference in returns between low volatility and market-cap weighted strategies was mostly explained by difference in Market beta, while Value, Size and Momentum factors were inconsistent between different markets (Chow, Hsu, Kuo, & Li, 2014).
All of the above-mentioned researches confirm that low volatility portfolios outperform market cap-weighted portfolios in all markets and that lower volatility or lower beta is a factor for the better performance. However, the importance of Value, Size and
Momentum factors vary across different markets and time frames.
Value investing and fundamental weighting. According to Fama and French (1992), there is premium that value stocks have over growth stocks (Fama & French, 1992). An investment strategy that tries to capitalize its gains on the value factor is called value investing. Value- EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 32 based portfolios are formed using stocks of the companies that have low fundamental ratios, such as low price-to-book ratio, low price-to earnings ratios or high dividend yields. Stocks that comprise Value portfolio are often called “cheap” stocks. Value investing is a type of contrarian investing that focuses on companies that are undervalued at this moment and is opposed to growth investing, which concentrates on stocks that are expected to increase their value in the future (Damodaran, 2012a). Value investment is based on an assumption of mean reversion, which suggests that prices of undervalued companies should eventually start increasing towards their historical mean. Traditionally, value portfolios were market capitalization weighted.
Fama and French in 1998 studied how value portfolios performed in international markets. They defined and classified value stocks as stock with high book value-to-market ratio, high earnings to price ratio, high cash flow to price ratio, or high dividend yield. The study showed that in 1975-1995 period each of value investing strategies outperformed market strategy at least in 12 of 13 countries. It also outperformed growth portfolio (as opposed to value) by 7% on an annual basis. Using three-factor model, Fama and French also showed that value factor was the strongest explanatory factor that contributed to the higher returns of value investing (Fama & French, 1998).
However, some recent studies disagree with the superiority of value investing.
According to Hsu, returns of traditional value indexes are not consistently higher than the ones of cap-weighted indexes. Hsu shows that S&P 500 value index consistently underperformed S&P 500 index in 3-years, 5-years, 10-years, 20-years, 30-years periods ending in 2013 (Hsu, 2014). Poor performance of traditional value indices was assigned to the fact that assets in value-based portfolios were cap-weighted. As the price of a company‘s stock rises, ceteris paribus, the company becomes less undervalued and at the same time increases its weight in the portfolio, which seems contradictory to the essence of value-based EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 33 portfolio, which is composed of most undervalued companies. Also, traditional value indices do not take into account the differences between price-to-book ratios in different sectors, which reduces the exposure to value factor as some overvalued companies from low price-to- book value sectors are taken into the portfolio and some undervalued companies from high price-to book value sectors are left out (Hsu, 2014).
Smart beta value investing strategies capture bigger part of value premium compared to cap-weighted market or cap-weighted value portfolios. Fundamental-weighting, which is used in some Smart Beta value strategies, removes the link between stock‘s price and its weighting and mitigates the problem cap-weighted portfolios have – increases in weights of stocks that become more expensive in between the rebalances. Also, because fundamentals show size of companies and industries rather than just a market valuation of companies worth, fundamentally-weighted portfolios represent the entire market more accurately than cap-weighted value portfolios. In 1984-2013 period in U.S. fundamentally-weighted value portfolios had a compounded annual growth rate more than 2% higher than cap-weighted market or cap-weighted value indices and also maintained higher average Sharpe ratio – 0.49 of fundamentally-weighted index vs 0.36 of S&P 500 cap-weighted Value index (Hsu, 2014).
The positive effect of fundamental-weighting was empirically proved. In 2005,
Arnott, Hsu and Moore ranked US companies according to their gross fundamentals – book value, five-year average cash flow, five-year average revenue, five-year average of gross sales, five-year average of gross dividends and total employment and composites of these fundamentals – and weighted them according to sizes of these components. The study showed that all types of fundamentally-weighted portfolios had higher returns and Sharpe ratios than cap-weighted indices in the U.S. market in 1962-2004 (Arnott, Hsu, & Moore,
2005). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 34
Growth investing. Growth investing is opposed to value investing, because it uses stocks that are relatively expensive due to their perceived growth perspectives. Few most popular growth strategies are historical growth (investing in companies showed persistent historical growth of the desired fundamental, such as earnings), expected growth (investing in companies are expected to grow in the desired fundamental, such as earnings) or high price- to-earnings ratio (investing in companies with highest price-to-earnings ratio, assuming that earnings of the company will have to rise in the future) (Damodaran, 2012b). Fama’s and
French’s three-factor model (1992) shows that value stocks outperform growth stocks and investing in growth portfolio would underperform value or market-cap portfolios in the long term.
However, some argue that investing in growth stocks has its merits. Damodaran
(2012) argues that simplest version of growth investing is investing in small capitalization stocks, because small companies, obviously, are more likely to growth than large capitalization matured companies. Damodaran proves that small capitalization stocks have significantly larger premiums than market-cap weighted and large capitalization strategies.
However, defining growth stocks as shares of small companies seems inappropriate, since generalization that small cap companies are growth companies is not necessarily true.
White Paper from RidgeWorth Investments (2009) shows that growth stocks outperformed value stocks for extended periods of time in 1980-2009 period in U.S. and that determining which strategy is better depends on the economic situation (RidgeWorth
Investments, 2009). George Clapham (2012) also argued, that there is no way to tell which strategy is better and that it depends at which point of economic cycle the investors are. If the economy is booming, growth strategies will outperform value strategies and vice versa
(Clapham, 2012). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 35
Papers advocating growth investing ignore the fact that value investing is empirically proved to outperform growth investing in the long term and try to prove their case by using inaccurate definitions of growth stocks or by excluding short term periods of time, during which growth strategies managed to outperform value strategies, or by using artificial metrics, such as the percentage of years growth investing outperformed value investing, that exclude margins of returns and risk and essentially do not prove that growth stocks are expected to outperform value stocks even in the short run.
Momentum investing. Momentum strategies are the strategies based on the assumption that investments that performed well in the past are expected to perform well in the future
(Berger, Israel, & Moskowitz, 2009). Momentum investors buy appreciating stocks and sell depreciating ones and periodically readjust so that the portfolio would contain “winners” of the last period. The reasons why Momentum works are usually attributed to different types of market inefficiency.
Jegadeesh and Titman (1993) proved that the stocks that were rising in last 3-12 months should be expected to rise in the following 3-12 moments. As Momentum investors buy stocks that were appreciating and sell the depreciating ones, this finding supports
Momentum investing. They also found that the reason why Momentum strategies work is market inefficiency – in particular, the fact that investors underreact to new available information of the companies (Jegadeesh & Titman, 1993).
Rouwenhourst (1998) found that Momentum strategy works using data from
European companies in 1980-1995. Portfolios composed of the companies that previously appreciated outperformed portfolios composed of depreciating companies in three-month, six-month, nine-month and twelve-month periods in terms of returns and Sharpe ratio
(Rouwenhorst, 1998). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 36
Polychronopoulos (2014) found that Momentum portfolio had higher returns than
Fundamentally-weighted portfolio, Low volatility portfolio and S&P 500 Index in US in
1967-2003 period. However, due to the highest volatility among all strategies, Momentum‘s
Sharpe ratio was low than the one of Low volatility portfolio. Using extended version of
Carhart‘s four-factor model, Polychronopoulos showed that even though Momentum portfolios have low exposure to Value factor, they have significantly higher exposure to growing stocks (Momentum factor), which is the reason why Momentum strategies outperform S&P500 and Fundamentally-weighted strategies (Polychronopoulos, 2014).
On the other hand, De Bondt and Thaler (1985) found that in 1933-1980 portfolios that consisted of previously appreciating stocks were outperformed by portfolios that consisted of previously depreciating stocks in the following 36 months. De Bondt and Thaler say that, oppositely to Jegadeesh and Titman, investors tend to overreact to changes in the directions of prices and that whenever the appreciating stock starts decreasing, the price of the stock drops more than it should in an efficient market (De Bondy & Thaler, 1985).
Griffin, Ji and Martin found that Momentum investing is also a good way to diversify portfolio internationally, because foreign Momentum indices have much lower correlation with U.S. Momentum index than foreign traditional indices have with US traditional indices
(Griffin, Ji, & Martin, 2004).
Methodology
The aim of this thesis is to compare portfolios that would represent above-mentioned passive investment strategies. In order to achieve this goal, formed portfolios have to be accurately compared. The following measures will be used to evaluate and compare portfolios that represent different investment strategies: returns, volatility and Sharpe ratio. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 37
Return. Returns show how much an asset – in this case an individual stock or a portfolio – gained or lost in particular period. Return of an individual stock is determined by this formula:
푃1−푃0 r= , where r is return of a stock, P0 is initial price of the asset and P1 is ending price of 푃0 the asset.
However, to show more accurate returns from investments in stock market, dividend adjusted formula of return should be used:
푃1−푃0+퐷 tr= , where tr is total return of a stock, P0 is initial price of the asset, P1 is ending price 푃0 of the asset and D is dividends.
To calculate return of portfolio, weighted returns of individual stocks are summed: pr=w1tr1+w2tr2+…+wntrn, where pr is portfolio return, wi is the weight of asset i in the portfolio and tri is total return rate of asset i in the portfolio.
There are two ways to calculate mean return of portfolio in period consisting of n years: arithmetic mean return and geometric mean return.
푝푟1+푝푟2+...+푝푟푛 Arithmetic mean return: pr = , where pri is the return of portfolio in year i and n n is the number of years.
푛 Geometric mean return: pri = √(1 + 푝푟1) ∗ (1 + 푝푟2) ∗. . .∗ (1 + 푝푟푛) − 1, where pri is the return of portfolio in year i and n is the number of years.
Arithmetic mean is preferred for estimation of an expected return in the single next period, while geometric mean is preferred when the investor is looking for an actual historical impact of returns on wealth (Bacon, Carino, & Stancil). As this thesis is concerned about the actual impact of historical returns on investor’s wealth, geometric mean will be used as a comparison measure. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 38
Volatility. Most widely used measure of risk of a stock or portfolio is volatility (standard deviation). Volatility shows how prices of assets vary over time– in this case these are the changes in prices of a stock or a portfolio.
To calculate volatility of a particular asset, variance of that asset first has to be calculated. The sample variance formula will be used, since the data that will be analyzed includes only a part of historical time-series data – not entire population will be analyzed:
푛 2 2=∑푖=1(xi−x̅) 2 s , where s is variance of a stock, xi is return of a stock at observation i, x̄ is a n−1 mean of sample of returns, and n is the sample size.
The most widely used measure of risk - volatility or a standard deviation - is a square root of variance: s = √푠2, where s is volatility (standard deviation) and 푠2 is variance.
Calculation of portfolio variance firstly requires returns of portfolio to be found, only then ex-post formula of portfolio variance can be used:
∑푛 (pr −̅pr̅̅̅)2 ps2= 푖=1 i , where ps2 is portfolio variance, 푝푟 is return of portfolio at observation i, 푝푟̅̅̅ n−1 푖 is average of returns and n is the sample size.
Standard deviation or volatility is calculated in the following way: ps=√푝푠2.
