Contrarian Investing Strategies in the Indian Stock Market

Transcription

1 Master Thesis Aarhus School of Business and Social Sciences, Aarhus University Msc in Finance, Department of Business Studies July 2011 Contrarian Investing Strategies in the Indian Stock Market Dziugas Tornau Supervised by: Stig Vinther Møller Aarhus School of Business and Social Sciences, Aarhus University 2011

2 Contents Section 1 - Introduction... 4 Abstract... 4 Objectives and goals... 6 Problem statement... 7 Empirical research, limitations and basis of theory and literature reviewed... 8 Structure... 8 Section 2 Classical and Behavioral finance theory overview Classical finance theory Market Efficiency Random Walk Hypothesis Capital Asset Pricing Model (CAPM) Behavioral finance theory Prospect Theory Herding and overreaction Limits to Arbitrage Section 3 What is contrarian investing? Motivation towards stock markets Value super investors Review of literature on market inefficiencies and value premium Section 4 Empirical research India s position in the global economy Bombay Stock Exchange and Sensex index Data applied Mean Reversion testing Discussion on mean reversion testing results Value premium and Betas One year holding strategy Equally weighted portfolios and Betas Value weighted portfolios and Betas Two year holding strategy Equally weighted portfolios and Betas

3 Value weighted portfolios and Betas years holding strategy Equally weighted portfolios and Betas Value weighted portfolios and Betas Portfolio Market Values Summary of the results Section 5 - Discussion on the reasons behind the results Classical finance approach Emerging markets study Bad states of the economy Behavioral finance approach Section 6 Discussion on rationality in economics and conclusion Rationality in economics, other disciplines and further research Conclusion Literature Appendixes

4 Section 1 - Introduction Abstract For a few decades value stock return premium over the growth stocks was reported in separate developed markets, internationally and in emerging markets by studies of J. Lakonishok et al (1994), E. Fama and K. French (1992, 1998) and others. B. Graham and D. Dodd started arguing on value investing as a successful investing discipline already in the early 1930s. Value investing is a process of buying stocks with low Price to Earnings, Price to Book Value, Price to Cash Earnings and other financial ratios and holding them to gain superior profits. It is also called contrarian investing style, in other words, looking for fundamentally undervalued stocks in the market. Most of the researchers and practitioners agree that such premium exists in the stock markets however there is no universal agreement on the causes of such phenomenon. The main objective of this thesis is to see whether value premium is present in the Indian stock market since the liberalization of it in the early 1990s. I failed to find any similar research done on the Indian stock market. Additionally, I look into the reasons for the value premium whether it can be explained by higher levels of fundamental risk and classical (also called modern) financial theory or can the reasons for market inefficiencies be based on irrationality of market participants and the groundwork of behavioral finance theorists. The concept of rationality in economic theory is also discussed. My empirical research is based on the Bombay Stock Exchange Sensex index composed of 30 large capitalization and liquid stocks from major sectors of economic activity. After sorting the stocks to value and growth portfolios and analyzing the holding strategies of one, two and three years I report an existing value premium, however the statistical tests do not confirm it to be significant. Extreme persistent volatility in the returns and small data sample can partly explain such test results. I also find an indication of value stocks carrying more fundamental risk, yet only for some cases of portfolios sorted on Price to Book 4

5 Value and Price to Cash Earnings ratios. Consequently, the behavioral finance theory is used to explain the reasons for the value premium found comparing value and growth portfolios sorted on Price to Earnings and Asset Growth financial ratios. Such factors as extrapolation, herding, overconfidence, framing, cultural differences, corporate governance and corruption are discussed as possible reasons for inefficiencies in the Indian stock market which lead to deviations from fundamental values and the existence of value premium. 5

6 Objectives and goals The main objective of this thesis is to prove that value investing strategies outperform growth strategies in Indian stock market and to compare the findings to similar studies carried out by J. Lakonishok et al (1991, 1994, 2004), Fama and French (1992, 1998 and others) and others which report existence of value premium in such markets as USA, developed European countries, Japan and some of emerging markets. Since India is one of the major developing markets in the world now, it is interesting to see whether similar findings can be obtained here as so far I know of no similar research done on the data of stock markets in this country. I use a simplified version of method of J. Lakonishok et al (1994) while comparing the value and growth portfolios. Additionally, for explanations of the value premium I use a wide selection of behavioral finance theory in contrast to classical financial explanations and aim to get a better understanding of how markets work in general and how the concept of rationality is developing in economic theory. By analyzing the value premium and market inefficiencies, the goal is not only to create a study with precise empirical outcome, but also to try to understand and explain the main psychological, social, cultural and other behavioral factors driving the financial markets and what reasoning lies under the choices made by market participants. By trying to achieve above goals, I am also willing to get a better understanding of yet quite untouched by academic financial literature Indian market by reviewing its recent development and position in today s world s economy. The existence of value premium in Indian stock market would prove that it has similar movements to the rest of the world s markets. Also, it would strengthen the idea that better performance of value stocks is not just sample related outcome and does not come from data mining. 6

