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You Can't Become Rich In Your Pocket Until You Become Rich In Your Mind | ||||
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There is a sense that insiders, analysts and portfolio managers must possess an advantage over the average investors in the marketTemporal Anomalies There are a number of peculiarities in return differences across calendar time that are not only difficult to rationalize but are also suggestive of inefficiencies. Furthermore, some of these temporal anomalies are related to the small firm effect described in the previous section. a. The January Effect Studies of returns in the United States and other major financial markets consistently reveal strong differences in return behavior across the months of the year. Figure 6.12 reports average returns by month of the year from 1926 to 1983. Returns in January are significantly higher than returns in any other month of the year. This phenomenon is called the year-end or January effect, and it can be traced to the first two weeks in January. The relationship between the January effect and the small firm effect adds to the complexity of this phenomenon. The January effect is much more accentuated for small firms than for larger firms, and roughly half of the small firm premium, described in the prior section, is earned in the first two days of January. Figure 6.13 graphs returns in January by size and risk class for data from 1935 to 1986. A number of explanations have been advanced for the January effect, but few hold up to serious scrutiny. One is that there is tax loss selling by investors at the end of the year on stocks which have lost money to capture the capital gain, driving prices down, presumably below true value, in December, and a buying back of the same stocks12 in January, resulting in the high returns. The fact that the January effect is accentuated for stocks which have done worse over the prior year is offered as evidence for this explanation. There are several pieces of evidence that contradict it, though. First, there are countries, like Australia, which have a different tax year, but continue to have a January effect. Second, the January effect is no greater, on average, in years following bad years for the stock market, than in other years. A second rationale is that the January effect is related to institutional trading behavior around the turn of the years. It has been noted, for instance, that ratio of buys to sells for institutions drops significantly below average in the days before the turn of the year and picks to above average in the months that follow. This is illustrated in Figure 6.14. It is argued that the absence of institutional buying pushes down prices in the days before the turn of the year and pushes up prices in the days after. The universality of the January effect is illustrated in Figure 6.15, which examines returns in January versus the other months of the year in several major financial markets, and finds strong evidence of a January effect in every market. b. The Weekend Effect The weekend effect is another return phenomenon that has persisted over extraordinary long periods and over a number of international markets. It refers to the differences in returns between Mondays and other days of the week. The significance of the return difference is brought out in Figure 6.16, which graphs returns by days of the week from 1962 to 1978. The returns on Mondays are significantly negative, whereas the returns on every day of the week are not. There are a number of other findings on the Monday effect that have fleshed I out. First, the Monday effect is really a weekend effect since the bulk of the negative returns is manifested in the Friday close to Monday open returns. The returns from intraday returns on Monday are not the culprits in creating the negative returns. Second, the Monday effect is worse for small stocks than for larger stocks. Third, the Monday effect is no worse following three-day weekends than two-day weekends. There are some who have argued that the weekend effect is the result of bad news being revealed after the close of trading on Friday and during the weekend. They point to figure 6.16, which reveals that more negative earnings reports are revealed after close of trading on Friday. Even if this were a widespread phenomenon, the return behavior would be inconsistent with a rational market, since rational investors would build in the expectation of the bad news over the weekend into the price before the weekend, leading to an elimination of the weekend effect. The presence of a strong weekend effect in Japan, which allowed Saturday trading for a portion of the period studies here indicates that there might be a more direct reason for negative returns on Mondays than bad information over the weekend. As a final note, the negative returns on Mondays cannot be just attributed to the absence of trading over the weekend. The returns on days following trading holidays, in general, are characterized by positive, not negative, returns. Figure 6.18 summarizes returns on trading days following major holidays and confirms this pattern. Evidence on Insiders and Investment Professionals There is a sense that insiders, analysts and portfolio managers must possess an advantage over the average investors in the market and be able to convert this advantage into excess returns. The evidence on the performance of these investors is actually surprisingly mixed. a. Insider Trading