The market is found to be somewhat inefficient and simple wagering strategies are identified that result in profitable returns (Woodland & Woodland, 2001). Considerable research in economics and finance has been devoted to the investigation of the efficient markets hypothesis. An issue that is the subject of intense debate among academics and financial professionals is the Efficient Market Hypothesis (EMH) (Higgins, 1992).[1] The fundamental question is whether prices fully reflect available information. If not, then in financial markets, it would be possible for an investor to devise a strategy that would earn above-average returns (Woodland & Woodland, 2001).[2]
EMH evolved in the 1960s from the Ph.D. dissertation of Eugene Fama. According to Fama (1965),[3] an efficient market is defined 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. Fama (1965)[4] adds that in an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value.
Moreover, Fama (1965)[5] and Achelis (2003)[6] state that security prices correctly and almost immediately reflect all information and expectations fully reflect all available information. EMH says that one cannot consistently outperform the stock market due to the random nature in which information arrives and the fact that prices react and adjust almost immediately to reflect the latest information (Achelis, 2003).[7] Therefore, it assumes that at any given time, the market correctly prices all securities; and the result is that securities cannot be overpriced or underpriced for a long enough period of time to profit therefrom Achelis (2003).[8]
Most individuals buy and sell under the assumption that the securities they are buying are worth more than the price that they are paying, while securities that they are selling are worth less than the selling price (Fama, 1965).[9] But if markets are efficient and current prices fully reflect all information, then buying and selling securities in an attempt to outperform the market will effectively be a game of chance rather than skill (Higgins, 1992).[10]
The random walk theory asserts that price movements will not follow any patterns or trends and that past price movements cannot be used to predict future price movements (Higgins, 1992).[11] This theory is primarily based on the “The Theory of Speculation” (1900) by Louis Bachelier who concludes that the mathematical expectation of the speculator is zero. Bachelier describes this condition as a “fair game.” Moreover, economic theory teaches the notion that in a perfectly efficient stock market, prices should follow a random walk. Under a random walk, historical data on prices and volume have no value in predicting future stock prices. In other words, statistical analysis and “technical analysis” is useless and trying to time the market is a fool’s errand (ABG Analytics, 2003).[12]
Fama (1970)[13] made a distinction between three forms of EMH: the weak form, the semi-strong form, and the strong form. The weak form of the hypothesis suggests that past prices or returns reflect future prices or returns (Russel & Torbey, 2003).[14] It also asserts that all past market prices and data are fully reflected in securities prices, therefore, technical analysis is of no use (Higgins, 1992).[15]
The inconsistent performance of technical analysts suggests that this form holds (Russel & Torbey, 2003).[16] However, Fama (1991)[17] expands the concept of the weak form to include predicting future returns with the use of accounting or macroeconomic variables. Russel and Torbey (2003)[18] state that the evidence of predictability of returns provides an argument against the weak form.
On the other hand, Fama (1991)[19] states that the semi-strong form of EMH asserts that security prices reflect all publicly available information. (Higgins, 1992) says that this form asserts that all publicly available information is fully reflected in securities prices so fundamental analysis is of no use. In addition, according to Russel and Torbey (2003),[20] there are no undervalued or overvalued securities and thus, trading rules are incapable of producing superior returns. When new information is released, it is fully incorporated into the price rather speedily. The availability of intraday data enabled tests which offer evidence of public information impacting stock prices within minutes (Patell & Wolfson, 1984; Gosnell, Keown & Pinkerton, 1996).[21] The semi-strong form has been the basis for most empirical research on the tests of market efficiency; however, recent research is including the weak form on the test (Russel & Torbey, 2003).[22]
The strong form suggests that securities prices reflect all available information, even private information (Fama, 1991).[23] According to Higgins (1992), this form asserts that all information is fully reflected in securities prices; as a result, even insider information is of no use. Seyhun (1998)[24] provides sufficient evidence that insiders profit from trading on information not already incorporated into prices. Hence the strong form does not hold in a world with an uneven playing field (Russel & Torbey, 2003).[25]
There are many empirical studies that attempt to contradict the efficient market hypothesis (Higgins, 1992).[26] Researchers have documented some technical anomalies and stock market anomalies that may offer some hope for traders. According to Higgins (1992),[27] the search for anomalies is effectively the search for systems or patterns that can be used to outperform passive strategies. The EMH became more controversial after the detection of these anomalies (Russel & Torbey, 2003).[28]
These phenomena have been rightly referred to as anomalies because they cannot be explained within the existing paradigm of EMH (Russel & Torbey, 2003).[29] It clearly suggests that information alone is not moving the prices (Roll, 1984).[30] These anomalies have led researchers to question the EMH and to investigate alternate modes of theorizing market behavior. Some of the more popular anomalies are discussed below.