7 Problem statement The main, leading, questions in this study are the following: Do the value investment strategies produce better results than growth investment strategies in the Indian stock markets? What is the reason for that greater risk or irrational choices made by market participants? While trying to answer the main questions a number of additional problems arise: What is value investing as such and what is the philosophy behind it? What financial theory is relevant to analyze it? Does the performance of value and growth stocks in Indian stock market goes in parallel with the findings of studies carried out with stock market data from USA, European markets, Japan and other emerging markets? What is the history of Indian stock market? Does it show a tendency to mean revert? Are there opportunities for successful long term value investing? After reviewing the results of the empirical study I will try to discuss whether the behavioral finance theories can explain the value premium, or it can be better explained by classical financial theory. Since the irrationality of market participants is a subject of my keen interest, the problem of perception of the concept of human mind in economics will also be touched. 7

8 Empirical research, limitations and basis of theory and literature reviewed The empirical research is based on data for companies listed in Bombay Stock Exchange Sensex Index which is extracted from DataStream database and therefore is susceptive to any changes or errors in the database. A full description of data extracted and financial measures used follows alongside the empirical research part of my work. I want to emphasize that I do not aim to create new theories or methods, but I am trying to use the ones already developed in the field and apply it to an unexplored market. I also try to put higher emphasis on reviewing behavioral theories as these studies are currently emerging as mainstream and historically were less touched and discussed in relation to standard finance which has been taught and analyzed for decades. Trying to get more insight to the field of research, I review not only large number of scientific articles published in solid academic journals and academic books related to the topic, but also sources of statistical data from governmental websites of United Kingdom, publications of inter-governmental organizations such as International Monetary Fund and non-governmental organizations such as Transparency international. Structure The structure is set to lead from the introduction to the main ideas of classic financial theories, comparing it to behavioral finance theory and presenting what are the contrarian investment strategies. The overview of the Indian stock market introduces the empirical part of the thesis followed by statistical tests on mean reversion, value premium and systematic risk in the market. The interpretation of the test results are provided afterwards. Before the main conclusions I also provide a discussion on the concept of rationality in economic theory. The sections will be set not only to follow each other in a continuous string, but also to complement and in some ways contradict with each other. Section 1 is introductory and sections 2 and 3 will be based on presenting different theories and strategies based on the reviewed literature. Section 4 is my own empirical study in 8

9 the Indian stock market. Section 5 will provide a discussion on the reasons of the results of the empirical research and section 6 will conclude the whole study, point out the most interesting lessons learned and insights gained and also discuss the opportunities of future research in the field. Structure scheme: Section 1 Abstract, objectives and goals, literature and data used, structure of the thesis Section 2 Introduction to main classical financial theories and behavioral finance theories Section 3 What is contrarian investing? Main investors and philosophy behind it Section 4 Empirical research, glance at the Indian market development since its liberalization, mean reversion, value premium and fundamental risk testing Section 5 Discussion on the results of the empirical research - classical finance explanations and behavioral finance explanations Section 6 Discussion on rationality in economic science, concluding remarks 9

10 Section 2 Classical and Behavioral finance theory overview Classical finance theory In this section I want to present some of the fundamental theories of standard finance as I believe that they can give some good starting insights in understanding why the markets work one or another way in practice. Below I review main ideas of Efficient Market Hypothesis, Random Walk and Capital Asset Pricing Model. Market Efficiency The Efficient Market Hypothesis (EMH) has been one of the cornerstone theories on market behavior since it has been developed by Eugene Fama in the 1960s till the 1990s when the behavioral finance started emerging with the emphasis on psychology and behavioral principles of market participants. E. Fama (1965) describes the efficient market as a market where there are large numbers of rational profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. Under this assumption there is no speculation in the markets, if everyone is rational. The only difference among the investors is the information that is available for them there will be no trade if there will be no information, that is, the reason to trade. This causes the market values to float around the real or fundamental values. The basic idea of the theory is that a capital market is said to be efficient if prices in the market fully reflect available information. When this condition is satisfied, market participants can not earn an economic profit (that is unusual or risk adjusted profits) on the basis of available information (Levich, 2001). The assumption is that the equilibrium model must exist in order for prices to fully reflect all the information available to market participants and therefore the real prices or returns of assets should always conform to their equilibrium prices/returns. According to R. Shiller (2008) the simplest version of EMH implies that the true value of the stock equals the present value of optimally discounted future dividends. So we can see 10