Sharpe ratio. Another measure that will be used to evaluate portfolio performance is Sharpe ratio. Sharpe ratio compares risk-adjusted returns between different portfolios. Sharpe ratio is an excess return of free-risk rate to volatility ratio, which shows portfolios excess returns to risk-free rate per unit of risk (volatility). To calculate Sharpe ratio, return and volatility of a portfolio have to be previously calculated.
pri−r푓 Sharpe ratio = , where 푝푟푖 is a return of portfolio i, rf is a risk-free rate (theoretical psi return of investment with no risk) and psi is portfolio volatility. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 39
Higher margin of Sharpe ratio suggests that portfolio had higher excess of the risk- free rate (rate of investment with no risk of financial loss) return per unit of risk (volatility) compared to portfolio with lower Sharpe ratio.
Analysis
Data selection
52 stocks that formed Oslo Bors Benchmark Index (OSEBX) as of 2015-04-01 were analyzed (see appendix 1). This particular index was chosen because of the fact that it eliminates the least liquid shares of Oslo Stock Exchange, but also leaves sufficient number of stocks for different portfolio formation strategies, while other investible indexes, that are considered to represent entire Oslo Stock Exchange, face one of these two problems –
OSEAX (all-shares index) does not eliminate least liquid companies and OBX consists only of 25 shares, which would not have been enough to expose the differences of portfolios formed according to different investment strategies.
The stocks and portfolios consisting of them were analyzed in 2005-2014 period.
Such period was chosen because of the fact that it includes both, the years when the whole market was appreciating and the years when it was depreciating, which represents long-term changes in the market better than shorter periods. Some of the strategies required data from years 2003 and 2004 to form the portfolio on 2005-01-01.
Few of the 52 shares were eliminated from the analysis beforehand. 5 shares: Aker
Solutions (AKSO), Entra (ENTRA), Golden Ocean Group (GOGL), Scatec Solar (SSO),
XXL (XXL) were eliminated because they were listed on Oslo Stock Exchange only in 2014 or 2015 and did not have sufficient data of stock returns to be included in the analysis of
2005-2014 period. Wilh. Wilhelmsen Holding ser. B share (WWIB) was eliminated because of 99% correlation with Wilh. Wilhelmsen Holding ser. A share (WWIA). Finally, Weifa
(WEIFA) and REC Solar (RECSOL) were not included in any of the portfolios that required EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 40 its market capitalization, since the data of these companies’ market capitalization was not found.
Also, some of the companies were included in the analysis only after they were listed on Oslo Stock Exchange. For example, if a stock was listed on 2006-06-05, it could have been included in some portfolios starting from year 2007. However, if the portfolio strategy required full-year data of share price movements, the stock could have been included in the portfolio only starting from 2008. Only 32 of 52 stocks that were in OSEBX index on 2015-
04-01, were also in OSEBX index on 2005-01-01, meaning that year 2005 portfolio at most could have included 32 shares.
The share prices were taken from Yahoo Finance database. Prices that were adjusted for dividends and stock splits were used in evaluation and comparisons of formed portfolios.
In most cases, the same adjusted prices were used in formation of portfolios that were based on share price movements. In some rare occasions, where the price of the stock was missing in a particular day, the price of the previous trading day was used.
Methodology for formation and evaluation of portfolios
All the portfolios were adjusted for trading costs. Trading costs included: initial costs of portfolio formation (buying stocks on 2005-01-01), annual readjustments (each transaction to rebalance portfolio after each year was taxed) and final sellout of the shares (2014-12-31) to realize the gains. As a fee for each transaction, the current online brokerage fee of the largest domestic broker, DNB Bank, was used - 0.05% (DNB).
In 2005-2014 there were on average 251.6 trading days each year. This number of days was used to annualize daily measures of stock returns. The risk-free rate that was used for calculating Sharpe ratio, was an average of daily Norwegian 10-year government bonds yields (3.119%) (Investing.com). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 41
In total, there were 8 portfolios that represent different investment strategies created. 7 of them represent different heuristic Smart Beta investment strategies, the strategies that break the link between the share price and its weight in the portfolio, and 1 of them was a market capitalization strategy, which, together with market capitalization weighted OSEBX index were used as benchmarks for comparison. To evaluate the performance of portfolios in whole 2005-2014 period, geometric annual average of returns and annualized 10-year daily standard deviations were used. 10-year Sharpe ratios were calculated using 10-year geometric average of returns and 10-year volatility. All portfolios were readjusted annually.
OSEBX and Market Capitalization portfolio
Formation of Market Capitalization portfolio. All companies that were listed at the end of the given year and that are now in the OSEBX index were included in the Market
Capitalization (MCap) portfolio. The market capitalizations (see appendix D) were found on each company’s annual reports. In case the company did not state its market capitalization in the annual report explicitly, the always-reported number of shares was multiplied by Yahoo
Finance provided closing share price at the end of a given year (non-adjusted share price).
The stocks in the MCap portfolio were weighted according to market capitalization of respective companies at the end of each year (see appendix E).
Performance of Market Capitalization portfolio. The market capitalization portfolio outperformed OSEBX index in terms of returns. The investment in the MCap portfolio at the beginning of 2005 would have increased investor’s assets by 199% (OSEBX – 143%) until the end of 2014 (see Figure 11). EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 42
350 Market Cap, 299 300 250
200 OSEBX, 243 150 100 50 -
Figure 11. Returns of OSEBX and Market Capitalization portfolios. Source: Yahoo Finance As shown in the table below, geometric average of annual MCap portfolio returns was
11.6%, 2.3 pp higher than average annual OSEBX return. However, this higher return was accompanied with also high standard deviation (volatility). As for return-risk reward, MCap had higher Sharpe ratio, thus, provided better reward-risk return for investors (see Table 8).
Table 8.
Performances of OSEBX and Market Capitalization portfolio.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 Year
Return OSEBX 40.5% 32.4% 11.5% -54.1% 64.8% 18.3% -12.5% 15.4% 23.6% 5.0% 9.3%
MCap 66.4% 38.3% 14.8% -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6%
St. Dev OSEBX 16.8% 24.2% 20.2% 49.2% 33.7% 23.3% 26.3% 18.0% 10.9% 14.9% 26.1%
MCap 38.3% 37.6% 20.4% 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2%
Sharpe OSEBX 2.22 1.21 0.41 -1.16 1.83 0.65 -0.59 0.68 1.88 0.12 0.24
MCap 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 0.29 Source: calculations by author.
The differences between performances of free float weighted OSEBX index and
MCap portfolio that is composed of OSEBX index stocks as of 2015-04-01 could be explained by the fact, that the composition of OSEBX index has been changing since 2005.
Some of the companies that are included in the OSEBX index now, were not included in the
OSEBX in 2005, but are included in MCap portfolio since 2005. Also, some of the EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 43 companies that used to be in the OSEBX index and affected its performance have not been a part of MCap portfolio.. Another reason why performances of these OSEBX and MCap could have differed is that different capitalizations are used to create the portfolios. OSEBX uses free-float capitalization while MCap was created using entire market capitalization of companies. Since MCap portfolio used the same dataset of stocks for its composition as did heuristic Smart Beta strategies and OSEBX index did not, MCap portfolio was used as a main benchmark for comparison with Smart Beta strategies.
Equally-weighted portfolio
Formation of Equally-Weighted portfolio. Equally-Weighted portfolio (EW) was formed by attributing identical weights to each stock in the portfolio. There were 32 stocks in portfolio in 2005 and 46 stocks in 2014, so the weights varied between 3.125% and 2.173%
(see appendix F).
Performance Equally-Weighted portfolio. EW portfolio outperformed MCap portfolio in terms of returns by a large margin. Investors who had invested in EW portfolio in 2005, until now would have profited more than 3 times more than the ones who chose to invest in MCap portfolio (see Figure 12).
800 Equal Weight, 700 735 600 500
400 Market Cap, 300 299 200 100 -
Figure 12. Returns of Equal Weight and Market Capitalization portfolios. Source: Yahoo Finance. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 44
On average, EW portfolio grew by 22.1% a year, 10.5pp more than MCap portfolio.
EW portfolio was also a lot less volatile, as the 10-year standard deviation was 6.1pp lower than the one of MCap portfolio. Consequently, EW portfolio had a much better Sharpe ratio
(see Table 9).
Table 9.
Performances of Equally-Weighted and Market Capitalization portfolios.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 Year Return EW 103.0% 43.8% 6.7% -54.8% 96.7% 24.1% -15.7% 25.4% 83.6% 10.1% 22.1%
MCap 66.4% 38.3% 14.8% -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6%
St. Dev EW 17.9% 22.1% 16.8% 40.7% 26.6% 23.7% 25.4% 17.7% 11.4% 14.5% 23.1%
MCap 38.3% 37.6% 20.4% 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2%
Sharpe EW 5.57 1.84 0.21 -1.42 3.52 0.89 -0.74 1.26 7.08 0.48 0.82
MCap 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 0.29 Source: calculations by author.
EW and MCap portfolios were almost identical in what stocks they consist of in each year (only WEIFA and RECSOL were removed from MCap portfolio), the only difference between them was how the stocks were weighted. EW portfolio was more exposed to small companies, since weights of all companies in it are equal and MCap attributes higher weights to larger companies – for example, the average weight of Statoil, the largest company on
Oslobors, in MCap portfolio was 35.82%. The much better performance of EW portfolio suggests that on average, smaller companies performed better than the large ones in the analyzed period in Norwegian market. It also strongly suggests that breaking the link between share price and its weight in the portfolio leads to better performance of an asset.
Low Volatility and High Volatility portfolios
Formation of Low Volatility and High Volatility portfolios. Low Volatility (LV) portfolio was formed using volatilities of stock returns of previous year. 10 least volatile stocks were EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 45 included in next year‘s portfolio (see appendix G). Oppositely, 10 stocks that were the most volatile were included in High Volatility (HV) portfolio (see appendix H). Each of the stocks in both portfolios were attributed a 10% weight so that they would be equally-weighted.
Performance of Low Volatility and High Volatility portfolios. HV portfolio outperformed both LV and MCap portfolios by a substantial margin. 10 year return of HV portfolio was over 1000%, while 10-year return of LV portfolio was relatively small – 268%. Still, LV portfolio had higher returns than MCap portfolio (see Figure 13).
1200 High Vol, 1121 1000
800
600
400 Low Vol, 368
200 Market Cap, 299
0
Figure 13. Returns of Low Volatility, High Volatility and Market Capitalization portfolios.
Source: Yahoo Finance.
LV portfolio grew on average by 13.9% a year, while HV portfolio grew by almost double this pace - 27.3%. Both of these portfolios grew faster than MCap portfolio, which had average annual growth rate equal to 11.6%.
On the other hand, average volatility of LV portfolio was only 19.3%, compared to 31.3% of
HV portfolio. The main reason for such high growth of HV portfolio is the year 2013, during which the portfolio grew by 275%. In this year, American Shipping Company (AMSC) itself grew by more than 2000%. Given the 10% weight in the portfolio, AMSC raised the returns EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 46 of HV portfolio in 2013 by more than 200%. If AMSC was excluded from the analysis in year 2013, the HV portfolio‘s annual returns would drop to 17.5%. Given that rate of return,
10-year Sharpe ratio of HV would drop from 0.77 to 0.46 – a Sharpe ratio lower than the one of LV strategy (see Table 10).
