On another hand, someone argue that the market anomalies and through analyzing the behavior of past share price, it is possible to make the predictability. Now the paper will list some empirical evidences against the weak form efficiency:
Seasonal effect.
Malkiel (2003) claims that January is a quite unusual month for the capital market return because in general, the share return will be higher during the first couple weeks for a year. That is called January Effect. To take advantage of January effect, investors should buy shares in December and sell in January. There is also a weekend effect, as French (1980) mentioned that there is an abnormal returns on Friday and falls on Monday which generate a lower return. From this viewpoint, due to the share return will fall on Monday, if the investors want the superior return, they should buy the shares on Monday or other weekday at a lower price, hold it during the weekdays and sell it in Friday at a higher price.
However someone argues that these seasonal patterns are not very reliable. Malkiel (2003) claims that these anomalies are not dependable from period to period. Arnold (2002, p617) also claims that these effects are not useful because the January effect only works when the share price in the end of year is low and will increase in the January. Then this lead to the investors rush to buy the shares in the end of the year because of the lower price. But if all the investors in the capital market try to purchase in end of year, this will push the share price go up. And then if all of investors sell the shares in January, that will reduce the price. As the result, no one can benefit from January effect.
Underreaction
Recently the behavioural finance becomes more obviously inconsistence with the random walk theory and weak-form EMH. The behaviouralists claim that there is a tendency for the investors to underreact to new information. As the Malkiel (2003 p61) described that “if the full impact of an important news announcement is only grasped over a period of time, the share price will show the positive serial correlation in the short period of time.” Because the investors are slow react to the news, then once the news is released, market doesn’t have the rapid response to it, then the market price may change gradually in a time of period. In this way, it is possible to predict the future share price and get superior return in post announcement period.
However Malkiel (2003) argues that many predictable patterns will disappear after they are published in the finance literature. The reason is simple because if all people predict that a share price will rise tomorrow, then everyone will buy it today, as result, the price will rise to the normal immediately today! At same time pattern is disappeared! Due to the existence of these patterns only last really short time, that is useless for most investor to get the excess returns. In this way, these patterns never guarantee the stable excess return for the investors.
Overreaction
In contrary to the underreaction, there are many evidences show a negative serial correlation i.e. return reversals, exists in the long run period. The investors tend to overreact to the new information. Fluck, Malkiel and Quandt (1997) found that if the selected share has got bad return in the first period (3-5 years), then they will have a good return in the next period time. On contrary, the shares with the good returns in the first period will have a lower return in the next period. That is due to the investor’s overreaction. Such as the first condition, due to the investor excessive pessimism to the bad news, the shares will be undervalued in the first period, however after long time undervalue, this share price tend to rise to a more fair level. In this way, they proof the very statistical evidence of the return reversals and the market inefficiency. Therefore it is possible to predict the future performance of portfolios. (Arnold 2003 pp614)
Semi strong form efficiency
Fama (1970) described semi-strong form as that share prices fully reflect all public information, including a company's history and information from financial statements, the industry and macroeconomic environment, e.g. annual report, new policy or the earning announcement etc. Therefore, under this form, the investor cannot get any superior returns by using fundamental analysis, such as analyze the company’s annual report or news announcement.
In order to test whether this form works in the real world, it needs to test the speed of the change of share prices in response to the new information release. The first test has been done by Fama, Fisher, Jensen and Roll (1969). In their study, they used the capital asset pricing model as the tool to do the comparison. They found the positive evidence on share price’s reaction to the new information releases. And most of the share price’s adjustment have been finished before the events are released to the public. And furthermore, once the news is received by the market, the prices will change to a fair level rapidly and accurately. They also claims that “the price reflect not only the direct estimates of prospective performance, but also information that requires more subtle interpretation.”
However there are some evidences against the semi-strong efficiency.
Price-earning formation
The company published account is the important source of the information about its performance. According to the semi-strong form, these information should be already reflected in the market price. However Basu (1977) study 1400 companies in period of 1956-1971, and found the low P/E ratio shares outperforming the high P/E shares by more than 7% per year. In this way, P/E ratio will be a indicator for share return.