11 the price as the forecast of future dividends of the stock. Of course not all companies pay dividends, but theoretically they should be paying at some point, otherwise their shares would not have value investors would not like to give away money for shares without receiving any return in the future. People are looking for future income and stock prices go up if there is information about future dividends or earnings. Following EMH it could be said that for example if the Price to Earnings ratio of the stock is low, something negative is expected to happen to the company s earnings or dividends in the future. Therefore a low Price to Earnings ratio can be seen as a forecaster of bad company results in the future. According to Elton et. al. (2003), the stock market crash of 1987 was one of major events to raise doubts in EMH as it was totally not in line with what the theory states. The EMH postulates that there is no point in trying to seek profits higher than those of the market itself, because all the new information is already incorporated in the prices. Most analytics agree that the information flow nowadays is much more efficient, than for example in 1929 when the Great Depression started, which implies that the markets should be more efficient in modern times and would not achieve such high volatility as in Indeed it would be naive to think that it is possible to beat the market after getting information from weekly or even daily newspapers when due to technological advance the trading nowadays is performed in a matter of seconds. Nevertheless, the stock market crashes of 1987 as well as a recent one in show that there are factors causing market inefficiency and it makes the market untrustworthy which is against the whole idea of EMH where the market participant should ideally stick to the market portfolio to optimize the returns. Therefore further in this study the biases both of human nature and of institutional origin are reviewed as factors opposing market efficiency. Furthermore, when it comes to testing market efficiency, researchers get to a situation where there is no true answer. To test efficiency one should assume some sort of equilibrium model to define normal security returns. If efficiency is rejected, this could be because the market is truly inefficient or because an 11

12 incorrect equilibrium model has been assumed, J. Campbell at. Al. (1997). Moreover, the joint hypothesis means that it is impossible to test if markets are truly efficient as market efficiency as such can never be rejected. The full market efficiency is quite unrealistic in practice - if costs for information carrying are involved, there are opportunities to achieve abnormal returns. J. Campbell et. al. (1997) discusses using such measures as relative efficiency, for example measuring one market against the other (e.g. Indian Bombay Stock Exchange vs. London stock exchange). The idea of market efficiency being an idealistic and unrealistic phenomenon although useful for relative measures is adequately described by comparison stating that a few engineers would ever consider performing a statistical test to determine whether or not a given engine is perfectly efficient such an engine exists only in the idealized frictionless world of the imagination. Nonetheless, though the existence of the perfect market efficiency is not fully realistic to be proven in the economic world, it might be helpful for obtaining relative measures and theoretical insights for further market analysis. Random Walk Hypothesis The Efficient Market Hypothesis is consistent with the Random Walk Hypothesis. An example of Random Walk can be taken from a drunken sailor a man starts at a point zero and takes a step in any direction. He then takes a second step, at any randomly oriented angle to the first, then a third to any direction, and continues for a while. If we assume that the person continues walking randomly for let s say 15 minutes, the best estimate would be that he ll end up in the same place where he started. The same might be applied for the stock prices if rises follow the falls and they do not depend on any given data. In this case there is no chance to earn any abnormal profit and the best investment strategy would be holding the market portfolio, Shleifer A. (2000). It is impossible to earn a profit from trading, because you cannot predict the change in the prices the market is precisely responding to the new information. This means that if the reality of the market is that the prices 12

13 follow the Random Walk, then trying any other trading strategies, which rely on some sort of historical sequence to predict the stock market movements in the future is a waste of time. However, according to E. Fama, 1965, the faster the analyst can identify situations with differences between the prices and their intrinsic value the longer he will do better than the investor just using a buy and hold strategy. Following this, the more sophisticated analysts exist in the market, the more efficient the market is and it is more likely to follow the Random Walk. Such assumption throws the fundamental analysis, which depends on analyzing the quality of management, economy or industry factors, out of the picture. Later in this paper I will test the Bombay Stock Exchange Sensex index returns for mean reversion and see if there exist any implications of Random Walk. Capital Asset Pricing Model (CAPM) The CAPM is probably the most famous model in the discipline of finance, assuming that people are rational and that they should always stick to holding the optimal portfolio. Below I provide the basic assumptions of the CAPM, as presented in Corporate Finance textbook by J. Berk and P. DeMarzo (2007). 1. All investors are risk averse and rational, aiming to maximize their economic utility function. They choose only the portfolios which maximize the expected return with the level of volatility or risk taken. Likewise, the premise is that while choosing between two portfolios with the same expected returns, the investors would go with the one which is less risky, or has a lower level of volatility. Moreover, the investors are highly diversified to minimize the risk. 2. All investors can buy and sell unlimited amounts of securities at competitive market prices, in other words trade without any costs for tax or transactions. They can also lend and borrow without limits at the risk free interest rate. 3. All investors share homogenous expectations concerning the expected future returns, risk and correlations of the securities. It is also assumed that the new 13