Table 10.
Performances of Low Volatility, High Volatility and Market Capitalization portfolios.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 Year Return LV 105.3% 27.1% 12.0% -51.6% 45.7% 13.4% -7.6% 15.4% 29.6% 13.9% 13.9% HV 137.1% 44.3% 6.8% -51.6% 105.6% 1.0% -35.5% 7.6% 275.0% 17.2% 27.3%
MCap 66.4% 38.3% 14.8% -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6%
St. Dev LV 15.1% 16.6% 14.5% 35.1% 22.1% 18.3% 23.6% 11.7% 9.3% 12.4% 19.3% HV 30.4% 31.9% 23.8% 41.0% 39.2% 27.4% 31.3% 31.8% 27.3% 23.7% 31.3%
MCap 38.3% 37.6% 20.4% 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2%
Sharpe LV 6.76 1.45 0.61 -1.56 1.93 0.56 -0.45 1.05 2.84 0.87 0.56 HV 4.41 1.29 0.16 -1.33 2.61 -0.08 -.123 0.14 9.95 0.59 0.77
MCap 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 0.29
Source: calculations by author.
As mentioned previously in this thesis, LV portfolios usually underperform other strategies in the years when market is booming and, oppositely, outperform other strategies when the market is in the recession. However, this research does not provide supporting evidence for this claim. In the most recessive year, 2008, LV and HV portfolios both decreased by 51.6%, which was even slightly lower more (1.4pp) than the one of MCap portfolio. There was also no consistent pattern of how returns change in the years when the market as a whole was increasing. On the other hand, LV had higher Sharpe ratio in 6 out of
8 years (negative Sharpe ratios excluded). Even though the 10-year Sharpe ratio computed using average return and volatility is higher for HV strategy, only 2 times HV portfolio had higher positive annual Sharpe ratio. It suggests that even though the analysis showed that HV strategy performed better in the analyzed period, it is hard to imagine another success story as EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 47
American Shipping Company had in year 2013 and that LV performed quite consistently better than HV. Also, both of these strategies outperformed MCap in both returns and Sharpe ratio.
Momentum and Contrarian portfolios
Formation of Momentum and Contrarian portfolios. Momentum portfolio (MOM) was made of the stocks that were appreciating most in the previous year (see appendix I). Said otherwise, MOM portfolio included individual stocks in which investing last year would have been the most profitable. Oppositely, Contrarian portfolio (CON) included only the stocks that dropped most in the previous year (see appendix J). Each of the portfolios consisted of
10 different stocks that were assigned 10% weights.
Performance of Momentum and Contrarian portfolios. Even though it has been trailing for most of the period, since 2013 MOM portfolio has been growing at a much faster pace than CON portfolio. In 10 year period, MOM portfolio had a return close to 1100% and CON portfolio had 854% (see Figure 14).
1400
1200 Momentum, 1193 1000 Contrarian, 954 800
600
400 MCAP, 299 200
0
Figure 14. Returns of Momentum, Contrarian and Market Capitalization portfolios. Source:
Yahoo Finance
MOM portfolio on average grew by 28.0% while CON portfolio showed a little slower growth rate – on average by 25.2% annually. Also, MOM was slightly less volatile EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 48 than CON.. As a result, MOM portfolio‘s Sharpe ratio was 0.90, CON portfolio‘s – 0.78.
Both strategies had twice higher annual returns than the MCap strategy, and were a little less volatile. Sharpe ratios of LV and HV strategies were also higher than the one of MCap strategy (see Table 11).
Table 11.
Performances of Momentum, Contrarian and Market Capitalization portfolios.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 year Return MOM 105.4 58.4% 4.6% -52.4% 71.3% 34.2% -27.0% 9.1% 234.5% 20.1% 28.0% % CON 161.4 42.9% -9.5% -58.5% 151.8% 28.1% -0.5% 37.8% 52.7% 0.7% 25.2% % MCap 66.4% 38.3% 14.8 -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6% % St. Dev MOM 25.4% 32.3% 21.7 46.7% 19.5% 26.8% 28.9% 18.7% 22.2% 23.2% 27.7% % CON 22.0% 19.3% 18.9 42.6% 36.0% 35.6% 31.2% 26.0% 20.1% 19.2% 28.3% % MCap 38.3% 37.6% 20.4 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2% % Sharpe MOM 4.03 1.71 0.07 -1.19 3.50 1.16 -1.04 0.32 10.40 0.73 0.90 CON 7.18 2.06 -0.67 -1.45 4.12 0.70 -0.12 1.34 2.46 -0.12 0.78
MCap 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 0.29
Source: calculations by author.
Carhart‘s four-factor model includes Momentum as a factor for a risk premium, meaning that assets that have been increasing recently, should be expected to be priced higher in the future.
The analysis suggests that this is true, as Momentum portfolio had higher returns. However, once again the results were strongly affected by remarkable growth of American Shipping
Company in 2013. If AMSC in 2013 was excluded from the analysis, Momentum‘s compounded annual growth rate and Sharpe ratio would be only 16.9% and 0.51 respectively, significantly lower than the current metrics and the metrics of contrarian strategy.
Growth portfolio
Formation of Growth portfolio. One of two portfolios based on fundamentals of the companies was Growth portfolio (GRW). This portfolio included all the growing companies, EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 49 the ones that showed growth in operating profit compared to operating profit last year. Since the portfolio only used relative to previous year measures, data collected was not converted to
NOK and the currency used in companies‘ reports was analyzed. Thus, data varied in both currency (NOK, DKK, EUR, USD) and metric number (kilo, mega) (see appendix K). All the companies that had positive and higher than last year‘s operating profits were included in the portfolio. The operating profits that were analyzed were taken from companies‘ income statements since 3rd quarter of 2004 until 3rd quarter of 2013. Financial statements are usually released only few months after the period ends. In this way, investor would not be able to choose which companies to invest to on January 1st if he wanted to use annual or 4th quarter results as a criteria, as they are released in February of the following year or even later. To overcome this problem, the operating profits of the 3rd quarter of the year were used as criteria. As a result of the fact that GRW portfolio included all growing, the number of companies in the portfolio varied from 15 to 25 (see appendix L).
Performance of Growth portfolio. GRW portfolio outperformed MCap portfolio by more than 2.5 times (539% vs 199%). However, until 2013 both portfolios were moving very similarly and GRW portfolio had outperformed MCap portfolio until 2013 only by 2pp
(136% growth versus 134% growth) (see Figure 15).
700 Growth, 639 600 500 400
300 MCAP, 299 200 100 0
Figure 15. Returns of Growth and Market Capitalization portfolios. Source: Yahoo Finance EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 50
The 8.7pp higher annual growth was also accompanied with 4.9pp lower average volatility and much higher Sharpe ratio. Growth portfolio. Most of its growth, once again, arose from AMSC in 2013, when growth portfolio rose by 136%. If AMSC in 2013 was eliminated, the annual growth rate would be 13.8% - only 2.2pp higher than growth MCap portfolio (see Table 12).
Table 12.
Performances of Growth and Market Capitalization portfolios.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 year Return Growth 58.8% 54.0% 0.5% -53.7% 87.1% 25.6% -30.7% 27.4% 136.0% 14.7% 20.3%
MCap 66.4% 38.3% 14.8% -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6%
St. Dev Growth 18.9% 22.0% 17.9% 45.6% 26.8% 23.9% 26.3% 18.2% 13.7% 12.6% 24.3%
MCap 38.3% 37.6% 20.4% 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2%
Sharpe Growth 2.94 2.32 -0.15 -1.24 3.13 0.94 -1.29 1.33 9.72 0.92 0.71
MCap 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 0.29 Source: calculations by author.
Even though GRW portfolio outperformed MCap quite consistently, the margins of outperformance are quite low. Even though GRW portfolio included AMSC in 2013, it had one of the smallest growth rate and Sharpe ratio out of all strategies that were analyzed. If
AMSC was eliminated in 2013, GRW strategy‘s returns would be the smallest out of all portfolios and so would be its Sharpe ratio. This also gives some support to French-Fama‘s three factor model, which states that Growth companies are expected to be priced lower in the future, because the potential growth is perceived by the market and included in the share prices, and thus Growth companies are priced higher.
Value portfolio
Formation of Value portfolio. Value (VAL) portfolio included shares with the lowest Price to Book Value ratio (P/BV) at the end of previous calendar year. The price of the company EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 51 that was used was market capitalization of the company at the end of each calendar year (see appendix M). As for Book Value, which is the same as the Equity section of the balance sheet, the 3rd quarter reports were used because of long delays between the end of the financial quarter and release of its financial report. At the end of calendar year, all the companies were ranked from lowest P/BV ratio to highest and 10 lowest ones were taken into portfolio. Each of the stocks was assigned 10% weight so that the portfolio would be equally- weighted (see appendix N). Most of the companies provided their financial data in NOK, however, few of them reported using other currencies - USD, EUR or DKK in particular. As
VAL portfolio, oppositely to GRW, used absolute and not relative measures, foreign currencies had to be converted into NOK. The exchange rates that were used for conversion were taken from xe.com. Exchange rates of the last day of the reported period were used for each conversion into NOK.
Performance of Value portfolio. Investment in VAL portfolio at the start of 2005-01-01 would have been more profitable than investment in any other analyzed portfolio. The 10- year return of VAL portfolio exceeds 1800%, which is more than 9 times higher than 199% total return of MCap portfolio (see Figure 16).
2500
2000 Value, 1921
1500
1000
500 MCAP, 299 0
Figure 16. Returns of Value and Market Capitalization portfolios. Source: Yahoo Finance EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 52
On average, VAL portfolio grew by 34.3% a year, 22.7pp more than the MCap portfolio. Not only that, VAL portfolio was also slightly less volatile than MCap portfolio, which led to much higher Sharpe ratio – 1.09 of VAL compared to 0.29 of MCap. VAL portfolio managed to capture highest annual growths of individual stocks in the period. For example, at the end of 2004 the company with second lowest P/BV ratio was Norsk Hydro
(NHY), the next year its stock increased by 319%. Similarly, at the end of 2008 Marine
Harvest (MHG) had second lowest P/BV and it increased by 302% in the following year.
Finally, outstanding 2050% increase of American Shipping Company (AMSC) stock in 2013 was also captured by VAL portfolio, as AMSC had the lowest P/BV ratio at the end of 2012
(see Table 13).
Table 13.
Performances of Value and Market Capitalization portfolios.
Year 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 10 year Return Value 151.2% 76.9% -3.7% -62.8% 103.9% 23.7% -3.9% 20.4% 269.7% 11.8% 34.3%
MCap 66.4% 38.3% 14.8% -50.2% 54.2% 14.3% -7.6% 9.6% 23.1% 3.7% 11.6%
St. Dev Value 26.5% 27.5% 17.6% 41.8% 39.1% 25.1% 30.6% 27.5% 24.6% 13.9% 28.6%
MCap 38.3% 37.6% 20.4% 48.9% 33.0% 21.7% 25.7% 16.9% 10.4% 15.6% 29.2%
Sharpe Value 5.59 2.68 -0.39 -1.58 2.58 0.82 -0.23 0.63 10.84 0.62 1.09
MCap 0.29 1.65 0.93 0.57 -1.09 1.55 0.51 -0.42 0.38 1.91 0.04 Source: calculations by author.
