Financial markets are mechanisms (formal and informal) that allow people to buy and sell financial securities, commodities and other items of value at a price. For decades now, these markets have contributed positively to the development of a nation’s economy, but their continuous efficiency has been debated by scholars. One of such reviews is Eugene Fama (1970) which supports the assertion that financial markets are “efficient” (that is, a market which prices always fully reflect available information).
The Efficient Market Hypothesis (EMH) views prices of securities in the financial markets as fully reflecting all available information. This theory of efficient capital markets is supported by the academic field of finance. However, the validity of the hypothesis has been questioned by critics in recent years. EMH is one of the hotly contested propositions in all social sciences. Even after several decades of research and literally thousands of published articles on the topic, economics have not yet reached a consensus about whether financial markets are efficient.
This essay comprises of three sections. Section 2 is a review of market efficiency. A brief history of market efficiency, the various market efficiency forms, and empirical tests for market efficiency are enumerated upon. Criticisms of the EMH and behavioural finance are further discussed. Section 3 concludes this work.
REVIEW OF MARKET EFFICIENCY
The concept of market efficiency is being employed by finance and economic professionals. There is a comprehensive review by Fama (1970) on the theory and evidence on market efficiency, which proceeds from theory to empirical work. He noted that most of the empirical work preceded development of the theory.
2.1 Brief History of Market Efficiency
The Efficient Market Hypothesis (EMH) was first expressed by Louis Bachelier, a French mathematician, in his PhD thesis in 1900. “In his opening paragraph, Bachelier recognizes that past, present and even discounted future events are reflected in market price, but often show no apparent relation to price changes. This recognition of the informational efficiency of the market leads Bachelier to continue in his opening paragraph, that if market, in effect does not predict its fluctuations, it does assess them as being more or less likely, and this likelihood can be evaluated mathematically” (Dimson and Mussavian 1998, p.92). Further research by Cowles and Jones in the 1930s and 1940s on stock prices showed that investors were unable to outperform the market. Both research followed the same principle of the random walk model. However, all these earlier studies were ignored as at that time.
The origin of the EMH was first given form by the works of two individuals in the 1960s. Eugene Fama and Paul Samuelson independently developed the same notion of market efficiency from their different research. Samuelson (1965) contribution is summarized by his article: “Proof that Properly Anticipated Prices Fluctuate Randomly”. The EMH was developed by Professor Eugene Fama at the University of Chicago Booth School of Business as an academic concept of study in the early 1960s. It was widely accepted up until decades ago where some empirical analysis by scholars have consistently found problems with the efficient market hypothesis. These anomalies will be addresses in section 2.4 of this work.
Forms of Market Efficiency
In 1970, Fama published a review of the theory and the evidence for the hypothesis. Included in his paper were the various forms of financial market efficiency: weak, semi-strong and strong forms. Empirical reviews were also carried out on the various forms of market efficiency.
Weak Form Efficiency
The weak form hypothesis shows that market prices fully reflect all information inferred from past price change. Future prices of stock cannot be predicted by analyzing prices from the past. This form of market efficiency opposes technical analysis which involves studying past stock prices data and searching for patterns such as trends and regular cycle. Future price movements follow a random walk and determined entirely by information contained in the price series.
Semi-Strong Form Efficiency
In this form, scholars believe that market prices reflect not only information implied by historic changes but also other publicly available information relevant to a company’s security. It implies that price of securities rapidly adjust to publicly available information such that no excess returns can be earned by trading on that information. Semi-strong efficiency asserts that neither technical analysis nor fundamental analysis will be able to produce excess returns for an investor.
Strong Form Efficiency
Dimson and Mussavian (1998) view this form of market efficiency as one which asserts that information known to any participant is reflected in market prices. Market prices reflect all available information including information available to company insiders, and no one can earn excess returns. If there are legal barriers to private information becoming public, as with insider trading laws, strong form of market efficiency is impossible, except in case where laws are universally ignored.