14 information is available to all investors at the same time, an assumption going in line with what the Efficient Market Hypothesis postulates. Put simply, the optimal portfolio is the best diversified portfolio, assuming that it maximizes the return and minimizes the risk. According to Elton et. al. (2003), CAPM assumes that the only portfolio a rational investor would hold would be the market portfolio and each investor can create his preferred risk-return combination and adjust for risk by adding lending or borrowing at a risk free rate to the market portfolio. The main equation of the model is stated below: r i =r f +β i (r m -r f ) The above risk-return relationship means that the expected return on the i th asset equals the risk free rate plus beta of the i th asset times the difference between the expected return of the market portfolio and the return rate of the risk free asset. The market portfolio is theoretically a portfolio of everything in the world - it includes all assets: all stocks, all bonds, real estate, oil assets and everything else available to invest in. The risk free asset is an asset that does not carry any risk for its return, for example one year US government bond, which of course requires the government to be trustworthy, meaning that it won t default on its debt. The measure that is most important from this model to my study, called Beta, β, is the regression coefficient obtained by regression of the return of the i th asset on the return of the market portfolio. It shows how much the stock reacts or relates to the market portfolio movements. For example, if the Beta equals one, it means that the stock moves in the same manner as the market portfolio if the market prices rise by 10%, the price of the stock also rises by 10%. If the Beta is 2, then if the market rises by 10%, the stock price rises by double of that amount 20% in value. In CAPM, Beta is the only risk measure affecting the return of the portfolio, also called the market or fundamental risk - all the other risk is excluded assuming 14

15 that it can be diversified away. Later in this paper, while testing the value premium of the contrarian strategies, I will compare the betas for value and growth portfolios trying to get an insight whether the value portfolios are riskier than the growth portfolios. Finally, I find it important to stress that the CAPM is based on very strict assumptions which usually do not hold in real life. The markets are constrained by laws, various cultural differences, different regulations, politics and other factors which contradict with the main assumptions in the model. Therefore, in the next section I continue with the basic ideas of Behavioral Finance proponents putting more emphasis on the irrationality of the investors and their decision making process. 15

16 Behavioral Finance theory The behavioral finance ideas started emerging in the early 1990s opposing the Efficient Market Hypothesis with research based on the judgment and decision making process of the participants of the financial markets. R. Thaler (1993) called behavioral finance as "simply open-minded finance". What makes behavioral finance theory different from the classical finance is that it is not only based only on mathematical calculus, but it applies all other social sciences as psychology, sociology, anthropology, political science or, since recently, neuroscience. The main ideas of this discipline were inspired by the breakthrough studies by psychologists D.Kahneman and A. Tversky on human biases and cognitive errors, which later developed to what is called a prospect theory. In this section I will review the main aspects of prospect theory, human biases influencing their irrational behavior in the markets and provide some ideas on arbitrage. There is a huge number of aspects that behavioral finance is scoping, so in the following pages I review only those ones which I see relevant for my further analysis. Prospect Theory The prospect theory is an alternative theory to the classical expected utility theory, describing the decision making process under risk. The expected utility theory, developed by Neumann and Morgenstern in the 1940s, states that while making a decision people look at the final states of wealth they can end up with. According to the prospect theory, when the stakes are small relative to investor s wealth, the investors do not think in terms of wealth, they think in terms of what might be gained or lost. Moreover, people s attitudes to gains and losses are different. The prospect theory suggests that people look at the change in wealth, or gains and losses relative to some reference point, which may vary from situation to situation, and display loss aversion - a loss function that is steeper than a gain function - Shleifer (2000). 16

17 Figure 1. Standard Utility Function (Fisher & Statman 1999) Figure 2. Value Function Prospect Theory (Fisher & Statman 1999) By introducing a value function, which is different for losses and gains, the prospect theory brought to the light one of the fundamental feature in behavioral finance that people are loss averse. The value function for losses is convex and steeper than the one for the gains, whilst the one for gains is concave. This implies that the feeling of pain of losing some amount is more intense than the feeling of satisfaction while gaining the same amount. Following this rationale proved by 17