VAL portfolio not only outperformed MCap portfolio, but also had 14pp higher average growth and higher Sharpe ratio than its opposing portfolio – GRW portfolio. This finding may also suggest that Value (cheap) companies that in this case were determined by low P/BV ratios could be expected to outperform growth (expensive) companies. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 53
Comparison of performances of all portfolios
Returns. VAL portfolio had the highest average annual growth rate, equal to 34.3%. VAL portfolio‘s average returns were more than 6pp higher than the ones of the second most profitable strategy – MOM (28.0%). Average growth of all 9 compared strategies was 21.3% and only 2 Smart Beta strategies – GRW and LV – grew slower than that. Average growth of
Smart Beta strategies (VAL, MOM, HV, CON, EW, GRW, and LV) was 24.4%, 14pp higher than the average (10.4%) of traditional passive strategies (MCap, OSEBX) (see Table 14).
Table 14.
Returns of all portfolios.
Strategy Compounded annual growth rate Value 34.3% Momentum 28.0% High Volatility 27.3% Contrarian 25.2% Equal Weight 22.1% Growth 20.3% Low Volatility 13.9% Market Capitalization 11.6 % OSEBX Index 9.3% Average 21.3% Source: calculations by author.
Volatility. As should be expected, the portfolio that had lowest average volatility was LV portfolio. Its volatility was 3.8pp lower than the one of EW portfolio, which had second lowest volatility (23.1%). Also as expected, the portfolio with highest average volatility was
HV portfolio, the one that consisted of individually most volatile shares. Moreover, it seems important to point out that all strategies (except LV, which was created specifically to lower volatility) that used equal-weighting (all except MCap and OSEBX) and that consisted of predetermined number of shares (10) had higher annual volatilities than the strategies that did EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 54 not have a predetermined number of shares in their portfolios (EW, GRW). It suggests that portfolios that had low number of shares in them (MOM, VAL, CON, HV) had higher volatilities than the strategies that had more shares in portfolios (EW portfolio consisted of
32-42 shares, GRW of 15-25 shares). It may imply (but not necessarily) that predetermined number of shares in portfolios (10) could have been too low and that increasing it could result to better diversification of risk and lower volatility of portfolios with predetermined number of shares (see Table 15).
Table 15
Volatilities of all portfolios.
Strategy Average Volatility Low Volatility 19.3% Equal Weight 23.1% Growth 24.3% OSEBX 26.1% Momentum 27.7% Contrarian 28.3% Value 28.6% Market Capitalization 29.2% High Volatility 31.3% Average 26.4% Source: calculations by author.
Sharpe Ratio. VAL portfolio had the highest Sharpe ratio, 1.09, which was 0.19 higher than the Sharpe of MOM portfolio, ranked in 2nd place. All Smart Beta strategies had higher
Sharpe ratios than MCap and OSEBX portfolios had. Also, only LV portfolio‘s Sharpe ratio was below average of all Sharpe ratios. It is important to point out that rankings of portfolios according to Sharpe ratio are very similar to rankings according to returns. The only difference is that HV strategy had 3rd highest returns, EW strategy had 5th highest returns and, oppositely EW had 3rd highest Sharpe ratio and HV had 5th highest. It is impossible to find such pattern when comparing Volatilities and Sharpe ratios. This suggests that differences EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 55 between returns were more influential than differences between volatilities when determining
Sharpe ratio rankings (see Table 16).
Table 16
Sharpe ratios of all portfolios.
Strategy Sharpe Ratio Value 1.09 Momentum 0.90 Equal Weight 0.82 Contrarian 0.78 High Volatility 0.77 Growth 0.71 Low Volatility 0.56 Market Capitalization 0.29 OSEBX 0.24 Average 0.68 Source: calculations by author.
Implications on Smart Beta Investing versus Traditional Passive Investing
There were 7 strategies representing Smart Beta investing (VAL, MOM, EW, CON,
HV, GRW, and LV) and 2 strategies that represented Traditional Passive investing (MCap,
OSEBX). All the 7 Smart Beta strategies individually had higher average annual returns than any of two Traditional Passive strategies. As mentioned before, on average Smart Beta outperformed Traditional Passive strategies by 14pp (24.4% versus 10.4%). Also, Smart Beta strategies on average had slightly lower volatility than Traditional Passive strategies
(26.1%% versus 27.6%). Consequently, Sharpe ratio of Smart beta strategies (using average return and volatility of all strategies) was significantly higher than the one of Traditional
Passive strategies (0.80 versus 0.26). Also, each of 7 Smart Beta strategies individually had better Sharpe ratio than any of the 2 Traditional Passive strategies. As all Smart Beta strategies performed better in terms of returns and Sharpe ratio than Traditional Passive EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 56 strategies, it seems safe to confirm that in 2005-2014 period in Oslo Bors Stock Exchange it would have been more profitable to invest using Smart Beta strategies rather than Traditional
Passive strategies. It also suggests, that widely discussed relationship between share price and its weight in portfolio in Traditional Passive strategies, was found to have negative impact on returns and Sharpe ratio in Oslo Bors stock exchange in the analyzed period.
Implications on Carhart‘s four-factor asset pricing model
Carhart in his four-factor asset pricing model stated that the price of an asset is dependent on these four factors:
Beta. The larger the stock‘s beta, the higher its expected price is.
Size. The smaller the company, the higher its expected price is.
Value. The cheaper the company, the higher its expected price is.
Momentum. The more stock has been appreciating in the recent period, the higher its
expected price is.
In some ways this analysis provides support for Carhart‘s four-factor model:
Beta. High Volatility portfolio outperformed Low Volatility portfolio by a large
margin. If we assume that Volatility and Beta can be used interchangeably because of
their high correlation, as it is done many papers that were cited previously, it would
be possible to say that higher Betas were rewarded with higher returns (higher
Volatilities were rewarded with higher returns)
Size. Equal Weight and Market Capitalization portfolios were almost identical in the
companies they included in all 10 years and the only difference between them was the
weights of stocks in the portfolio. Equal Weight portfolio strongly outperformed
Market Capitalization portfolio, which suggests that on average smaller companies
performed better than larger companies, because Equal Weight portfolio was much
more exposed to small companies than the Market Capitalization portfolio. This EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 57
finding supports the positive influence of Size factor, which states that small
companies are expected to have higher returns than large companies, on expected
returns.
Value. Value (cheap) portfolio had higher returns (14pp) than Growth (expensive)
portfolio which implies that cheap stocks should be expected to be priced higher in
the future.
Momentum. Momentum portfolio had slightly higher returns than Contrarian
portfolio (opposite to Momentum), which implies that appreciating stocks are more
likely to be priced higher than the depreciating stocks.
As it is seen from this analysis, all 4 portfolios that were formed using the criteria, that,
according to Carhart, should increase returns of the portfolio (HV – High Beta, EW –
Small, VAL - Cheap, MOM - Appreciating), managed to outperform the portfolios that
could be treated as opposites of the above-mentioned portfolios (LV – Low Beta, MCap –
Large, GRW – Expensive, CON – depreciating). It gives some support that Carhart‘s four
factors are actually influencing the asset prices positively. However, regressive analysis
of Carhart‘s four factors on stock prices in Oslobors in 2005-2014 period should be
performed to confirm or reject this hypothesis.
Recommendation
Assuming that returns in 2015 will be the same as historical averages of last 10 years, investors would be recommended to invest in Value portfolio, as it performed best (in both returns and Sharpe ratio) in the 2005-2014 period. The Value portfolio for year 2015 would consist of the following 10 stocks, each of them having 10% weight in the portfolio:
Wilh. Wilhelmsen Holding ser. A (WWI)
Storebrand (STB)
Fred. Olsen Energy (FOE) EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 58
Subsea 7 (SUBC)
Seadrill (SDRL)
Petroleum Geo-Services (PGS)
Stolt-Nielsen (SNI)
Wilh. Wilhelmsen (WWASA)
Aker (AKER)
Olav Thon Eiendomsselskap (OLT)
As mentioned previously, in 10-year period Value portfolio grew by 34.3% annually, had
28.6% volatility and 1.09 Sharpe ratio.
Conclusions
1. Norway‘s political and economic indicators showed that Norway is among world‘s
leaders in political stability and economic strength, suggesting that Norway‘s capital
market could be treated as a relatively stable investment destination. Oslo Stock
Exchange was found to be undervalued, as Norway‘s market capitalization to GDP
ratio was found to be one of the lowest among economically developed countries.
Oslo Stock Exchange was also found to outperform major world‘s stock markets, as
its most commonly used share index (OSEBX) outperformed world‘s most commonly
used indices (S&P500, Nikkei225, FTSE100) in 2005-2014 period. Above-mentioned
factors prove Oslo Stock Exchange‘s attractiveness for investments. On the other
hand, high correlation between Oslo Stock Exchange‘s largest Energy sector and
Brent oil price were found, proving that investments in Oslo Stock Exchange could be
highly exposed to oil price risk. Also, for foreign investors, high exchange rate risk
was found, because NOK/USD exchange rate has been steadily decreasing since the
beginning of 2013. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 59
2. Indices that represented different Smart Beta investment strategies in US market were
analyzed during 2005-2014 period. 5 out of 6 Smart Beta indices outperformed
traditional passive free-float capitalization weighted index. Average annual growth of
these 5 strategies was found to be 1.9pp to 3.6pp higher than the one of free-float
capitalization weighted index. Out of 6 strategies, only High Beta index
underperformed free-float weighted index by 5.6pp in a given period. Literature
analysis gave supporting evidence that Smart Beta strategies outperform market-
capitalization, or free-float capitalization weighted strategies consistently. Various
Smart Beta strategies (fundamentally-weighted, equally-weighted, low volatility, low
beta, value, growth, momentum) were empirically proved to outperform market
capitalization weighted strategy in various world‘s markets and time frames. Only few
exceptions were found when Smart Beta strategies underperformed market
capitalization weighted strategy. All of these exceptions were explained by
inconsistencies when forming portfolios or by the fact that analysis was performed in
small capitalization markets. Smart Beta‘s outperformance was explained by higher
exposure to four Carhart‘s asset pricing factors: market, size, value, momentum.
3. 52 companies that were a part of Oslo Stock Exchange Benchmark Index (OSEBX)
were used for the formation of portfolios. Using these stocks, 8 portfolios that
represent different passive investment strategies were created. All portfolios were
annually readjusted. 7 of 8 portfolios represented Smart Beta investment strategies
and 1 represented traditional market capitalization weighted strategy. Methodology
for the formation of different portfolios was found in various scientific papers. Market
Capitalization weighted portfolio consisted of all analyzed shares that were weighted
according to market capitalizations of companies. Equally-weighted portfolio
consisted of all of analyzed stocks that were assigned identical weights. Low EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 60
Volatility portfolio was formed using 10 equally-weighted shares that were least
volatile in the previous calendar year. Momentum portfolio was formed using 10
equally-weighted shares that appreciated most in previous calendar year. Shares of all
companies, that had higher positive operating profit compared to previous year, were
included in Growth portfolio and were assigned equal weights. Value portfolio was
created using stocks of 10 companies that had lowest price-to-book value ratios. Also,
two portfolios that represented opposite of Low volatility and Momentum strategies
were formed. High-Volatility (opposite of Low volatility) portfolio was formed using
10 shares that were most volatile in the previous calendar year. Contrarian (opposite
to Momentum) was formed using 10 shares that were depreciating most in the
previous calendar year.
