Efficient Market Hypothesis: Is the Stock Market Efficient - Literature review Example

?Running Head: Efficient Market Hypothesis: Is the Stock Market Efficient? Efficient Market Hypothesis: Is the Stock Market Efficient? [University] Efficient Market Hypothesis: Is the Stock Market Efficient? Introduction Efficient Market Hypothesis (EMH), introduced four decades ago, was the dominating theory in the academic community that explained how the financial market works. Nowadays, although it is challenged by both the theoretical and practical studies (e.g. Pesendorfer, 2006; Lim and Tan, 2003; Lo and Mackinlay, 1999), EMH remains one of the major building blocks of modern finance. This theory asserts that the financial markets are "informationally efficient", which means the current prices of assets (i.e., stock, bonds) reflect all the available information. The EMH view of the market is that, when information arises, it spreads very quickly and changes the prices of assets appropriately without delay. Since the information or news is by definition unpredictable, the resulting price changes must be unpredictable. This is called the "random walk" theory (Norstad, 2006). Thus, in the stock market, no investor can select stocks by analysing available stock information and achieve returns greater than those obtained from randomly selected stocks (Hough, 2008). Despite the wide acceptance of EMH in the academic community for several decades, EMH has not caught the investor's imagination. Almost all professional investors believe they can predict stock prices by analysing information and so beat the market (Christine, 2008). Some of them, including Peter Lynch, Warren Buffet, and Bill Miller, have outperformed the market over long periods. The success of those investors, which is difficult to attribute to pure luck, contradicts EMH. At the same time, EMH has become less universally accepted in the academic community. Some researchers dispute that the market may not behave consistently with EMH. For example, most stock exchanges crashed in October 1987 at the same time. It is impossible to explain such a scale of price changes by reference to any information or news at the time. The works against EMH can be divided into two categories. Some research, such as behavioural finance, attack the foundation of EMH, which assumes that investors are rational (Harrison, 2005; Pesendorfer, 2006). They assert that the price changes in a market, especially the anomalistic changes, could be explicable by some irrational or emotional actions of the investors. The other category of work against EMH is more on the practical side. They try to test EMH empirically and find evidence inconsistent with EMH (e.g. Cooper, 1999; Lehmann, 1990). The key part of such work is searching in the historical data for the patterns that show the potential predictability of the stock prices. EMH and Its Three Forms The Efficient Market Hypothesis has been the dominating theory in this area for the past several decades. It states that the current market price fully reflects all the information available. This means that given the information, no prediction of future prices can be made. The core of EMH is built on the assumption of investor rationality (Bray, 1981). Under this assumption, investors have a long-term perspective and they act calmly to achieve that perspective. Note that EMH allows that an individual investor may act irrationally: anyone may overreact or underreact to the information in the market. The market as a whole, however, always shows the price that fully and instantly reflects all the information. There are different types of information in the market: Private information. This is also called insider information. It is material information about a company's activities that has not been disclosed to the public. It is illegal for an investor to make profit based on insider information in the major world stock markets (Christine, 2008). Fundamental information. Fundamental information includes a company's financial history and current standing such as earnings, sales, and management. It also includes data of the current state of the economy, such as the inflation rate. Fundamental analysis uses such information to evaluate the performance of a company and predict its probable stock price evolution (Christine, 2008). Technical information. Technical information refers to historical financial market data, including price, volume, moving averages of the price, and other market indicators. Based on such information, the technical analysis attempts to identify non-random price patterns and trends in the stock market and exploit those patterns (Christine, 2008). Fama (1970) made a distinction between three forms of EMH according to the type of information considered: Strong-form EMH. Stock prices fully reflect all public and private information and no one can earn excess returns. According to the strong-form EMH, even insider information