The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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Performance Evaluation with Transactions Data: The Stock Selection of Investment Newsletters
Published: 12/17/2002 | DOI: 10.1111/0022-1082.00165
Andrew Metrick
This paper analyzes the equity‐portfolio recommendations made by investment newsletters. Overall, there is no significant evidence of superior stock‐picking ability for this sample of 153 newsletters. Moreover, there is no evidence of abnormal short‐run performance persistence (“hot hands”). The comprehensive and bias‐free transactions database also allows for insights into the precision of performance evaluation. Using a measure of precision defined in the paper, a transactions‐based approach yields a median improvement of 10 percent over a corresponding factor model. This compares favorably with the precision gained by adding factors to the CAPM.
Should Investors Avoid All Actively Managed Mutual Funds? A Study in Bayesian Performance Evaluation
Published: 12/17/2002 | DOI: 10.1111/0022-1082.00319
Klaas P. Baks, Andrew Metrick, Jessica Wachter
This paper analyzes mutual‐fund performance from an investor's perspective. We study the portfolio‐choice problem for a mean‐variance investor choosing among a risk‐free asset, index funds, and actively managed mutual funds. To solve this problem, we employ a Bayesian method of performance evaluation; a key innovation in our approach is the development of a flexible set of prior beliefs about managerial skill. We then apply our methodology to a sample of 1,437 mutual funds. We find that some extremely skeptical prior beliefs nevertheless lead to economically significant allocations to active managers.
Reinforcement Learning and Savings Behavior
Published: 11/25/2009 | DOI: 10.1111/j.1540-6261.2009.01509.x
JAMES J. CHOI, DAVID LAIBSON, BRIGITTE C. MADRIAN, ANDREW METRICK
We show that individual investors over‐extrapolate from their personal experience when making savings decisions. Investors who experience particularly rewarding outcomes from 401(k) saving—a high average and/or low variance return—increase their 401(k) savings rate more than investors who have less rewarding experiences. This finding is not driven by aggregate time‐series shocks, income effects, rational learning about investing skill, investor fixed effects, or time‐varying investor‐level heterogeneity that is correlated with portfolio allocations to stock, bond, and cash asset classes. We discuss implications for the equity premium puzzle and interventions aimed at improving household financial outcomes.