The SEC defines an insider to be a officer or director of the firm or a major stockholder (holding more than 5% of the outstanding stock in the firm). Insiders are barred from trading in advance of specific information on the company and are required to file with the SEC when they buy or sell stock in the company. If it is assumed, as seems reasonable, that insiders have better information about the company, and consequently better estimates of value, than other investors, the decisions by insiders to buy and sell stock should affect stock prices. Figure 6.19, derived from an early study of insider trading by Jaffe, examines excess returns on two groups of stock, classified on the basis of insider trades. The buy group includes stocks where buys exceeded sells by the biggest margin, and the sell group includes stocks where sells exceed buys by the biggest margin. While it seems like the buy group does significantly better than the sell group in this study, advances in information technology have made this information on insider trading available to more and more investors. A more recent study of insider trading examined excess returns around both the date the insiders report to the SEC and the date that information becomes available to investors in the official summary. Figure 6.20 presents the contrast between the two event studies. Given the opportunity to buy on the date the insider reports to the SEC, investors could have marginal excess returns, but these returns diminish and become statistically insignificant, if investors are forced to wait until the official summary date. None of these studies examine the question of whether insiders themselves make excess returns. The reporting process, as set up now by the SEC, is biased toward legal and less profitable trades, and away from illegal and more profitable trades. Though direct evidence cannot be offered for this proposition, insiders trading illegally on private information must make excess returns. b. Analyst Recommendations Analysts clearly hold a privileged position in the market for information, operating at the nexus of private and public information. Using both types of information, analysts issue buy and sell recommendations to their clients, who trade on its basis. While both buy and sell recommendations affect stock prices, sell recommendations affect prices much more adversely than buy recommendation affect them positively. Interestingly, Womack (1996) documents that the price effect of buy recommendations tends to be immediate and there is no evidence of price drifts after the announcement, whereas prices continue to trend down after sell recommendations. Figure 6.21 graphs his findings. Stock prices increase by about 3% on buy recommendations whereas they drop by about 4% on sell recommendations at the time of the recommendations (3 days around reports). In the six months following, prices decline an additional 5% for sell recommendations, while leveling off for buy recommendations. Though analysts provide a valuable service in collecting private information, or maybe because they do, there is a negative relationship in the cross-section between returns earned by stocks and the number of analysts following the stock. The same kind of relationship exists between another proxy for interest, institutional ownership, and returns. c. Money Managers Professional money managers operate as the experts in the field of investments. They are supposed to be better informed, smarter, have lower transactions costs and be better investors overall than smaller investors. The earliest study of mutual funds by Jensen suggested that this supposition might not hold in practice. His findings, summarized in Figure 6.22, as excess returns on mutual funds, were that the average portfolio manager actually underperformed the market between 1955 and 1964. These results have been replicated with mild variations in the conclusions. In the studies that are most favorable for professional money managers, they break even against the market after adjusting for transactions costs, and in those that are least favorable, they underpeform the market even before adjusting for transactions costs. The results, when categorized on a number of different basis, do not offer much solace. For instance, Figure 6.23 shows excess returns from 1983 to 1990, and the percentage of money managers beating the market, categorized by investment style. Money managers in every investment style underperform the market index. Figure 6.24, from the same study, looks at the payoff to active portfolio management by looking at the added value from trading actively during the course of the year and finds that returns This table indicates that a money manager who was ranked in the first quartile in a period had a 26% chance of being ranked in the first quartile in the next period and a 27% chance of being ranked in the bottom quartile. There is some evidence of reversal in the portfolio managers in the lowest quartile, though some of that may be a reflection of the higher risk portfolios that they put together. While the evidence is depressing for active portfolio management as a whole, there are a few bright spots. Carhart (1992) looked at mutual funds and concluded that there was some persistence at the extremes - a small group of exceptional managers who outperform a passive strategy and another group who consistently underperform, largely because they have high expenses. |
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