In this paper, we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (1962-1985) and for all sub-periods for a variety of aggregate returns indexes and size-sorted portfolios. Although the rejections are largely due to the behavior of small stocks, they cannot be ascribed to either the effects of infrequent trading or time-varying volatilities. Moreover, the rejection of the random walk cannot be interpreted as supporting a mean-reverting stationary model of asset prices, but is more consistent with a specific nonstationary alternative hypothesis.
This book is an ambitious effort by three well-known and well-respected scholars to fill an acknowledged void in the literature-a text covering the burgeoning field of empirical finance. As the authors note in the preface, there are several excellent books covering financial theory at a level suitable for a Ph.D. class or as a reference for academics and practitioners, but there is little or nothing similar that covers econometric methods and applications. Perhaps the closest existing text is the recent addition to the Wiley Series in Financial and Quantitative Analysis written by Cuthbertson (1996). The major difference between the books is that Cuthbertson focuses exclusively on asset pricing in the stock, bond, and foreign exchange markets, whereas Campbell, Lo, and MacKinlay (henceforth CLM) consider empirical applications throughout the field of finance, including corporate finance, derivatives markets, and market microstructure. The level of anticipation preceding publication can be partly measured by the fact that at least three reviews (including this one) have appeared since the book arrived. Moreover, in their reviews, both Harvey (1998) and Tiso (1998) comment on the need for such a text, a sentiment that has been echoed by numerous finance academics.So, does the book live up to its advance billing? For the most part, the answer is yes. The book is comprehensive and up to date, yet also relatively accessible and self-contained. As such, it no doubt will serve as the basic text for Ph.D. courses in empirical finance throughout the country. It also will find a role as an invaluable reference for academics and practitioners in the field. Finally, those interested in learning more about the study of financial markets will find it an excellent introduction to the relevant issues, applications, and methodologies.
In this paper, we test the random walk hypothesis for weekly stock market returns by comparing variance estimators derived from data sampled at different frequencies. The random walk model is strongly rejected for the entire sample period (1962-1985) and for all sub-periods for a variety of aggregate returns indexes and size-sorted portfolios. Although the rejections are largely due to the behavior of small stocks, they cannot be ascribed to either the effects of infrequent trading or time-varying volatilities. Moreover, the rejection of the random walk cannot be interpreted as supporting a mean-reverting stationary model of asset prices, but is more consistent with a specific nonstationary alternative hypothesis.
The profitability of contrarian investment strategies need not be the result of stock market overreaction. Even if returns on individual securities are temporally independent, portfolio strategies that attempt to exploit return reversals may still earn positive expected profits. This is due to the effects of cross-autocovariances from which contrarian strategies inadvertently benefit. We provide an informal taxonomy of return-generating processes that yield positive [and negative expected profits under a particular contrarian portfolio strategy, and use this taxonomy to reconcile the empirical findings of weak negative autocorrelation for returns on individual stocks with the strong positive autocorrelation of portfolio returns. We present empirical evidence against overreaction as the primary source of contrarian profits, and show the presence of important lead-lag relations across securities.
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