is of no use. Semi-strong Form EMH. Stock prices fully reflect all publicly available information, so that no one earns excess return by utilising that information. The semi-strong form EMH implies that fundamental analysis cannot beat the market. Weak-form EMH. Stock prices fully reflect all historical market data such as the price and volume. The weak-from EMH implies that technical analysis will not produce excess returns. Despite the traditional support for EMH in the academic community, most investors still believe they can make profit by predicting the stock prices or trends. Almost all professional investors rely to some extent on the analysis of past or current information when they make investment decisions. For example, Warren Buffet, one of the most successful investors in history, applies fundamental analysis for predicting the future price of stocks and has consistently earned excess returns for decades. In the existing literature there are also many research papers claiming that applying appropriate methods can provide successful predictions. Evidence against the EMH There are a large number of studies of the weak-form EMH in the finance literature. Behavioural Finance challenges the theoretical foundation of EMH (Harrison, 2005). It argues that the investors in the market are irrational. The anomalies in market prices and returns may be inexplicable via EMH alone. Examples are the south sea bubble of 1720 and the stock market crash of October 1987, where most stock exchanges crashed at the same time. It is almost impossible to explain the bubble or the scale of those market falls by reference to any news event at the time. Other studies focus on finding empirical evidence against the weak-form EMH. According to EMH, the prices of returns can be represented by a random walk model. Intuitively, any result based on the technical data that contributes to the departure from the random walk refutes the weak-form EMH. Some studies apply standard statistical correlation tests to uncover linear dependencies in the stock data (e.g. Annuar et al., 1991; Ko and Lee, 1991). Their results, showing little linear dependencies, cannot significantly reject the random walk hypothesis. However, the lack of linear dependencies does not imply that the stock series are random. There might be other non-linear forms of dependencies in the underlying stock data which cannot be detected by the traditional statistical method. Even Fama (1970: 394) acknowledges this possibility, "Moreover, zero covariances are consistent with a fair game model, but as noted earlier, there are other types of nonlinear dependence that imply the existence of profitable trading systems, and yet do not imply nonzero serial covariances". Sarantis (2001) suggests that there exists non-linearity in most financial returns in general, including the stock market returns. As Lim and Tan (2003) pointed out, however, the evidence of non-linearity only shows the violation of the random walk model. There is no doubt that the evidence supporting the random walk model can be considered as evidence for EMH. Nevertheless, the violation of the random walk model (i.e., dependence in the stock data and other statistical results) implies only the potential of predictability in the stock returns. It may not be considered as evidence of market inefficiency directly (Ko and Lee, 1991). One has to further demonstrate that those violations, which are represented by patterns detected in past technical stock data, can be applied by investors to earn excess return in the market. A recent theory that implies the weak form inefficiency indicates that the stock market systematically overreacts to new information (Delong et al., 1990). The corresponding contrarian strategy of buying past losers and selling past winners should make a profit because the past losers (winners) are likely to become future winners (losers). This provides the evidence of predictability of stock returns and suggests the results can be explained as market inefficiency. Opposition to the concept of the efficient market, however, is not new. Keane (1991, p. 33), for example, writes, A market where price behaviour appears to be influenced by the month of the year, the day of the week, whether Friday falls on the thirteenth, or by the outcome of the Super Bowl game…does not inspire confidence in the economic values of its signals. Examining the efficient market literature, Ball (1994) discusses the early consistent evidence supporting the efficient market hypothesis and the subsequent empirical research which apparently contradicts it. He discusses a number of factors for this change. First, that early evidence was "swept under the rug." A second reason is the improvement in research techniques and lower computational costs. Lastly, the research has shifted to areas where anomalies are more likely to occur, such as more uncommon phenomena. Bernstein (1999) believes that since investors and analysts