18 numerous experiments of D.Kahneman and A. Tversky, people are willing to risk more when facing losses than when facing winning situations. In the stock market this can be seen when market participants do not sell stocks when stock prices are falling in order to avoid or postpone losses and otherwise try to sell the winning stocks too early, without exploiting them to the end, Tvede (1999). This often leads to results which are not in line with the best interest of investors. What more, the decisions depend on the way the problems are framed. The reference point might be defined both as a positive or a negative outcome and based on that the decision makers might become either risk averse when the outcome is seen as a gain or risk seeking if the outcome is seen as a loss, which causes a so called framing effect, S. Plous (1993). Another important finding coming from the prospect theory and many experiments by A. Tversky and D. Kahneman is that people are overconfident about their abilities. When the markets are booming and everyone is earning money, people tend to attribute these achievements to their own ability to choose a winning stock. This can be explained by a wish to stay in control even when people are not in control and underestimate the risks of the market. Moreover, when individuals get overconfident they trade more than they should and lose huge amounts due to costs. T.Odean and B. Barber (2000) find that individual households in the US which trade at a highest rate on average earn 6% less than the market portfolio and this underperformance can be explained by overconfidence. According to R. Shiller (2000) overconfidence is one of the main factors why high trading volumes can be observed in markets - "Another aspect of overconfidence is that people tend to make judgments in uncertain situations by looking for familiar patterns and assuming that future patterns will resemble past ones, often without sufficient consideration of the reasons for the pattern or the probability of the pattern repeating itself." To sum up, the prospect theory is more about how the human decisions under uncertainty are made in reality and the classical utility function is based on how those decisions should be made if everyone was rational. I do not state that the 18

19 behavioral finance opposes everything what is created by the classical theories in finance. However it relaxes the strong assumption of market participant rationality to make the theory closer to the reality of the human world. Herding and overreaction Individual investors tend to gain interest in the same stocks at the same time and lose their interest in the same stocks at the same time, something that is called a herding behavior. According to T. Odean et. al. (2007), the investors do not spend time to analyze each stock in the market - they tend to buy the ones that already are in the centre of attention. People wait for a stock to draw their attention and then buy it if it suits their preferences. Therefore the individual investors are usually buying stocks which are circulating in the media or are traded in huge quantities. In the 2007 research on Taiwan market, T. Odean et al, find the relationship between the overall size of investments in the market and the market performance. The results show that when the investors as a group invested more funds in the market, it performed worse in the next 6 months. When the money started to be pulled out of the market, the market started doing better. Similar research by T. Odean et al was conducted in United States market in 2007 with the individual stocks. The outcome was that if many investors buy a stock one year, it underperforms in the following year. In contrast, when the investors started selling the stock, it performed better the upcoming year. Herding behavior comes to the light when people think they do not have sufficient information and believe that the knowledge of other people can make the decision on investment easier and faster. T. Odean mentions investment clubs, where usually some people pitch on a few stocks and in order not to embarrass themselves amongst others, tend to go with the stocks which have a strong rationale - good past performance, success stories in the media - stocks that other investors are also buying in the market. Usually, such practice ends up in pushing the stock s price too high and in the end the stock gets overpriced and is going to underperform. The research held by T. Odean and his colleague s shows that there 19

20 is a connection between the herding behavior and the deviations from the fundamental values in the stock markets. Limits to Arbitrage Following the Efficient Market Hypothesis, the prices reflect their fundamental value. This means that there are no discrepancies in the pricing of securities and therefore no chance to earn excess risk adjusted profits in the markets there is no so called "free lunch". Behavioral finance theory argues against it, stating that there might be situations in the market where prices do not reflect their fundamental values and these are caused by the market participants which are driven by investor sentiment and are irrational. The longstanding classical view is that the deviations from fundamental value are very quickly fixed by the rational traders in the market whenever a deviation from a fundamental value is appears, the rational traders spot the good opportunity to invest and quickly use this opportunity bringing the price back to its fundamentals or correcting the mispricing. The behavioral finance theorists do not agree with the first part of this situation that the deviation from the fundamental price is always a good investment opportunity. They argue that "even when an asset is wildly mispriced, strategies designed to correct the mispricing can be both risky and costly, rendering them unattractive. As a result, the mispricing can remain unchallenged", N. Barberis & R. Thaler (2003). I believe it is enough theory to get an insight on main views which are used in this study and I will use more of behavioral finance and behavioral economics ideas while analyzing the results of my empirical research on the performance of the contrarian strategies in the Indian stock market. In the next section I try to review the contrarian or value investing strategies and philosophy behind this type of investing, which is mainly based on exploiting deviations from the fundamental values of securities. 20

