Contrarian investment strategies have become a dominant theme in finance especially since the performance of value stocks is not limited to the US market. In this study I will refer to value stock as those stocks that have relatively low price when compared with a fundamental or book value. On the contrary, glamour stocks are those with a relatively high price relative to their fundamental value. Therefore, contrarian investors would make a bet against the market. Researchers and academics believe that valuation remains the best arbiter of future returns and valuation opportunities are best presented in non-consensual ideas.
A contrarian philosophy is to invest against the herd, not for the sake of it, but to refute and reform the consensus. It needs to estimate the intrinsic value of a firm and purchase shares when their price is well below that value to enhance his/her returns and potentially decrease the risk exposure. Value strategies have proven to create the possibility for superior performance and past literature is in agreement that such performance is achievable however, the controversy lies in the reasons why such performance was achieved (Alan, et al., 2001). One the one hand, investors adopt the contrarian strategy to invest against those investors who extrapolate the past performance. On the other hand, some say that contrarian investments achieve higher returns because they are deemed to be riskier. Whichever way it is interpreted, contrarian investment strategies are one of the anomalies of the Efficient Market Hypothesis (EMH).
Efficient Market Hypothesis (EMH) is one of the most explored phenomenon in finance and investment. EMH states that the market has the ability to reflect the “true” prices of financial assets. In other words, when a new piece of information is released the market prices should reflect that information quickly and accurately (Lumby & Jones, 1999). Until the beginning of the twenty-first century, economists and the academia have accepted the EMH and agreed that market prices of financial assets had the ability to reflect all information available inclusive of new information without delay. Thus, neither fundamental analysis nor technical analysis would enable investors to achieve abnormal returns by holding a randomly selected portfolio of stock. However, in recent decades the academics began to dissect and dispute the EMH concluding that it is a much more complicated matter than they were led to believe by the standard finance theory. Particularly, they began to investigate the anomalies of EMH and discovered a different approach to finance theory such as the behavioral finance. Standard finance theory assumes that investors have little difficulty making financial decisions because they make those decisions based on prompt and accurate information, not influenced by their emotions. Behavioral finance however, examines the psychology of financial decision-making using mechanisms such as cognitive errors, overconfidence, role of biases in decision making, such as the rule of thumb when making certain investment decisions, the pain of regret and problems of self-control, against the standard finance theories such as capital asset pricing theory, option pricing and arbitrage theories (Statman, 1995).
The aim of this paper is to investigate mean reversion, that is, the investors’ ability to earn profits by investing in portfolio of assets that have been sorted using accounting ratios. To be more specific, the investors would buy stocks with low market prices relative to their fundamental values. Researchers assume that there is a negative serial correlation in market prices (Brouwer, et al., 1997) giving contrarian investors the ability to pursue the value premium by investing against the market trend.
Lakonishok, et al., 1994, Basu, 1977 and Fama and French 1992 have shown that stocks with higher earnings (dividends, book-to-value or other measures of value) to price ratios have earned higher returns than those with lower ratios, over the subsequent years. These results and other previous literature have raised the question: How efficient are financial markets?
Lumby and Jones, 1999, have identified three levels of efficient markets:
Weak form efficiency
Semi- strong efficiency
Strong form efficiency.
The idea that market prices incorporate all available information is no longer accepted. Fama, 1970 carried out tests to determine how efficient financial markets really are, against the three efficiency levels. Weak form efficiency implies that market prices reflect all market information and states that past return will have no effect on future returns making technical analysis a redundant tool for earning higher returns. Semi-strong efficiency implies that market prices reflect all publicly available information stating that a company’s stock price reflects all publicly available information making fundamental analysis a redundant tool since it cannot give any advantage to investors to find mispriced stocks. Strong form efficiency implies that market prices reflect all publicly and privately available information such as insider information that is not yet released by the company. This is an extreme case scenario which gives investors an exploitative power over the information regarding the market price formation.
