Value Investing by Kumaran Seenivasan

Value Investing in Security Analysis Is it applicable today and can it beat the Swedish market?

Master Thesis, May 2007

Authors:

Daniel Hansson Alexander Torstensson

Advisor:

Maria G책rd채ngen

ABSTRACT Title:

Value Investing in Security Analysis - Is it applicable today and can it beat the Swedish market?

Date:

28 of May 2007

Course:

Master Thesis in Corporate Finance, 10 Swedish credits (15 ECTS)

Authors:

Daniel Hansson Alexander Torstensson

Advisor:

Maria G책rd채ngen

Key words:

Security Analysis, Value Investing, Behavioural Finance, Investment Strategy, Finance, Valuation

Purpose:

This study aims to investigate how the Value Investing methodology first established in Security Analysis can be successfully implemented on the Swedish financial market. The study intends to test this methodology against a Swedish market index.

Methodology:

Based on the theories of Security Analysis, we have created a somewhat modified model to collect and select the necessary input and furthermore to value securities. This model is used to test if Value Investing can succeed on the Swedish market. The approach is deductive and quantitative.

Theoretical: Framework

The Efficient Market Hypothesis and Behaviour Finance constitutes for the fundamental theories related to Security analysis. We further consider the theories of risk and the key figures used in the selection process and the valuation model.

Conclusion:

We are able to conclude that our portfolio beat the market index during the studied period. This would suggest that the weak form efficient market is breached. We also found that the Swedish market is too small to get the full effect of diversification since the hurdles that are setup only leaves us with a small number of companies to choose from.

TABLE OF CONTENTS 1 INTRODUCTION _________________________________________________________ 1 1.1 Background ________________________________________________________________ 1 1.2 Problem Discussion __________________________________________________________ 2 1.3 Purpose____________________________________________________________________ 3 1.4 Delimitations _______________________________________________________________ 3 1.5 Target Group_______________________________________________________________ 4 1.6 Thesis Outline ______________________________________________________________ 4

2 SECURITY ANALYSIS ____________________________________________________ 6 2.1 Introduction________________________________________________________________ 6 2.2 Stock market fluctuations_____________________________________________________ 6 2.3 The strategy ________________________________________________________________ 7 2.4 Central value _______________________________________________________________ 8 2.5 The margin of safety _________________________________________________________ 8 2.5.1 Diversification _________________________________________________________________ 10

2.6 The Appraisal Method ______________________________________________________ 10 2.7 Value investing in Conscious investor __________________________________________ 11 2.8 Value investing and the new economy__________________________________________ 12

3. METHODOLOGY _______________________________________________________ 14 3.1 The research model_________________________________________________________ 14 3.1.1 Selection of companies ___________________________________________________________ 3.1.2 The hurdles ____________________________________________________________________ 3.1.3 The model_____________________________________________________________________ 3.1.4 Delimitations and adjustments _____________________________________________________

14 15 16 17

3.2 Portfolio formation _________________________________________________________ 17 3.2.1 Motives for formation____________________________________________________________ 18

3.3 Data input ________________________________________________________________ 19 3.3.1 Choice of time period studied______________________________________________________ 19 3.3.2 Stock data _____________________________________________________________________ 19 3.3.3 Benchmarking index_____________________________________________________________ 20

3.4 Approach and Trustworthiness _______________________________________________ 20 3.4.1 A deductive and quantitative approach_______________________________________________ 20 3.4.2 Reliability _____________________________________________________________________ 20 3.4.3 Validity _______________________________________________________________________ 21

4 THEORETICAL FRAMEWORK____________________________________________ 22 4.1 The Efficient Market Hypothesis______________________________________________ 22 4.1.1 Forms of efficient market _________________________________________________________ 22

4.2 Behavioural finance ________________________________________________________ 23 4.2.1 Prospect theory _________________________________________________________________ 4.2.3 Herd behaviour _________________________________________________________________ 4.2.3 Anchoring _____________________________________________________________________ 4.2.4 Over-confidence/over-optimism____________________________________________________

24 24 26 26

4.3 Risk theory________________________________________________________________ 28 4.3.1 Utility theory __________________________________________________________________ 28

4.3.2 Diversification _________________________________________________________________ 28 4.3.3 International ___________________________________________________________________ 29

4.4 Multiple key figures ________________________________________________________ 29 4.4.1 P/E Ratio______________________________________________________________________ 29 4.4.2 Current ratio ___________________________________________________________________ 30

5 EMPIRICAL FINDINGS __________________________________________________ 31 5.1 The model in practice _______________________________________________________ 31 5.2 Company selection _________________________________________________________ 32 5.3 Investment return __________________________________________________________ 33

6 ANALYSIS______________________________________________________________ 36 6.1 Results ___________________________________________________________________ 36 6.1.1 Dividends _____________________________________________________________________ 36 6.1.2 Investment analysis______________________________________________________________ 36

6.2 Model ____________________________________________________________________ 37 6.2.1 Critics to the model______________________________________________________________ 38 6.2.2 The use of financial ratios_________________________________________________________ 40

6.3 Analysing risk _____________________________________________________________ 40 6.3.1 Portfolio risk ___________________________________________________________________ 41 6.3.2 Market risk ____________________________________________________________________ 41 6.3.3 Diversification _________________________________________________________________ 41

6.4 The market________________________________________________________________ 42 6.4.1 The Market and Irrational behaviour ________________________________________________ 42

7 CONCLUSION __________________________________________________________ 44 7.1 Concluding remarks ________________________________________________________ 44 7.2 Further Studies ____________________________________________________________ 45

REFERENCES ___________________________________________________________ 46 EXHIBIT A_______________________________________________________________ 49 EXHIBIT B_______________________________________________________________ 50

1 INTRODUCTION This chapter contains a background to the thesis subject and presents the research problem which leads to the purpose of this study. Furthermore the delimitations are discussed and conclusively a description of the target group and the outline of this study are presented.

1.1 Background During our financial studies we have repeatedly come across Warren Buffet and his company Berkshire Hathaway (BRK) as a reference in many different contexts. He has been described as a guru within finance but we have never been fully introduced to the background of his success. As a self- made billionaire admired by many; the 76 year old Buffet entered the Forbes 400 list (The 400 richest people in the world) in 1979 and is currently holding a respectable second place1. Few people, among them ourselves, seem to know the ideas that have set the foundation of his success which stems from the strategies set forth in the book Security Analysis by Graham & Dodd first published in 1934.

As a university student at Columbia, Buffet was the only student ever to earn an A+ on the security analysis course given by Benjamin Graham2. The admiration for his professor and his interest in the strategies made him apply for a position at Grahamâ&#x20AC;&#x2122;s company GrahamNewman Corporation, in 1954. When Graham retired in 1956 Buffet left the company to start his own business and in 1962 he became the owner of the textile company BRK for a mere 8 dollars a share. In 1969 BRK turned into the business that it is known for today, as one of the most successful investment firm in the world3. The current BRK share price is about USD 1097004 and has rewarded Buffet with an annual return of 24 per cent during this 45 year time period. Worth noting is that BRK, under

http://www.forbes.com/lists/2007/10/07billionaires_The-Worlds-Billionaires_Rank.html http://www.spiegel.de/international/0,1518,423682,00.html 3 http://www.iht.com/articles/ap/2006/10/23/business/NA_FIN_US_Berkshire_Stock.php 4 http://finance.yahoo.com/q?s=BRK-a 2

Buffet’s control, has never made a split and has only paid out dividends once in the amount of ten cents per share in 1967. Buffet’s comment on this issue were: “I must have been in the bathroom when the dividend was declared”5.

As the primary spokesman for value investing Buffet made one of his most famous speech at the 50th anniversary of the Security Analysis book at Columbia University in 1984. In this speech he comments on the factors that have been successful for him during the years. He claims that it is not a coincidence that three (the ones he was able to follow) out of the four colleagues at Graham-Newman Corporation has become utterly successful with their investments since they left the company which shaped them in the same manner. For this occurrence he makes a simile with coin tossing monkeys, that if few monkeys were able to toss a coin with heads up repeatedly it may be seen as mere chance but if hey all came from the same zoo something great must have been accomplished by the zoo keeper6.

1.2 Problem Discussion Despite the increasing number of financial institutions and the use of new improved financial instruments the majority of mutual funds still do not exceed the returns of the stock market indices, in the long term (Bogle, 2005).

In addition to bad performance by these financial institutions offering investing proficiency they tend to charge substantial amount of money at different stages of the investment such as buying fees, selling fees and managing fees. This makes the total return on the investment even worse in comparison to market indices. This compensation system shifts all the risk to the investor and leave only the upside to the fund manager, since he or she makes money when the fund perform well and risks nothing when it does not. In the mentioned speech at the 50th anniversary of Security Analysis, Buffet brought the matter of high returns and lower risks to the discussion of market efficiency. He argued that

5 6

http://beginnersinvest.about.com/cs/warrenbuffett/a/aawarrenbio_3.htm The superinvestors of Graham and Doddsville, Warren Buffet 1984

the market is indeed inefficient and that the value investing methodology shows that there is a gap between the value and the market price of stocks.

