A Non-Random Walk Down Wall Street
Andrew W. Lo
Language: English
Pages: 448
ISBN: 0691092567
Format: PDF / Kindle (mobi) / ePub
For over half a century, financial experts have regarded the movements of markets as a random walk--unpredictable meanderings akin to a drunkard's unsteady gait--and this hypothesis has become a cornerstone of modern financial economics and many investment strategies. Here Andrew W. Lo and A. Craig MacKinlay put the Random Walk Hypothesis to the test. In this volume, which elegantly integrates their most important articles, Lo and MacKinlay find that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns. Their book provides a state-of-the-art account of the techniques for detecting predictabilities and evaluating their statistical and economic significance, and offers a tantalizing glimpse into the financial technologies of the future.
The articles track the exciting course of Lo and MacKinlay's research on the predictability of stock prices from their early work on rejecting random walks in short-horizon returns to their analysis of long-term memory in stock market prices. A particular highlight is their now-famous inquiry into the pitfalls of "data-snooping biases" that have arisen from the widespread use of the same historical databases for discovering anomalies and developing seemingly profitable investment strategies. This book invites scholars to reconsider the Random Walk Hypothesis, and, by carefully documenting the presence of predictable components in the stock market, also directs investment professionals toward superior long-term investment returns through disciplined active investment management.
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years. 2.5. Conclusion should be less than unity when q = 2 (since negative serial correlation is implied by this process). Also, the rejection of the random walk should be stronger as q increases (larger z*(q) values for larger q).22 But Tables 2.1 and 2.2 and those in Lo and MacKinlay (1987b) show that both these implications are contradicted by the empirical evidence.23 Weekly returns do not follow a random walk, but they do not fit a stationary mean-reverting alternative any better. Of
ore direct evidence of this skewness is presented in Table 3.4, in which the fiactiles of the variance ratio test statistic are reported. See also the discussion in Section 3.4.1. 3.3. Properties of the Test Statistic under the Null Hypotheses Table3.2. Empirical quantiles of the (Diclq-Fuller)t-statistic associated with the hypotheskB = 1 in theregressionX,= , ~ + w t + B & - ~ E,, where ct is ZID N(0,l). Each m corresponds to a separate and independent simulation expenenment based upon
(A2) through (A4) are restrictions on the maximal degree of dependence and heterogeneity allowable while 5 ~ h e rare e several other ways of measuring the degree statistical dependence, giving rise to other notions of "mixing."For further details, see Eberlein and Taqqu (1986),Rosenblatt (1956),and White (1984). 6.2. Long-Range Vmus Short-Range Dqbendence 151 still permitting some form of the law of large numbers and the (functional) central limit theorem to obtain. Although (A2) rules out
and Rosenman (1984) (Eutures contracts). These and earlier applications of R/S analysis by Mandelbrot and Wallis (1969a) have three features in common: (1) They provide no sampling theory with which to~udgethe statistical significance of their empirical results; (2) they use the 4, statistic which is not robust to short-range dependence; and (3) they do not focus on the RIS statistic itself, but rather on the regression of its logarithm on (sub)sample sizes. The shortcomings of (1) and (2) are
example, a drug that stimulates the production of red blood cells), some considered breakthroughs in biotechnology. Similarly, even in efficient financial markets there are very handsome returns to breakthroughs in financial technology. Of course, barriers to entry are typically lower, the degree of competition is much higher, and most financial technologies are not patentable (though this may soon change) hence the "half life" of the profitability of financial innovation is considerably smaller.