4. All Smart Beta portfolios were found to outperform Market Capitalization weighted
portfolio and Oslo Stock Exchange Benchmark Index in both returns and Sharpe ratio
using tax-adjusted returns. Different Smart Beta portfolios had 2.3pp to 22.7pp higher
average annual returns than Market Capitalization weighted portfolio, which itself
was found to outperform OSEBX index by 2.3pp on annual basis. Value strategy was
found to be the most effective, as Value portfolio had highest annual returns (34.3%)
and highest Sharpe ratio (1.09), both significantly higher than the metrics of
Momentum portfolio, which had second highest returns (28.0%) and second highest
Sharpe ratio (0.90). As could be expected, Low volatility portfolio was the least
volatile (19.3%) and High-Volatility portfolio was most volatile (31.3%) in the
analyzed period. Interestingly, High-Volatility portfolio outperformed OSEBX by
high margins of returns (18.0 pp) and Sharpe ratio (0.53), while in US market S&P
High Beta index (similar to the formed High-Volatility portfolio for Norwegian
market) performed worse than S&P 500 index. Overall, Smart Beta strategies were EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 61
found to consistently outperform Market Capitalization weighted strategy in
Norwegian market, suggesting that break the link between share price and its weight
in the portfolio leads to higher returns. Also, under certain assumptions, the analysis
showed that portfolios, that as a formation criteria used one of four Carhart‘s factors
(high beta, small in size, relatively cheap, appreciating) outperformed opposites of
these portfolios (low beta, large in size, relatively expensive, depreciating).
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 62
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EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 68
Appendices
Appendix A. List of analyzed companies Company Ticker Akastor AKA Aker AKER Aker Solutions AKSO American Shipping Company AMSC Atea ATEA Bakkafrost BAKKA Bionor Pharma BIONOR Biotec Pharmacon BIOTEC BW LPG BWLPG Det norske oljeselskap DETNOR DNB DNB DNO DNO Ekornes EKO Entra ENTRA Fred. Olsen Energy FOE Gjensidige Forsikring GJF Golden Ocean Group GOGL Kongsberg Automotive KOA Kongsberg Gruppen KOG Marine Harvest MHG Nordic Semiconductor NOD Norsk Hydro NHY Norwegian Air Shuttle NAS Norwegian Property NPRO Olav Thon Eiendomsselskap OLT Opera Software OPERA Orkla ORK Petroleum Geo-Services PGS Prosafe PRS REC Silicon REC REC Solar RECSOL Royal Caribbean Cruises RCL SalMar SALM Scatec Solar SSO Schibsted SCH Seadrill SDRL Statoil STL Stolt-Nielsen SNI Storebrand STB Subsea 7 SUBC Telenor TEL TGS-NOPEC Geophysical Company TGS Tomra Systems TOM Veidekke VEI Weifa WEIFA Wilh. Wilhelmsen WWASA Wilh. Wilhelmsen Holding ser. A WWI Wilh. Wilhelmsen Holding ser. B WWIB XXL XXL Yara International YAR Source: Oslobors.no EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 69
Appendix B. Annual returns of the analyzed companies ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB 2004 55.60% 45.45% -45.50% -46.26% 22.94% 34.57% 2005 21.77% 53.57% 139.78% 184.89% -29.34% 77.25% 21.02% 2006 45.49% 30.82% 83.56% 101.50% 31.25% 55.08% -33.78% 103.73% 22.49% 2007 -3.10% 20.00% -7.15% -15.46% 19.53% 17.03% 15.82% -29.05% -6.22% 2008 -69.04% -32.22% -68.85% -56.85% -73.31% -59.73% -42.29% -64.76% -67.46% 2009 104.69% 85.70% 100.43% 22.68% -80.59% 216.90% 9.92% -52.52% 144.73% 2010 18.12% -74.06% 43.24% -10.22% -23.11% 18.68% 20.83% 49.70% -20.15% 32.97% 2011 -51.37% 18.95% -22.24% 14.06% -81.13% 5.43% -19.78% -17.32% -37.21% 224.69% -25.51% 2012 25.19% 31.27% 103.95% 42.55% 88.12% 7.34% 72.61% 63.69% 7.16% -8.08% 22.83% 2013 39.63% 25.23% 10.39% 11.03% 2053.16% 9.32% 61.53% 4.28% 74.66% -19.16% 57.64% 2014 -1.11% 18.47% -13.88% -20.72% -8.34% 34.66% 84.71% -13.43% 73.53% -7.37% -29.07% 4.73%
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT 2004 1.86% 7.32% 207.02% -6.60% -35.31% 135.93% -56.59% 37.64% 2005 784.78% -6.58% 172.25% 25.29% 13.57% 2.70% 319.06% 480.88% 17.46% 2006 -23.65% 19.16% 16.80% 20.00% 40.02% 172.73% -32.85% 123.44% 20.00% 78.95% 2007 -12.35% -33.22% 1.88% -29.65% 93.69% -38.76% -52.17% 33.98% 81.72% 2.31% -4.72% 2008 -55.85% -29.84% -38.15% -93.32% -3.24% -69.91% -20.06% -63.46% -78.17% -90.86% -40.73% 2009 13.93% 86.02% 25.71% 107.46% 15.93% 302.85% 296.76% 75.23% 211.65% 122.26% 60.39% 2010 78.90% 38.69% 20.31% -12.77% 52.64% 47.40% 153.06% -4.21% 2.17% -23.40% 27.87% 2011 -17.35% -34.40% -20.72% 27.15% -70.35% -11.94% -57.28% -39.92% -35.53% -52.78% -27.15% -2.78% 2012 21.38% 2.66% 25.91% 23.35% -3.27% 13.54% 96.00% 0.69% 1.21% 154.69% 13.35% 27.59% 2013 159.94% -5.69% 6.08% 56.31% 290.54% 5.96% 44.42% 91.03% -0.19% 30.79% -12.62% 38.04% 2014 -33.97% 22.72% -70.82% 17.76% -0.35% -0.58% 43.47% 70.40% 60.53% 46.76% 38.93% 33.42%
OPERA ORK PGS PRS REC RECSOL RCL SALM SCH SDRL STL SNI 2004 167.17% 45.58% 22.39% 43.44% 50.22% 29.00% 146.79% 2005 152.72% 161.29% 63.36% 70.53% -9.67% 15.52% 67.94% 24.73% 2006 -34.10% 186.88% 104.88% 55.24% -14.24% 10.40% 88.80% 8.75% -13.44% 2007 -11.00% 60.24% 7.68% 6.79% 142.11% -11.58% 5.61% 25.89% 6.55% -14.64% 2008 38.68% -55.31% -82.47% -72.49% -76.63% -59.71% -39.34% -64.76% -58.00% -31.23% -55.88% 2009 12.88% 31.15% 140.50% 44.84% -30.61% 60.23% 78.66% 56.75% 169.61% 31.33% 14.52% 2010 44.93% 2.88% 36.61% 31.41% -52.59% 87.45% 39.17% 33.19% 35.00% -1.12% 78.32% 2011 -1.14% -17.90% -28.97% -6.39% -81.85% -45.93% -47.96% -12.86% 1.19% 14.36% -13.83% 2012 7.70% 14.42% 44.85% 20.50% -65.92% 19.09% 56.28% 56.81% 2.75% -6.42% -1.82% 2013 163.85% 2.63% -23.62% 5.55% 128.04% 56.64% 65.56% 72.77% 26.31% 11.18% 46.27% 2014 14.89% 13.71% -38.82% -46.80% -27.05% 21.43% 115.70% 87.60% 19.35% -65.55% -6.06% -24.59%
STB SUBC TEL TGS TOM VEI WEIFA WWASA WWI YAR 2004 35.10% 140.49% 29.22% -16.96% 112.85% -28.96% 2005 0.44% 91.90% 21.08% 103.21% 41.24% 131.54% 61.36% 22.82% 2006 36.15% 53.35% 81.08% 65.11% -11.16% 44.81% -6.12% 45.02% 2007 -28.50% 1.19% 13.07% -42.17% -10.48% 25.18% -36.66% -10.74% 77.42% 2008 -69.55% -67.78% -63.20% -53.55% -37.93% -56.05% -71.57% -54.26% -40.85% 2009 136.10% 135.85% 75.08% 202.44% 19.79% 142.71% 563.31% 31.21% 81.35% 2010 10.36% 56.30% 19.58% 31.84% 42.02% 9.68% -25.16% 43.20% 29.98% 2011 -28.36% -23.24% 7.13% 2.81% 3.67% -20.37% 19.28% -29.04% -20.26% -27.17% 2012 -10.60% 17.82% 19.58% 38.80% 26.65% 20.75% -83.95% 75.52% 15.18% 15.03% 2013 41.31% -11.63% 34.94% -7.78% 14.82% 17.18% -56.72% 26.10% 32.39% 0.05% 2014 -22.96% -34.07% 9.99% 5.11% 4.22% 58.52% 29.31% -17.38% -14.46% 32.65% Source: Created by author, using Yahoo Finance data EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 70