This contradicts the Efficient Market Hypothesis (EMH) on which todayâ&#x20AC;&#x2122;s commonly used valuing methods are based on such as the Discounted Cash Flow model (DCF). This valuation model is greatly influenced by the beta value in the Capital Asset Pricing Model (CAPM). Buffet further argues that the use of beta as risk measure is not a valid measurement since if the stock being bought to a lower price than it has been traded for earlier, the Beta value increases. This should according to Buffet rather lower the risk because the stock is being bought at an abnormally low price. This leads to our main question; can the individual investor make his own valuations and surpass the market without increasing the risk?

1.3 Purpose This study aims to investigate how the Value Investing methodology first established in Security Analysis can be successfully implemented on the Swedish financial market. The study intends to test this methodology against a Swedish market index.

1.4 Delimitations The study is performed during the years of 1995 through 2006 and includes all companies which are or have been primarily listed on the Swedish Stock Exchange. As a consequence we do not suffer from survivorship bias that might have affected the results.

Since the study aim to show if the value investing strategy can beat the market as a whole, transaction costs will not be included. Involving these would only serve to influence the results and make it harder to interpret. The reader will have to make his or her own assessment regarding the costs of the transactions.

1.5 Target Group This thesis is aimed for those that want to develop their understanding within the investment area and get further knowledge in how this renowned investment strategy can be implemented. This group should include professionals as well as the common man or woman.

1.6 Thesis Outline Chapter two describes the concept of value investing developed in the Security Analysis. We introduce the main theories underlying Security Analysis and further expand how this theory from 1934 is interpreted in the world as of today.

Based on the previous chapter, Security Analysis, chapter three focuses on the somewhat modified process to collect and select the necessary input and furthermore the valuation of securities. This discussion is followed by describing the method used to test if Value Investing can succeed on the Swedish market. Conclusively we discuss the research approach and trustworthiness of our method and model.

In chapter four we describe the theoretical framework and hypothesis related to the Security Analysis and our research. The Efficient Market Hypothesis and Behaviour Finance constitutes for the fundamental background. We further consider the theories of risk and the key figures used in the model.

The fifth chapter concretizes the results from our study. It shows and describes the results of the selected companies as well the investments portfolios. The last show the return of the combined and individual portfolios compared to the market index.

The sixth chapter begins with a discussion about the results. The realized return is further analyzed and discussed. The model and its implications are analyzed by tying it to earlier research and the related theories, certainly those associated with market fluctuations which proved to be essential for this study.

The concluding chapter of this thesis summarizes the model based on our empirical findings and the analysis. At the end some suggestions for further research are presented.

2 SECURITY ANALYSIS This chapter describes the concept of value investing developed in the Security Analysis. We introduce the main theories underlying Security Analysis and further expand how this theory from 1934 is interpreted in the world as of today.

2.1 Introduction In 1934 the two professors at Columbia University in New York published Security Analysis. This book set the foundation to what has been renowned as Value Investing. This is a technique where one uses the fundamental economic principles to compute a ”fair value” or a “central value” for stocks, bonds and indices. This study however will exclusively concentrate on the valuation and investment strategies of common stocks. The books main arguement is that stocks for different reasons become over- and undervalued. By knowing their central value opportunities of making abnormal returns will arise. The Security Analysis theory addresses the importance of using a margin of safety in order to reduce the risk as well as ensuring that one is buying at unusually low price. The book also emphasises on distinguishing between an investor and a speculator. “An investment operation is one which, upon thorough analysis, promises safety of principle and satisfactory return. Operations not meeting these requirements are speculative.” (Graham and Dodd, 1951 pp. 38)

2.2 Stock market fluctuations Security analyses discuss the behaviour of the security markets as an introduction to why it is important to consider market fluctuations. This is the main approach to the whole concept of value investing. Graham and Dodd (1951), states that almost all companies have a price at which they are sound investments and that market fluctuations create levels of investing and divesting. These market movements are fundamental to the value investing theory and create the opportunities of buying a stock to a lower price than its real value. The fluctuations of the market and that of the broader business cycles are the ones of interest. The short-run price

movements in the time perspective of daily or monthly basis are believed to be less valid (Graham and Dodd, 1951 pp. 23). The fluctuations in longer time periods than a month are described as the touchstone for successful investing for two reasons. 1. They are a measure of the success of the investment. 2. They are a guide to the selection of securities and the timing of the transactions (Graham, 1949 pp. 23).

Moreover, Graham (1949) argues that when the general market goes up or down almost all investors will have similar changes in their portfolio values. Under bull markets when the prise levels rise and continue to do so the investor is neither smart nor richer when he or she cashes in unless he or she either is definitely through buying stocks which is not very likely or, absolutely determined to reinvest only at a substantially lower level. Therefore in a continuous investment strategy the profit is not realized until the later reinvestment has taken place. The true trading profit is thus the difference between the previous selling price and the cost for achieving the new investment (Ibid). In bear markets the price level of many sound stocks is temporarily unusually low. Graham show evidence that in some cases share prices has fallen by 50 percent without any clear indications that the underlying assets show any major changes in performance.

2.3 The strategy These market swings give the investor opportunities to make profits by either timing or pricing. The strategy for timing is simply to buy and hold the security when the price is believed to rise and further to sell or retrain from buying when prices are believed to fall. This investor will end up as a speculator. The strategy of timing is also associated with the characteristics of wanting to make the profit in a hurry. Therefore keeping un-invested money does not give the possibility of these quick profits as well as a loss of dividends (Graham 1949).

However, the strategy of pricing is connected to the characteristics of the investor. By being rational and not trying to predict the market movements but rather seeing clear investment opportunities in buying certain value stocks at extraordinary low prices. The investor following this strategy is not explained as trying to be smarter than the crowd but instead acting a bit less irrational than the others. This corresponds to the evidence shown that in a

bull market, stocks might be dangerously overpriced. Therefore Graham stresses the importance for an investor to stick to a model or a concept and to get an independent way of valuating shares in times of optimism and pessimism. It is required by the investor to keep mentally strength and not be carried away by current market climate (Ibid). The final words of Graham when finishing “The intelligent investor” were,

You are neither right nor wrong because the crowd disagrees with you. You are right because your data and reasoning are right (Graham, 1949).

2.4 Central value By studying the market fluctuations for each stock we are able to attain a central value which is the value a stock does not deviate far from in the time perspective of a couple of years. It is shown that for larger companies that the value derived from such reasoning corresponds rather well to other methods of independent analysis of the market value. Here the authors address a distinction between small and large size businesses. They claim that large scale businesses are more accurately valued by their accounting figures such as earnings and capital structure. These kind of firms are more attractive for the above defined investor. On the other side we have the small size businesses which attract the speculative investor. The difference originates from that these firms are more difficult to value in the same manner by key accounting figures. This is because their value is on a larger scale derived from psychological factors of management competence, competitiveness and future success. These psychological factors are more complicated to appraise correctly (Graham and Dodd, 1959).

2.5 The margin of safety The three words that are continuously repeated in both Security Analysis and Intelligent Investor are “Margin of Safety”. The essence of this is both risk management and the opportunity of making a safe profit and is the key of how to value an enterprise according to value investing. Margin of safety is classified into two set of factors, quantitative and qualitative. The former is regarded as a company’s statistical view. The authors bring up four main headings associated with the quantitative factors. 1. Capitalization, 2. Earnings and

dividends, 3. Assets and liabilities and 4. Operating statistics. The qualitative factors focuses on the nature of the business; the relative position of the individual company in the industry; its physical, geographical, and operating characteristics; the character of management; and the outlook for the company and industry in general (Graham and Dodd 1951).

As shown later in this chapter the valuation model developed in Security Analysis will use a multiple which based on qualitative factors. Since this factor puts too much personal opinion to the valuation process as well as making the study bias it is therefore disregarded from this study.

The valuation process is performed in two steps. These steps consist of selecting representative stocks and value them in order to judge at what level they are attractive to buy. Both steps are based on the qualitative factors in the margin of safety discussion.

When selecting the stocks one seeks to distil companies which show the best margin of safety. By analysing accounting figures such as debt ratios, earnings power, creditability and capitalization the unsafe companies are sorted out. Low level of debt is preferred because it brings lower risk. Concerning the earnings power not only the companyâ&#x20AC;&#x2122;s ability and strength to deliver earnings is of importance but also the stability of the earnings growth is of importance. The creditability is a measure of risk in terms of giving an indication of the companyâ&#x20AC;&#x2122;s ability to pay its obligations. Lastly the capitalization in terms of market value should be deemed to pass certain levels indicating stability in the firm. (Graham and Dodd 1951)

In the valuation process where a value below the stocks central value is regarded as the accepted level the investor has a margin of safety. This margin can absorb any unexpected and unfavourable future development as well as any miscalculations made by the investor. (Graham, 1949 pp. 245) In this way the result from the investment is more likely to have a satisfactory outcome even though the performance of the company is not brilliant (Graham and Dodd, 1951 pp. 408).

Even a substantial margin of safety is not sufficient to guarantee to safe and successful outcome which is why diversification becomes essential in making individual investment decisions (Graham, 1949 pp. 245). 9

2.5.1 Diversification Graham (1949) enlightens the importance of the principles of diversification as being connected to margin of safety. The margin of safety is meant to increase the possibility of making a satisfying return on the investment. This possibility is larger than making a loss but still it is not a guarantee of not ending up in the red. The benefits of simply adding more margin of safety investments to a portfolio, the more certain is the outcome to be in the black when aggregating a larger number of investments.