However Schwert (2001) point out that the investment strategies of purchasing value stock (low P/E ratio stock) doesn’t work properly in 1990s. His test shows that if the sample data was collected form 1990s, then low P/E ratio stock cannot generate the excess return.
Size effect
Banz (1981) analyse monthly returns over period of 1931-75 on the share listed on New York Stock Exchange. Over this period, the share of 50 smallest companies outperformed the share of 50 largest companies by an average of 1% per month. More recently, Fama and French (1993) do the similar test of small size effect. They examined the data from 1963-1990. As result, they also found the same tendency that small companies’ shares generate the higher monthly return than large one. In this way, the small-firm effect can be an indicator for the future share return. And based on this effect, the return of a company will decrease when its size/market capitalization gets bigger.
However someone argue that the small size effect doesn’t work recently, especially in 1980s to 1990s. During that period, the share of the large size companies generated higher return than the small one. For example in UK, Arnold (2003 pp618) show that in period of 1950s-1980s, the share of small companies produced the 5.2% return higher than large one annually. But in period of 1989-2000, the large companies produce the 4.3% return higher than small one. Aronld (2003) believes that the reason of these opposite result in different period might because the too many investors notice this effect and rush to exploit it in the late of 1980s. As the general rule, people cannot make money by following market. Therefore this makes the small size effect be disappear! Malkiel (2003) also believe that the reliability of small size effect may be influenced by some bias, such as: these study which aims to test small size effect just use the data from the survived small companies. But the problem is this database didn’t include the one that have bankrupted. So these researches only test this effect through the performance of today’s small companies, not the failed one. This may lead to the bias of their study.
Strong Form efficiency
Fama (1970) said in strong form efficiency, the share prices fully reflect all public and private information. Therefore the investors cannot get the excess return, even they have the inside information. Again, this does not mean that the investors can't success, it only means that success should not be predicted.
However many studies have showed that only early exploitation of the new information or the patterns can earn the excess return. Some insiders, such as the directors of the company who may grasp the price sensitive information earlier than the public can make the excess return. But this kind of “insider dealing” is illegal at all. As Arnold (2003) mentioned that inside dealing will cause a unfair game. Only the insiders can make the excess return, then the outsiders will feel be cheated. Once these outsiders lose their confidence on investment, the whole game is close to be end. In order to avoid this happen, all the capital markets traded the insider dealing as the crime!
Apart from these directors of the companies, there are some of the investment professionals are pure outsiders, but they also have lots of the superior information compared with the normal investors. They just grasp these information or knowledge about companies through analyzing the company’s situation and its environment to make the predictability. As Arnold (2003) said that these investment analysts always visit the companies and participate to discuss companies’ opportunities and potential problems. Therefore they are very familiar with the companies’ situation, so their predictability about companies’ future will be very valuable! In order to test this viewpoint, Jensen (1968) analyze 115 mutual funds in period of 1955-1964. As result he found that most of these portfolio managers can not beat the market at all. More recently, Fama (1991) also do some research on the performance of mutual fund and institutional portfolio managers. And he found that these people only made a small abnormal gross returns before the tax, but little of them can make the superior return and can beat market! We should notice that EMH allow the existence of the minor excess return. In this way, although the analyst may achieve some small excess return, but it can not proof that market is inefficient.
Further Explanation
In these parts mentioned above, I have discussed the “for and against” empirical evidence for the EMH. Now this paper will provide the further explanation for EMH.
As Malkiel (2003) said that all researches who claiming the death of the EMH are greatly exaggerated; and the views believe that market prices are predictable has been vastly overstated.
Firstly, it’s no doubt that some anomalies do exist in market place. However the central question is whether these anomalies can persist in the long time, and by exploiting these effects or indictors, whether it is possible for most investors to predict the future share price. Therefore the long-run reliability of these effects are doubtful! Lots of the evidence shows that these anomalies can not persist longer due to lots of investors rush to exploit the same effects and indictors, and this will prevent these anomalies generate the ourperformance in the future.
