Mutual fund performance with learning across funds |
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| Affiliation: | 1. University of Valladolid, Spain;2. Complutense University of Madrid, Spain;3. Champagne School of Management, Troyes, France;4. IRG, Université Paris Est, Créteil, France;5. Linköping University, Sweden;1. Amrut Mody School of Management, Ahmedabad University, India;2. Department of Management Studies, Malaviya National Institute of Technology Jaipur, India;1. The Wharton School of Business, The University of Pennsylvania, Philadelphia, PA 190104, USA;2. The Eli Broad College of Business, Michigan State University, East Lansing, MI 48824, USA;3. Johnson College of Business, Cornell University, Ithaca, NY 14850, USA |
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| Abstract: | The average level and cross-sectional variability of fund alphas are estimated from a large sample of mutual funds. This information is incorporated, along with the usual regression estimate of alpha, in a (roughly) precision-weighted average measure of individual fund performance. Substantial “learning across funds” is documented, with significant effects on investment decisions. In a Bayesian framework, this form of learning is inconsistent with the assumption, made in the past literature, of prior independence across funds. Independence can be viewed as an extreme scenario in which the true cross-sectional distribution of alphas is presumed to be known a priori. |
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