Finance Markets and Investment: Market Efficiency Hypothesis


The market Efficiency hypothesis has over the years received numerous criticisms due to its impractical theories and policies that prove insignificant in today’s changing economy. The purported irregularities or anomalies of stocks markets about their behavioral underpinnings are reported to represent strong evidence against the EMH in relation to their predictability and efficiency. Basic findings suggested by various researchers in this essay have proven that the relationships between predictability and efficiency no longer prove significant since they are contradictory in nature. The results of this analysis demonstrate that irregularities in the market behavior are connected to systematic factors such as stock sizes, price-earnings ratios, and price-book value ratios rather than the pre-calculated tests that prove impractical to some firms. The most controversial issue in financial markets is the possibility of whether the financial markets are efficient in allocating or using economic resources and information.

Criticism of Market efficiency hypothesis

The efficient market hypothesis (EMH) popularly known as the Random walk theory states that stock prices fully reflect information about their current values and there is no way investors would earn excess profit by using any other information. Therefore, current prices should reflect the information contained in all past prices including charts and technical analysis, valuable in finding undervalued stocks. The current prices should also reflect the information contained in past prices of all public information including financial statements and news reports as well as the private sectors which should help investors to consistently find undervalued stocks. This hypothesis is embedded in financial fundamentals that explain how prices change and how changes occur in stock markets. It’s widely understood that market inefficiencies are errors that make market price biased making prices greater than or less than the true value of market prices. This hypothesis implies that investors without the information will not beat the market, stocks prices will not deviate from the true values and no group of investors will beat the market at any given time. This is to mean that stock prices do not have to be random at all times-contrary to the random theory hypothesis, and there can be large deviations from the true stock values.

Efficient market hypotheses have also been unable to perform market tests that provide the basis for a scheme to beat the market and earn excess returns. These inefficiencies have always been attributed to the inability of stocks to trade hence higher transactions costs and the existence of profit-maximizing investors who are unable to recognize the potential for excess returns and improvise schemes that will replicate excess returns and provide resources to trade on stock on unstable markets. Investors always try to identify securities that are undervalued and are expected to increase in the future. They often think that they can select securities that will outperform the markets by using this market information which apparently never works. According to Clarke and his colleague’s theory of efficient markets, attempts to use forecasting and valuation techniques as aiding tools in investment decision does not prove effective since the advantage gained does not exceed the transaction and research costs incurred, therefore no one can predictably outperform the markets. This theory that claims that investors cannot outperform the markets seems incorrect since many successful market analysts such as Peter Lynch, George Soros among others have used the same techniques and outperformed the markets.

The most crucial hypothesis of EMH is the inherent slogan of trust market prices stated by Clarke, Jannik, and Mandelker as “At any point in time, prices of securities inefficient markets reflect all known information available to investors”. This means that investors entirely rely on this market information for investment decisions and in this case, all stocks are fairly priced and investors get what they paid for which is not usually the case. Under normal circumstances, investors do not usually get what they paid for as they do not perform similarly since some are likely to experience profits and losses at some point. The capital market theory according to Clarke, Jandik and Mandelker means that “the price of a security reflects the present value of its future expected cash flow”. In their explanation, they include factors such as volatility, liquidity, and risk of bankruptcy as components of price determination which further explains that the rationality of the price is based on changes in prices which are expected to be random and unpredictable-hence the name, the random walk.

The introduction of new information in the markets can be efficient to some investors and inefficient to others in relation to differential tax ratios and transactions costs, which serves as an advantage to some and relative to others. The hypothesis that claims that information announcements will either increase or decrease stock prices stated in Bacon & Gerdorff is not consistent with Clarke’s and his colleague’s 3argument of market hypothesis theory that states that markets benefit from predicting prices. Price changes entirely depend on the arrival of new information, and therefore current prices reflect all new information gathered from the markets at any given time. This could mean that investors have time to trade and profit from new information. Over the years, it has always been believed that markets are efficient in reflecting information about stocks and stock markets. The accepted view was that when new information arises, it spreads in the market which is then incorporated into the prices. This theory does not provide any technical analysis that explains how past prices predict future prices or even fundamental analysis which provide financial information of company’s earnings and asset values in the selection of undervalued stocks.

Malkiel also argues that the profitability of market information depends on investors’ ability to identify over and undervalued stocks which requires a significant amount of time and money to determine miss-priced stocks. Therefore as analysts compete against each other to find these stocks, the chances of finding and exploiting such stocks become slimmer and in equilibrium perspective, few analysts may be able to profit from such detection.

