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The Efficient Market Theory says that security prices correctly and almost immediately reflect all information and expectations. It says that you 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. Therefore, it assumes that at any given time, the market correctly prices all securities. The result, or so the theory advocates, is that securities cannot be overpriced or under priced for a long enough period of time to profit from them.
The Theory holds that since prices reflect all available information, and since information arrives in a random fashion, there is little to be gained by any type of analysis, whether fundamental or technical. It assumes that every piece of information has been collected and processed by thousands of investors and this information (both old and new) is correctly reflected in the price. Returns cannot be increased by studying historical data, either fundamental or technical, since past data will have no effect on future prices.
A crucial feature of the EMH is A large number of investors who follow the movements of the shares price analyse the effect and buy/sell share in a way that causes the shares price to adjust to the new information.
The implications of this are
• EM requires some minimum amount of trading.
• More trading by more investors will lead to faster price adjustment and therefore more efficiency.
• At any point in time share prices should be an unbiased reflection of all currently available information including the risk involved.
Markets can be
• Perfectly efficient one in which every securitys price equals its intrinsic value at all times
• Economically efficient Some anomalies may exist but unable to generate abnormal profits due to market imperfections such as commissions, taxes, etc.
Three levels of Market Efficiency
Weak form
• market level data
• past price or volume information
Semi-strong form
• public information
• past information
Strong form
• All public information
• all (non-public) information
Weak Form
Prices reflect all past price and volume data. Past price changes unrelated to future price changes. The implication for technical analysis, which relies on the past history of prices, is that it is of little or no value in assessing future changes in price as market adjusts or incorporates this information quickly and fully.
Semi-strong Form
Prices reflect all publicly available information and all past information. Investors cannot act on new public information after its announcement and expect to earn above-average, risk-adjusted returns. Encompasses weak form as a subset
Strong Form
Prices reflect all information, past, current and private. No group of investors should be able to earn abnormal rates of return by using publicly and privately available information. Encompasses weak and semi-strong forms as subsets.
"Anomalies are empirical results that seem to be inconsistent with maintained theories of asset-pricing behaviour. They indicate either market inefficiency (profit opportunities) or inadequacies in the underlying asset-pricing model. After they are documented and analyzed in the academic literature, anomalies often seem to disappear, reverse, or attenuate. This raises the question of whether profit opportunities existed in the past, but have since been arbitraged away, or whether the anomalies were simply statistical aberrations that attracted the attention of academics and practitioners", Schwert (00).
Some of the more common anomalies are discussed below.
Quarterly Earnings Reports Study finds that if a firm experiences unexpected positive changes in earnings (0+% higher than expected) then earns positive abnormal returns for up to 6 weeks. This doesnt support EMH (prices arent adjusting rapidly). There is also some debate as to whether the abnormal returns are found to exist due to
• Inefficiencies in the market (consensus favours this option)
• Inefficiencies in event study model used to compute expected returns.
The abnormal return was related to the size of the unanticipated earnings change (called earnings surprise).
P/E Ratios and Returns General contention firms with low P/Es will outperform those with high P/Es (high growth companies are overvalued by the market and therefore have high P/Es, but low-growth firms are undervalued, leading to low P/Es). If this is really true this would go against EMH.
Studies Basu (17) divided stocks into 5 P/E classes and determined the risk/return for the portfolios. Findings
High P/E group earned %
Low P/E group earned 16% and had lower risk (based on beta) even after adjusting for size, industry effects, and infrequent trading.
The Size Effect Do larger firms (based on Market Value) perform better or worse? Findings
Small firms (over the Long run) perform better than large firms (after adjusting for risk), although this effect is not consistent over time. There are lots of arguments over the small firm effect. Small firms arent traded as frequently and therefore, daily returns arent appropriate (because the prices experience serial correlation over time and that affects results). Roll says this causes the beta (and therefore the risk) to be underestimated. Reinganum (18) redid study based on this and found out he was right, but it still didnt completely remove the small-firm effect.
The Fama (18) study finds that a companys return is dependent upon size and price-to-book value, not beta. This would suggest that the market is inefficient.
Impact of Trading Activity Look at number of analysts who follow the stock and divided intogroups (highly followed, moderately followed, neglected). Found that there was also a neglected firm effect thus individuals might do well to invest in small neglected firms. It was thought that this effect maybe explained by trading volume in that those firms that were not traded heavily were skewed in some way. If they were then this might help explain the small firm effect (because small firms generally experience a lower trading volume). But, no, there was no significant difference in returns for those firms that experience low volume versus high volume.