2.6 The Appraisal Method The second step in the valuation process according to security analysis consists of measuring the future dividends and earnings. Earnings should be estimated for a future period of at least five years. The multiplier in the model constitutes to the capitalization rate and is multiplied by the estimated earnings and dividends. The multipliers as mentioned are highly influenced by the intangible assets which are based on the longer term expectations and qualitative factors. These multipliers are therefore as mentioned the analysts own perspective and believe of the company being studied (Graham and Dodd 1951 pp. 411). The adjustments for asset value are only considered in the extreme ranges when either the intangible assets are extremely low in relation to earning power value or the net current assets alone exceed the earning power value (Ibid pp. 405) Below this formula is shown.

earnings   M  dividend +  ± Possible adjustments for asset value 3  

Since the valuation model was developed during the 1930’s and based on empirical research from the beginning of that century it no longer functions. Therefore it is more essential to put emphasis on how a model based on the value investing principles is modified to function in today’s environment. .

2.7 Value investing in Conscious investor John Price, a professor in economics and mathematics at the University of New South Wales, has during the last 10 years tried to interpret the strategy of value investing by looking at the original work of Benjamin Graham and the legacy that passed on to his apprentice, Warren Buffet. Price has constructed a model which interprets the views of value investing in a way that is more suitable for the present market situation.

In an article he describes his views on value investing. The article starts by contradicting those that regard Warren Buffetâ&#x20AC;&#x2122;s success as a statistical anomaly. He describes the chances for the success to be regarded as a statistical anomaly is one in 100 billion of random investors (Kelly and Price, 2004 pp. 52-54).

Price identifies some key concepts that he has identified from the work of Warren Buffet and Benjamin Graham. These concepts are then composed into a working strategy for investing. By using the quantitative factors as described above the investor is according to Price able to beat the market. These factors are divided in the two steps for the valuation method. The first step is selecting representative companies using hurdles and the other part is used for the valuation of the individual companies selected (Ibid).

The selecting process includes looking at default risk measures such as the quick ratio, current ratio and interest coverage. These are good measures to assure that the company can meet its short term obligations. As a good proxy for management effectiveness we look at a high and consistent return on equity (ROE) and here Price suggests a suitable figure of 20 per cent and refers to acquisition criteria that Buffet uses in his investments. The last criterion in the selection process is that of debt. Levels of debt should be kept low so that the company is able to meet is obligations in the future; this assures the investor that the company can meet its obligations even in times of despair (Ibid).

For valuation of the companies Price looks at different historical figures such as price to earnings ratio (P/E), earnings per share (EPS), sales and the famous margin of safety concept. He also emphasizes the importance of earnings stability. A stable and increasing earnings pattern is more likely to continue in the future as mentioned in the article, Buffet prefers companies that are virtually certain to have higher earnings five to ten years from now. Here 11

Price adopts his measure of future stability earnings growth (STAEGR). This measure shows how an exponential curve can be fitted to the observed earnings data. More weight is put upon the most recent earnings and it allows for outliers and negative earnings to be adjusted. His study shows that this enhances the ability to make more correct earnings assessments (Ibid).

2.8 Value investing and the new economy In the introduction of the first edition of â&#x20AC;&#x153;The Intelligent Investorâ&#x20AC;? (1949), Graham states on the initial page that he is well aware of that change are inevitable since the book has crystallized out of past experience and that it may become obsolete during the passage of time. As described earlier in this chapter some modification has to be made to meet the new market conditions. But we are also able to acknowledge that the cornerstones of value investing have remained relatively intact.

Each decade since the book was initially released the number of securities, investors and overall access to information has increased dramatically. The increased attention for the financial markets has made it more difficult to find real bargains in ones back yard but the increasing number of securities and easy access to international markets makes the investor able to widen his or hers scope of activities. This is of course accompanied by a larger and more time consuming screening process. Nevertheless, the possibility of diversification as described above is one obvious benefit of the larger and more open economy.

A further example of how the environment has changed is that Graham would have assessed the market to be fully 550 per cent overvalued during the 2000 high and the subsequent correction in 2002 showed that the market was still overvalued by 195 per cent. The conclusion drawn from this is that Graham had found a good indicator of market overvaluation during the short time horizon but it also shows us how the valuation standards change over time.

Graham, in his original edition, (Graham, 1949) dedicated a full thirty seven pages to the importance of management control. He felt that it was important for the investor to feel that he owned a piece of the business and to play an active role as an owner of the company. The individual investor of today has less to say about the control of the company and the larger 12

number of market participants have diluted the influence on the companyâ&#x20AC;&#x2122;s management. The increasing number of securities makes it easier for disgruntled investors to find similar companies with more effective leadership. They tend to prefer to sell the stock rather than trying to influence management strategies. This has made the market adapt a notion of rent-astock rather than own-a-stock philosophy which contradicts the corner stones of the 1930â&#x20AC;&#x2122;s. During the early decades of the 20th century dividends played a large part in the valuation of firms. Since then its significance has declined since the amount paid out to investors has diminished. Investors have seen a move towards stock repurchases as a way of paying out excess cash to existing shareholders. As a consequence dividends have become less important within the value investing framework (Bogle, 2005).

3. METHODOLOGY Based on the previous chapter, Security Analysis, this chapter focuses on the somewhat modified process to collect and select the necessary input and furthermore to the valuation of securities. This discussion is followed by describing the method used to test if Value Investing can succeed on the Swedish market. Conclusively we discuss the research approach and trustworthiness of our method and model.

3.1 The research model The models described in the previous security analysis chapter encourage the investor to make personal estimations within the frames of the value investing theory. Naturally we aim to create a model which is independent of personal assessments and values but still follows this theory and methodology as close as possible. The model used in this study is therefore somewhat modified and simplified to suit the necessary research strategy.

3.1.1 Selection of companies A very important and extensive part of value investing is the selection of companies to study. The selection of companies is also a part of the margin of safety concept and suggests to, in a strict manner sort out companies with the aid of hurdles. This process rules out a large quantity of companies at every hurdle and will finally end up with a selection which represents the securities of interest. When Conscious investor tested its strategies on the S&P 1007 only 7 passed the hurdles of financial history of 10 years, ROE at least 20 per cent, earnings per share growth of minimum 20 per cent and a high degree of stability of earnings growth. (Price and Kelly, 2004 pp. 55) Since this is a relatively small number of companies, we realized we had to both lighten and 7

S&P100 is a subset of S&P 500 and consists of 100 major bluechip companies across diversed industry groups. (www.standardandpoors.com)

reduce the number hurdles being used since this test had not yet included the hurdles of debt and the three credibility ratios. It is also a fact that the number of companies listed in the Stockholm exchange is only a fraction of the total US market on which the value investing theories are based upon.

We therefore chose to work with the hurdles we found most relevant. This procedure was conducted in a strict fashion with regard to keep hurdles for each category creditability, profitability and stability.

3.1.2 The hurdles The first two hurdles that the companies have to pass are market cap over 1 billion SEK and to have been continuously listed on the exchange for at least five consecutive years. The first one aims to include only larger companies since they are considered to have more stable figures. That the company has been listed for five years is important since we need sufficient amount of data to make our assessment of the company within our model.

Kelly and Price discuss the importance of ROE as it is a good indicator for management performance. This is primarily one of the quantitative factors but still tells us a little about management performance and as such it can also be seen as a kind of qualitative factor. Buffet uses a figure of 20 per cent for his investment decisions (Ibid). We decided to lower this figure to 15 per cent. It is still sufficiently high but let more companies pass through.

The next set of hurdles is related to risk. The purpose of these risk hurdles are to sort out which companies have the ability to sustain and pay its long and short term liabilities. Professor Price says that Warren Buffet prefers little or no debt at all. However the default figure of the debt to equity ratio according to Price is a maximum of 50 per cent. We decided to stick with this number. Of importance is also the ability to pay short term obligations and it is measured through the current and quick ratios as well as the interest coverage. We decided to keep the current ratio. This decision was based upon the fact that if the company has a high ROE and low debt there should be no problem paying the interest. The quick ratio is virtually the same as the current ratio. The current ratio hurdle was set at 1.5 this is in accordance with Price and theory. Finally the formula for the current ratio is shown below.

Current Ratio =

Current Assets Current Liabilities

3.1.3 The model The companies that succeed in meeting the requirements stated above are tried in the model. Each companyâ&#x20AC;&#x2122;s EPS for the last five years are added and checked for stability and overall performance. Stability is checked as the sum of the percentage difference between earnings. This is an alternative version of the STAEGR measure used by Kelly and Price (2004). It gives us an indication of the probability that earnings will continue in the same direction in the future. Our portfolio holding period is two years resulting in that we have a shorter horizon of investment than that of Price and Kelly. Therefore we are not as interested in the long term growth prospects as their model. We aim to include those shares that exhibit the highest level of stability in earnings.

Moreover, the model computes at what price levels we should invest and divest. This is done by calculating the average of the high and low P/E ratios from the past five years. The mean figure is then multiplied with the last yearâ&#x20AC;&#x2122;s reported EPS and creates our central value for the stock.

