Improved Forecasting of Mutual Fund Alphas and Betas

Harry Mamaysky, Matthew Spiegel and Hong Zhang

Review of Finance, 2007, vol. 11, issue 3, 359-400

Abstract: This paper proposes a simple back testing procedure that is shown to dramatically improve a panel data model's ability to produce out of sample forecasts. Here the procedure is used to forecast mutual fund alphas. Using monthly data with an OLS model it has been difficult to consistently predict which portfolio managers will produce above market returns for their investors. This paper provides empirical evidence that sorting on the estimated alphas populates the top and bottom deciles not with the best and worst funds, but with those having the greatest estimation error. This problem can be attenuated by back testing the statistical model fund by fund. The back test used here requires a statistical model to exhibit some past predictive success for a particular fund before it is allowed to make predictions about that fund in the current period. Another estimation problem concerns the use of a single statistical model for all available mutual funds. Since no one statistical model is likely to fit every fund, the result is a great deal of misspecification error. This paper shows that the combined use of an OLS and Kalman filter model increases the number of funds with predictable out of sample alphas by about 60%. Overall, a strategy that uses very modest ex-ante filters to eliminate funds whose parameters likely derive primarily from estimation error produces an out of sample risk-adjusted return of over 4% per annum. Copyright 2007, Oxford University Press.

Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (48)

Downloads: (external link)
http://hdl.handle.net/10.1093/rof/rfm018 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:revfin:v:11:y:2007:i:3:p:359-400

Ordering information: This journal article can be ordered from
https://academic.oup.com/journals

Access Statistics for this article

Review of Finance is currently edited by Marcin Kacperczyk

More articles in Review of Finance from European Finance Association Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().