Some academics assimilate the contrarian investment with the overreaction hypothesis claiming that people tend to overreact to good or bad performance of a company and argue that as a consequence of the overreaction of the market, value stocks significantly outperform glamour stock (Andrew and Craig, 1990). Further more recent research suggests that the effect of the overreaction hypothesis is more pronounced in some parts of the world than others. For example, Doan, et al., 2014, through their research on the Australian stock market have shown that, depending on the time horizon, the contrarian strategies prevails in the short-term and momentum strategies prevail in the medium- to long-term. Their study of the momentum and contrarian investment strategies in the Australian stock market found mixed findings of previous studies in the same market.
Therefore this study aims to examine this phenomenon on the UK equity market and it will be interesting to see how contrarian investment strategies perform over the recent financial crisis. A collection of 113 stocks will be analyzed using fundamental analysis for a period of 10 years, 2000-2010, where the returns for subsequent five years will be monitored. Section 2 will look at the existing literature on contrarian investments and its causes. Section 3 will detail the methodology used to analyze and construct the portfolios. In this section I will provide additional data on which ratios will be used to differentiate between value and glamour stocks. Section 4 will present and interpret the results of the study. Section 5 will present the concluding remarks and recommendations for improvements.
2. LITERATURE REVIEW
2.1 BEHAVIORAL FINANCE
We currently find ourselves in an environment of low growth, which reduces the margin for investment error. In a high return environment mista
kes are less costly because the returns can help overcome the frustration. Nowadays, the search for enhanced returns requires ever more discipline, conviction, ingenuity and courage. As humans we have to make many decisions as way of living and are faced with questions such as: Should I have a healthy lunch or a McDonald’s burger? How much should I tip my waiter? We make these decisions with ease by using a set of rules of thumb called “heuristic” rules that allow us to run our lives without which we would be paralyzed due to the volume of daily choices we would be faced. Behavioral finance is the study of those and other financial decision making biases that can be avoided, if we are aware what caused them. Below I have discussed some of the behavioral biases that affect the investment behavior.
Confident investors tend to overestimate their abilities when picking stocks and tend to overlook broader factors that influence the performance of their portfolio. Overconfidence is often linked with too much trading which could have a negative effect on their portfolio. Professors Brad Barber and Terry Odean analyzed the returns of US investors, differentiating between them as most active and least active traders and found that those investors with the lower trading activity achieve a higher portfolio return than those who were most active (Barber and Odean, 1999).
2.1.2 Representativeness heuristic
Kahneman and Tversky introduced representativeness heuristic as part of their research into cognitive error and it is used to analyze an individual’s behavior when he/ she is face with the probability of an event of uncertainty. The results of many experiments conducted by them have shown that individuals judged the probability of an event by its representativeness, i.e. event A is judged more probable than event B if event A is more representative than event B (Kahneman & Tversky, 1974).
One of the interesting experiment performed by Kahneman and Tversky is when a set of participants were given the following information about Linda; “she is single, outspoken, 31 years old and very bright. While studying philosophy, she was very concerned with issues of discrimination and social justice and was involved in antinuclear demonstrations”. The participants would then had to choose which one of the following event is most probable:
Linda is a bank teller (A), or
Linda is a bank teller and is active in the feminist movement (B).
The results have shown that 87% of the participants have chosen event B as the most probable event. This is a surprising result since the rules of probability state a combination of 2 events cannot be more probable than one simpler event. Therefore, this proves that the vast majority of the participants have used representativeness heuristic to judge Linda’s ability as a bank teller (Kahneman & Tversky, 1983).
Investing in the “best” business in the stock universe can still be a bad investment if you invested at the wrong price. Likewise, a “bad” business can become a profitable investment if it has been bought at a relatively low price. Fortunately for contrarian investors, markets are not always efficient and investors are not always rational resulting in mispriced businesses where contrarianism has its best effect.