This figure is then multiplied with the margin of safety, which provides us with additional safety in the valuation process as it lowers the price the stock should be purchased at. (Graham and Dodd, 1951) and (Graham, 1949) suggests that for a stock, the level for purchase should be below two thirds of the central value. Though this model uses the range advised for valuing an index, 80 to 120 per cent of the central value and differs from that of the stock valuation. The reason for this increase in purchase level stems from a lack of companies remaining after the selection process. This level gives a larger number of investment objects. The new range of buying at 80 per cent and selling at 120 per cent is also in accordance with Grahamâ&#x20AC;&#x2122;s last modifications of his theories (Morris, 1976)

The emphasize on dividends for a long term return on investment is in our case neglected due to the short period of holding the stocks. This will ultimately effect of our portfolio negatively. This decision was based upon the lack of information as to what date these were paid to investors. It is a problem which arises from the strategy, where we purchase stocks during the whole year until the beginning of the next year. It would be too general to assume that the dividends for the year should be included to our portfolio.

3.1.4 Delimitations and adjustments Companies showing negative earnings, EPS close to zero or EPS-outliers one year need special attention. The model and the earnings stability indicator either sorts out some companies or gives them non relevant levels for purchase and are since disregarded. It is therefore essential to implement limitations to which companies should be rejected as an investment one specific year. If the company has more than one year of negative earnings it is not regarded as an interesting candidate and is deleted from the selection list. In cases when companies have earnings deviating more than 100 per cent they are usually sorted out by the earnings stability indicator, however if this turns out to be a one time occasion due to some non operational reason it will be adjusted by disregarding that year from the sample. However, if this unusual return is negative the company is abandoned.

3.2 Portfolio formation In order to get as many test periods as possible during the study resulting in a more dynamic strategy we keep two overlapping portfolios at any given time. The first portfolio is formatted at the beginning of year 1995 and the second portfolio is created in the beginning of 1996. Each portfolio has an initial value of 100 000 SEK.

Every portfolio is created at the first trading day of the year. If our model gives a buy signal at the starting date the asset is purchased. The aim is to keep five individual stocks at every formation and as such the capital in the portfolio is divided into five parts, each aimed to be invested in a single issue. As a consequence, if not sufficient number of companies reach the value for purchase according to the model at the initial date, the corresponding amount is kept during the year and the companies of interest are added when it meets its target price. This 17

means that when the portfolio finally contains five shares it is full and no more shares are thus added.

After two years all assets of the portfolio are sold if they not already have exceeded their selling point during the two year period. The gains/losses are realized and the new accumulated amount is divided into five parts and the process explained above is continued.

It is important to mention that the stock suited for investment has to meet its buying price during the first year. This is because the overlapping portfolio is formatted the year after and as such it is based on more recent and accurate figures. We also have to consider the possibility that we during the portfolio formation period are not able to meet the buying signal for as many as five shares and consequently the corresponding proportion is kept in the portfolio without any interest.

3.2.1 Motives for formation The decision to keep two overlapping portfolios was made in order to get as many portfolios as possible since Graham stated in his 1976 interview that the assets should be divested if they have not reached their selling point during this period of time of two years (Morris, 1976). By this approach we have a more dynamic strategy since we in this way are able to capture more investment opportunities which results in a more active strategy. We also decided that the stock was forced to fall below its purchase level during the first year since the other portfolio which then was to be formatted had more recent figures to rely on. This decision was also made since the stock would have the suggested time to reach potentially higher levels.

3.3 Data input

3.3.1 Choice of time period studied In order to test the method of value investing in an unbiased way we chose to start at a random year in the past so that we have the ability to construct an adequate number of portfolios. With this reasoning the only limitations in choosing time period of our study was the existence of historical data for our selected key figures. Since these figures should be collectable at a minimum of five years before the year of our portfolio formation period began we chose to start at the year of 1990 since their were considerable amounts of data missing before that. To choose a period prior to that would have left us with conflicting results and as such we decided to start collecting the data needed from that year and forward.

3.3.2 Stock data The data needed for our analysis was collected through the databases used by Datastream. The benefits of using Datastream is that it can easily be integrated with Microsoft excel. This in turn limited the risk for errors when transferring the data and increases our ability to work with the data in an efficient way.

For every study year we started by collecting the market values of all companies listed on the Swedish exchange at the beginning of 1995, these companies were thereafter individually checked to see if they had reported data of EPS and P/E as far as five years back. These stocks were kept and those who did not were deleted. When the set of companies were established we went forward and collected ROE, debt to total assets ratio and current ratio for the last financial year. These accounting numbers were then used in order to further make a selection of the companies that remained after the initial sorting. Market data were then collected in order to move to the second step, the valuation of the selected stocks. The data needed for this part was recorded P/E annual high and low and EPS for the last five year period. In order to perform the test we also required the preceding two years of market high and low prices for the stock so that it can be checked if and to what price an investment would have been made.

3.3.3 Benchmarking index In order to evaluate the result of the two individual portfolios it is of essence for this thesis to make a comparison with the overall market movements. The study is performed on the Swedish market and therefore need to be compared with a well established Swedish index. Aff채rsv채rldens Generalindex (AFGX) is well known and frequently used in studies made on the Swedish market. In addition it is often used by fund managers. AFGX is a weighted index which means that every stock is weighted in accordance to its value on the exchange as a whole. It includes stocks from the major companies on the Stockholm exchange. The index also considers reinvested dividends.

3.4 Approach and Trustworthiness 3.4.1 A deductive and quantitative approach Our study has a deductive approach where we already have created the model and strategy for investing and thus collect the financial data needed for the model in order to select and value the stocks of these selected companies (Jacobsen, 34). Since all input in the model consists of financial figures this research consequently has a quantitative approach (Ibid, 38).

3.4.2 Reliability To give our study reliability, the data has been collected from Datastream which is regarded as a reliable source. In addition a random sample of the collected data has been controlled to different databases used by Datastream as well as the companies own annual reports. Stock prices have also been further checked on the homepages of Aff채rsv채rlden and OMX. These controls have also made sure that the time base for the data is corresponding to our investment dates i.e. so that the EPS used is derived from the past four quarters.

3.4.3 Validity The validity of this thesis refers to how well the theoretical framework corresponds with the empirical. Since the qualitative factors from the margin of safety discussion are excluded from both the selection process as well as the valuation of companies this discussion is of interest. In additions, the strategy used is less dynamic than it would be in reality. Concerning the exclusion of qualitative factors it is of more importance to perform an unbiased research and including them would not fulfil this. For the strategy, this is reduced by investing in two different portfolios parallel every other year. We have also chosen the time period for no other reason that the access to reliable data.

4 THEORETICAL FRAMEWORK In this chapter we describe the theoretical framework and hypothesis related to the Security Analysis and our research. The Efficient Market Hypothesis and Behaviour Finance constitutes for the fundamental background. We further consider the theories of risk and the key figures used in the model.

4.1 The Efficient Market Hypothesis The main discussion in Security Analysis is that the market is not efficient which then would give abnormal price fluctuations. This central argument is based on the Efficient Market Hypothesis (EMH). During the 1960’s Eugene F Fama developed the foundation for the EMH by conducting a series of studies in order to show how stock market prices reflects the available information. These studies were presented in a well known article “Efficient capital markets: A review of the theory and empirical work” (1970).

Fama defines an efficient market as a market in which prices always “fully reflect” all available information (Fama, 1970 pp. 383). The theory states that historical information gives no further value difference for the price of the financial instrument. This leads to that only new information will affect prices. Therefore this theory suggests that all price movements between the releases of new information are random walks and that in the long run it is not possible to receive higher returns than the market (Arnold, 2005). The EMH divides the degree of efficiency of the market into three main categories; weak, semi strong and strong form.

4.1.1 Forms of efficient market Weak-form efficiency: The first and weakest form of efficiency suggests that market prices reflect only information contained in the past. Individual investors are not able to surpass the returns of the market

portfolio by basing their decisions on historical figures alone other than by chance. This would exclude all trading strategies based on historical performance such as technical analysis (Fama, 1970).

Semi-strong efficiency: The semi strong form insists that all relevant public information is reflected in the market price. This means that the price levels are adjusted instantly and correctly when new information concerning the firm is released. The semi-strong form deems that fundamental analysis is futile and the investor can therefore not succeed better than the market. Buying and selling will just induce higher transaction costs (Ibid).

Strong-form efficiency: This form claims that all relevant information which affects the company is reflected in the stock price. With this form even insider trading or individuals having inside information will still not make abnormal returns and hence outperform the market (Ibid).

4.2 Behavioural finance During the last two decades the EMH has been criticised by a large number of researchers. The Nobel price awarded Kahnemann and his co-writer Tversky presented in 1979 the groundbreaking foundations of this approach to market fluctuations where they linked psychological research with economic science. The subject of behavioural finance has become an acknowledge counterpoint to the EMH. The theories that have surfaced upon the discovery of psychological influence on the stock market should not be seen as separate categories. Instead, to fully understand the implications on the market it should be seen as an entirety since there is no single theory that is able to explain the psychological influence on the area of finance.

4.2.1 Prospect theory The ground breaking article mentioned above developed the prospect theory. This theory was a new way to understand how investors act when having to decide between different risky prospects. In their article they criticized the expected utility theory of being unable to explain why individuals tend to be attracted to both insurance and gambling simultaneously. Moreover, they empirically discovered that people differently weigh outcomes that are only probable and outcomes which are obtained with certainty. They further show that value tends to be assigned to gains and losses rather than absolute assets.

One results of Kahnemann and Tverskyâ&#x20AC;&#x2122;s study is a value function which is concave for gains, implying risk aversion, and convex for losses implying risk seeking behaviour. Generally the curve for losses is steeper than for gains meaning that losses have greater impact on individuals utility than gains do.

