Review of Financial Studies Vol. 21 No. 1 2008
Estimating the Dynamics of Mutual Fund Alphas and Betas
Abstract
This article develops a Kalman filter model to track dynamic mutual fund factor loadings. It then uses the estimates to analyze whether managers with market-timing ability can be identified ex ante. The primary findings are as follows: (i) Ordinary least squares (OLS) timing models produce false positives (nonzero alphas) at too high a rate with either daily or monthly data. In contrast, the Kalman filter model produces them at approximately the correct rate with monthly data; (ii) In monthly data, though the OLS models fail to detect any timing among fund managers, the Kalman filter does; (iii) The alpha and beta forecasts from the Kalman model are more accurate than those from the OLS timing models; (iv) The Kalman filter model tracks most fund alphas and betas better than OLS models that employ macroeconomic variables in addition to fund returns.
- DOI
- 10.1093/rfs/hhm049
- Volume
- 21
- Issue
- 1
- Pages
- 233-264
- Language
- en
- Sources
- openalex crossref