Empirical Tests for Market Efficiency
Test of weak form efficiency
Test for random walk have been conducted as a test for weak form efficiency. As earlier explained, the idea of weak form efficiency is that the best forecast of the future price of a security is the current price. Past price movements are not useful to predict future prices.
The first statement and test of the Random Walk Hypothesis (RWH) was that of Bachelier, a French mathematician in his 1900 PhD thesis, “The Theory of Speculation”. He recognized that past, present and future events are reflected in market prices, concluding that commodity prices fluctuate randomly. Cowles and Jones (1937) tested the RWH. In their study, they compared the frequency of “sequences” and “reversals” in past stock returns, where the former are pairs of consecutive returns with the same sign, and the latter are pairs of consecutive returns with opposite signs. Their article suggested that professional investors were in general unable to outperform the market.
Kendall (1953) examined 22 UK stocks and commodity price series using statistical analysis. He found out that there were random changes involving series of prices from one term to the next, which were observed at fairly close intervals. The resulting data behave like wandering series. According to Dimson and Mussavian (1998), the near-zero serial correlation of price changes was an observation that appeared inconsistent with the views of economists. These empirical observations came to be labeled “the Random Walk Model”.
Osborne (1959) analyzed US stock prices data, applying methods of statistical mechanics to the stock market, with a detailed analysis of stock price fluctuation. His research showed that common stock prices have properties which are similar to the movement of molecules. His article indicated support for the RWH.
The random walk model emerged as a prominent theory in the mid- 1960s. In 1964, Cootner published his papers on the topic while Fama (1965b) published his dissertation arguing for the random walk hypothesis. Fama reviewed the existing literature on stock price behaviour, examining the distribution and serial dependence of stock markets returns and concludes that there is strong evidence in favour of the random walk model.
Test of Semi-Strong Efficiency
In testing for semi-strong market efficiency, it is believed that the adjustments to previously unknown news must be of a reasonable size and instantaneous. Consistent upward and downward adjustments after the initial change must be looked for. If such adjustments exist, it would suggest that investors had interpreted the information in a biased fashion and hence in an inefficient manner.
Fama et al. (1969) tested the speed of adjustment of stock prices to new information. The study provided evidence on the reaction of share prices to stock split and earnings announcements. The market appears to anticipate the information, while most of the adjustments are completed before the event is revealed to the market. There is a rapid and accurate adjustment of the remaining price once the news is released. The Fama et al. study concludes that “the evidence indicates that on the average the market judgments concerning the information implication of a split are fully reflected in the price at least by the end of the split month but most probably almost immediately after the announcement date” (p.20).
In Jensen (1969), a sample consisting of the portfolios of 115 open-end mutual funds was used to statistically test for evidence in support of semi-strong efficient market. The rational was to address the following questions: (1) If the mutual funds on the average provided investors with returns greater than, less than, or equal to returns implied by their level of systematic risk and capital asset pricing model? (2) And if the funds in general provided investors with efficient portfolio. The Jensen study concludes that current prices of securities completely capture all effects of all currently available information. Therefore, attempts by mutual funds provider to analyze past information more thoroughly have not resulted in increased returns.
However, on the contrary, a recent study by Asbell and Bacon (2010) tested the effects of announcing insider purchases on the stock price’s risk adjusted rate of return for a randomly selected sample of 25 firms on November 26, 2008.These stocks were traded on NYSE or NASDAQ. Statistical test for significance were conducted and results show a slightly positive reaction prior to the announcement and a significant positive reaction after the announcement. Their findings fail to support efficient market theory at the semi-strong form level as documented by Fama (1970). “Specifically, for this study the announcement of insider purchases is viewed as a mixed signal, no significant insider trading before the purchase date, but a significant upwards trend after the purchase date. Investors appear to receive the insider purchase news as an opportunity to buy and gain in the future from their investments. Evidence here suggests no sign of insider trading prior to the gain in the announcement date. The market’s positive reaction to the announcement suggests that the company and the stockholders have nothing to fear, even though the results test the strength of market efficiency” (Asbell and Bacon 2010, p.180).
