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INTRODUCTION
Efficiency of stock markets has recently been a highly debated subject among the investors. One theory which attempts to define the mechanism behind share price behaviour is Efficient market hypothesis which has spawned a revolution in the 1960’s when it was introduced by Professor Eugene Fama. He defined an 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” (Fama, 1970). The assumptions of the theory have since been challenged by critics who have brought in psychological and behavioural models to explain the share price behaviour more effectively than EMH. The following examines the basis of these arguments and attempts to identify areas where EMH has fallen short in describing share price behaviour.
EFFICIENT MARKET HYPOTHESIS – THE THEORY
EMH, a theory first expressed by the French mathematician Louis Bachelier and was subsequently developed by Prof. Eugene Fama at University of Chicago as an academic concept basically states that “a financial market is informationally efficient when market prices reflect all available information about value” (Fama, 1970). Exploring deeper into this definition leads to the concept of market efficiency which assumes that at any given time the share market prices of particular stock reflect all the information available. This means that news regarding securities spreads very fast and is incorporated to their prices without delay. Based on the form of efficiency, three major versions of this hypothesis can be identified;
1) Weak form
This assumes that the all the present prices of shares traded reflect all past publicly available information. This means that Technical analysis, which uses past stock prices to predict future prices, cannot be used to generate excess returns than those generated by a randomly selected portfolio of individual stocks. But there is the probability for using Fundamental analysis, which uses published financial information such as asset prices and earnings to identify undervalued stock in order to generate excess returns.
2) Semi-Strong form
This form of efficiency states that share prices reflect all newly available public information in a rapid and unbiased fashion which restricts the usage of both technical and fundamental analysis in order to beat the market. Consistent changes in the share prices to the new information reflects an unbiased response in the market while an adjustment to prices which is both instantaneous and reasonable indicates a rapid response.
3) Strong form
This is the form of efficiency where it is assumed that all information whether public or private, is reflected in security prices. Under this hypothesis, even an investor with access to insider information cannot reap excess returns as the prices already reflect the private information relating to a company.
- Random Walk
An associated term of EMH is “random walk” which states that “if the flow of information is unimpeded and information is immediately reflected in stock prices, then tomorrow’s price changes will be independent of today’s prices and would clearly reflect tomorrow’s news” (Malkiel, 1996). Due to the unpredictability of news, the resulting changes will also be unpredictable and thus “random” which allows even an inexperienced investor to reap identical returns to an expert investor.
CRITICISMS OF EMH
EMH is disputed by many experts based on anomalies identified relating to trading. On one front EMH is found to be insufficient in explaining the rationality behind the behaviour of investors in trading which subsequently affects the markets. This area is developed in to another branch of finance known as behavioural finance. On another front, experts found stock prices to be partially predictable on the basis of past patterns and fundamental valuation methods. They include aspects such as calendar effects which are being rejected by the assumption of unpredictability under random walk. A third aspect which is called value investing has proven the effective use of fundamental analysis in beating the market which is assumed to be impossible under EMH. These are discussed below.
1) BEHAVIOURAL FINANCE
This branch of finance assumes that the investors are imperfect in perceiving reality and therefore makes irrational and illogical decisions which affect the markets and returns. This cognitive biases lead to contradictions to the EMH where the returns gained by each investor differ. Work of psychologists such as Daniel Kahneman, Amos Tversky & Richard Thaler point towards several cognitive biases which stand to prove that EMH has flaws in accounting for human reasoning and rationality.
- Mental accounting
According to behaviour life cycle hypothesis by Shefrin & Thaler (1988) people mentally frame their assets in to different categories and assign different levels of utility to each asset group. Here, each asset group is viewed differently as belonging to their wealth or disposable income. For example, perception of monetary returns as dividend is viewed differently than those received as capital gains because dividends are related to increase of their disposable income while capital gains are related to increase of wealth. Therefore the utility assigned to each group differs which has implications for their behaviour.
- Biased expectations
Overconfidence on part of the investors may also lead to irrational decisions being made. There may be occasions where investors in search of profit maximisation may ignore reality which leads to losses. For example, between 1973 and 1990, earnings forecast errors have been anywhere between 25% and 65% of actual earnings.