21 Section 3 What is contrarian investing? Motivation towards stock markets Jeremy Siegel in his book "Stocks for the long run" (2007) studies US stock returns for the period of and finds that average stock return through those years was 6.8% while the same measure for risk free asset, short term government bonds was 2.8%. He also finds similar evidence in other developed markets. It shows that stocks have a significant 4% higher yearly return than bonds, which is a phenomenon called equity premium or equity premium puzzle in other studies. J. Siegel concludes that the optimal portfolio should be heavily concentrated towards stocks. The book might be criticized due to the fact that 200 years of historical data is a too long period to look back and that most of the insights come from the 20 th century, which was the most successful in US economy. Also, most today s long term investors invest for periods not longer than years, which according to R. Shiller s "Irrational Exuberance" (2000) is not necessarily a risk free period. According to R. Shiller (1998), assuming the rationality of investors the equity premium could be easily related to higher risk carried by stocks in the short runs. Instead, he points to J. Siegel s book, and the evidence that in the long runs long term bonds have carried more risk. According to J. Siegel, long term bonds were not so volatile on the short term basis, however very volatile in long periods of time. Shiller (1998) and S. Benartzi and R. Thaler (1995) relate the equity premium to the framing bias and myopic loss aversion people frequently review new data about the companies they invest in and tend to concentrate on not losing in short investment horizons such as 1 year horizon. Instead they could plan for a longer period in the future and increase their investing horizon while making peace with smaller short term losses. Such indication of stock market producing higher returns motivates me to look into the investing strategies in the stock universe. 21

22 Value super investors The value investing has its roots in the 1930s following the Great Depression, when Benjamin Graham and David Dodd laid foundations for this investment style in their book called "Security Analysis" (1934) and B. Graham s book "The Intelligent Investor" (1949). These authors argue against the efficiency in the markets, stating that due to market not holding all the information about the company, there might be discrepancies in how companies are valued. The main idea is to buy stocks which are undervalued in the market and hold them till their value is corrected. In 1984 Warren Buffet published an essay called "The Superinvestors of Grahamand-Doddsville" as an opposition to the proponents of Efficient Market Hypothesis. In this publication he shows the returns achieved in the markets by nine investment funds including his own, run by people who were previously taught investing by Benjamin Graham in Columbia Business School in the 1950s. His research shows that all of these funds subsequently outperformed the S&P 500 market index in the long term. Of course, the technological advance and the speed of data exchange since those days have made the market absorb way more information, however as discussed before, it is still argued by behavioral finance proponents that there are discrepancies in the marked due to investor irrationality. The publication by W. Buffet might be criticized as being not a strictly academic paper, however it provides additional motivation to look into the academic research done on the topic since it was published and try to find a value premium in today s biggest emerging markets - specifically India in this study. 22

23 Review of literature on market inefficiencies and value premium The contrarian investors in the long run see the low Price to Earnings, Price to Book Value, Price to Cash Earnings and other financial ratios as an indication that the stock is undervalued and that in the future it will regain the true value or what is called their intrinsic, fundamental value. It is contradictory to classical view that assets are priced rationally in the market and that high price measures signal a persistent strong expected performance of such securities. Market analysis related to contrarian investing can be traced back to S. Basu (1977) investigating the performance of US stocks based on their Price to Earnings (P/E) ratio. He concludes that over the 14 year period of , the stocks with lower P/E ratio earn higher absolute and risk-adjusted rates of return than the stocks with higher P/E. Assuming that his models were correct such finding was one of the first indications about the inefficiency in the markets. The P/E information was not fully absorbed by the market, therefore creating disequilibrium and an opportunity to invest and gain an abnormal profit. The "old and gold" US market analysis by J. Lakonishok et. al. (1994) incorporates more financial ratios of the past performance of securities. In addition to Earnings to Price (E/P), they use Book to Market (B/M), Cash Flow to Price (C/P) and Past Growth of Sales (GS) measures. Over the 22 year period , they find that value stock portfolios (the ones with higher E/P, B/M, C/P, and lower G/S) outperform the growth stock portfolios, which they also call glamour portfolios. Moreover, they do not find differences in fundamental risk of portfolios. Set aside the risk and data snooping bias explanations, the authors conclude that the market participants make judgmental errors and overestimate the expectations on the returns of growth portfolios based on their good ratios of past performance. This also brings out the agency problem in the institutions. It is easier for managers to advocate for investing in growth stocks as they seem to be a more prudent investment for majority of investors. Growth stocks seem safer and less likely to be distressed in the future. This way a lot of value stocks are removed from the possible investment perspective as there are e to run into financial troubles due to 23

24 their poor past performance. Moreover, most investors may have shorter horizons than required for value investing, they want to earn abnormal profits in a few upcoming months rather than wait for on average smaller pay-off for a few years. J. Lakonishok and L. Chan review their findings in 2004 and come back to the same conclusions as in They also test whether the value premium has a time specific nature and do not find it time-specific. L. Chan et. al. (1991), provides similar findings for the stock market in Japan as for the US and especially large value premium is observed for portfolios sorted by Price to Book Value ratio over 1% per month. Of course, the conditions in US and Japan are different as Japans stock market was on a high rise in the 1980s so it is hard to conclude that value premium is an international phenomenon just after these two studies. E. Fama and K. French (1992, 1993, 1995, 1996, 1998 and 2006) introduce some empirical contradictions to the classical CAPM. They mention size effect, meaning market capitalization having an extra impact on returns together with β. Their findings contradict to the fact that over the period of the average security returns are positively related to market fundamental risk β. They conclude that the variation in market returns can be associated with the size factor, Earnings to Price, Book to Market and leverage ratios. R. Banz (1981) also finds that the average returns for small cap stocks are too high and the average returns for large cap stocks are too small given their beta. Moreover, Fama and French (1998) examine 13 markets outside US, specifically Europe, Asia and Australia and conclude that for the period 1975 to 1995, the value premium can be found in twelve of thirteen markets and that the value premium of the global portfolios is more than 7% per year. Again, they conclude that CAPM cannot explain the value premium and the authors argue that the value premium comes due to risk not picked up by the model - "this conclusion is based on evidence that there is common variation in the earnings of distressed firms that is not explained by market earnings, and there is common variation in the returns 24