Appendix C. Annual volatilities of the analyzed companies ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB 2004 74.38% 38.19% 123.60% 69.31% 112.95% 20.32% 2005 35.39% 37.41% 37.05% 43.77% 52.07% 117.57% 18.44% 2006 39.46% 29.79% 45.35% 43.62% 48.84% 59.10% 87.77% 56.68% 24.42% 2007 30.80% 22.46% 37.37% 26.05% 42.74% 46.05% 73.48% 46.26% 21.72% 2008 66.42% 31.66% 89.82% 55.63% 120.93% 55.72% 73.75% 43.22% 69.78% 2009 45.23% 29.98% 66.13% 44.27% 87.64% 42.06% 58.59% 112.01% 70.35% 2010 38.84% 82.66% 41.96% 30.16% 103.15% 29.59% 239.00% 69.55% 43.41% 30.82% 2011 41.14% 29.84% 50.28% 38.44% 146.10% 33.24% 52.31% 59.49% 52.36% 78.73% 39.53% 2012 31.83% 22.88% 45.97% 24.73% 141.38% 28.03% 37.96% 68.63% 51.78% 36.21% 30.13% 2013 19.58% 20.40% 35.46% 20.99% 165.40% 20.99% 24.29% 58.00% 52.17% 25.26% 24.40% 2014 22.08% 19.52% 35.01% 25.63% 38.98% 21.79% 28.32% 72.88% 79.71% 36.19% 42.36% 21.21%
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT 2004 25.71% 24.29% 43.94% 28.98% 90.80% 82.98% 60.07% 33.97% 2005 66.59% 26.47% 40.82% 27.33% 64.94% 53.85% 177.61% 55.37% 37.96% 2006 56.80% 31.47% 36.31% 45.46% 29.88% 62.76% 38.26% 69.80% 38.63% 32.35% 2007 42.63% 29.96% 27.11% 46.53% 26.18% 45.94% 48.73% 30.08% 31.29% 28.43% 22.39% 2008 101.52% 59.29% 53.90% 118.88% 40.73% 65.88% 107.31% 70.32% 62.68% 70.46% 55.31% 2009 85.24% 56.06% 38.49% 74.89% 40.34% 68.58% 67.67% 55.24% 62.09% 81.17% 49.31% 2010 49.48% 34.48% 31.91% 54.14% 29.03% 38.24% 61.71% 34.26% 47.56% 41.36% 32.36% 2011 57.12% 43.40% 37.86% 24.60% 59.25% 38.47% 48.83% 56.02% 37.94% 46.75% 33.77% 23.27% 2012 44.05% 39.70% 28.67% 18.15% 55.24% 30.48% 54.40% 40.98% 30.32% 41.25% 26.12% 22.47% 2013 31.03% 30.08% 22.37% 18.67% 39.07% 23.88% 21.79% 33.55% 17.92% 44.07% 25.55% 22.81% 2014 54.95% 25.71% 41.59% 17.81% 39.95% 22.26% 26.99% 34.77% 22.41% 39.49% 25.73% 28.93%
OPERA ORK PGS PRS REC RECSOL RCL SALM SCH SDRL STL SNI 2004 68.26% 37.41% 23.86% 26.86% 27.88% 24.47% 39.47% 2005 50.23% 77.65% 42.58% 32.41% 24.64% 30.34% 114.04% 31.11% 2006 63.21% 116.26% 49.92% 38.91% 26.36% 30.66% 52.34% 84.73% 35.36% 2007 45.43% 29.46% 39.06% 26.77% 45.88% 28.43% 33.65% 34.61% 28.47% 38.91% 2008 64.73% 61.16% 86.24% 76.42% 107.16% 81.97% 63.45% 60.12% 84.13% 53.72% 56.67% 2009 61.57% 38.24% 62.56% 45.72% 72.39% 75.65% 55.29% 65.97% 53.01% 34.80% 45.93% 2010 45.72% 24.60% 46.25% 33.40% 59.37% 39.97% 47.66% 39.25% 35.04% 22.68% 34.29% 2011 44.43% 29.39% 52.35% 34.52% 79.57% 45.21% 57.01% 37.74% 30.14% 27.90% 40.67% 2012 40.90% 17.21% 38.37% 28.82% 81.17% 33.21% 40.31% 25.88% 20.85% 18.75% 26.69% 2013 31.27% 19.52% 28.40% 22.72% 84.98% 23.97% 25.90% 23.46% 18.37% 13.64% 21.64% 2014 39.04% 19.11% 39.29% 38.66% 64.22% 49.19% 29.23% 28.18% 43.12% 39.31% 23.45% 26.17%
STB SUBC TEL TGS TOM VEI WEIFA WWASA WWI YAR 2004 25.04% 51.06% 22.97% 46.19% 28.06% 60.06% 2005 30.29% 39.40% 28.16% 44.62% 43.23% 29.70% 31.47% 29.89% 2006 31.96% 45.30% 28.80% 45.18% 36.15% 35.36% 24.55% 31.94% 2007 39.19% 36.04% 28.99% 42.54% 34.60% 45.66% 43.68% 24.02% 34.48% 2008 89.26% 75.50% 56.03% 85.66% 48.90% 58.52% 59.93% 46.24% 79.89% 2009 68.15% 58.45% 42.82% 53.01% 43.13% 35.94% 156.70% 38.49% 52.32% 2010 39.91% 40.82% 26.16% 44.69% 32.62% 28.06% 49.61% 28.31% 39.39% 2011 52.30% 38.08% 24.32% 52.08% 35.76% 26.48% 53.44% 44.83% 41.47% 40.48% 2012 46.68% 32.65% 20.30% 32.77% 28.90% 22.61% 101.59% 34.51% 33.84% 27.41% 2013 29.37% 25.90% 16.06% 29.75% 28.51% 17.57% 125.64% 25.11% 25.28% 20.08% 2014 25.72% 31.73% 21.05% 37.05% 27.59% 23.63% 49.16% 28.56% 21.72% 22.62% Source: Created by author, using Yahoo Finance data EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 71
Appendix D. Market capitalizations of companies (NOK million) ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB 2005 1943 530 2122 4772 139 74271 2006 2370 771 5464 15164 233 452 90736 2007 3751 1184 10256 29019 154 903 112348 2008 4252 1549 9407 24533 190 705 105366 2009 1408 1859 2900 9914 925 1586 114 248 34167 2010 2995 1269 4952 11687 179 4776 125 118 83624 2011 3345 2845 6515 10131 138 5609 2418 315 177 2528 133399 2012 1541 3556 4724 11216 27 5991 1788 266 145 9487 95366 2013 1844 4578 8472 15291 52 6075 2956 511 167 9783 114667 2014 2387 5578 8134 16055 1132 6165 4639 552 402 7870 7909 176725
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT 2005 1544 4551 5023 2970 414 36934 248 4348 2006 5522 4576 14702 3720 2891 2164 53659 1451 5033 2007 10406 5266 18367 2526 5250 19794 1638 74873 1829 8978 2008 9121 3517 19695 1778 10170 12141 791 89222 3526 7015 8556 2009 4027 2467 12273 1858 9840 3653 620 31964 770 1226 5070 2010 4588 4419 14807 2262 10590 15125 1809 55858 3934 6119 8196 2011 8207 5892 17195 1973 15960 22057 4185 69118 4062 5160 9687 2012 6768 3609 13407 34650 590 13920 9261 2413 56479 1927 3670 8388 2013 9532 3406 16128 39700 602 14940 17809 2370 57619 5060 4662 9474 2014 24763 3029 16468 57850 2351 15300 30307 4527 55945 6618 3987 11390
OPERA ORK PGS PRS REC RCL SALM SCH SDRL STL SNI STB 2005 57648 2800 6264 78232 11911 205784 11032 16274 2006 2233 41099 4660 10400 71236 13919 335690 14326 15059 2007 1491 73027 25920 21614 55810 60732 15443 37176 533898 11326 19811 2008 1508 108543 20700 16739 59640 53698 4532 16308 52050 540101 9740 25510 2009 2140 46260 4365 5760 18816 19706 2678 5748 21944 362880 4218 7536 2010 2436 57845 15091 7586 11929 31734 4738 14051 58978 461716 4787 17798 2011 3503 57816 18550 9938 15210 59700 6335 17849 80694 441946 8501 19639 2012 3515 45552 16117 10669 2810 32731 3090 15924 91720 489457 7021 13992 2013 3829 49071 21080 11987 2885 40380 5065 25435 95246 442235 6661 12067 2014 10216 47950 15954 10711 6942 63347 8384 43038 119220 467561 9686 17052
SUBC TEL TGS TOM VEI WWASA WWI YAR 2005 96213 3927 5944 2889 7525 25435 2006 113410 8284 8621 5506 11927 25253 2007 197766 13726 7594 6683 11385 35119 2008 218198 7734 6398 7054 9995 60437 2009 77335 3691 3729 2982 4418 35514 2010 134367 10806 4241 6659 5673 63980 2011 156645 13608 5780 7020 9350 8045 83022 2012 35940 158393 13704 5936 5174 6292 6341 59816 2013 44100 175868 18773 7438 5883 10934 7309 69000 2014 38655 220548 16646 8363 6525 12485 9374 68009 Source: Created by author, using Yahoo Finance data and financial statements of the analyzed companies EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 72
Appendix E. Weights in market capitalization portfolio ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB 2005 0.29% 0.08% 0.32% 0.71% 0.02% 11.06% 2006 0.27% 0.09% 0.61% 1.70% 0.03% 0.05% 10.19% 2007 0.26% 0.08% 0.71% 2.02% 0.01% 0.06% 7.83% 2008 0.28% 0.10% 0.61% 1.60% 0.01% 0.05% 6.88% 2009 0.19% 0.25% 0.38% 1.31% 0.12% 0.21% 0.02% 0.03% 4.52% 2010 0.26% 0.11% 0.43% 1.01% 0.02% 0.41% 0.01% 0.01% 7.26% 2011 0.25% 0.21% 0.48% 0.75% 0.01% 0.41% 0.18% 0.02% 0.01% 0.19% 9.85% 2012 0.12% 0.27% 0.36% 0.85% 0.46% 0.14% 0.02% 0.01% 0.72% 7.26% 2013 0.13% 0.33% 0.60% 1.09% 0.43% 0.21% 0.04% 0.01% 0.70% 8.19% 2014 0.14% 0.33% 0.49% 0.96% 0.07% 0.37% 0.28% 0.03% 0.02% 0.47% 0.47% 10.58%
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT 2005 0.23% 0.68% 0.75% 0.44% 0.06% 5.50% 0.04% 0.65% 2006 0.62% 0.51% 1.65% 0.42% 0.32% 0.24% 6.03% 0.16% 0.57% 2007 0.73% 0.37% 1.28% 0.18% 0.37% 1.38% 0.11% 5.22% 0.13% 0.63% 2008 0.60% 0.23% 1.29% 0.12% 0.66% 0.79% 0.05% 5.83% 0.23% 0.46% 0.56% 2009 0.53% 0.33% 1.62% 0.25% 1.30% 0.48% 0.08% 4.22% 0.10% 0.16% 0.67% 2010 0.40% 0.38% 1.28% 0.20% 0.92% 1.31% 0.16% 4.84% 0.34% 0.53% 0.71% 2011 0.61% 0.43% 1.27% 0.15% 1.18% 1.63% 0.31% 5.10% 0.30% 0.38% 0.71% 2012 0.51% 0.27% 1.02% 2.64% 0.04% 1.06% 0.70% 0.18% 4.30% 0.15% 0.28% 0.64% 2013 0.68% 0.24% 1.15% 2.83% 0.04% 1.07% 1.27% 0.17% 4.11% 0.36% 0.33% 0.68% 2014 1.48% 0.18% 0.99% 3.46% 0.14% 0.92% 1.81% 0.27% 3.35% 0.40% 0.24% 0.68%