The January Anomaly Investors, toward December, usually sell off to take advantage of losses on stock for tax purposes. After December, they typically want to reacquire the stocks, or reinvest their proceeds from the tax sale. This implies that in November/December there will be a large supply of stocks and in January there will be a large demand for stocks. EMH supporters argue that arbitrageurs should eliminate any effect as they would buy in December and sell in January. But, in approximately 0% of the years since 16, small firms have outperformed large firms, with approx. 40% of the return being earned in January.
Keim (18) finds
• Volume for stocks that had experienced losses during the year increased in December
• Volume for stocks that had appreciated experienced low volume (therefore, didnt sell because would have had to pay capital gains).
• In January, there were significant positive abnormal returns for stocks that had experiences losses during previous year.
Keim finds that over 50% of January effect takes place within the first week of January, particularly the first day. Other researchers have found that, while it was originally thought to be a small firm effect, it was a low price effect. The January effect was also tested in Australia (tax year ends in July, not in January). The same phenomenon exists for July (thus, some explanation for the tax effect), but the effect persists in January in Australia. It also existed in Canada which didnt have a capital gains tax during the time period tested.
Other Calendar Effects The Weekend Effect On Mondays the stock market generally goes down. Further examination revealed that this was due to an adjustment the weekend effect stock prices change from Fridays close to Mondays open and otherwise Mondays returns were positive. Also, the Monday effect was positive during January but negative for all other months and the size effect only existed in January. Keim finds that small firms do tend to have an all-day Monday effect, but larger firms have a weekend effect. Also, prices tend to rise on the last trade of the day.
Despite strong evidence that the stock market is highly efficient, there have been scores of studies that have documented long-term historical anomalies in the stock market that seem to contradict the efficient market hypothesis. While the existence of these anomalies is well accepted, the question of whether investors can exploit them to earn superior returns in the future is subject to debate. Investors evaluating anomalies should keep in mind that although they have existed historically, there is no guarantee they will persist in the future. If they do persist, transactions and hidden costs may prevent out performance in the future.
Researchers that discover anomalies or styles that produce superior returns have two choicesgo public and seek recognition for discovering the technique; or use the technique to earn excess returns. Its common for money to flow into strategies that attempt to exploit anomalies and this in turn causes the anomaly to disappear. Further, even anomalies that do persist may take decades to pay off.When searching large amounts of data, correlations between variables may occur randomly and therefore may have no predictive value. Anomalies that have existed over the longest time frames and have been confirmed to exist in international markets and out of sample periods are particularly persuasive.
Despite the documentation of the numerous existing market anomalies, they are not
significant enough to completely nullify the weak form and semi-strong form EMH,
which means that most investors are still not able to consistently beat the market.
However, many well-known individual investors have claimed that they have consistently beaten the market over the last few decades. As mentioned earlier, an efficient market does not mean that inefficiencies do not exist. It simply means that such inefficiencies do not exist for a very long period of time because the market forces are quick in correcting them. In many instances, a small investor will spot an under priced or an overpriced asset, but he/she is unable to take advantage of it. The main reason is because the transaction costs far outweigh the potential profits from such inefficiencies in most instances. In general, an investor needs to invest a huge amount of money in order to profit from such inefficiencies. In addition, most individual investors would have to spend a great deal of time to research these inefficiencies if they are to exploit them.
Appendix
Basu, S. (18) The Relationship between Earnings Yield, Market Value and Return for NYSE Common Stocks Further Evidence, Journal of Financial Economics, 1, 1-156.
Fama, E. F. (18), Market Efficiency, Long-Term Returns, and Behavioral Finance," Journal of Financial Economics, 4, 8-06.
Keim, D. B. and R. F. Stambaugh (184), A Further Investigation of the Weekend Effect in Stock Returns, Journal of Finance, , 81-85.
Schwert G. W. (00), Financial Research and Policy Working Paper No. FR 0-1 Basu, S. (18) The Relationship between Earnings Yield, Market Value and Return for NYSE Common Stocks Further Evidence, Journal of Financial Economics, 1, 1-156.
Reinganum, M. R. (18), The Anomalous Stock Market Behavior of Small Firms in January Empirical Tests for Tax-Loss Selling Effects, Journal of Financial Economics, 1, 8-104.
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