25 on distressed stocks that is not explained by the market return". Value premium in various markets is also found by studies of Bird and Whitaker (2003 & 2004, developed European markets), O.Risager (2008, 2010, Denmark) and other researchers, therefore this phenomenon is becoming widely accepted and value investing is becoming a popular investing strategy among market practitioners. What is interesting, that the results of the above studies show that the value premium also exists in the most emerging markets (Fama & French, 1998). A contradicting example is H. Gonenc and M. Karan (2003) study in Istanbul stock exchange, which finds that growth portfolios outperform value portfolios. I have not found a thorough research made on the value premium in India over the years since the market was liberalized, so this is one of the first attempts to analyze this huge market. Another research I want to mention is based on asset growth ratio of the company and its implications to the returns of the company. Cooper et al. (2008), compare Asset Growth ratio to ratios which are determined as predictors of returns by previous researches such as Book to Market ratio and find that Asset Growth itself is a solid predictor of the stock returns in the US markets. They find an almost 20% yearly return premium for stocks with lower Asset Growth ratio, which is a significant spread. Cooper et al concludes that such results are "most consistent with the interpretation that investors over extrapolate past gains to growth". The Asset Growth ratio is quite new to research in comparison with other ratios I use, therefore I found it interesting to use for the analysis of the Indian market and see if the findings are consistent with the ones in the US market. Before continuing to the next section on the empirical research, a short presentation of the concept of market mean reversion is needed. One of the basic researches done in the field by J. Poterba and L. Summers, 1988, provide a wide study in eighteen markets on market mean reversion. Their results show that the returns in the market auto correlate positively in short horizons and negatively over the long horizons. However, their statistical tests do not reject the Random walk. I will test the mean reversion in the Indian stock market in the beginning of my 25

26 empirical part, as mean reversion is one of the core foundations needed for successful long term value investing, firstly meaning that there are deviations between stock prices and their fundamental values and secondly that they are changing and in the long term stock prices get to their fundamentals. The empirical research which I will present in the following pages differs from the studies presented above in a way that it chooses an Index which holds fewer stocks - only 30 stocks constitute the Bombay Stock Exchange Sensex index. To have a reasonable number of stocks in one portfolio, I form only two portfolios, one for value and one for growth stocks. Therefore in a way it is a much simpler study to compare with others, however it is limited within a scope of a master thesis. A more thorough study with more stocks, fragmented portfolios and cross-sectional return analysis could be achieved while taking PhD studies, which the author considers as an attractive opportunity in the future. Next section starts with a glance at the Indian perspective in the world s economy and introduction to Bombay Stock Exchange Sensex Index. 26

27 Section 4 Empirical research India s position in the global economy Since India is often referred as an economy that together with China will overtake worlds economic leader s status in the future, I find it necessary to have a quick glance at India s perspective in the world s economy and what are the projections for its future. Since my study s main scope is not the economic analysis of a country, I review only some factors, numbers and studies that seemed most interesting and representative of the state of Indian economy and relevant for interpreting the Indian stock market. Interesting studies about the movement of the centre of global economic activity were carried out by a professor from London School of Economics Danni Quah. His 2010 research based on calculations of all GDP produced on planet, shows that the center of global economic activity on earth in 3 decades moved from being west of London, somewhere Atlantic in between of UK and USA, towards Asia, which can be explained by continuing rise of China, India and other Asian Economies. Figure 3 Shifts in Global Economic Center 27

28 The same study also provides data comparing growth of combined Indian and Chinese economies to the growth of US economy: Table 1 Growth of China and India against growth in USA Ratio of absolute growth (China+India)/US 0,13-3,2 0,33 1,67 0,93 The data that author uses here is the inflation-adjusted GDP at market exchange rates. Interestingly, the US economy shrank in 1991 at the same time as China s and India s economies grew, therefore the figure is negative. US were in recession in 2001 also, therefore the numbers for these dates are provided separately. From the table above we can see that the ratio of absolute growth, comparing China and India to US grew from 0,13 in the period to 0,93 in period , just before the Credit Crunch crisis. In his 2011 study D. Quah draws projections to the future to see where the world economic center will be in 2050s. For these calculations growth indicators from almost 700 locations on the planet are used. Below we can see the global economy s center of gravity shifting towards the area just between China and India in the 2050s, black color spots changing to red ones. Figure 4 Projected center of world economic activity in