Reversion is a property of the stock market that is not fully appreciated by al investors. A significant part of the literature based on financial markets suggests that investors tend to overreact to certain information. If a company announced a good performance, investors tend to be over optimistic in their forecasts and likewise, if the company has announced bad performance they tend to be over pessimistic (Andrew and Craig, 1980). However, following the market’s overreaction the price will tend to move towards its fundamental value suggesting that there is some of reversion in returns. This suggests that if stocks that have done well in the past does not mean they will continue to do well in the future and vice versa, stocks that have performed poorly in the past will tend to do better in the future. Therefore a successful implementation of the contrarian investment strategy implies investing in a portfolio of stocks that have been performing poorly in the past and their price is therefore below their fundamental value.
DeBondt and Thaler, early in1990s, investigated whether the stock market overreacts to information by looking at the behavior of security analysts, what they considered to be a “reasonable source of rationality”. Their conclusion was that we are humans which means that we are prone to make naïve forecasts which are too extreme and definitely not rational resulting in an anomalous market. Interestingly, they have found the same pattern in economists’ forecasts when analyzing exchange rates and macroeconomic variables and concluded that “overreaction can pervade even the most professional of predictions”. Perhaps they are correct and the recent financial crises of 2008 has proven that fear makes the best of us.
This study is based on the Lakonishok, Shleifer and Vishny’s paper “Contrarian investment, extrapolation and risk” from 1994 and it is built on the belief that investors to not fully appreciate reversion. They classified stocks into value and glamour stocks based on financial ratios such as book to market ratio (B/M), cash flow to price ratio (CF/P), earnings to price ratios (E/P) and growth in sales (GS). They gathered stock traded on either New York Stock Exchange (NYSE) or the American Stock Exchange (AMEX). In order to build their portfolios, at the end of April in any given year they ranked the stocks according to a fundamental ratios and then divided the stocks into 10 portfolios where Portfolio 1 was made up of stocks with the lowest value of the ratio and Portfolio 10 comprised the stocks with the highest value of the ratio. Over the next five years they have monitored the performance of each portfolio.
They have found that value stocks (for example, Portfolio 10 out of 10) have outperformed the glamour stocks, even in the first year after the portfolio formation. The value stocks realized an astonishing average return of 19.8% compared with 9.3% of the glamour stocks. By adopting the buy-and-hold strategy for the five subsequent years, the value portfolio yielded 146.2% whereas the glamour portfolio yielded only 56%. An important fact that they outlined through their paper is that the gap between returns of value and glamour stocks increases as the years increase. Thus, contrarian investment is a profitable strategy in the long-term.
Furthermore, they investigated if these results are affect by the size of the companies and if some ratios were more important than others. Not surprisingly, value stock still outperformed the glamour stocks but interestingly they have found that GS and CF/P were the main drivers of the results contradict with Fama & French, (1992) who stated that equilibrium returns are best defined by the B/M, E/P and size and suggested that these ratios can be identifies as measures of risk.
These results were reproduced by both David (1994) based on a sample of large US companies over a 30 year period and Chan, Hamao and Lakonishok (1991) investigating the Japanese stock market. Extensive research produced by Dreman, 1997, and Graham and Dodd, 1934 have proven that value strategies have outperformed the glamour strategies and hence beat the market. They used the same methodology and applied fundamental analysis to identify value stocks from glamour stock. Their findings accentuates the expectation that value stock outperform glamour stock, particularly those stock with
higher earning-to-price ratios are likely to earn higher returns ((Basu, 1977), (Chan, et al., 1991) and (Fama & French, 1992)).
The question what we should ask ourselves is: How likely are the excess returns of value stocks to persist in the long term?
