Rethinking Performance Evaluation / Campbell R. Harvey, Yan Liu.

Format:

Book

Author/Creator:

Harvey, Campbell R.

Contributor:

National Bureau of Economic Research.

Liu, Yan.

Series:

Working Paper Series (National Bureau of Economic Research) no. w22134.

NBER working paper series no. w22134

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2016.

Summary:

We show that the standard equation-by-equation OLS used in performance evaluation ignores information in the alpha population and leads to severely biased estimates for the alpha population. We propose a new framework that treats fund alphas as random effects. Our framework allows us to make inference on the alpha population while controlling for various sources of estimation risk. At the individual fund level, our method pools information from the entire alpha distribution to make density forecast for the fund's alpha, offering a new way to think about performance evaluation. In simulations, we show that our method generates parameter estimates that universally dominate the OLS estimates, both at the population and at the individual fund level. While it is generally accepted that few if any mutual funds outperform, we find that the fraction of funds that generate positive alphas is accurately estimated at over 10%. An out-of-sample forecasting exercise also shows that our method generates superior alpha forecasts.

Notes:

Print version record

March 2016.