A Non-Random Walk Down Wall Street
Author | : Andrew W. Lo |
Publisher | : Princeton University Press |
Total Pages | : 449 |
Release | : 2011-11-14 |
ISBN-10 | : 9781400829095 |
ISBN-13 | : 1400829097 |
Rating | : 4/5 (097 Downloads) |
Download or read book A Non-Random Walk Down Wall Street written by Andrew W. Lo and published by Princeton University Press. This book was released on 2011-11-14 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.