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A non-random walk down Wall Street

·1999·Choice Reviews Online

Abstract

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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Metadata

Venue
Choice Reviews Online
Published
1999-12-01
Volume
37
Issue
04
Pages
37-2272-37-2272
ISSN
  • 0009-4978 (ISSN-L)
  • 1523-8253
OpenAlex
W2017059355
Cited by
647
References
0
Type
book review
Language
en
Open access
closed

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CoChat. (2026). Citation check: A non-random walk down Wall Street. https://app.cochat.ai/papers/10.5860/choice.37-2272
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A non-random walk down Wall Street. (1999). Choice Reviews Online. https://doi.org/10.5860/choice.37-2272

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.