Performance Evaluation with Transactions Data: The Stock Selection of Investment Newsletters


  • Andrew Metrick

    1. Harvard University and NBER
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    • Department of Economics, Harvard University and NBER. I thank John Campbell, Gary Chamberlain, Paul Gompers, John Graham, Campbell Harvey, Leslie Jeng, Susie Metrick, Jack Porter, Andrei Shleifer, René Stultz, Sheridan Titman, Richard Zeckhauser, an anonymous referee, and seminar participants at the NBER, the 1997 NBER Summer Institute, Harvard, MIT, and Chicago for helpful comments, Daniel Chen and Alex Tsai for editorial assistance, and James Choi and Tom Knox for excellent and tireless research assistance. Mark Hulbert was very generous with his time, advice, and data. This project was partially supported by the Richard Herrnstein Fund at Harvard University.


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.