Test of Strong Form Efficiency
The principle in testing for strong form efficiency is that a market needs to exist where investors cannot consistently earn excess returns over a long period of time. Even if some managers are observed to consistently beat the market, it is believed that no refutation even of strong form efficiency follows: with hundreds of thousands of fund managers worldwide, even a normal distribution of returns (as efficiency predicts) should be expected to produce some “star” performers.
Maloney and Mulherin (2003) provide a test of strong form market efficiency on how quickly and accurately the stock market process the implications of the space shuttle crash that occurred January 28th, 1986. Although information about the Challenge crash was not available to the public until 11:47am, there were lots of variations attributed to the stock of the four firms prior to this announcement. The study shows the speed and manner in which Morton Thiokol was distinguished from the other three firms as a possible cause of the crash. The existence of prior knowledge about the O-ring problem associated with the space shuttle programme, suggested that investors who were aware of this private information facilitated the price discovery process on the day of the explosion. The price discovery process was not attributed to the informed traders, though some segment of the market quickly reacted to the news of the disaster.
Further evidence from the study revealed that there was no abnormal volume or stock price movements in Morton Thiokol on days of prior shuttle launches. Also, there was no abnormal short interest in Morton Thiokol on the days of previous launches, nor were there any short sales on the day of the explosion prior to the launch time. The Challenger case study shows that the information processed by the market participants is not simply some linear combination of private and public components but often complex and can produce complicated price patterns in which the relation between information arrival and price discovery is not always direct.
2.4 The Efficient Market Hypothesis and Its Critics
The efficient market hypothesis was widely accepted by academic financial economists decades ago. However, this theory has become less universal and debated by scholars in recent years. Some of the critics of market efficiency have been centred on the following: size effect, seasonal and day-of-the-week effect, excess volatility, short term effects and long-run return reversal, and stock market crashes. These criticisms or attacks on the efficient market hypothesis will now be analyzed below and the beliefs that stock market prices are partially predictable.
The “size effect” is one anomaly found by critics. Some empirical studies such as Banz (1981) and Reinganum (1981) showed that small-capitalization firms on the New York Stock Exchange (NYSE) earned higher average return than predicted. There is tendency for small company stocks to generate larger returns than those of larger company stocks over long periods of time. It is reasonable to suggest that one should rather be interested in the extent to which higher returns of small companies represent a predictable pattern that allow investors to make excess profit. “If the beta measure of systematic risk from the Capital Asset Pricing Model is accepted as the correct risk measurement statistics, the size effect can be interpreted as indicating an anomaly and a market inefficiency, because using this measure, portfolios consisting of smaller of smaller stocks have excess risk-adjusted returns” (Malkiel 2003, p.17). Fama and French (1992) study show that the average relationship between beta and return during the 1963- 1990 period was flat. This is not consistent with the “upwards sloping” as predicted by the CAPM. In one of their exhibits, within the size deciles, the relationship between beta and return continues to be flat suggesting that size may be a far better proxy for risk than beta. Their findings should not be interpreted as indicating that markets are inefficient.
However, it seems that the small-firm anomaly has disappeared since the initial publication of the papers that discovered it. The different risk premium for small-capitalization stocks has been much smaller (practically no gains from holding smaller stocks) since 1983, than it was during the period 1926- 1982.
The “Seasonal and Day-of-the-week pattern” is another anomaly propagated by critics of the efficient market hypothesis. Some research have found that January has been a very unusual month as stock market returns are usually very high during the first two weeks of the year. This has been particularly evident for stocks of small companies, as the so-called “January effect” seems to have diminished in recent years for shares of large companies. There also appear to be a number of day-of-the-week effects as French (1980) study show a significantly higher Monday effects.
