Forecasting Stock Returns Through an Efficient Aggregation of Mutual Fund Holdings

Abstract

We develop a stock return-predictive measure based on an efficient aggregation of the portfolio holdings of all actively managed U.S. domestic equity mutual funds, and use this model to study the source of fund managers' stock-selection abilities. This generalized-inverse alpha (GIA) approach reveals differences in the ability of managers to predict firms' future earnings from fundamental research. Notably, the GIA's return-forecasting power is not subsumed by publicly available quantitative predictors, such as momentum, value, and earnings quality, nor is it subsumed by methods shown in past research to forecast stock returns using fund holdings or trades.