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In an efficient market the return on a security is compensating the investor for time value of money and risk. The efficient market theory relies on the fact that stock prices follow a random walk, which means that price changes are independent of one another. Thus, stock prices follow a random walk if
- The movement of stock prices from day to day do not reflect any pattern
- Statistically speaking
- The movement of stock prices is random
- Time series of stock returns has low autocorrelation
In an efficient market competition ensures that
- New information is quickly and fully assimilated into prices
- All available information is reflected in the stock price
- Prices reflect the known and expected, and respond only to new information
- Price changes occur in an unpredictable way
The efficient market hypothesis comes in three forms: weak, semi-strong and strong efficiency
Weak form efficiency
- Market prices reflect all historical price information
Semi-strong form efficiency
- Market prices reflect all publicly available information
Strong form efficiency
- Market prices reflect all information, both public and private
Efficient market theory has been subject to close scrutiny in the academic finance literature, which has attempted to test and validate the theory.
Tests of the efficient market hypothesis
The weak form of market efficiency has been tested by constructing trading rules based on patterns in stock prices. A very direct test of the weak form of market efficient is to test whether a time series of stock returns has zero autocorrelation. A simple way to detect autocorrelation is to plot the return on a stock on day t against the return on day t+1 over a sufficiently long time period. The time series of returns will have zero autocorrelation if the scatter diagram shows no significant relationship between returns on two successive days.
- Consider the following scatter diagram of the return on the FTSE 100 index on London Stock Exchange for two successive days in the period from 2005-6.
- As there is no significant relationship between the return on successive days, the evidence is supportive of the weak form of market efficiency.
The semi-strong form of market efficiency states that all publicly available information should be reflected in the current stock price. A common way to test the semi-strong form is to look at how rapid security prices respond to news such as earnings announcements, takeover bids, etc. This is done by examining how releases of news affect abnormal returns where
- Abnormal stock return = actual stock return - expected stock return
As the semi-strong form of market efficiency predicts that stocks prices should react quickly to the release of new information, one should expect the abnormal stock return to occur around the news release. Figure 7 illustrates the stock price reaction to a news event by plotting the abnormal return around the news release. Prior to the news release the actual stock return is equal to the expected (thus zero abnormal return), whereas at day 0 when the new information is released the abnormal return is equal to 3 percent. The adjustment in the stock price is immediate. In the days following the release of information there is no further drift in the stock price, either upward or downward.
Figure 7: Stock price reaction to news announcement
Tests of the strong form of market efficiency have analyzed whether professional money managers can consistently outperform the market. The general finding is that although professional money managers on average slightly outperform the market, the outperformance is not large enough to offset the fees paid for their services. Thus, net of fees the recommendations from security analysts, and the investment performance of mutual and pension funds fail to beat the average. Taken at face value, one natural recommendation in line with these findings is to follow a passive investment strategy and "buy the index". Investing in the broad stock index would both maximize diversification and minimize the cost of managing the portfolio.
Another, perhaps more simple, test for strong form of market efficiency is based upon price changes close to an event. The strong form predicts that the release of private information should not move stock prices. For example, consider a merger between two firms. Normally, a merger or an acquisition is known about by an "inner circle" of lawyers and investment bankers and firm managers before the public release of the information. If these insiders trade on the private information, we should see a pattern close to the one illustrated in Figure 8. Prior to the announcement of the merger a price run-up occurs, since insiders have an incentive to take advantage of the private information.
Figure 8: Stock price reaction to news announcement
Although there is ample empirical evidence in support of the efficient market hypotheses, several anomalies have been discovered. These anomalies seem to contradict the efficient market hypothesis.
Classical stock market anomalies
Small poor-performing smallcap stocks have historically tended to go up in January, whereas strong-performing largecaps have tended to rally in December. The difference in performance of smallcap and largecap stock around January has be coined the January-effect.
Although new stock issues generally tend to be underpriced, the initial capital gain often turns into losses over longer periods of e.g. 5 years.
Stocks generally tend to rise immediately after being added to an index (e.g. S&P 500, where the index effect was originally documented)
Smallcap stocks have historically tended to rise on Fridays and fall on Mondays, perhaps because sellers are afraid to hold short positions in risky stocks over the weekend, so they buy back and re-initiate.
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. Moreover, there seem to be a tendency that anomalies disappear as soon as the academic papers discovering them get published.
Behavioural finance applies scientific research on cognitive and emotional biases to better understand financial decisions. Cognitive refers to how people think. Thus, behavioural finance emerges from a large psychology literature documenting that people make systematic errors in the way that they think: they are overconfident, they put too much weight on recent experience, etc.
In addition, behavioural finance considers limits to arbitrage. Even though misevaluations of financial assets are common, not all of them can be arbitraged away. In the absence of such limits a rational investor would arbitrage away price inefficiencies, leave prices in a non-equilibrium state for protracted periods of time.
Behavioural finance might help us to understand some of the apparent anomalies. However, critics say it is too easy to use psychological explanations whenever there something we do not understand. Moreover, critics contend that behavioural finance is more a collection of anomalies than a true branch of finance and that these anomalies will eventually be priced out of the market or explained by appealing to market microstructure arguments.