Topic
Investment management
About: Investment management is a research topic. Over the lifetime, 3600 publications have been published within this topic receiving 59194 citations.
Papers published on a yearly basis
Papers
More filters
••
TL;DR: The authors showed that the strong bias in favor of domestic securities is a well-documented characteristic of international investment portfolios, yet the preference for investing close to home also applies to portfolios of domestic stocks.
Abstract: The strong bias in favor of domestic securities is a well-documented characteristic of international investment portfolios, yet we show that the preference for investing close to home also applies to portfolios of domestic stocks. Specifically, U.S. investment managers exhibit a strong preference for locally headquartered firms, particularly small, highly levered firms that produce nontraded goods. These results suggest that asymmetric information between local and nonlocal investors may drive the preference for geographically proximate investments, and the relation between investment proximity and firm size and leverage may shed light on several well-documented asset pricing anomalies.
2,702 citations
•
23 Aug 2015
TL;DR: In this article, the authors developed a statistical framework for both parametric and nonparametric tests of market-timing ability, and used it to evaluate the performance of investment managers.
Abstract: In Merton (1981; hereafter referred to as Part I), one of us developed a basic model of markettiming forecasts where the forecaster predicts when stocks will outperform bonds and when bonds will outperform stocks but does not predict the magnitude of the superior performance. In that analysis, it was shown that the pattern of returns from successful market timing has an isomorphic correspondence to the pattern of returns from following certain option investment strategies where the implicit prices paid for the options are less than their "fair" or market values. This isomorphic correspondence was used to drive an equilibrium theory of value for market-timing forecasting skills. By analyzing how investors would use the market timer's forecast to modify their probability beliefs about stock returns, it was shown that the conditional probabilities of a correct forecast (conditional on the return on the market) provide both necessary and sufficient conditions for such forecasts to have a positive value. In the analysis presented here, we use the The evaluation of the performance of investment managers is a much studied problem in finance. Based upon the model developed in Part I of this paper, the statistical framework is derived for both parametric and nonparametric tests of market-timing ability. If the manager's forecasts are observable, then the nonparametric test can be used without further assumptions about the distribution of security returns. If the manager's forecasts are not observable, then the parametric test can be used under the assumption of either a capital asset pricing model or a multifactor return structure. The tests differ from earlier work because they permit identification and separation of the gains of market-timing skills from the gains of micro stock-selection skills. * Earlier versions of the paper were presented in seminars at Berkeley, Carnegie-Mellon, University of Chicago, Dartmouth, Harvard, University of Southern California, and Vanderbilt; we thank the participants for their comments. Aid from the National Science Foundation is gratefully acknowledged.
1,565 citations
•
TL;DR: In this paper, the authors proposed a new factor model that consists of the market factor, a size factor, an investment factor, and a return-on-equity factor.
Abstract: Motivated from investment-based asset pricing, we propose a new factor model that consists of the market factor, a size factor, an investment factor, and a return-on-equity factor The new model [i] outperforms the Carhart (1997) four-factor model in pricing portfolios formed on earnings surprise, idiosyncratic volatility, financial distress, equity issues, as well as on investment and return-on-equity; [ii] performs similarly as the Carhart model in pricing portfolios on momentum as well as on size and book-to-market; but [iii] underperforms in pricing the total accrual deciles Our model's performance, combined with its clear economic intuition, suggests that it can serve as a new workhorse model for academic research and investment management practice
1,277 citations
•
01 Feb 2002
TL;DR: In this paper, the stock market is safer for long-term investors and strategic asset allocation in continuous time has been discussed, with a focus on the life cycle of a portfolio.
Abstract: 1. Introduction 2. Myopic Portfolio Choice 3. Who Should Buy Long-Term Bonds? 4. Is the Stock Market Safer for Long-Term Investors? 5. Strategic Asset Allocation in Continuous Time 6. Human Wealth and Financial Wealth 7. Investing over the Life Cycle
998 citations
•
01 Jan 1999
TL;DR: Lo and MacKinlay as discussed by the authors found that markets are not completely random after all, and that predictable components do exist in recent stock and bond returns, and pointed out 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.
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.
870 citations