Secondly, Malkiel (2003) believes that many of the anomalies is just the result of “data snooping”, i.e. letting the computer search through the data sets of past share prices in the hopes of finding some relationships. Therefore it is not surprising that some seemingly significant but wholly spurious correlations have been found, especially when some researches really hope their works can show some anomalous results rather than boring confirmations of randomness. (Malkiel 2003 pp74)
Next, maybe there are evidences of some investors beat the market successfully. However many people argue that outperformance by one or a few investor in a market cannot proof the inefficiency of market because it is difficult to determine whether outperformance is made by skill or luck. Additionally, in many cases, strong performers in one period will make a underperformance in subsequent periods. Lots of studies have found little or no correlation between strong performers from one period to the next. Therefore these examples can’t proof that they success just due to exploiting true anomaly.
Finally, even if there is a dependable predictable relationship, investors may not earn the excess return due to the transaction cost. For example, as Malkiel (2003) said that the transaction costs involved in trying to exploit the January effect are sufficiently large that the predictable pattern is not economically meaningful.
Conclusion
What can we conclude about the EMH? From theoretical point of view, EMH is reliable. However market efficiency is difficult to test. The reason that there are lots of counterpoints come out may be explained as the shortcoming of current asset pricing models.(Ball 1978) With the passage of time, there will be some more reliable asset pricing model occur.
One thing is clear that the academic tests are not the same thing as managing the real money. From a practical point of view, markets are neither perfectly efficient nor completely inefficient. I do believe that irrational pricing and predictable patterns in share returns may well exist and even persist for periods of time. And the markets may also be influenced by fashions, such as the Internet bubble in late of 1990s evident the incorrect share pricing. In this way, for a short period of time, the market may lose its efficiency temporarily, but finally this kind of inefficiency will be corrected! In the long-term period, that is just an exception that only persist short period of time, so it can’t proof that the market is completely inefficient.
Reference:
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Ball, R. (1978). “Anomalies in Relationships Between Securities’ Yields and Yield-Surrogates”, Journal of Financial Economics, 6, pp. 103-26.
-
Banz, R.(1981). “The Relationship Between Return and Market Value of Common Stocks”, Journal of Financial Economics, 9, pp. 3-18.
-
Basu, S. (1977). “The Investment Performance of Common Stocks in Relation to their Price to Earnings Ratio: A Test of the Efficient Markets Hypothesis”, Journal of Finance, 32, pp. 663-682.
-
Rattiner, J. H.(2002). Efficiency Expertise. Financial Planning. Jun2002, Vol. 32 Issue 6, p79
-
Kendall, M (1953). “The Analysis of Economic Time Series”, Journal of the Royal Statistical Society, Series A, 96, pp. 11-25.
-
Malkiel, B.G (2003). The efficient market hypothesis ad its critics. Journal of economic perspectives. Vol 17. Winter 2003 pp59-82.
-
French,K (1980). Stock returns and the weekends effect. Journal of financial economics March 1980 pp55-69
-
Fluck,Z; Malkiel,B and Quandt,R (1997) the predictability of stock returns: a cross-sectional simulation. Review of economics and statistics. 79:2 pp176-183
-
Fama, E. Fisher, L. Jensen, M and Roll, R (1969). “The Adjustment of Stock Prices to New Information”, International Economic Review, 10, pp. 1-21.
-
Bernard,V.L. and Thomas, J.K (1989) post-earing announcement drift: delayed price response or risk premium?” journal of accounting research. 27
-
Fama,E and French,K (1993) Common risk factors in the returns on stocks and bonds. Journal of finance. 33:1
-
Jensen, M. (1968). “The Performance of Mutual Funds in the Period 1945-1964”. Journal of Finance, 23, pp. 389-416.
-
Schwert, G.W (2001) anomalies and market efficiency. Handbook of Economics of finance. Chapter 17. Holland.
