CHAPTER 11: THE EFFICIENT MARKET HYPOTHESIS
The correlation coefficient between stock returns for two non-overlapping periods should be zero. If not, one could use returns from one period to predict returns in later periods and make abnormal profits.
No. Microsoft’s continuing profitability does not imply that stock market investors who purchased Microsoft shares after its success was already evident would have earned an exceptionally high return on their investments.
Expected rates of return differ because of differential risk premiums.
No. The value of dividend predictability would be already reflected in the stock price.
No, markets can be efficient even if some investors earn returns above the market average. Consider the Lucky Event issue: Ignoring transaction costs, about 50% of professional investors, by definition, will “beat” the market in any given year. The probability of beating it three years in a row, though small, is not insignificant. Beating the market in the past does not predict future success as three years of returns make up too small a sample on which to base correlation let alone causation.
Volatile stock prices could reflect volatile underlying economic conditions as large amounts of information being incorporated into the price will cause variability in stock price. The Efficient Market Hypothesis suggests that investors cannot earn excess risk-adjusted rewards. The variability of the stock price is thus reflected in the expected returns as returns and risk are positively correlated.
The following effects seem to suggest predictability within equity markets and thus disprove the Efficient Market Hypothesis. However, consider the following:
Multiple studies suggest that “value” stocks (measured often by low P/E multiples) earn higher returns over time than “growth” stocks (high P/E multiples). This could suggest a strategy for earning higher returns over time. However, another rational argument may be that traditional forms of CAPM (such as Sharpe’s model) do not fully account for all risk factors which affect a firm’s price level. A firm viewed as riskier may have a lower price and thus P/E multiple.
b. The book-to-market effect suggests that an investor can earn excess returns by investing in companies with high book value (the value of a firm’s assets minus its liabilities divided by the number of shares outstanding) to market value. A study by Fama and French1 suggests that book-to-market value reflects a risk factor that is not accounted for by traditional one variable CAPM. For example, companies experiencing financial distress see the ratio of book to market value increase. Thus a more complex CAPM which includes book-to-market value as an explanatory variable should be used to test market anomalies.
c. Stock price momentum can be positively correlated with past performance (short to intermediate horizon) or negatively correlated (long horizon). Historical data seem to imply statistical significance to these patterns. Explanations for this include a bandwagon effect or the behavioralists’ (see Chapter 12) explanation that there is a tendency for investors to underreact to new information, thus producing a positive serial correlation. However, statistical significance does not imply economic significance. Several studies which included transaction costs in the momentum models discovered that momentum traders tended to not outperform the Efficient Market Hypothesis strategy of buy and hold.
d. The small-firm effect states that smaller firms produce better returns than larger firms. Since 1926 returns from small firms outpace large firm stock returns by about 1% per year. Do small cap investors earn excess risk-adjusted returns?
The measure of systematic risk according to Sharpe’s CAPM is the stock’s beta (or sensitivity of returns of the stock to market returns). If the...
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