Another theory which comes under this is Gambler’s fallacy by Daniel Kahneman & Amos Tversky (1974) which assumes a condition where an investor may predict gains at the end of continuous losses in share prices through inaccurate application of probability. It may also be applied by investors in the opposite direction by predicting losses after successive gains in the market. Both conditions lead to irrational decisions by investors.
- Representative heuristics
This includes instances where investors see correlations between the price of shares and the reputations of the companies they belong to. But in reality it is acceptable that they may not provide accurate representations of their potential for growth as in most cases the shares of good companies are fairly valued. The reputation may also affect how information is processed when news relating to particular companies arises. Information bias may lead to traders holding on to the shares although bad news arises about the company which is against rational behaviour.
The inability of EMH to take into account the effect of human reasoning and rationality has led to it being identified as an incomplete model for describing share price behaviour. According to Richard Thaler (1999), the errors in reasoning by quasi-rational investors, who are prone to make mistakes, may provide an opportunity for rational investors to profit which is not the case as assumed by EMH.
In addition to the above, EMH assumes that information is “freely available” to all participants in the market but it may be said that cognitive biases may decide how each individual may perceive the available information which decides whether they will make a profit or not.
2) CALENDAR EFFECT
The calendar effects are assorted theories which assume that certain times of the week, months and years are good or bad times for investments as they are subject to above average price changes in market indexes. This adds an aspect of predictability to share prices which is not possible under the assumptions of EMH. Following are instances where the share price is accepted by many investors to be partially predictable;
- Monday effect
This is where it is assumed that the prevailing trends displayed at the closure of markets on Friday will continue along the same line on the Monday. Contradictory to this assumption, Gibbon & Hess (1981) claimed that stock prices go down on Mondays regardless of the prices on Friday.
- January effect
January effect describes the unusually high returns generated at trading during the first two weeks of the year. Haugen and Lakonishok (1988), in their book “The incredible January Effect” has attributed this to the increase of purchases following the drop in prices during December as most investors sell off their stock at low prices to create tax losses in order to offset capital gains. The drop in prices in December sparks purchases which pushes up the price levels again in January.
- Halloween effect
This includes a belief that the stock prices show a general upward trend from November to April and shows signs of downward movement afterwards. This sparks selling off of shares in May and purchases again around Halloween and hence the name Halloween effect.
The existence of the calendar effects gives rise to an idea that market behaviour is at least partially predictable which is deemed to be impossible under EMH. This argument is countered by Malkiel (2003) due to them being non-dependable from time to time. He states that even if the effects are non-random, the transaction costs for exploiting them would be higher than the returns expected to be generated through them. Effects such as January effect are no longer considered valid as increasing number of people use tax-sheltered retirement plans which write off the need to create tax losses.
3) “BEATING THE MARKET” THROUGH VALUE INVESTING
EMH assumes that no investor is able to “Beat the Market” but there are techniques in the market which is actually aimed at beating the market and at the same time generating high revenues for investors. According to Lakonishok, Shleifer and Vishny (1994), Value investing is an investment strategy involving the purchase of stocks which are trading at a less price level than the intrinsic value which is identified through forms of fundamental analysis. This technique was taught by Ben Graham & David Dogg at Columbia Business School and was mastered by investment guru Warren Buffet who developed the idea further. He advises investors to “find an outstanding company at a sensible price rather than a large number of generic companies at bargain price” (Buffet, 2001).
The technique assumes that the market overreacts to good or bad news which results in changes to prices and the purchase occurs when prices seems deflated and is experiencing a bear market. But there is risk in purchasing in bear market as prices may fall further. In addition the lack of standard for valuating stock and arriving at the intrinsic value may lead to investors experiencing different results. Here, the difference between the market value and the intrinsic value of a share is identified as “margin of safety”. Characteristics of value stocks include “stocks with lower-than-average price-to-book or price-to-earnings ratios and/or high dividend yields” (Buffet, 2001).