Figure 1 Value function, (Kahneman et al, 1979)

4.2.3 Herd behaviour An important part of behavioural finance is the concept of herding. It is regarded as a prime component of rational and irrational excess market price deviations. Herding describes in what way individuals are influenced by others to make decisions. This behaviour shows that

people do not base their decisions on their own rationality but rather on the actions of the majority of their surrounding.

The paper by Bikhchandani and Sharma (2001) distinguish herding as spurious or intentional where the difference lies in to what degree investors intend to follow their fellow investors. Spurious herding is a fundamental kind of action taken by a large number of investors that individually have come to the same and most rational conclusion. As such herding behaviour emerges it does not contradict the EMH. It rather supports it since all participants make their own decisions regarding their investment based on fundamental information available to all market participants.

Intentional herding is an inefficient form of decision making where the investor bases his or her decision upon that of others. If an investor has decided to make an investment and the majority of the market has decided not to. When the initial decision to invest is reversed on the grounds of the crowd it is seen as intentional herding. This is a behaviour which contradicts the EMH and therefore creates excess volatility and systematic risk. (Bikhchandani et al, 2001)

The decision to reverse the investment can be further explained by the information cascade phenomenon, which grounds in individuals fears of other individuals knowing more or having different information. This fear influences the decision making individual to reconsider and instead go with the actions of others (Bikhchandani et al, 1992).

Noise trading is a kind of herd behaviour in which the individual investor makes his decision based solely on the observed actions of other market participants and simply just follows the prevailing trend. These investors have doubts in their own ability to make informed decisions and since see it as more informed to follow the crowd and therefore feel as a part of the herd. These uninformed short term traders are a great cause to short term fluctuations in the observed market prices (Froot et al, 1992).

4.2.3 Anchoring Anchoring is a term originating from psychology which has become useful within the field of behavioural finance. It describes the tendency that humans put too much emphasis on a certain piece of information when making a decision. This piece of information can in the absence of any solid news “anchor” in historical information no longer relevant for the present situation. It has been shown that analysts put to much emphasize on past earnings figures so that estimates of future earnings are not revised enough to reflect new information. This leads to positive earnings surprises being more positive than anticipated and negative surprises of being more negative than estimated (Shefrin, 2000 pp. 20).

Research has shown that this tendency can have major impact on investment decisions as well as the valuation process of companies. This in particular when using the discounted cash-flow method analysts tend to adjust the components in the valuation process so that the final price is rather close to the present price instead of working from the bottom up. (Montier, 2002 pp. 5) Due to this phenomenon the Reversed Engineered DCF has been developed in order to counteract the effect of anchoring. It means that the analysts works in the other direction, starting with the present price and work down to discover the impact of each component in the model and from that stand point value what a change in each component affects the pricing of the company. (Montierl, 2002 pp. 9)

4.2.4 Over-confidence/over-optimism People tend to overvalue their capabilities when making investment decisions. The theories stems from a classic study by Lichtenstein Fischoff and Phillips, (1977). In that study they made an experiment by handing out annual reports from 12 companies to professional investors and asked them to make judgements of the companies’ future performance. The result showed that 47 per cent of the judgements where right but as many as 65 per cent felt confident that they were right. This was measured by the mean confidence rating. Literature show that financial analysts and market forecasters’ exhibits a high degree of overconfidence and are therefore not well calibrated (Montier, 2002 pp. 2). According to Odean (1998) overconfidence increases volatility on the market since the turnover in investments tended to be higher for this group of investors. 26

Overconfidence however, appears to be a fundamental factor promoting the high volume of trade we observe in speculative markets. Without such overconfidence, one would think that there would be little trading in financial markets." Shiller (2000)

4.3 Risk theory

4.3.1 Utility theory The utility theory seeks to find in a mathematically way the definition of decision making under uncertainty. It is based on five axioms, the axioms of cardinal utility. These assumptions can be roughly summarized by that the individual investor is assumed to always make completely rational decisions among thousand of alternatives. Further, the expected utility rule states that the decision maker chooses an alternative or strategy which maximizes his or her utility of the outcome (Copeland et al, 2005 pp. 47).

This theory of investor choice can moreover be combined with portfolio sets and thereby maximize expected utility. This is done by combining assets within portfolios in such way that the variances of the chosen portfolios are minimized. However, this theory which is further developed to the Capital Pricing model relies among other assumptions that the market is efficient (Copeland et al, 2005).

4.3.2 Diversification The risk-averse investor seeks to limit his or her risk exposure. An easy way to reduce risk is to spread and thereby diversify ones assets. The decrease in risk through diversification can as well be shown in a mathematical way in the utility theory which shows that as the number of assets in the portfolio increases the variance of the portfolio consequently decreases (Arnold, 2005).

According to (Solnik, 1974) increasing amounts of securities reduces risk but that the effect is more substantial when the initial four securities are composed to a portfolio and that 90 per cent of the diversification effect emerges when the investor holds a portfolio of ten to fifteen different shares. The benefit of holding even more shares is considered to be marginal. The strong effect of diversification by these limited amounts of shares should be seen as positive since a lot of individuals lack sufficient funds for holding an excess amount of shares. In addition the increased transaction costs incurred by an increasing number of shares must also be taken into account. However, the method of diversification is limited to solely deal with 28

the unsystematic risk. The remaining risk which cannot be diversified away is the systematic risk also known as market risk. This brings us to the discussion of international diversification.

4.3.3 International The benefit of diversification by constructing portfolios of international stocks is further considered by Solnik (1974). He shows that the diversification effect is even more significant when constructing portfolios which contain international shares. In this way the systematic risk is reduced since no domestic market exhibits perfect positive correlation with the one of another countryâ&#x20AC;&#x2122;s. He concludes in his study that an internationally assembled portfolio exhibits 50 per cent less risk than a domestically constructed portfolio. According to (Dimson et al, 2002) the Swedish market correlates with the world market by 0.62 (1990-2000) and the same figure for (1996-2000). Two of the markets in the study that Sweden correlates most with are Germany and France by a correlation of 0.76 and the lowest correlation is found in Ireland 0.27 (Ibid).

These findings can as such be used to enhance the effects of

diversification.

4.4 Multiple key figures 4.4.1 P/E Ratio A very commonly used, as well as popular, approach to value stocks is the multiple valuation. There are several common multiples measuring price in relation to some form of performance. In our model for investigating the potential undervalued stocks we use the P/E ratio. This ratio is simply the price of a company divided by its earnings;

P/E ratio =

MarketValue Earnings

The P/E ratio is usually measured on a single stock basis meaning that one divides the share price by the latest reported annual earnings per share. The P/E multiple does not tell whether

the stock is correctly valued but rather how it is valued in relation to the competitive firm’s stocks. Investors estimate a share’s value as the amount they are willing to pay for each unit of earnings (Arnold, 2005 pp. 922). A high P/E suggests that the market is expecting a high earnings growth in the future compared to companies with a lower P/E ratio (Ibid). Koller et al (2005 pp. 371) mean that multiples are frequently misused and misunderstood. The reason for this is that some analysts tend to calculate an industry average P/E ratio and use this figure as a basis for establishing the fair value for a company. An industry average does not take into account that companies in the same industry can vary dramatically in their expected growth rate, return on invested capital and capital structure. The P/E ratio is as shown above based on a company’s earnings. Earning or net income is an accounting figure including operating and non-operating items. This bring two dimensions of criticism of the P/E multiple. Firstly, since earnings include the non-operating items of a company their actual operating performance usually measured by Return on Invested Capital might differ though the earnings of two companies are comparable. Secondly, due to different accounting standards as well as different tax levels earnings of two comparable companies from different countries can differ due to that aspect as well.

4.4.2 Current ratio The current ratio is an accounting ratio defined as the current assets divided by current liabilities. It is designed to measure the ability to meet obligations through the liquidation of assets. Critiques of this measure say it is a static view of liquidity based only on balance sheet figures for a given point in time and rather suggests to measure liquidity of an ongoing concern by the company’s capacity to cover current liabilities with cash flows. (Lancastere et al, pp. 28). There is no strict boarder of good or bad Current ratio value but a values below one usually rise concern of the liquidity and thereby the ability of paying the obligations.

5 EMPIRICAL FINDINGS The following chapter concretizes the results from our study. It shows and describes the results of the selected companies as well the investments portfolios. The last show the return of the combined and individual portfolios compared to the market index.

5.1 The model in practice To further emphasize exactly how the model functions we have added an illustrated example below. Allgon was one of the companies to pass through the initial hurdles in 1999. As the figure shows, the company had quite stabile and increasing earnings during the test period which consisted of the five years prior to 1999. The calculated variance of 0,914 shows that the relative magnitude of the deviations over time is at a satisfactory level. The historical P/E numbers from 1994 to 1998 are combined to make an average and it is then multiplied with the margin of safety figure of 0.8. 1999-01-01 Year Company ALLGON AB EPS Variance

P/E High Low

Stock price Sell Buy

112,5185 75,01232

1994 1

1995 2

1996 3

1997 4

1998 5

2,6

2,1 0,192

3 0,429

3,8 0,267

3,7 0,026

31,35 12,37

42,14 20,95

27,42 14

36,84 20,92

33,92 13,51

jan-99

Mkt price Closing 1999-01-01 High 80,5 Low

Sum 15,2 0,914

Average P/E

1999 171,5 75

Average 1,092

25,342

2000 279 74

Figure 2. An illustrative example of the model

The next step is to combine the EPS for 1998 with the calculated figure from the previous step. This forms the level of purchase at 75 SEK. This figure is then multiplied with 1.5 to compute the level of 112.5 SEK which is the level for divestment of the asset at hand following that 80 to 120 percent range of the central value.

