Evidence Inconsistent with the Weak Form of the Efficient-Market Hypothesis
Recall that the weak form of the efficient-market hypothesis (the random-walk notion) says simply that the technical analysis of past price patterns to predict the future is useless because any information from such as analysis will already have been incorporated in current market prices. If today’s direction – up or down, forward or backward – does indeed predict tomorrow’s step, than you will act on it today rather than tomorrow. Thus, if market participants were confident that the price of any security would double next week, the price would not reach that level over five working days. Why wait? Indeed, unless the price adjusted immediately, a profitable arbitrage opportunity would exist and would be expected to be exploited immediately in an efficient market. The arbitrageur (or “arb” as these players are now known on Wall Street) would simply buy today and then sell out at a big profit next week. If the flow of information is unimpeded then tomorrow’s price change in speculative markets will reflect only tomorrow’s “news” and will be independent of the price change today. But “news” by definition is unpredictable and thus the resulting price changes must also be unpredictable and random.
A “random walk” would characterize a price series where all subsequent price changes represent random departures from previous prices. More formally, the random-walk model states that investment returns are serially independent, and that their probability distributions are constant through time.
The earliest empirical work on the random-walk hypothesis generally found that stock price changes from time to time were essentially independent of (or unrelated to) each other. While some of these studies found that there was some slight correlation between successive price changes, researchers concluded that profitable investment strategies could not be formulated on the basis of the extremely small dependencies found.
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More recent work, however, indicated that the random-walk model does not strictly hold. As will be noted below, some consistent patterns of correlations, inconsistent with the model, have been uncovered. Nevertheless, it is less clear that violations exist of the weak form of the efficient-market hypothesis, which states only that unexploited trading opportunities should not persist in any efficient market.
Stocks do sometimes get on one-way streets.
Several studies completed during the 1980s have been inconsistent with the pure random-walk model. They show that price changes measured over short short periods of time do tend to persist. For example, researchers Andrew Lo and A.Craig MacKinlay found that for two decades ending in the mid-1980s, broad portfolio stock returns for weekly and monthly holding periods showed positive serial correlation. In other words, a positive return in one week is more likely not to be followed by a positive return in the next week.
Well, that looks like interesting news to an investor. However, this rejection of the random-walk model is due largely to the behavior of small stocks in the portfolios, which are less frequently traded than larger capitalization stocks. In part, such serial correlation may be induced by new information about the market being incorporated into large capitalization stocks first and into the smaller stocks with a tag. Thus, positive portfolio moves since the good news gets incorporated into the prices of smaller stocks only later in some instances, when the small stocks are finally traded. In any event, the research findings do not necessarily imply any inefficiences in stock price formation. It is not clear that an investor who pays commission costs can formulate a trading strategy to exploit the small correlations that have been found.
But eventually stock prices do change direction and hence stockholder returns tend to reverse themselves. Buying stocks that performed poorly durting the past two years or so is likely to give you above-average returns over the next two years. This is the finding of research carried out by Eugene Fama and Kenneth French as well as by James Poterba and Lawrence Summers. In research jargon, they say that while stock returns over short horizons such as a weel or a month may be positively correlated, stock returns over longer horizons, such as a year or more, display negative serial correlation. Richard Quandt and I have confirmed that this result continued to hold throughout the 1980s. Thus, a contrarian investment strategy – that is, buying those stocks that have had relatively poor recent performance – might be expected to outperform a strategy of buying those stocks that recently produced superior returns. The implicit advice to investors is to shun recently fashionable stocks and concentrate one’s buying on those stocks that are currently out of favor.
Of all the anomalies that have been uncovered or alleged, this one strikes me not only as one of the most believable but also as potentially most beneficial for investors. Certainly we know that fads and fashions can play a rôle in stock pricing. At times. Growth stocks have been all the rage; at other periods electronics stocks or biotechnology securities have caught investors’ fancies. No matter what the fad, all carried stock prices to extremes and led to severe losses for investors who purchased at the apex. If investors could avoid buying at the top of an unwarranted “bubble,” serious investment mistakes could be avoided. Similarly, if those stocks that were overly popular turn out to be poor investments, perhaps the stocks that have recently been shunned by investors – the ugly ducking of the investment world – will eventually come out from under their cloud. Particularly when such a contrarian approach is wedded to a fundamental-value approach (to avoid buying stocks simply because they are unpopular), investors may well benefit from such a strategy. The psychological explanation for such reversals in realized stock returns suggests the dominance of “castle-in-the-air” builders among investment decision-makers. If stock prices were always influenced by fads and fashions which tended to arise and then decay over time, such reversals in returns would be expected. Hence, many investigators have concluded that the evidence concerning reversals in returns is inconsistent with the efficient-market hypothesis. Well – maybe yes, but maybe no. There are both logical and statistical reasons to continue to stand by the theory of efficient markets.
Return reversals over different time periods are often rooted in solid economic facts rather that psychological swings. The volatility of interest rates constitutes a prime economic influence on share prices. Since bonds – the frontline reflectors of interest-rate direction – compete with stocks for the investor’s dollars, one should logicallyexpect systematic relationships between interest rates and stock prices. Specifically, when interest rates go up, share prices should fall, other things being the same, so as to provide larger expected stock returns in the future. Only if this happens will stocks be competitive with higher-yielding bonds. Similarly, when interest rates fall, stocks should tend to rise, since they can promise a lower total return and still be competitive with lower-yielding bonds.