Rozeff and Kinney (1976)[31] documented the so-called “The January Effect” in which there is an evidence of higher mean returns in January as compared to other months. They used the NYSE stocks (1904-1974) and discovered that the average return for the month of January was 3.48 percent as compared to only .42 percent for the other months. The evidence is supported by Bhardwaj and Brooks (1992),[32] Eleswarapu and Reinganum (1993 cited in Russel and Torbey)[33] who made later studies. This finding also applies to other countries (Gultekin & Gultekin, 1983),[34] for bonds (Chang and Pinegar, 1986).[35]
In the Monday Effect, French (1980)[36] discovers that, through his analysis of daily returns of stocks (1953-1977), there is a tendency for returns to be negative on Mondays whereas they are positive on the other days of the week. He notes that these negative returns are caused only by the weekend effect and not by a general closed-market effect (Russel & Torbey, 2003).[37] In Addition, Agrawal and Tandon (1994)[38] find significantly negative returns on Monday in nine countries. However, Steeley (2001[39]) finds that the weekend effect in the UK has disappeared in the 1990s.
Another documented anomaly is the Small Firm Effect. Banz (1981)[40] who analyzed the 1936-1975 period reveals that excess returns would have been earned by holding stocks of low capitalization companies.
Russel and Torbey (2003)[41] state that there is substantial documented evidence on both over and under-reaction to earnings announcements. DeBondt and Thaler (1985)[42] has strong evidence that is consistent with stock prices overreacting to current changes in earnings. Bernard (1993)[43] provides evidence that is consistent with the initial reaction being too small, and being completed over a period of at least six months. In addition, Ou and Penman (1989)[44] argue that the market underutilizes financial statement information. Thus, the evidence suggests that information is not impounded in prices instantaneously as the EMH would predict (Russel & Torbey, 2003).[45]
Researchers also discovered the “The Weather” anomaly. Saunders (1993)[46] shows that the New York Stock Exchange index tends to be negative when it is cloudy. In addition, recent studies find that stock market returns are positively correlated with sunshine, and that rain and snow have no predictive power (Hirshleifer and Shumway, 2001). [47]
Behavioral finance, which claims that one can beat the market, has been challenging the foundations of the efficient market hypothesis (Fama, 1997). [48] Under this new school, behavioral finance theorists argue that by carefully studying investor behavior, active money managers can identify profitable clues about what stocks to buy and when; and believe that investors make predictable and systematic mistakes when processing information about the stock market (Fama, 1997).[49] Behavioral finance which is supported by evidence from cognitive psychology also believes that what cause people to make errors in judgment (overconfidence, greed, fear) can be observed, recorded and exploited (Fama, 1997).[50]
DeBondt’s and Thaler’s (1985)[51] analysis of long-term return anomalies as early as 1933, shows that when stocks were ranked on three- to five-year past returns, past winners tended to be future losers and visa versa. The theory asserts that stocks performing poorly will actually do very well on average over the next few years, so it is good strategy to buy these undervalued stocks (Fama, 1999).
Thaler and DeBondt (1985)[52] attribute these long-term return reversals to investor overreaction, which is the notion that investors overreact to information about companies and stocks, sending prices to unnaturally high or low levels (Fama, 1999). However in the subsequent years, investors will realize they were overreacting to the news and stock prices will drift to their correct levels. In the lag time, investors who are aware of the overreaction can make money on the correcting price drift (Thaler & DeBondt, 1985).[53]
Moreover, according to (Thaler & deBondt, 1985),[54] investors may also make the mistake of underreacting to financial news; for example, after a company announces good news, such as higher than expected returns, investors may initially underreact to the news, not pushing the stock price high enough and only gradually incorporating its full import into the stock price. Supporters of behavioral finance say that evidence of investor overreaction and underreaction signals an inefficient market, however, they have not made a case strong enough to replace the efficient market theory (Fama, 1999).[55]
Fama (1997)[56] considers that there is indeed a developing literature that challenges the EMH, and argues that stock prices adjust slowly to information. With this, it is suggested that one must examine returns over long horizons to get a full view of market inefficiency (Fama, 1997).[57]
According to Higgins (1992),[58] the paradox of efficient markets is that if every investor believed a market were efficient, then the market would not be efficient because no one would analyze securities. In effect, efficient markets depend on market participants who believe the market is inefficient and trade securities in an attempt to outperform the market. The studies on EMH have made an invaluable contribution to the understanding of the securities market (Russel & Torbey, 2003).[59] However, there seems to be growing discontentment with the theory. While it is true that the market responds to new information, it is now clear that information is not the only variable affecting security valuation.