OPERA ORK PGS PRS REC RCL SALM SCH SDRL STL SNI STB 2005 8.58% 0.42% 0.93% 11.65% 1.77% 30.64% 1.64% 2.42% 2006 0.25% 4.62% 0.52% 1.17% 8.00% 1.56% 37.70% 1.61% 1.69% 2007 0.10% 5.09% 1.81% 1.51% 3.89% 4.23% 1.08% 2.59% 37.20% 0.79% 1.38% 2008 0.10% 7.09% 1.35% 1.09% 3.90% 3.51% 0.30% 1.07% 3.40% 35.29% 0.64% 1.67% 2009 0.28% 6.11% 0.58% 0.76% 2.49% 2.60% 0.35% 0.76% 2.90% 47.96% 0.56% 1.00% 2010 0.21% 5.02% 1.31% 0.66% 1.03% 2.75% 0.41% 1.22% 5.11% 40.04% 0.42% 1.54% 2011 0.26% 4.27% 1.37% 0.73% 1.12% 4.41% 0.47% 1.32% 5.95% 32.61% 0.63% 1.45% 2012 0.27% 3.46% 1.23% 0.81% 0.21% 2.49% 0.24% 1.21% 6.98% 37.23% 0.53% 1.06% 2013 0.27% 3.50% 1.50% 0.86% 0.21% 2.88% 0.36% 1.82% 6.80% 31.56% 0.48% 0.86% 2014 0.61% 2.87% 0.95% 0.64% 0.42% 3.79% 0.50% 2.58% 7.14% 27.99% 0.58% 1.02%
SUBC TEL TGS TOM VEI WWASA WWI YAR 2005 14.32% 0.58% 0.88% 0.43% 1.12% 3.79% 2006 12.74% 0.93% 0.97% 0.62% 1.34% 2.84% 2007 13.78% 0.96% 0.53% 0.47% 0.79% 2.45% 2008 14.26% 0.51% 0.42% 0.46% 0.65% 3.95% 2009 10.22% 0.49% 0.49% 0.39% 0.58% 4.69% 2010 11.65% 0.94% 0.37% 0.58% 0.49% 5.55% 2011 11.56% 1.00% 0.43% 0.52% 0.69% 0.59% 6.13% 2012 2.73% 12.05% 1.04% 0.45% 0.39% 0.48% 0.48% 4.55% 2013 3.15% 12.55% 1.34% 0.53% 0.42% 0.78% 0.52% 4.92% 2014 2.31% 13.20% 1.00% 0.50% 0.39% 0.75% 0.56% 4.07% Source: Created by author
EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 73
Appendix F. Weights in equal-weight portfolio 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 3.13% 2.78% 2.56% 2.50% 2.50% 2.44% 2.27% 2.27% 2.27% 2.17% ASC ASC ASC ASC ASC ASC ASC ASC ASC ASC AFG AFG AFG AFG AFG AFG AFG AFG AFG AFG AKER AKER AKER AKER AKER AKER AKER AKER AKER AKER AKA AKA AKA AKA AKA AKA AKA AKA AKA AKA ATEA ATEA ATEA ATEA ATEA ATEA ATEA ATEA ATEA ATEA BIONOR BIONOR BIONOR BIONOR BIONOR BIONOR BIONOR BIONOR BIONOR BIONOR DNB DNB DNB DNB DNB DNB DNB DNB DNB DNB DNO DNO DNO DNO DNO DNO DNO DNO DNO DNO EKO EKO EKO EKO EKO EKO EKO EKO EKO EKO FOE FOE FOE FOE FOE FOE FOE FOE FOE FOE KOG KOG KOG KOG KOG KOG KOG KOG KOG KOG MHG MHG MHG MHG MHG MHG MHG MHG MHG MHG NOD NOD NOD NOD NOD NOD NOD NOD NOD NOD NHY NHY NHY NHY NHY NHY NHY NHY NHY NHY NAS NAS NAS NAS NAS NAS NAS NAS NAS NAS OLT OLT OLT OLT OLT OLT OLT OLT OLT OLT OPERA OPERA OPERA OPERA OPERA OPERA OPERA OPERA OPERA OPERA ORK ORK ORK ORK ORK ORK ORK ORK ORK ORK PGS PGS PGS PGS PGS PGS PGS PGS PGS PGS PRS PRS PRS PRS PRS PRS PRS PRS PRS PRS RCL RCL RCL RCL RCL RCL RCL RCL RCL RCL SCH SCH SCH SCH SCH SCH SCH SCH SCH SCH STL STL STL STL STL STL STL STL STL STL SNI SNI SNI SNI SNI SNI SNI SNI SNI SNI STB STB STB STB STB STB STB STB STB STB SUBC SUBC SUBC SUBC SUBC SUBC SUBC SUBC SUBC SUBC TEL TEL TEL TEL TEL TEL TEL TEL TEL TEL TGS TGS TGS TGS TGS TGS TGS TGS TGS TGS TOM TOM TOM TOM TOM TOM TOM TOM TOM TOM VEI VEI VEI VEI VEI VEI VEI VEI VEI VEI WWI WWI WWI WWI WWI WWI WWI WWI WWI WWI YAR YAR YAR YAR YAR YAR YAR YAR YAR YAR AMSC AMSC AMSC AMSC AMSC AMSC AMSC AMSC AMSC BIOTEC BIOTEC BIOTEC BIOTEC BIOTEC BIOTEC BIOTEC BIOTEC BIOTEC KOA KOA KOA KOA KOA KOA KOA KOA KOA SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL SDRL NPRO NPRO NPRO NPRO NPRO NPRO NPRO NPRO REC REC REC REC REC REC REC REC WEIFA WEIFA WEIFA WEIFA WEIFA WEIFA WEIFA WEIFA SALM SALM SALM SALM SALM SALM SALM DETNOR DETNOR DETNOR DETNOR DETNOR BAKKA BAKKA BAKKA BAKKA GJF GJF GJF GJF WWASA WWASA WWASA WWASA BWLPG RECSOL Source: Created by author. EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 74
Appendix G. Companies in low volatility portfolio (10% weights) 2005 DNB TEL PRS EKO STB DNO RCL SCH VEI KOG 2006 DNB RCL EKO KOG TEL VEI YAR STB SCH SNI 2007 DNB WWI RCL TEL AFG KOG SCH EKO YAR STB 2008 DNB OLT AFG WWI AKER KOG PRS FOE RCL NPRO 2009 AFG KOG BIOTEC WWI TOM STL FOE OLT AKER ATEA 2010 AFG STL VEI ORK FOE WWI KOG ATEA TEL TOM 2011 STL ORK TEL VEI WWI KOG ATEA AKER DNB FOE 2012 OLT TEL GJF VEI STL ORK AFG SDRL ATEA NPRO 2013 ORK GJF STL TEL SDRL OLT VEI AFG AKER SCH 2014 STL TEL VEI NHY SDRL GJF ORK ASC YAR AFG Source: Created by author
Appendix H. Companies in high volatility portfolio (10% weights) 2005 SUBC WWI NAS ORK ATEA ASC NHY NOD BIONOR AKER 2006 OPERA ATEA NOD NAS MHG DNO ORK STL BIONOR NHY 2007 DNO BIOTEC ATEA MHG OPERA NHY STL BIONOR ORK SDRL 2008 WEIFA OPERA VEI REC MHG ATEA BIOTEC KOA NOD BIONOR 2009 SDRL TGS PGS STB AKA DNO REC NOD KOA AMSC 2010 MHG DNB REC KOA RCL NPRO DNO AMSC BIOTEC WEIFA 2011 SALM DNO WEIFA KOA REC NOD BIOTEC AFG AMSC BIONOR 2012 BIOTEC WEIFA NOD SALM DNO KOA BIONOR DETNOR REC AMSC 2013 DNO AKA STB BIOTEC MHG KOA BIONOR REC WEIFA AMSC 2014 OPERA NOD AKA KOA NAS BIOTEC BIONOR REC WEIFA AMSC Source: Created by author
Appendix I. Companies in momentum portfolio (10% weights) 2005 FOE ORK SNI SUBC NHY VEI ASC SCH PGS AFG 2006 DNO NAS NHY AKER FOE ORK OPERA AKA VEI TGS 2007 ORK MHG OLT NHY PGS BIOTEC AKER SDRL AKA TEL 2008 ATEA REC KOG NAS YAR NHY SDRL VEI AFG ORK 2009 OPERA KOG NOD EKO STL AFG TOM FOE SALM OLT 2010 WEIFA MHG NOD ATEA NAS TGS SDRL DNB VEI PGS 2011 NOD RCL DNO SNI SUBC KOG BIOTEC MHG OPERA AKA 2012 DETNOR GJF WEIFA AFG STL AKER TEL ATEA TOM TGS 2013 NAS AKA MHG AMSC WWASA BAKKA BIONOR SCH SALM PGS 2014 AMSC KOA BAKKA OPERA DNO REC NOD BIOTEC SCH SALM Source: Created by author
Appendix J. Companies in contrarian portfolio (10% weights) 2005 PRS EKO DNO KOG TOM WWI NOD AKER ATEA NAS 2006 TEL DNB OLT SCH MHG NOD STB EKO RCL ATEA 2007 SCH STL WWI TOM SNI RCL DNO NOD BIONOR OPERA 2008 SNI AKER STB BIOTEC KOA EKO WEIFA MHG TGS NOD 2009 STB MHG WEIFA PRS AMSC REC NAS PGS NPRO KOA 2010 AKER TOM KOG SNI DNO OPERA BIONOR REC BIOTEC AMSC 2011 STL NHY AKER KOA DETNOR AMSC NPRO WEIFA REC AFG 2012 BIOTEC NOD RCL SALM ASC NAS MHG KOA AMSC REC 2013 EKO NHY NOD SNI KOA STL DETNOR STB REC WEIFA 2014 ORK YAR NHY EKO TGS SUBC NPRO DETNOR PGS WEIFA Source: Created by author EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 75
Appendix K. Operating profit (in currencies and metric numbers used in financial statements)
ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB OP 2003Q3 59906.0 12312.0 324.0 -9.7 -11.6 1303.0 OP 2004Q3 71919.0 15333.0 217000.0 223.0 -57.7 -3.3 2498.0 OP 2005Q3 193943.0 25009.0 445000.0 610.0 4.5 -30.0 -1.7 -1400.0 3334.0 OP 2006Q3 240685.0 49129.0 733000.0 807.0 0.9 -218.2 -4.0 -12464.0 3558.0 OP 2007Q3 287246.0 62857.0 905000.0 12.0 -1.0 50.5 -13.3 -9065.0 4498.0 OP 2008Q3 140011.0 81364.0 994000.0 381.0 2.8 64.5 0.2 -19059.0 3649.0 OP 2009Q3 112571.0 89000.0 789000.0 -109.0 6.2 64.3 -0.2 -28446.0 2762.0 OP 2010Q3 125799.0 78000.0 653000.0 -283.0 8.6 70.6 82.5 -8.1 -8047.0 -253.1 4157.0 OP 2011Q3 20109.0 61000.0 129000.0 -70.0 10.4 97.6 70.0 -17.1 -5676.0 -118.7 4072.0 OP 2012Q3 44900.0 11000.0 834000.0 98.0 13.3 96.5 86.2 -15.4 -6973.0 -2317.6 3541.0 OP 2013Q3 68600.0 150000.0 699000.0 77.0 12.9 70.8 186.8 -23.0 -4981.0 70291.0 -518.0 4881.0
