Forecasting Stock Returns Through an Efficient Aggregation of Mutual Fund Holdings
提出一种基于美国主动管理型国内股票共同基金持仓有效聚合的股票收益预测指标（GIA），发现基金经理通过基本面研究预测未来盈利的能力差异，且该预测力未被动量、价值等公开量化指标及过往研究中的持仓或交易方法所覆盖。
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.