Forecasting mutual fund performance: Combining return-based with portfolio holdings-based predictors

Sebastian Müller, Nikolay Pugachyov and Florian Weigert

No 26-01, CFR Working Papers from University of Cologne, Centre for Financial Research (CFR)

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.

Keywords: Mutual funds; performance prediction; composite predictor (search for similar items in EconPapers)
JEL-codes: G11 G12 G20 G23 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:cfrwps:336774

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