Fama and French, (1990) attempted to explain the outperformance tendency of value strategies by adjusting their asset pricing model to include size and value as factors of market risk in the capital asset pricing model (CAPM). The famous three-factor model reflects that the value and small cap stocks outperform the market. Debating the three-factor model, Gregory, et al., (2001), through a comprehensive classification of stocks: one-way categorization as used by Fama and French in the three-factor model and two-way categorization based on both past performance and future expected performance. For the period of January 1975 to December 1998, using the one-way classification of stocks, they have found the three-factor model broadly explained the differences in returns of value and glamour stocks. However, the two-way classification portfolios shown that value stocks significantly outperformed glamour stocks in the UK and these results are robust when controlling for book-to-market and size factors. These results contained differences that were not accounted by the three-factor model, which is nothing more but a rational risk-pricing model.
Antoniu, Galariotus and Spyrou, (2006), produced a study on the London Stock Exchange to identify whether short-term contrarian profits can be achieve and investigated what are the sources of such profits. Based on the Fama and French (1996) three-factor model they have decomposed the profits according to these factors and the results have shown that in the UK contrarian investment strategies outperformed the market and most importantly these results are robust even when taking into account the risk, seasonality and market frictions characteristics of the portfolios. Their conclusion was that investors overreact to firm specific information.
These finding are parallel to Lakonishok, et al., (1994) who have shown that glamour stocks underperform value stocks when a book-to-market strategy, as well as other financial ratios, is used. Most importantly in their research, they provide evidence to other critics of contrarian investments such as “the size effect”, the claim that value portfolios are riskier and optimism and pessimism of investors.
Some argue that smaller companies face a larger possibility of bankruptcy and therefore are part of a less competitive market requiring a higher return to compensate investors for taking on the additional risk. Lakonishok, et al., (1994) based on market capitalization selected the top 50% of the companies in their portfolio and evaluated the portfolio. Not surprisingly they have found the same results as before and hence, disproving the size effect.
Another factor of increased profitability of contrarian investment strategies is inadequate treatment of risk. In order to address this issue, Lakonishok, et al., (1994), analyze the difference in returns of value stocks and returns of glamour stocks and evaluate how the strategy will perform over time. They have found out of the 22 years examined only in 5 years the glamour stocks outperformed value stocks, out of which 4 have incremental differences and only in 1979 the difference was more significant, 16.8%. Furthermore, when analyzing the broader European market, Brouwer, et al., (1997) have found similar results as Lakonishok, et al., (1994) where the variance of stocks explained only a small part of the return differences between value and glamour stocks.
Optimism and pessimism is the result of forecasts made without a full appreciation of reversion. Using the two-way classification of stocks they separated those stocks that appear to be in favor of the market defined by growth of sales (GS) and cash flow to price (CF/P) ratio. In the pre-portfolio formation period glamour stocks had a lower CF/P ratio of 0.08 compared to value stocks CF/P ratio of 0.279 and outperformed the value stocks with returns rising by 139% for glamour stock and only by 22.5% for value stocks, a clear indication that the market preferred the glamour stocks and had more optimistic expectations. In the contrary in the post-portfolio formation period the glamour stocks had shown a much less impressive growth in fundamentals’ value. Particularly, the cash-flow performance of glamour stocks is lower than expected prior to portfolio formation even though over the 5-year period it reached a value almost double that of value stocks. The growth of sales performance of glamour stocks mimics a similar trait with pre-formation values being much higher than post-formation values outlining the consequences of investors being too extreme in their predictions.
2.4 MARKET EFFICIENCY
One of the most influential theories that the financial markets gave build upon is the Efficient Market Hypothesis (EMH). EMH states that the market has the ability to reflect the “true” value of stocks incorporating all available information and when a new piece of information is released, the market will quickly and accurately reflect it through its listed prices. Thus, fundamental analysis and technical analysis would prove useless in helping investors achieve abnormal returns. However the value of a company, the stock price, is calculated based on existing information about the company as well as future information such as investment opportunities that the company holds (Miller and Modigliani, 1961). Therefore, if the valuation of a stock in based on future interpretation how can it be classified as efficient?
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