Performance of Investment Analysts, Mutual Funds, and the Efficient Market Hypothesis.

We have seen that one implication of the efficient market hypothesis is that when purchasing a security, you cannot expect to earn an abnormally high return, a return greater than the equilibrium return. This implies that it is impossible to beat the market. Many studies shed light on whether investment advisers and mutual funds (some of which charge steep sales commissions to people who purchase them) beat the market.

One common test that has been performed is to take buy and sell recommendations from a group of advisers or mutual funds and compare the performance of the resulting selection of stock swith the market as a whole. Sometimes the advisers’ choices have even been compared to a group of stocks chosen by throwing darts at a copy of the financial page of the newspaper tacked to a dartboard. The Wall Street Journal, for example, has a regular feature called "Investment Dartboard" that compares how well stocks picked byinvestment advisers do relative to stocks picked by throwing darts. Do the advisers win?

To their embarrassment, the dartboard beats them as often as they beat the dartboard. Furthermore, even when the comparison includes only advisers who have been successful in the past in predicting the stock market, the advisers still don’t regularly beat the dartboard. Consistent with the efficient market hypothesis, mutual funds also do not beat the market. Not only do mutual funds not outperform the market on average, but when they are separated into groups according to whether they had the highest or lowest profits in a chosen period, the mutual funds that did well in the first period do not beat the market in the second period.

The conclusion from the study of investment advisers and mutual fund performance is this: Having performed well in the past does not indicate that an investment adviser or a mutual fund will perform well in the future.This is not pleasing news to investment advisers, but it is exactly what the efficient market hypothesis predicts. It says that some advisers will be lucky and some will be unlucky. Being lucky does not mean that a forecaster actually has the ability to beat the market.

The efficient market hypothesis predicts that stock prices will reflect all publicly available information. Thus if information is already publicly available, a positive announcement about a company will not, on average, raise the price of its stock because this information is already reflected in the stock price. Early empirical evidence also confirmed this conjecture from the efficient market hypothesis. Favorable earnings announcements or announcements of stock splits (a division of a share of stock into multiple shares, which is usually followed by higher earnings) do not, on average, cause stock prices to rise.

Although the efficient market hypothesis is usually applied to the stock market, it can also be used to show that foreign exchange rates, like stock prices, should generally follow a random walk. To see why this is the case, consider what would happen if people could predict that a currency would appreciate by 1% in the coming week. By buying this currency, they could earn a greater than 50% return at an annual rate, which is likely to be far above the equilibrium return for holding a currency. As a result, people would immediately buy the currency and bid up its current price, thereby reducing the expected return.

The process would stop only when the predictable change in the exchange rate dropped to near zero so that the optimal forecast of the return no longer differed from the equilibrium return. Likewise, if people could predict that the currency would depreciate by 1% in the coming week, they would sell it until the predictable change in the exchange rate was again near zero. The efficient market hypothesis therefore implies that future changes in exchange rates should, for all practical purposes, be unpredictable; in other words, exchange rates should follow random walks. This is exactly what empirical evidence finds.

Mark Stuart is an editor of the electronic weekly <a href="http://www.auto-insurance-review.info" target="_blank">Auto Insurance Review</a>.

Mark Stuart is an editor of the electronic weekly Auto Insurance Review.

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