Market Anomalies

According to Damodaran, markets anomalies are those market practices that deviate from the normal common rules. Numerous studies on market efficiencies have covered various examples of market behaviors that are inconsistent with the tests models industry analysts have put in place to measure risks and returns that often defy rational explanations. The persistence of these theory patterns suggests that there exist problems in some of the anomalies used in measuring risks and returns which ignores financial markets behaviors. On psychological and behavioral elements of stock-price determination, econometricians argue that stock prices are at a considerable extend predictable. This hypothesis may not be entirely true since some anomalies of stock markets do not create portfolio trading opportunity that enables investors to earn extraordinary risks adjusted returns. First of all, efficiency is defined by Malkiel as one that “does not allow investors to make extra returns above-average returns without accepting above risks”. Does this mean that markets can be efficient even if they sometimes make errors in valuation? Are markets still efficient when market participants are irrational? Are markets still efficient when stock prices exhibit greater volatility?

Markets have been perceived to reflect new information rapidly, which is then reflected in the prices, hence EMH makes us believe that markets are efficient because they allow investors to earn above-average risk-adjusted returns. If this statement was indeed true, the internet bubble that occurred during 1999 would have not have occurred in the first place. According to Malkiel, stock markets may be a voting mechanism in the short term, and weighing mechanisms in the long term, which means the true value of an asset, will win out in the end. In another argument, investors cannot exploit markets anomalies or patterns that may exist. In my

perception, predictable patterns are predicted to be sufficiently robust, which may mean investment opportunities for investors, and after they have been published, they certainly can not make any profits. The efficient market hypothesis also does imply that investors will not beat the market, stocks prices will not deviate from the true values and no group of investors will beat the market at any given time, which is not entirely true.

A non-random walk

Short-term momentums supporting the notion of randomness in stock prices such as reaction to new information support the view that stock markets only hold on to information that affects stock prices at the present and does not reflect on how they behave in the future. Lo and MacKinlay assertions that short term serial correlations are not zero are valid in the sense that investors attempt to move in the same direction reject the hypothesis of random walks. In another argument, Lo and Mamaysky, and Wang suggest that the use of the non parametric statistical techniques that recognize patterns such as head and shoulder and double bottoms may have modest predictive power. According to Ross and Randolph classification, Weak theory stipulates that an investor can’t achieve positive abnormal returns by using past information on the stock prices. It’s believed that when markets are weak, the stock prices must have already incorporated past information prior to the announcement.

Another Ross’s and Randolph’s theory known as the ‘Random Walk’ stresses states that investors may not always agree on the value of stock prices hence causing the stock prices to go up and down. She continues that although the real value may be unknown, the prices fluctuate around their intrinsic value hence making the market inefficient. In the Semi-Strong form Markets, stock prices reflect on all the available public information and investors entirely rely on this for market analysis. This would mean that investors without the available information will not be able to outperform the market. The theory does not prove sufficient since none of the market analysts has tested the hypothesis by examining the adjustment of the market to publicly available information such as merger announcements.

Economists in behavioral finance connect short-term momentums to be consistent with psychological feedback mechanisms. This implies that people are instantly drawn into the markets when stock prices rise, a term he refers to as the bandwagon effect. This is explained in Shiller who describes the psychological effect that took place in the U.S stock markets during the 1990s that resulted in irrational exuberance. Another linkage of short-term momentums of psychological behavioral feedback mechanisms is the tendency of investors to under-react to new information. This, therefore, means that the full impact of new information in the markets can only be effected over a period of time, and stock prices for this case will exhibit a positive serial correlation. Behavioral finance of momentum, as opposed to EMH of randomness, seems reasonable in interpreting markets results as an indication that markets are inefficient.

Odean on the other hand argues that stock markets do not display mathematically perfect random walk. To understand this hypothesis, it is important to distinguish statistical significance from economic significance. From a statistical perspective, the variables giving rise to price momentum are extremely small hence investors can not entirely rely on them to realize excess returns. This simply implies that investors paying transaction costs based on variables earlier discussed such as buy and hold strategy, may not necessarily realize excess returns. Quite a several investors lamented that buy and hold strategy statistical evidence of positive momentum, due to large transaction costs involved in an attempt to exploit the whatever momentums that existed. This simply implies that investors may not realize profits due to the transaction costs incurred in their execution.

The behavioral hypothesis about the bandwagon effect and under-reaction of new information does not provide enough evidence to support the hypothesis that stipulates such effects occur systematically. Fama and French employ event studies that seek to determine if stock prices respond efficiently to information. The empirical studies included events such as stock splits, dividend actions, mergers, initial public offering, earning surprises, and new exchange listings. Fama findings concluded that under-reaction to information is just as common as an overreaction, and post-event continual is just as common as post-event reversals of abnormal returns. He also explains that returns anomalies arise from particular models and results tend to disappear when exposed to different statistical approaches. This, therefore, means that different methods to adjust risks, contrary to efficient Markey hypothesis theory.