Under the EMH, it is assumed that no investor should ever be able to “beat the market”. But the success of investors such as Warren Buffet stand as a fact that the market can be beaten which leads to the basic assumption of EMH to be viewed as irrelevant. In addition, it displays the ability to apply of fundamental analysis in exploiting the share prices which can only be used with the weak form of market efficiency. Also, the existence of a margin of safety makes irrelevant another assumption of EMH that shares always trade at their fair value, making it impossible for investors to purchase them at deflated prices.
CONCLUSION
Through the above analysis, the following evaluations can be made;
Due to the high number of requirements for defining an efficient market, it may be impossible for an efficient market to exist anywhere in the world. Especially with regard to strong form of efficiency, it may be said the existence of such a market would be highly controversial due to its illegality of making public the insider information for a company.
In addition the inability of the theory to define human behaviour will remain to be its serious flaw. The theory of “random walk” may be disputed here as it assumes that an inexperienced investor may be able to reap identical returns to an expert investor but under practical conditions the reasoning and the reactions displayed by two people towards identical information may be different which may differentiate the returns they may achieve in trading. Due to the fact that human aspect is the main force connected with trading and not supercomputers, predictability and pricing irregularities may appear. But with the increasing prospect of using computers and increasing number of calculating and modelling software, it may be said that the efficiency may be increased in the future.
Aspects such as calendar effects cannot be written off the argument as they continue to attach a sense of predictability to share prices which is rejected by EMH.
The global financial crisis served as a proving ground to EMH where it was accepted by some to have held up well but was heavily criticised by many such as Richard Prosner, an innovator in Law & Economics, a prominent judge and University of Chicago law professor, as a failure due to the assumption under EMH that markets are self-correcting which lead to laissez-faire capitalism (New Yorker, 11 January 2010).
Above all, the most convincing evidence that the assumptions of EMH may not be applicable, comes from investors such as Warren Buffet who continues to “beat the market” with value investment techniques and earn high financial returns.
Therefore based on the above evidence it can be concluded that Efficient Market Hypothesis may not be a sufficient explanation for share price behaviour.
BIBLIOGRAPHY
1) Buffett, W., Cunningham. L. ed., 2001, “The Essays of Warren Buffett”, The Cunningham Group, pp: 256.
2) Cassidy, J., 2010, After the Blowup, “The New Yorker”, [Online] (Updated 11 January 2010), Available at: http://www.newyorker.com/reporting/2010/01/11/100111fa_fact_cassidy. [Accessed 01 August 2010]
3) Fama, E., 1970, “Efficient Capital Markets: A Review of Theory and Empirical Work,” Journal of Finance, 25, pp: 383-417.
4) Gibbons M., and Hess P., 1981, “Day of the Week Effects and Assets Returns,” Journal of Business, vol. 54, pp: 579-596.
5) Haugen, R. A. and Lakonishok J., 1988, “The Incredible January Effect”, Homewood: Dow Jones-Irwin.
6) Investopedia.com, 2004, “Working Through The Efficient Market Hypothesis”, [Online] (Updated 12 February 2004), Available at: http://www.investopedia.com/articles/basics/04/022004.asp [Accessed 25 July 2010]
7) Lakonishok, J., Shleifer A., and Vishny R. W., 1994, “Contrarian Investment, Extrapolation, and Risk”. The Journal Of Finance, 49(5), pp: 1541-1578.
8) Malkiel, B. G., 1996, “A Random Walk Down Wall Street”, W. W. Norton
9) Malkiel, B. G., 2003, “The Efficient Market Hypothesis and Its Critics”. Princeton, NJ: Center for Economic Policy Studies, Princeton University
10) Shefrin, H. H. and Thaler, R. H., 1988, "The behavioral life-cycle hypothesis", Economic Inquiry, 26 , pp: 609-643
11) Thaler, R. H., 1999, "Mental accounting matters", Journal of Behavioral Decision Making, 12(3) , pp: 183-206
12) Tversky, A. and Kahneman D., 1974, "Judgment under uncertainty: Heuristics and biases". Science 185 (4157): pp: 1124–1131
