Stock market prices.

• Author: Lo, Andrew W.
• Position: Research Summaries

Stock Market Prices

Since the catastrophic stock market crash of October 1929 and the resulting Great Depression, economists and policymakers have been extremely interested in the behavior of financial asset prices. The Securities Exchange Act of 1934 and the creation of the Securities and Exchange Commission were direct consequences of the turbulent markets of the 1920s, and much subsequent regulatory legislation has been designed to reduce the wild price swings generally associated with "speculative" investors. In the wake of the more recent "October Massacre," understanding how and why equity prices fluctuate has never been more important. This summary describes some of what my coauthors and I have learned recently about the random nature of stock price movements.

The Random Walk

One of the earliest characterizations of rationally determined stock prices is the random walk model, which says that future price changes cannot be predicted from past price changes. First developed from rudimentary economic considerations of "fair games," the random walk has received broad support from the many early empirical studies confirming the unpredictability of stock returns, generally using daily or monthly returns of individual securities.

However, one of my papers with A. Craig McKinlay shows that the random walk model does not fit aggregate weekly returns during 1962-87.(1) In fact, the weekly returns of a portfolio containing one share of each security traded on the New York and American Stock Exchanges (called an "equally weighted" portfolio) exhibit an autocorrelation of 30 percent, implying that about 10 percent of the variability of next week's return is explained by this week's return! An equally weighted portfolio containing only the stocks of "smaller" companies, companies with relative low market values, has an autocorrelation of 42 percent and is as high as 49 percent during 1975-87.

This fact surprises many economists because a violation of the random walk hypothesis necessarily implies that price changes can be forecast to some degree. The existence of these weekly correlations suggests that there are unexploited profit opportunities. Two other facts add to this puzzle: 1) weekly portfolio returns are strongly positively autocorrelated, but the returns to individual securities generally are not; in fact, the average autocorrelation across securities is negative (but insignificant); and 2) the predictability of returns is quite sensitive...