This simply means that the study of EMH which gives equal weight to post-announcements of returns can produce different results from a study that weighed the stocks according to their value. These momentums do not offer investors a dependable way to earn returns. Another inconsistency hypothesis is that of momentum strategy which referrers to buying stocks that display positive serial correlation. For example, during the 1990s, stock prices seemed to produce positive returns but highly negative returns during 2000. This is to means that stock-price patterns are fashionable in helping investors predict stocks that will yield high returns. But evidently, predictable patterns often disappear soon they are published because anomalies employed tend to concentrate on results obtained from sifting through mountains of financial data.

Temporary Anomalies

A number of tests that measure returns across certain periods are reported to be difficult to rationalize hence jeopardizing the credibility of the results obtained. Some of the temporary anomalies include January and weekend effects.

January Effect

Studies conducted on major financial markets reveal that there exist strong differences in return behaviors across different months of the year, January to be precise. January returns have consistently been higher than returns of any other month, a phenomenon I call the ‘January effect. Therefore the relationship between January effect and small firms adds to the complexity of market efficiency tests. The studies continue to assert that January’s first two weeks are more favorable to smaller firms as many of them report double premiums.

Secondly, countries employ different tax systems and the January effect may seem inapplicable. Another rationale that contradicts this theory is that the January effect is directly related to the institutional trading behavior which should not be averaged as part of the firm’s earnings because their buys and sells of stocks fall significantly below average on the days before the January effect and the months that follow.

The weekend effect

The Weekend effect in market analysis refers to the differences between Mondays to Fridays. It should however be noted that the negative returns on Monday are not a result of intraday returns. The theory on stock returns behaviors are inconsistent with the rational market hypothesis since investors s expect the bad news over the weekend hence making the weekend effect theory unreliable market efficiency test. Also, the negative attributes of weekends cannot be entirely blamed to the absence of trading over the weekend.


Efficient market hypotheses are always provocative given the implications they have on market efficiencies, investment management, and research as a whole. If an efficient market is defined as a market where the price is unbiased in estimating the true value of stocks, then price determination modules should be transparent and made available to everyone. It’s also evident that the capacity of markets to correct inefficiencies depends part on ease of trading, transaction cost, and the vigilance of profit-seeking investors in the market rather than the unfounded modules business analysts are trying to suggest. The research also explains strategies that can be used to test market efficiencies but the only test that seems reliable is the event study tests which examine market reactions to information and Portfolio studies, which evaluate the returns of portfolios based on observable characteristics.

Irregularities in the market behavior are connected to systematic factors such as stock sizes, price-earnings ratios, and price-book value ratios as well as time have been reported to be inefficient. Market analysts, who on the other hand have the power to solve these inefficiencies, have a difficult time consistently beating financial markets. The persistence of irregularities and the inability of market analysts to beat markets prices are demonstrated by the gap that exists between empirical tests on paper and real-world money management and the failures of model risks and returns to others. Basic findings suggested by various researchers in this essay have proven that the relationships between predictability and efficiency no longer prove significant since they are contradictory in nature. The results of this analysis demonstrate that irregularities in the market behavior are connected to systematic factors such as stock sizes, price-earnings ratios, and price-book value ratios rather than the pre-calculated tests that prove impractical to some firms.

Reference List

Bacon, F & Gerdorff, N, ‘U.S Mergers and Acquisition: A Test of Market Efficiency’, Journal of Finance and Accountancy, 2007, pp.1-8.

Bollerslev, T, & Hodrick, R J, ‘Financial Market Efficiency Tests’, National Bureau of Economic Research, vol. 4108,1992, pp. 1-78

Clarke,J, Jandik, T & Mandelker, G, ‘ The Efficient Markets Hypothesis’, Journal of Finance, vol.22, 1991, pp.1-22

Damodaran, A, ‘Market Efficiency: Definitions and Tests’, Financial Review Journal , 2007, pp.1-45.

Fama, E, & French, K, ‘Permanent and Temporary Components of Stock Prices,’ Journal of Political Economy, vol.96, 1988, pp. 246-273.

Lo, A W, & MacKinlay, A C, A Non-Random Walk Down Wall Street, Princeton University Press, Princeton, 1999

Lo, A W, Mamaysky,H, & Jiang, W, ‘Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation,’ Journal of Finance, vol.55, 2000, pp. 1705-1765

Malkiel, B G, A Random Walk Down Wall Street, 1st.edn, Norton & Company, New York, 1973

Odean, T, ‘Do investors trade too much?’ American Economic Review, vol. 89, 1999, pp.1279-1298

Ross, S A & Randolph, W A, Corporate Finance, McGraw-Hill Companies, United States, 2008

Shiller, R.J, ‘Do stocks prices move so much to be justified by subsequent changes in dividends?’ American Economic Review, vol. 71, no.3, 1981, pp. 421-36