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Searching for mutual fund winners? the strategy is to outbid both, the benchmark and the peer group

Mateus, C., Mateus, I. & Todorovic, N. ORCID: 0000-0003-4875-623X (2023). Searching for mutual fund winners? the strategy is to outbid both, the benchmark and the peer group. Applied Economics, 56(11), pp. 1268-1282. doi: 10.1080/00036846.2023.2175778


Standard Fama-French-Carhart models define ‘winners’ as funds that generate the highest excess returns given the factor risks involved; however, they do not provide information on whether such winners are outperforming their prospectus benchmark or their peer group. In addition, existing literature relying on these models, by and large, does not find evidence of persistence in performance. In this paper, we propose a two-stage procedure that allows investors to select ‘true’ winners(losers) which generate the highest factor-risk-adjusted performance relative to the benchmark and the peer group simultaneously. Utilizing both adjustments at the same time results in a strong predictive ability, leading to a selection of funds that persist in performance. Our true winner funds have statistically significant superior benchmark-adjusted alphas, peer group adjusted alphas and Sharpe ratios one year ahead, which are significantly different from those generated by the true loser funds. The results are robust to extended investment horizon, and alpha estimation method, and they are not driven by outliers, size of fund-sorts, or any particular period within our sample.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Economics on 25 Feb 2023 available at:
Publisher Keywords: US equity mutual funds, benchmark-adjusted alphas, peer-group-adjusted alphas, performance ranking
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Departments: Bayes Business School > Finance
SWORD Depositor:
[thumbnail of Searching for mutual fund winners - final accepted Pdf.pdf] Text - Accepted Version
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