At the bottom right are the future market price highs and lows and the current market price at the date for the portfolio formation. The closing price of 80.5 SEK at the end of 1998 is 31

slightly higher than that of our investment level. Following the daily close we found that the target price of 75 SEK was hit in mid January 1999 and the asset was added to the portfolio. Consequently the market price high of 171.5 SEK was hit after our purchase level and since it is higher than the level of 112.5 SEK that the model decided to sell for, the 50 per cent gain is realised during the first year.

5.2 Company selection As can be seen from the table below the number of companies that passes the initial hurdles of market cap of one billion SEK, ROE higher than 15 per cent, current ratio above 1.5 and a debt to equity ratio of maximum 50 per cent are quite few when compared to the overall number of shares listed. The number of companies that passes are pretty steady and the average selection of companies are 17 with a median value of 18.

Portfolio formation period 95--97 96--98 97--99 98--00 99--01 00--02 01--03 02--04 03--05 04--06 05--07

Number of companies passing the initial hurdles 21 19 18 18 20 19 18 10 12 15 21

Number of companies invested in 5 5 2 3 4 5 5 5 4 2 3

Table 1

The table shows that the 2001 crash affected the number of companies that met our hurdles. The settling market levels left us with only 10 potential candidates for our portfolio in 2002; a drop of 44 per cent in a single year. Yet the portfolio was filled with 5 stocks that investment period. This effect of few companies passing the hurdles was persistent until the start of 2005.

We were also able to conclude that some companies were recurrent in the study after the initial hurdles were conducted. One of the companies passed the hurdles for every single year from 1995 to 2005, that company was the clothing chain Hennes & Mauritz (H&M). Exhibit A shows this in detail.

5.3 Investment return The empirical results of the value investing strategy performed in this thesis are demonstrated in the diagrams 1, 2 and 3 below. Diagram 1 (portfolios versus index return) shows the return of each portfolio in comparison with the return for the index for each investment period of two years. The diagram show that out of eleven studied periods our portfolios perform better than the AFGX in five periods. Two of these years contain negative results where our portfolios make losses of 6 and 5 per cent respectively. This can be compared with the losses of the AFGX which reaches 48 and 19 per cent respectively in the same period. We are also able to conclude that AFGX exhibits greater fluctuations than our portfolios.

Portfolio vs. Index Return

Return 100%

80%

60%

40%

20%

-20%

19951997

19961998

19971999

19982000

19992001

20002002

20012003

20022004

20032005

20042006

20052007

-40%

-60%

Time period

Portf olio Return

AFGX Return

Diagram 1

Diagram 2 and 3 shows the accumulated returns for each portfolio. The time base for the comparing index follows that of the portfolio it is compared with. These two diagrams measures and compares the actual performance. The performance of Portfolio A is shown in Diagram 2. The time period lasts 12 years form the 1st of January 1995 to the 31st of December 2006. Investing 100 000 SEK in Portfolio A would have yielded 472 000. The return of AFGX would have yielded 431 000. This result in that Portfolio A outperforms

AFGX by 9.5 per cent during this 12 year period. Worth noting is the difference in fluctuations over the studied period.

Portfolio A vs AFGX

Value 500 400 300 200 100 0 1995

1997

1999

2001

2003

2005

2007

Year Portfolio A

AFGX

Diagram 2

Portfolio B which only lasts for a ten year period, January 1st 1996 to December 31st 2005, does not outperform AFGX. The return of AFGX surpass Portfolio B by some 8.5 percent yielding, in absolute measures, 293 000 SEK compared to 270 000 SEK. As portfolio A, portfolio B exhibits less volatility in returns than AFGX.

Portfolio B vs AFGX

Value

350 300 250 200 150 100 50 0 1996

1998

2000

2002

2004

2006

Year Portfolio B

AFGX

Diagram 3

Altogether investing according to the original strategy by starting with an initial amount of 200 000 SEK and investing half of that amount in each portfolio and further considering the

whole 12 year period as our investing period the results for the combined portfolios are 741 000 SEK. The same initial amount would have yielded 724 000 SEK if invested in AFGX. The difference in the end is 2.3 per cent over the period. The annual compounded return of our combined portfolio was 18.2 per cent.

It is essential to be aware of the weaknesses of our portfolios when compared to AFGX. Firstly, the return on the portfolios is not the total return since they do not include dividends. Secondly, due to the strategy requiring five investments each period with no possibility to reinvest the required return is often reached before the end of the period. In addition, if not five of the representative stocks reach the suggested price level for purchase, the funds will not yield any return at all during these two years.

To give a measure of the inefficiency we performed the same strategy with portfolios only containing three stocks each investment period. The three stocks were as well chosen on the basis of best stability indicator or first to reach the suggested buying level. The results for the combined portfolio strategy as above were 991 625 SEK compared to the 724 000 SEK for the initial five asset portfolio. The three stock strategy thereby outperformed the AFGX by 37 per cent. The annual return for this strategy was 21,1 per cent. Se Exhibit B.

6 ANALYSIS This part begins with a discussion about the results for the two portfolios. The realized return is further analyzed and discussed. The model and its implications are analyzed by tying it to earlier research and the related theories, certainly those associated with market fluctuations which proved to be essential for this study.

6.1 Results Not only did we under a 12 year period achieve to beat the market but we also have to take into consideration that the model and strategy used have some discrepancies with reality such as the exclusion of dividends and the rather long periods of holding inactive cash. We assess these discrepancies to be in favour of the model and consequently taking them into consideration the portfolios would have beaten the index even more.

6.1.1 Dividends We have reasons to believe that the selected securities having passed the hurdles are securities paying out dividends exceeding the average amount on the market. These companies perform high and stable earnings in combination with low debt and high current ratio. This means that these securities do not belong to the group of companies being in rapid growth stages and consequently not in the urgent need for funds.

6.1.2 Investment analysis The strategy used to perform test is designed to give high reliability and thus we were not able to be as dynamic as we would have been in real life. However, following the value investing methodology described in this paper in reality has a great possibility in succeeding even better. First of all the strategy used here only makes the selection of representative securities

once a year based the most recent figures at that time, January 1st. The information from companiesâ&#x20AC;&#x2122; quarterly reports might open the doors for more investment opportunities and thereby increase the efficient use of capital.

Moreover, the strategy requires five investments each period. These five securities often reach their level of purchase late during the first year and are often sold before the end of the second year. In this way funds miss out on new investment opportunities appearing during the year which further could be included and most likely increase the return. In addition, out of the total 11 investment years there are as much as 6 occasions where the portfolio does not reach its requirement of five different securities for each period. This sequentially leads to funds not being used at all and as a consequence does not yield any rate of return. An example of this is can be viewed in exhibit A, investment period 2004 â&#x20AC;&#x201C; 2006, where only two investments are made. Their average return for the 2 securities we hold is well over 40 per cent but, since 3/5 of the capital is held un-invested, the total return for portfolio B that year is only 18 per cent.

The three stock portfolio: To give a measure of the inefficiency of holding cash un-invested we decided to see what would happen if we computed portfolios which required only three stocks. This strategy showed remarkably better results. Outperforming the AFGX by a full 37 per cent during the whole period and resulting in an annual return for this strategy of 21.1 per cent. It shows that being more dynamic by having a more active investment approach is likely to improve returns. But this action further limits the benefits of the diversification principles.

6.2 Model The model being used including the security selection process is undoubtedly simple though very efficient. By sorting out companies showing high earnings using the ROE hurdles in combination with low debt and default risk in the debt to total assets and current ratio hurdles, the only securities we are dealing with become those that are regarded as highly safe by the market. In addition to this we add the two stability hurdles, the market capitalization and earnings stability indicator. This means that we to the most possible extent isolate the model and investment strategy to focus on market fluctuations. These fluctuations we believe are due 37

to two main reasons, systematic influences and behavioural matters influencing the whole market or the particular security. These market aspects will be further discussed in the market analysis section.

The study period includes two periods of bull markets. Generally, the performance of our model is weaker during these periods of rapid price increases. These are also the periods when less than five securities are obtained, suggesting that our model believes that the market is overvalued. Though, as mentioned as a cause to why the model does not purchase sufficient amount of securities but on the other hand it follows the theories of Graham (1948) and Graham and Dodd (1951).

The only time periods during our study when the market index was showing losses were during the years of market collapse, 2000 to 2003. During the study periods 2000-2002, 20012003 and 2002-2004 AFGX declined 27, 48 and 19 per cent respectively. Our portfolios only showed negative returns during the two latter time periods but at a much more moderate level, 6 and 5 per cent respectively. Only 7 out of the total amount of 15 securities during this period gave negative returns. From this point of view the model we have created once again follows the general theories of security analysis of avoiding the bull market peaks and resisting market declines. This shows how the model follows the desired strategy of the rational investor explained in the Security Analysis. Interestingly, Berkshire Hathaway showed a similar trend during this period.

6.2.1 Critics to the model When using the model there are certain situations that need special care. If there are dramatic changes for companies that occur in the negative direction the model is not able to undertake these in satisfying manner. To exemplify this we will show the situation for Ericsson during the market crash (Figure 2).