It’s easy to see how fluctuations in interest rates can produce reversals in stocks. Suppose interest rates go up. This causes both bond and stock prices to fall and tends to produce low and often negative rates of return over the time periods when the interest rates rose. Suppose nw that interest rates fall back to ttheir original level. This causes bond and stock prices to rise and tends to produce very high returns for stockholders. Thus, over a cycle of interest-rate fluctuations, we will tend to se relatively large stock returns following low stock returns – that is, exactly the kinds of return reversals need to be due to fads that decay over time. They can also result from the very logical and efficient reaction of stock-market participants to fluctuations in interest rates.
Obviously, in any given period there are many influences on stock prices apart from interest rates so one should not expect to find a perfect correspondence between movements of interest rates and stock prices. Nevertheless, the tendency of interest rates to influence stock prices could account for the sorts of return reversals that have been found historically, and such a relationship is perfectly consistent with the existence of highly efficient markets.
Statistically, there are also reasons to doubt the “robustness” of this finding concerning return reversals. It turns out that correlations of returns over time are much lower in the period since 1940 then they were in the period before 1940. Thus, the employment of simple contrarian investment strategies is no guarantee of success. And even if fads are partially responsible for some return reversals (as when a particular group of stocks comes in and out of favor), fads don’t occur all the time.
So what’s an investor to do? As the careful reader knows, I believe that the stock market it fundamentally logical. I also recognize that the market does get carried away with popular fads or fashions. Similarly, pessimism can often be overdone. Thus, “value” investors operating on the firm-foundation theory will often find that stocks which have produced very poor recent returns may provide very generous returns in the future. Knowing that careful statistical work also supports this tendency, at least to some extent, should give investors an additional strategy coupled with a firm-foundation approach. But remember that the statistical relationship is a loose one and that some unpopular stocks may be justly unpopular. Certainly some companies that have been doing downhill may continue to go “down the tubes.” The relationships are sufficiently loose and uncertain that one should be very wary of expecting sure success from any simple contrarian strategy.
Stocks are subject to seasonal moodiness, especially at the beginning of the year and the end of the week
Discoveries of several apparently predictable stock patterns indicate that a walk down Wall Street may not be perfectly random. Investigators have documented a “January effect,” where stock returns are abnormally higher during the first few days of January. The effect appears to be particularly strong for smaller firms. Even after adjusting for risk, small firms appear to offer investors abnormally generous returns – with the excess returns being largely produced during the first few days of the year. Such an effect has also been documented for several foreign stock markets. This led to one book being published during the 1980s with the provocative title The Incredible January Effect. Investors and especially stockbrokers, with visions of large commissions dancing around in their heads, designed strategies to capitalize on this “anomaly” believed to be so dependable.
One possible explanation for a “January effect” is that tax effect are at work. Some investors may sell securities at the end of the calendar year to establish short-term capital losses for income-tax purposes. If this selling pressure depresses stock prices prior to the end of the year, it would seem reasonable that the bounce-back during the first week in January could create abnormal returns during that period. While this effect could be applicable for all stocks, it would be larger for small firms because stocks of small companies are more volatile and less likely to be in the portfolios of tax-exempt institutional investors and pension funds. One might suppose that traders would take advantage of any excess returns during this period. Unfortunately, however, the transactions costs of trading in the stocks of small companies are substantially higher than for larger companies (because of the higher bid-asked spreads) and there appears to be no way a commission-paying ordinary investor could exploit this anomaly.
Other investigators have also documented a so-called weekend effect, where average stock returns are negative from the close of trading on Friday to the close of trading on Monday. In other words, there is some justification for the expression “blue Monday on Wall Street.” According to this line of thinking, you should buy your stocks on Monday afternoon at the close, not on Friday afternoon or Monday morning, when they tend to be selling at slightly higher prices.
The general problem with these anomalies is that they are typically small relative to the transactions costs required to exloit them, and they are not always dependable in that they often fail soon after being discovered. The “small firm effect” is a good example. No sooner had it been discovered in the early 1980s than it failed to work: Small stocks were relatively poor performers throughout ,such of the bull market of the 1980s. Moreover, even during January (1989 being a case in point), small stocks would often underperform larger issues.
Even if the “small firm effect” were to persist (and the date to suggest that higher returns have been earned from small company stocks over very long periods of history), it’s not at all clear that such a finding would violate market efficiency. A finding that small company stocks outperform the stocks of larger companies on a risk adjusted basis depends importantly on how one measures risk. Beta (relative volatility), the risk measure typically used in the studies that have found anomalies, may be a very poor measure of risk. Thus, its is impossible to distinguish if the abnormal returns are truly the result of inefficiencies or result instead because of inadequacies in our measure of risk. The higher returns for smaller companies may simply be the requisite reward owed to investors for assuming a greater risk of disappointment in the investment returns they expect, just as larger returns are achieved over the long run from investing in relatively volatile long-term bonds than from more predictable short-term Treasury Bills.
In conclusion, serious questions remain concerning the adjustment for risk involved in documenting the “January/small firm effect.” Moreover the dependability of the phenomenon is open to question. Finally, the magnitudes of the “start-of-the-year” and “end-of-the-week” effects are very small relative to the transactions costs involved for the individual investor to exploit them. Consequently, I am not prepared to admit that important violations of weak-form market efficiency have been uncovered.
Burton G. Malkiel. A Random Walk Down Wall Street, including a life-cycle guide to personal investing. First edition, 1973, by W.W. Norton and company, Inc.