Fama (1999)[60] acknowledges that the efficient market hypothesis is not a bullet-proof description of price formation, but that following the standard scientific rule, market efficiency can only be replaced by a better specific model of price formation, itself potentially rejectable by empirical tests. Moreover, Fama (1999)[61] argues that the behavioral finance camp has not come up with a good alternative to market efficiency.
With this, Russel and Torbey (2003)[62] propose that the EMH paradigm be refined to embody the psychological and speculative aspects of the stock market. Einhorn (1976)[63] remarks that, “We should always be open to the idea of developing new paradigms incorporating some aspect of decision making that has heretofore been neglected.” (205) Russel and Torbey (2003)[64] also suggest that the critics of EMH must present unambiguous, consistent, and direct empirical evidence on the irrational aspect of stock market behavior.
[1] Supra Higgins
[2] Woodland, L. M. & Woodland, B. M. (2001) Market efficiency and profitable wagering in the national hockey league: Can bettors score on longshots? Southern Economic Journal, Vol. 67.
[3] Supra Fama (1965)
[4] Ibid.
[5] Ibid
[6] Achelis, S. B. (2003) Efficient market theory. Available at [investopedia.com]. Accessed 25/09/03].
[7] Ibid
[8] Ibid
[9] Supra Fama (1965)
[10] Supra Higgins
[11] Ibid
[12] ABG Analytics and Consulting, LLC. (2003) The efficient market hypothesis, random walks, and our trading philosophy. Available at [www.abg-analytics.com]. Accessed [25/09/03].
[13] Supra Fama (1970)
[14] Supra Russel and Torbey
[15] Supra Higgins
[16] Supra Russel and Torbey
[17] Supra Fama (1991)
[18] Supra Russel and Torbey
[19] Supra Fama (1991)
[20] Supra Russel and Torbey
[21] Patell, J. and Wolfson, M. (1984) The intraday speed of adjustment of stock prices to earnings and dividend announcements. Journal of Financial Economics 13, 223-252; Gosnell, T.F., Keown A. J. and Pinkerton, J. M. (1996) The intraday speed of stock price adjustment to major dividend changes: Bid-ask bounce and order flow imbalances. Journal of Banking and Finance 20, 247-266.
[22] Supra Russel and Torbey
[23] Supra Fama (1991)
[24] Seyhun, N. (1998) Investment intelligence from insider trading, MIT Press.
[25] Supra Russel and Torbey
[26] Supra Higgins
[27] Ibid
[28] Supra Russel and Torbey
[29] Ibid
[30] Supra Roll (1984)
[31] Supra Rozeff and Kinney
[32] Bhardwaj, R.K. and Brooks L. D. (1992) The January anomaly: Effects of low share price, transaction costs, and bid-ask bias. Journal of Finance 47, 553-575.
[33] Supra Russel and Torbey
[34] Supra Gultekin and Gultekin
[35] Chang, E. and Pinegar, M. (1986) Return seasonality and tax-loss selling in the market for long-term government and corporate bonds. Journal of Financial Economics 17, 391-415.
[36] Supra Fama (1980)
[37] Supra Russel and Torbey
[38] Agrawal, A. and Tandon, K. (1994) Anomalies or illusions? Evidence from stock markets in eighteen countries. Journal of International Money and Finance 13, 83-106.
[39] Steeley, J.M. (2001) A note on information seasonality and the disappearance of the weekend effect in the UK stock market. Journal of Banking and Finance 25, 1941-1956.
[40] Supra Banz
[41] Supra Russle and Torbey
[42] De Bondt, W.F.M., and Thaler, R. H. (1985) Does the stock market overreact? Journal of Finance 40, 793-805.
[42] Bernard, V. L. (1993) Stock price reaction to earnings announcements: A summary of recent anomalous evidence and possible explanations. Advances in Behavioral Finance, Russell Sage Foundation, 303-340.
[44] Ou, J. and S. Penman (1989) Financial statement analysis and the prediction of stock returns. Journal of Accounting and Economics 11, 295-329.
[45] Supra Russel and Torbey
114 Saunders, E.M.J. (1993) Stock prices and Wall Street weather. American Economic Review 83, 1337-1345.
115 Hirshleifer, D. and T. Shumway (2001) Good day sunshine: Stock returns and the weather. SSRN Working Paper, Forthcoming, Journal of Finance.
[48] Supra Fama (1997)
[49] Ibid
[50] Ibid
[51] Supra Debondt and Thaler
[52] Ibid
[53] Ibid
[54] Ibid
[55] Supra Fama (1999)
[56] Supra Fama (1997)
[57] Ibid
[58] Supra Higgins
[59] Supra Russel and Torbey
[60] Supra Fama (1999)
[61] Ibid
[62] Supra Russel and Torbey
[63] Einhorn, H.J. (1976) A synthesis: Accounting and behavioral science. Journal of Accounting Research 14PD, 196-206.
[64] Supra Russel and Torbey
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