spend so much time and energy in obtaining, evaluating, and then using financial information there is an inherent benefit in doing so. This is in direct conflict with the Efficient Market Hypothesis since it implies that the benefit must exceed the marginal costs. The final indictment of EMH may come from the fact that the 2001 Nobel Prize for Economics was awarded to three Americans (George A. Akerlof, A. Michael Spence, and Joseph E. Stiglitz) who challenge the concept of EMH by writing about imperfect or asymmetric information as a reason for inefficient markets (Hilsenrath, 2001). Another anomaly in the efficient market theory is the Dow Jones dividend strategy, advanced by Michael O'Higgins (1992). The dividend strategy consists of buying stocks that make up the Dow Jones Industrial Average (DJIA) with the highest dividend yields. The portfolio requires little supervision by the investor because once the portfolio is selected, it is kept for a year and then reconstructed. Wunder and Mayo (1995) compare the Dow Jones dividend strategy during a longer period than O'Higgins, and consider risk as well as returns. Their conclusion is that the only way the Dow Jones dividend strategy consistently beats the DJIA and the S&P 500 is by embracing more risk. Furthermore, the Overreaction Hypothesis (ORR) contradicts the Efficient Market Hypothesis (EMH) by espousing the view that if excessive investor sentiment causes stock prices to be abnormally high, then a price reversal should be predictable. Dissanaike's (1997) evidence seems to support this theory. Another theory that opposes the EMH is the complexity theory. In his book, Patterns in the Dark, Peters (1999) argues that the efficient market hypothesis and the capital asset pricing model are gross and often misleading oversimplifications. According to Peters, the reason these concepts are so heavily defended is because they provide simple equations which make research much easier. Peters studies 103 years of daily Dow Jones Industrial Average data to arrive at his conclusions. He contends that the market's short-term behaviour can be described as a stochastic, non-linear process, and that its long-term behaviour indicates a nonlinear, dynamic, and chaotic process. Conclusion The predictability of the stock market has long been a fascinating problem in both academic society and industry. One of the enduring ideas is the Efficient Market Hypothesis (EMH), which is defined by Fama in 1970. EMH states that the financial market is informationally efficient - that is, the current price has fully reflected the current information on the market. In this regard, the price is unpredictable given the available information. However, literature reviewed above has challenged that hypothesis, arguing that the financial market does not follow a random model, but can be predicted in a way. References Annuar, M., Ariff, M., and Shamsher,M. (1991). Technical analysis, unit root and weak-form efficiency of the KLSE. Banker's Journal Malaysia 64 (April), 55-58. Ball, R. (1994). The development, accomplishments and limitations of the theory of stock market efficiency. Managerial Finance, 20(2/3), 3-48. Bernstein, P. L. (1999). A new look at the Efficient Market Hypothesis. The Journal of Portfolio Management, 25(2), 1-2. Bray,M. (1981), Futures Trading, Rational-Expectations, and the Efficient Markets Hypothesis, Econometrica 49, 575-596. Christine S., (2008). Strategies, Allocation & Performance: Equity Derivatives - Capital market trends join the mainstream, Mandate. London. Cooper, M. (1999), Filter rules based on price and volume in individual security overreaction, Review of Financial Studies 12, 901-935. Delong, J.B., Shleifer,A., Summers, L.H., and Waldmann, R.J. (1990), Noise Trader Risk in Financial-Markets, Journal of Political Economy 98, 703-738. Dissanaike, G. (1997). Do stock market investors overreact? Journal of Business Finance & Accounting, 24(1), 27-49. Fama, E. (1970), Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance 25,383-417. Harrison,G.W. (2005), Advances in behavioral economics, Journal of Economic Psychology 26, 793-795. Hilsenrath, J. E. (2001, October 11). Three Americans win Nobel for Economics - Citing faulty information, they challenge theory of efficient markets. The Wall Street Journal, A2. Hough, J. (2008). Your next great stock , Hoboken, NJ: John Wiley & Sons. Keane, S. M. (1991). Paradox in the current crisis in Efficient Market Theory. The Journal of Portfolio Management, 17(2), 30-34. Ko, KS. and Lee,S.B. (1991) A comparative analysis of the daily behavior of stock returns: Japan, the U.S and the Asian NICs. 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(2001), Nonlinearities, cyclical behaviour and predictability in stock markets: international evidence, International Journal of Forecasting 17,459-482. Wunder, G. & Mayo, H. (1995). Study supports Efficient-Market Hypothesis. Journal of Financial Planning, 8(3), 128. Read More