Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/336774 
Year of Publication: 
2026
Series/Report no.: 
CFR Working Paper No. 26-01
Publisher: 
University of Cologne, Centre for Financial Research (CFR), Cologne
Abstract: 
We introduce a simple yet powerful method for enhancing mutual fund performance prediction by combining individual predictors into a composite predictor. This composite approach integrates information from 19 well-established return-based and portfolio holdings-based predictors from the literature. It effectively identifies top decile funds that outperform bottom decile funds by a risk-adjusted 4.56% per annum. Furthermore, it achieves statistically significant outperformance for long-only fund investments against the average active and passive fund. Both return-based predictors (e.g., fund alpha and the t-statistic of alpha) and holdings-based predictors (e.g., skill index and active weight) contribute equally to the composite predictor's success.
Subjects: 
Mutual funds
performance prediction
composite predictor
JEL: 
G11
G12
G20
G23
Document Type: 
Working Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.