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT OP 2003Q3 127.3 91.8 63.4 70.0 -170.7 -3.4 6.4 -41368.0 99.8 OP 2004Q3 121.0 115.8 -43.7 71.0 -23.3 16.9 8.6 -16081.0 201.7 OP 2005Q3 37.7 107.6 139.4 149.0 97.8 26.4 13.4 56253.0 374.0 OP 2006Q3 88.2 123.7 397.4 51.4 126.0 748.4 15.4 13.3 54856.0 618.2 OP 2007Q3 150.3 102.8 460.7 5.2 215.0 -6.1 11.2 12.6 168210.0 290389.0 847.0 OP 2008Q3 26.9 106.3 907.1 -3.7 306.0 -1342.6 19.6 2.4 193378.0 -615171.0 327.0 OP 2009Q3 -9.6 146.5 609.4 -6.6 340.0 313.5 28.5 0.7 475581.0 319172.0 301.0 OP 2010Q3 198.0 130.3 633.3 1.0 537.0 1044.7 47.8 0.3 573300.0 229600.0 378.0 OP 2011Q3 34.7 95.5 642.1 773.1 5.0 543.0 -27.8 47.3 2.2 923300.0 230600.0 425.0 OP 2012Q3 126.3 106.7 580.6 1606.9 3.4 544.0 1.4 36.5 -0.2 822400.0 -34000.0 260.0 OP 2013Q3 63.6 216.7 567.3 1673.3 6.2 408.0 835.9 33.8 0.6 637700.0 57600.0 493.0
OPERA ORK PGS PRS REC RCL SALM SCH SDRL STL SNI STB OP 2003Q3 1083 14.8 134 249161 96 12168 52956 1737.4 OP 2004Q3 -3013 92 45.6 30.4 358381 251 16091 30408 632.9 OP 2005Q3 -5137 1040 56.6 33.1 400456 215 23872 63782 1127.5 OP 2006Q3 -6754 1167 90.2 50.7 422 419609 174 64.3 30168 23816 714.1 OP 2007Q3 8015 750 167.4 70.3 495 482834 107 120 96.2 24383 48202 894.8 OP 2008Q3 22692 973 187.8 61.2 537 461907 74 172 173.6 47006 47634 -1205.3 OP 2009Q3 4625 664 56.454 77.1 -665 306841 225.1 305 393.7 28258 39284 908.0 OP 2010Q3 34761 1008 -26.782 83 155 445502 300.7 388 431.2 28225 39100 709.0 OP 2011Q3 62264 937 44.492 69 -1282 507742 134 369 480 39263 40083 -52.0 OP 2012Q3 79466.36 829 110.9 68.7 -378 452137 109 312 413 40900 31698 458.0 OP 2013Q3 95238.1 677 97.9 90.4 -179 444209 360.4 395 471 39300 48908 810.0
SUBC TEL TGS TOM VEI WEIFA WWASA WWI YAR OP 2003Q3 -6.5 2300.0 9210.0 85.3 60.4 26.0 OP 2004Q3 42.5 2895.0 14701.0 75.6 163.9 41.0 1132.0 OP 2005Q3 42.9 3472.0 30580.0 72.5 254.5 61.0 1177.0 OP 2006Q3 108.5 5216.0 38072.0 194.1 247.8 -9511.0 43.0 1626.0 OP 2007Q3 125.0 4213.0 32880.0 130.3 311.1 -19535.0 78.0 1576.0 OP 2008Q3 112.9 3947.0 75751.0 115.4 335.2 -24290.0 49.0 4350.0 OP 2009Q3 66.7 4500.0 59100.0 131.6 223.5 -19091.0 42.0 -117.0 OP 2010Q3 64.4 3751.0 53487.0 -54.1 232.8 -32885.0 55.0 70.7 1402.0 OP 2011Q3 172.8 4507.0 61019.0 210.9 206.4 -45603.0 73.0 156.7 4398.0 OP 2012Q3 228.2 5119.0 101315.0 171.8 243.2 -45662.0 239.0 253.0 2601.0 OP 2013Q3 269.2 6005.0 79862.0 189.1 336.2 -3500.0 67.0 86.0 2011.0 Source: Created by author, using financial statements of the analyzed companies EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 76
Appendix L. Weights in growth portfolio (equally-weighted) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 5.88% 4.00% 5.00% 4.76% 4.76% 6.67% 4.35% 4.55% 5.00% 4.55% ASC ASC ASC ASC AFG AFG ASC AMSC ASC ASC AFG AFG AFG AFG AKER AMSC AMSC ATEA AKER AFG DNB AKER AKER AKA AKA EKO ATEA FOE AKA BAKKA EKO AKA AKA ATEA AMSC KOG DNB KOA AMSC DNB KOG DNB DNB DNB ATEA MHG DNO KOG BAKKA EKO NOD FOE DNO DNO BIONOR NOD FOE NHY DNO GJF NHY KOG EKO FOE EKO NAS KOA NAS EKO KOA OLT MHG FOE KOG FOE NPRO KOG NPRO GJF MHG PGS NOD MHG NAS KOG PRS MHG OLT KOG NHY RCL NHY OLT OLT NOD SALM NOD OPERA MHG NPRO SCH NAS ORK OPERA NAS SCH NAS PGS OPERA OLT STL OLT PGS PGS OPERA SDRL OLT RCL PGS OPERA SUBC ORK PRS PRS ORK STB OPERA SDRL STL PRS TEL PGS RCL REC PGS TEL ORK STL STB SALM TGS PRS STL RCL REC TOM PRS SNI SUBC SCH VEI RCL SUBC SDRL SCH REC SUBC TEL SDRL WWI STL TEL SNI SDRL RCL TEL TGS SNI SNI TGS STB STL SALM TGS VEI STB STB TOM SUBC TGS SCH TOM WWASA SUBC SUBC YAR VEI VEI SDRL WWASA WWI TEL TEL WWI YAR VEI WWI TOM TGS WWI YAR VEI VEI YAR WWI YAR Source: Created by author EVALUATION OF PASSIVE INVESTMENT STRATEGIES IN OSLO STOCK EXCHANGE 77
Appendix M. Price-to-book value ratios ASC AFG AKA AKER AMSC ATEA BAKKA BIONOR BIOTEC BWLPG DETNOR DNB P/BV 2005 4.87 1.42 1.14 0.54 5.51 1.56 P/BV 2006 4.12 2.00 1.56 1.65 12.45 10.71 1.68 P/BV 2007 4.86 2.42 1.90 2.80 4.28 8.16 1.69 P/BV 2008 2.84 2.82 1.39 1.25 6.89 3.35 1.49 P/BV 2009 1.26 2.87 0.37 0.41 1.06 0.67 10.69 1.28 0.44 P/BV 2010 2.70 1.52 0.59 0.67 0.38 1.84 6.77 1.27 0.97 P/BV 2011 2.86 2.81 0.66 0.64 0.67 1.91 3.07 3.95 4.88 0.72 1.24 P/BV 2012 1.31 3.81 0.34 0.79 0.11 1.68 1.69 1.21 2.79 2.87 0.84 P/BV 2013 1.65 4.21 0.73 1.14 0.22 1.71 2.65 2.39 5.80 3.54 0.95 P/BV 2014 2.10 4.98 0.71 1.20 2.71 1.69 2.79 2.97 10.20 1.32 2.25 1.29
DNO EKO FOE GJF KOA KOG MHG NOD NHY NAS NPRO OLT P/BV 2005 1.84 4.58 0.99 1.65 3.89 0.44 1.31 1.01 P/BV 2006 7.98 4.19 2.72 2.24 2.50 11.61 0.59 8.66 0.83 P/BV 2007 15.04 4.83 4.69 4.96 3.28 1.59 6.62 0.78 6.40 1.41 P/BV 2008 8.05 2.93 5.16 3.33 4.59 0.90 2.93 0.89 6.83 1.03 1.05 P/BV 2009 1.57 2.15 2.97 1.70 3.66 0.35 2.70 0.60 0.74 0.18 0.59 P/BV 2010 2.26 3.13 2.73 1.41 2.84 1.39 7.93 1.16 2.91 1.16 1.02 P/BV 2011 4.76 3.61 2.63 1.32 3.65 1.90 12.98 1.21 2.26 1.03 1.09 P/BV 2012 2.94 2.27 1.85 1.52 0.42 2.46 0.88 7.62 0.66 0.94 0.68 0.84 P/BV 2013 2.88 2.23 2.14 1.66 0.42 2.44 1.66 6.19 0.77 2.13 0.95 0.90 P/BV 2014 4.74 1.96 1.97 2.31 1.52 2.30 2.32 10.69 0.74 2.25 0.78 0.90
OPERA ORK PGS PRS REC RCL SALM SCH SDRL STL SNI STB P/BV 2005 2.04 1.34 1.98 2.37 4.69 2.63 1.95 1.66 P/BV 2006 8.14 1.13 1.75 3.29 2.04 4.45 3.50 1.87 1.66 P/BV 2007 2.94 1.64 7.99 6.09 5.44 1.57 4.90 2.20 4.46 1.53 2.28 P/BV 2008 2.93 2.05 5.53 2.21 5.23 1.38 3.82 3.17 2.65 4.27 1.28 2.64 P/BV 2009 3.75 0.92 0.72 0.85 3.14 0.53 2.26 1.07 1.21 1.81 0.54 0.50 P/BV 2010 4.05 1.22 1.74 5.05 0.95 0.70 3.87 2.55 2.12 2.40 0.52 1.08 P/BV 2011 5.57 1.30 2.09 4.01 0.48 1.22 4.06 3.10 2.58 2.10 0.90 1.11 P/BV 2012 5.01 1.15 1.70 4.35 0.19 0.72 1.55 2.43 2.51 1.88 0.83 0.75 P/BV 2013 4.81 1.57 1.97 4.13 0.31 0.84 1.87 3.91 2.50 1.43 0.78 0.61 P/BV 2014 9.64 1.61 1.28 2.49 1.22 1.18 3.10 6.78 2.51 1.38 1.03 0.77
SUBC TEL TGS TOM VEI WWASA WWI YAR P/BV 2005 2.11 2.60 2.22 1.98 1.58 2.36 P/BV 2006 2.39 4.41 3.71 3.27 2.20 1.94 P/BV 2007 3.35 5.10 3.50 4.12 1.93 2.28 P/BV 2008 3.40 2.54 4.02 3.84 1.47 3.58 P/BV 2009 0.93 1.11 2.25 1.55 0.84 1.06 P/BV 2010 1.62 2.30 2.33 3.47 0.78 1.54 P/BV 2011 1.64 2.56 3.30 3.65 1.50 0.91 2.48 P/BV 2012 1.16 1.69 2.71 2.92 2.53 1.00 0.72 1.44 P/BV 2013 1.24 2.32 2.99 3.51 2.85 1.22 0.62 1.40 P/BV 2014 0.99 2.82 2.24 3.25 2.96 1.28 0.68 1.22 Source: Created by author, using Yahoo finance data and financial statements of the analyzed companies
Appendix N. Companies in value portfolio (10% weights) 2005 NHY AKER FOE OLT AKA NAS PGS AFG DNB WWI 2006 NHY OLT ORK AKA AKER STB DNB PGS SNI YAR 2007 NHY OLT SNI RCL MHG ORK DNB AKA WWI SDRL 2008 NHY MHG NPRO OLT AKER SNI RCL AKA WWI DNB 2009 NPRO MHG AKA AKER DNB STB RCL SNI OLT NHY 2010 AMSC SNI AKA AKER RCL WWI REC DNB OLT STB 2011 REC AKER AKA AMSC DETNOR SNI WWI NPRO OLT STB 2012 AMSC REC AKA KOA NHY NPRO RCL WWI STB AKER 2013 AMSC REC KOA STB WWI AKA NHY SNI RCL OLT 2014 WWI AKA NHY STB NPRO OLT SUBC SNI RCL AKER 2015 WWI STB FOE SUBC SDRL PGS SNI WWASA AKER OLT Source: Created by author