29 The research of D. Quah is a novel view towards changing powers in world economy and it reasonably shows that the center of world economic activity is moving towards Asia, and India s placement in it can be clearly seen. In a shorter horizon, according to the data from International Monetary Fund World Economic Outlook (2011), India is experiencing rising credit growth and increasing inflation and the growth of the economy should slow down a bit, however still keep up above the trend of whole Asia. It is projected that the GDP will grow 8% in 2011 and 7% in 2012 with infrastructure and favorable conditions for corporate investment being the main driving forces behind it. Since this study s main target is investing strategies in Indian stock market, I am not putting much emphasis on analysis of Indian economic growth in the past. However, factors such as English language being de facto one of Indian national languages and immigration numbers in Great Britain (around 2% of whole Great Britain population in the last decade were Indians - imply better opportunities for communicating with international business and a rise of outsourcing possibilities that international companies undertake in India. Also, a factor of being only one of 2 countries in the world where the population is above 1 billion people remains a notable estimate of the potential economic power of the country. Having that in mind an important figure seems to be the age of Indian population. According to (2007), in Great Britain Indian population age estimation is lower than that of native white British or white Irish and the majority of Indians in Great Britain are 20 to 50 years old, around third of them having managerial and professional occupations. According to United States Census Bureau, International Data Base (2010) the overall Indian population is estimated to be around 1.1 billion with more than a quarter of it being below 25 years old and more than 65% younger than 35, which implies that India has a huge labor potential. With positive projected growth numbers, huge labor potential and optimistic sentiments in the market, India is becoming one of the major economic forces in the world. 29

30 Bombay Stock Exchange and Sensex index In this study I use data form Sensex Index, which is the first benchmark index of the Indian stock market, calculated at Bombay Stock Exchange. Established in 1875 Bombay Stock Exchange (BSE) is the oldest stock exchange in Asia. It has the largest number in the world of listed companies (around 5000) and was among 10 of the world s leading exchanges in number of electronic trading system s transactions in December The total market capitalization of companies listed in BSE was around 1.3 Trillion USD in February 2010 ( The Sensex Index consists of 30 stocks with the idea to represent large and financially strong companies across major economic sectors, as per charts below. Figure 5 Sectorwise Market Capitalisation in BSE Sensex Index 30

31 Figure 6 Sectorwise distribution pie chart for BSE Sensex Index The Sensex index was first calculated in 1986, however I chose to pick up data starting in early 1990s when the economic liberalization in India started. At first the index was calculated as a market value weighted index, and since 2003 it is calculated under free float market capitalization weighted methodology, the main difference being that the first method weights its components according to their full market capitalization and the second one considers only shares available for public trading. 31

32 Data applied and methodology All the data for empirical research was taken from Thomson Reuters DataStream database. It is the largest statistical financial database in the world containing around 140 million time series, more than data types and million indicators and instruments. 30 constituents of Bombay Stock Exchange Sensex Index are analyzed. While looking up historical data for Sensex constituents, DataStream provides data for only those constituents which compose the index at the present time. Therefore I found it necessary to extract the data for each company which was included in the index since January 1991 separately, trying to avoid the survivorship bias. During 25 years around 80 companies were listed in the index and all the companies composing the Sensex index and the historical changes are provided in the appendices. It might be argued that an index with more stocks could have been chosen, however since the 30 stocks in Sensex index are of large capitalization and liquid I find the Index representative and believe that if the value premium can be find in this index, it might as well be found in other Indian Stock Market indexes too. Yearly time series data for Return Indexes, Price to Earnings, Price to Book Value, Price to Cash Earnings, Total Asset size, Market Value and Beta measures were all extracted from the database. For more details on specific calculations, everything is provided in the attached Excel sheets in Appendices. The returns for mean reversion testing were calculated from Price Index which s daily, monthly and yearly equivalents were also extracted from the database. Yearly Gross Domestic Product (GDP) data was also taken form DataStream it is valued in billions of Rupees, all the data and calculations based in this research are in local currency. It was impossible to collect data for all the companies composing the index each year, so most of the years the value and growth portfolios are formed of less than 30 stocks. Not all beta figures were found also, e.g. I could not find this statistic for Reliance Industries Ltd., which is one of the largest companies considering market value. Therefore a measure of 1 is chosen for all years given that the company s market value is large and its movements follow similar patterns as the market. 32