2001-01-01 Year Fรถretag ERICSSON AB EPS Variance

P/E High Low

Stock price Sell Buy

1996 1 0,656

29,02 16,44

91,12808 60,75205

jan-01

1997 2

1998 3

1999 4

2000 5

1,097 1,203 1,114 0,672256 0,096627 0,073982

1,928 0,7307

30,86 17,08

39,56 18,32

88,98 28,44

Sum 5,998 1,573565154

85,67 39,51

Market price Closing 2001-01-01 High 83 Low

Average P/E

88,111 23,183

Average 1,309335

39,388

44,778 Closing 2003-01-01 2,96 7,25

Figure 2 Ericsson in the beginning of its big fall

At the standpoint when we make our decision Ericsson still shows a positive result for earnings even though the stock price has fallen dramatically during the last three quarters. We can se that the level for purchase for the Ericsson stock is at 60 SEK. This price is based on the last reported earnings and due to stable earnings in the past the stability indicator shows no reason to worry. But since Ericsson was traded the past two years at PE multiples over 80 the model suggests a PE average of 39. By analyzing the PE ratios from before the rally starting during 1999 an average PE of 39 seems far too high.

In the case of Ericsson the investment never went through thanks to that five other selected companies fell below the purchasing level before Ericsson. However there is another situation worth noting. H&M which has been a forerunner passing all hurdles every year by showing almost no debt, high returns and still keeping a high current ratio. Before the bubble 1999 to 2002 H&M never fell to the price level set by the model. During the Bull market 1999 and 2000 H&M traded at an earnings multiple above 100 resulting in that our level for purchase increased dramatically as in the case with Ericsson. The outcome of this became that H&M as well fell below suggested buying levels the remaining three years. In contrast to Ericsson this was an advantage to our results.

The model and these two examples are linked to theory in two ways. According to the Margin of Safety theory the importance of regarding the qualitative factors are shown. By being aware of extreme PE multiples in the past one can make own adjustments and judgements changing the opinion of making an investment or not. On the other hand, considering the theories of anchoring, personal judgements during this time period were likely to be irrational indeed. We have reason to believe most investors in Sweden were not able to foresee the

magnitude of the bear market and still had the price levels of 160 as a reference. This would mean that buying below 80 SEK looked like an attractive price level showing an example of anchoring.

6.2.2 The use of financial ratios Despite the critics of the P/E ratio as a valid tool for valuing securities we asses the usage of P/E multiples to oversee this criticism. Given that we have sorted out stable companies which show a capital structure with low levels of debt and which are primarily listed on the Swedish stock market they have their accounting figures are reliable. Moreover the model only looks upon the historical P/E measures for the individual company and not comparing it with othersâ&#x20AC;&#x2122;. These multiples give a fair indication of the market fluctuations where some companies are valued very differently from time to time although they seem to perform similarly.

The current ratio is sufficient also for two reasons. Due to the relatively short investment horizon in combination with low debt and high ROE we are reasonably certain that the companies operations generate sufficient capital to pay their obligations two years ahead.

6.3 Analysing risk The theories related to risk have different views on this matter. The utility theory and CAPM model does not agree with that purchasing a security at an abnormally low price would decrease the risk as described within the value investing framework. As discussed according to the utility theory this event increases the risk since the variance increases. The fracture between these two theories boils down to that security analysis make a distinction between stocks. Security analysis makes the distinction between safe stocks and stocks regarded as not safe enough. The CAPM only considers the individual securityâ&#x20AC;&#x2122;s variance to that of the market, measured as beta.

6.3.1 Portfolio risk When looking at the investment results for this investigation, both portfolios show less variation over time than that of the market index. By just looking at the graphs this suggests that CAPM would give our portfolios a beta lower than one. This conclusion could be drawn since our combined portfolio perform worse in bull markets and better in bear markets without short selling or borrowing. If this is true our portfolios should be unable to beat the market index in the long run according to the EMH. Since our combined portfolio is able to beat the market it would indicate that the market is inefficient. But we also have to consider that this is not sufficient proof since the EMH theories states that it can be beaten by mere chance.

6.3.2 Market risk Security analysis does neither include a discussion about the market risk and nor supply ways of managing it. According to the utility theory (CAPM), under its assumptions, it is not possible to reduce the systematic risk by diversification. As we will show below the benefits of international diversification might reduce this risk for value investing strategies.

6.3.3 Diversification Both the theory of diversification and Security analysis recommend holding 15 different securities. The median figure for companies that passed the initial hurdles during the time for this study was 18. The possibility of 80 per cent of these companies to fall below the level of purchase was not very likely. As table 1 shows we were not able to have full portfolios during the study consisting of five shares. The relatively low number of shares within the portfolio limits the diversification effect.

Although the model does not benefit from a full diversification effect we were surprised to see from our results that our portfolios displayed less volatility (diagram 2 and 3) than the overall market index. In the initial process of developing this method we expected to see less fluctuation in our portfolios since that was in accordance with the theory of value investing but we revised that belief when the number of stocks fell well below the recommended 10. As

such we were both surprised and pleased to see that the portfolios were behaving as initially expected.

This might be explained by the fact that our hurdles make us focus on larger and more established companies than the average company on the market. These companies are often less volatile since they often stem from more established industries.

6.4 The market Fluctuations on the market are of the essence for value investing as well as this research. The whole investigation and the test depend on securities that temporarily become undervalued. This opens up for the discussion of to what extent the market fluctuations tend to be greater than motivated and if this creates a gap between the price and the true value of securities. We discovered at an early stage, before computing the selected companies that almost all of them fluctuated in their highest and lowest recorded PE multiple by about 50 per cent. The question was then whether they would fluctuate at ranges suitable for the model.

6.4.1 The Market and Irrational behaviour In the theory part of this thesis we introduce the concept of behavioural finance which might partly explain the great volatility on the market. These are often connected with actions of irrational investors. The following is a transcript from the speech that Warren Buffet held at Columbia University.

When a price of a stock can be influenced by a herd on wall street with prices set by the margin by the most emotional or the greediest person or the most depressed person it is hard to argue that the market always prices rationally in fact market prices are frequently nonsensical (Buffet, 1984).

So are the price changes that we find in our study a sign of irrational behaviour? It can be concluded that the market during our studied period exhibited great swings away from fundamental values. These are according to theory greatly enhanced by the uninformed

investor and come in the form of herding, overconfidence and anchoring. We believe that these theories have some explanation to the success of value investing.

It is interesting that Graham and Dodd as early as the 1930â&#x20AC;&#x2122; developed a strategy based on the theories not yet developed but some decades later come to play a central role for the science of economic and finance.

7 CONCLUSION To conclude this thesis about the value investing strategy we in this chapter summarize the model based on our empirical findings and the analysis. At the end some suggestions for further research are presented.

7.1 Concluding remarks The aim for this thesis was to investigate how the value investing concept could be applied on the Swedish market and to benchmark against a well established index.

The results of this study were convincing; by creating a model based on the value investing principles our portfolio was during a twelve year period able to beat the Swedish market index AFGX. However this model had to be modified in order to be implemented on the Swedish market. Therefore we are not able to safely conclude that it breached the efficient market hypothesis but the results suggest that the weak form of market efficiency is under scrutiny. We were also able to conclude that the individual portfolios exhibited less variation than the market. Relating risk to variance our study shows a less risky portfolio giving a higher return than the market. This adds another argument to question the efficiency of the market.

As we concluded in our analysis the Swedish market is too small to effectively implement this strategy. The lack of companies meeting the requirements of the value investing model is the main issue for our study. This makes it inevitable to go abroad to seek potential investments. Investors tend to be biased towards their home market, but the internationalization of stock markets and the ongoing consolidation within the industry will most definitely make it easier for investors to pass borders to make their investments.

During the process of writing this thesis OMX, the owner of the Stockholm exchange, was under a friendly takeover by NASDAQ (Adler, 2007). If this deal were to be accepted by its owners a giant covering several markets would be formed and consequently make it easier for

Swedish investors to invest internationally and thus more efficiently use value investing strategies. This would give great diversification advantages.

One of the advantages of the model is that it limits the investors need and tendencies of making personal and irrational assessments of the company studied. The investorâ&#x20AC;&#x2122;s decision will solely be based upon the actual figures. This will serve to prevent the investor to be burdened by the different psychological factors brought forward by the behavioural finance theories. It will rather give him or her opportunities to benefit from these exaggerated market movements explained by behavioural finance theories. The question is if the individual investor is able to withstand the substantial information flows that emerge in times of great bull markets as can be seen on the Stockholm exchange at present.

To conclude the analysis related to the model and strategy we asses the model to be a very helpful tool in the matter of guiding the investor to invest safely and rationally.

7.2 Further Studies When having worked closely with the model for some time a lot of questions arise during the process. These questions circle around the possibilities of implementing value investing more efficiently. Apart from the most natural suggestion of taking this study further to a larger market we also suggest as a future theme for research, the margin of security level in the valuation part of the model. We believe that there could be a more optimal range than investing at 80 per cent and divesting at 120 per cent of the central value.

The second suggestion derives from the stock selection part of the model. We clearly discovered that firms from certain industries were continuously sorted out due to their capital structure. We therefore assume that the hurdles sorting out representative companies should be adjusted for different industries such as firms within the financial sector and real estate companies deserve other levels of debt to total asset. Thus we suggest researchers to investigate in optimal levels for these hurdles yet giving the wanted effect of margin of safety.