In line with the study by Malkiel (2003), the problem with the predictable patterns or anomalies (seasonal effects) is that they are not dependable from period to period. The non-random effects (even if they were dependable) are very small relative to the transaction costs involved in trying to exploit them. Investors do not appear to take advantage of the abnormal returns in January and buy stocks in December, thus eliminating the abnormal returns.
“Excess Volatility” effect is another anomaly considered here. The critics believe stock market appears to display excessive volatility (that is, fluctuations in stock prices may be much greater than is warranted by fluctuations in their fundamental value). Criticizing the efficient market hypothesis on the basis of volatile assets prices looks conceptually wrong. This argument supports the review by Szafarz (2010) which asserts that efficiency is about rationality and information, not about stability. The study shows that variance bounds and stability are not part of market efficiency and therefore, one should not reject market efficiency on the basis of excess volatility test. However, speculative bubbles are compatible with rational valuation, and hence constitute possible outcome of the efficiency market dynamics.
“Short-run Effect and Long-run Return Reversals” is another argument against market efficiency. Some reviews show that some positive serial correlations exist when stock returns are measured in the short-run (period of days or weeks). But many other studies have shown evidence of negative serial correlation (return reversal). Return reversal can also be termed as mean reversion. This means that stocks that had done poorly in the past are more likely to do well in the future because there will be a predictable positive change in the future price, suggesting that stock prices are not a random walk.
Despite all these, the finding of mean reversion is not uniform as it is a bit weaker in some periods, than it is for other periods. It is known that the strongest empirical results are found in periods of Great Depression. “There was a statistically strong pattern of return reversal, but not one that implied inefficiency in the market that would enable investors to make excess return” (Malkiel 2003, p.11). In line with this, one can believe that this forecast is due to overreaction in stock market prices. Behavioural economists attributes the imperfection in the financial markets to a combination of cognitive biases such as overreaction, overconfidence, representative bias, information bias and various other predictable human errors in reasoning and information processing. Of course, it is impossible to rule out the existence of behavioural or psychological influences on stock market pricing.
2.5 Behavioural Finance
A new breed of behavioural economists attributes the imperfection in the financial markets to psychology and behavioural elements of stock-price determination. This approach is a more promising alternative to the efficient market hypothesis. Behavioural finance applies the concept from other social science to understand the behaviour of stock prices. Psychologists believe that people are loss averse and are unhappy when the suffer losses than they are when they make gains. Also, people tend to be overconfident in their own judgment. “As a result, it is no surprise that investors tend to believe that they are smarter than other investors and so are willing to assume that the market typically does not get it right and therefore trade on their beliefs” (Mishkin & Eakins 2009, p.142). Overconfidence and social contagion can provide an explanation for speculative bubbles in stock markets.
However, in line with the defenders of efficient market hypothesis, one can say that behavioural finance strengthens the case for EMH in that it highlights biases in individuals and committees, not competitive markets. Behavioural psychologists, mutual fund managers and economists are all drawn from the human population and are therefore subject to the biases that behaviouralists showcase.
The concept of EMH asserts that current market price of a security instantly and fully reflects all available information. Investors cannot consistently achieve returns in excess of average market returns on a risk-adjusted basis, given the information publicly available at the time. The EMH has been applied extensively to theoretical models and empirical studies of financial securities prices, generating considerable controversy as well as fundamental insight into the price discovery process. Some of the arguments against the EMH involve size effects, seasonal effects, excess volatility, mean reversion and market overreaction. Some of these anomalies pertaining to market efficiency can be explained by the impact of transaction costs. That is, cost-benefit analysis made by those willing to incur the cost of acquiring the valuable information in other to trade on it. There is also no clear evidence that these anomalies seriously challenge the EMH.
Psychologists and behavioural economists recently, argue that EMH is based on counterfactual assumptions regarding human behaviour. One cannot rule out the existence of behavioural or psychological influences on stock market pricing. Behavioural finance should therefore be seen as a case that strengthens the EMH as price signals in financial markets are far less subject to individual biases highlighted by Behavioural Finance.
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