A Non-Random Walk Down Wall Street

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 tantalising 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.

A Non-Random Walk Down Wall Street 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.