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Bikhchandani, S. Hirshleifer, D and Welch, I (1992) “A Theory of Fads, Fashion, Custom and Cultural Change as Information Cascades” The Journal of Political Economy, October 1992, pp. 992-1026.

Bogle, J (2005) The Intelligent Investor by Benjamin Graham; Foreword HarperCollins Publishers Inc.

Buttet, W. E (1984) “The Superinvestors of Graham and Doddsville” Hermes – Columbia Business School Magazine, 1984, pp. 3-15. De Bondt,W. F. M. and Thaler, R (1985) “Does the stock market overreact?” The Journal of Finance, 40(3), 793–805. Copeland, T. E. Shastri, K. and Weston, F. J (2005, 4th edition) Financial Theory and Corporate Policy Pearson Education Limited.

Dimson, E. Marsh, P. and Staunton, M (2002) Triumph of the Optimist: 101 Years of Global Investment Returns Princeton University Press, 2002.

Fama, Eugene F (1970) “Efficient Capital Markets: A Review of Theory and Empirical Work”. The Journal of Finance, May 1970, pp. 383-417.

Fischhoff, B. Slovic, P. and Lichtenstein, S (1977) “Knowing with certainty: the appropriateness of extreme confidence”. Journal of Experimental Psychology, Human Precision and Performance, 1977:4, pp. 552–564.

Froot, K.A. Scharfstein, D.S. and Stein, J.C (1992) “Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation” The Journal of Finance, September 1992, pp. 1461-1484. Graham, B (1949) The Intelligent Investor HarperCollins Publishers Inc.

Jacobsen, D. I (2002) Vad hur och varför? Studentlitteratur.

Kahnemann, D. and Tversky, A (1979) ”Prospect theory: Analysis of Decision Under Risk”. Econometrica, March 1979, pp. 263-291. Koller, T. Goedhart, M. and Wessels, D (2005 4th edition) Valuation John Wiley & Sons.

Montier, J (2002) Behavioural Finance John Wiley & Sons Ltd.

Morris, V. F (1976) “A proposed Revision of Benjamin Graham’s 1974 Valuation Formula” Financial Analyst Journal, November 1976, pp. 21.

Odean, T (1998) “Volume volatility, price and profit when all traders are above average” Journal of Finance, December 1998.

Price, J and Kelly E, (2004) “Warren Buffett: Investment Genius or Statistical Anomaly?”.

Shefrin, H (2000) Beyond Greed and Fear Harvard Business School Press.

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Solnik, B.H (1974) “Why not Diversify Internationally rather than Domestically?” Financial Analyst Journal, 1974, pp. 48-54.

Databases

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Internet references

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Adler, J. (2007) ”Nasdaq köper OMX” Dagens Industri (http://www.di.se/nyheter, 2007 05 27)

Forbes ”The Worlds Billionaires” (http://www.forbes.com/lists/2007/10/07billionaires_The-Worlds-Billionaires_Rank.html, 2007 04 19) Kennon, J ”Warren Buffet Biography” http://beginnersinvest.about.com/cs/warrenbuffett/a/aawarrenbio_3.htm (2007 04 25) Pitzke, M (2006) ”Investor to Give Away Fortune” Spiegel Online (http://www.spiegel.de/international/0,1518,423682,00.html, 2007 04 23)

The Herald Tribune (2006) “Shares of Warren Buffet's Berkshire Hathaway close at record $100,000” The Associated Press (http://www.iht.com/articles/ap/2006/10/23/business/NA_FIN_US_Berkshire_Stock.php, 2007 04 19)

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EXHIBIT A Porfolia A

Portfolio B

Strategy 5 investments per year for 2 years

Stock

year 95

ASTRA AB INVESTMENT AB LATOUR PHARMACIA AB SSAB SVENSKT STAL AB ERICSSON AB

1,95 2,60 0,45 11,12 3,90

1,54 2,16 1,58 1,33 1,93

ERICSSON AB SANDVIK AB SECO TOOLS AB HALDEX AB INVESTMENT AB LATOUR

5,94 1,26 1,57 2,43 3,69

1,74 1,94 2,07 1,66 1,58

INDUSTRIVARDEN AB INVESTMENT AB LATOUR Only 2 companies passed the hurdles

3,47 4,62

1,50 1,22

Adjusted one year

year 96

year 97

year 98

ALLGON AB LINDAB AB SECO TOOLS AB

year 99

year 00

year 01

year 02

year 03

year 04

ALLGON AB ELDON AB HALDEX AB LINDAB AB

(Due to time priority)

Stability

1,03 1,31 1,18

1,50 1,50 1,32

0,48 0,41 1,15 0,80

1,50 1,50 1,50 1,28

Capital in

100 000

Capital out

170 593

Capital in

100 000

Capital out

179 845

Capital in

170 593

Capital out

195 098

Capital in

179 845

Capital out

227 486

Capital in

195 098

Capital out

264 532

ELECTROLUX AB HOGANAS AB IBS AB SANDVIK AB WM-DATA AB

9,22 0,40 6,13 0,27 1,33

1,50 1,20 0,76 1,21 0,59

Capital in

227 486

Capital out

239 775

AB LINDEX HOGANAS AB JM AB OEM-INTERNATIONAL AB PEAB AB

1,10 0,73 2,35 0,76 1,77

0,96 0,84 0,68 0,64 1,56

Capital in

264 532

Capital out

247 501

B&B TOOLS AB HENNES & MAURITZ AB JM AB SANDVIK AB TV4 AB

1,02 1,02 1,84 0,55 0,55

1,12 1,00 0,44 1,17 1,02

Capital in

239 775

Capital out

228 022

ELECTROLUX AB HENNES & MAURITZ AB KARLSHAMNS AB NEW WAVE GROUP AB

0,43 1,16 2,12 2,09

1,19 1,29 1,38 1,50

Capital in

247 501

Capital out

314 492

Capital in

228 022

Capital out

269 675

Capital in

314 492

Capital out

472 130

ELECTROLUX AB HENNES & MAURITZ AB

0,36 0,94

1,37 1,54

Only 2 companies passed the hurdles

year 05

Total portfolio return

Return/Loss (1+return percentage)

HENNES & MAURITZ AB HOGANAS AB SSAB SVENSKT STAL AB

1,25 0,28 3,00

1,51 1,04 2,96

Total return Return Portfolia A Return PortfolioB

372% 170%

AFGX

AFGX Return 84,7

71%

138

63%

100

80%

172,2

72%

138

14%

190,4

38%

172,2

26%

316,3

84%

190,4

36%

277,7

46%

316,3

231,4

-27%

277,7

-6%

145,2

-48%

231,4

-5%

188,4

-19%

145,2

27%

221,2

52%

188,4

18%

293,4

56%

221,2

50%

365,3

65%

AFGX 95-07 AFGX 96-06

331% 193%

271%

EXHIBIT B Porfolia A

Portfolio B

Strategy 3 investments per year for 2 years

Stock

year 95

ASTRA AB INVESTMENT AB LATOUR PHARMACIA AB

1,95 2,60 0,45

1,54 2,16 1,58

Capital in

SANDVIK AB SECO TOOLS AB HALDEX AB

1,26 1,57 2,43

1,94 2,07 1,66

Capital in Capital out

189043,8

3,47 4,62

1,50 1,22

Capital in

175869,6

Capital out

217974,5

year 96

year 97

year 98

year 99

year 00

year 01

year 02

year 03

year 04

year 05

Stability

INDUSTRIVARDEN AB INVESTMENT AB LATOUR Only 2 companies passed the hurdles

Return/Loss

Capital out

100000 175869,6

100000

ALLGON AB LINDAB AB SECO TOOLS AB

1,03 1,31 1,18

1,50 1,50 1,32

Capital in

189043,8

Capital out

272507,7

ALLGON AB ELDON AB LINDAB AB

0,48 0,41 0,80

1,50 1,50 1,28

Capital in

217974,5

Capital out

310937,6

9,22 0,40 0,27

1,50 1,20 1,21

Capital in

272507,7

AB LINDEX HOGANAS AB OEM-INTERNATIONAL AB

1,10 0,73 0,76

0,96 0,84 0,64

Capital in

310937,6

Capital out

252747,7

B&B TOOLS AB HENNES & MAURITZ AB JM AB

1,02 1,02 1,84

1,12 1,00 0,44

Capital in Capital out

303404,6

ELECTROLUX AB HENNES & MAURITZ AB KARLSHAMNS AB

0,43 1,16 2,12

1,19 1,29 1,38

Capital in

252747,7

Capital out

324640,8

ELECTROLUX AB HENNES & MAURITZ AB Only 2 companies passed the hurdles

0,36 0,94

1,37 1,54

Capital in

303404,6

Capital out

395776,6

Capital in

324640,8

Capital out

595848,9

(Due to time priority) ELECTROLUX AB HOGANAS AB SANDVIK AB

HENNES & MAURITZ AB HOGANAS AB SSAB SVENSKT STAL AB

1,25 0,28 3,00

1,51 1,04 2,96

Capital out

Total return Return Portfolia A Return PortfolioB

496% 296%

Absolute combined return 991 625

0,758696

0,890438

0,23941

0,441505

0,426486

355337

0,303952

-0,18714

355337 -0,14615

0,284446

0,304451

0,83541

396% AFGX 95-07 AFGX 96-06

331% 193%