---
title: ML Methods for Selecting Mutual Funds with Positive Alpha
url: https://www.ml-quant.com/papers/repec/eee-jfinec-v-150-y-2023-i-3-s0304405x23001770/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:eee:jfinec:v:150:y:2023:i:3:s0304405x23001770
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0304405X23001770%3Bh%3Drepec%3Aeee%3Ajfinec%3Av%3A150%3Ay%3A2023%3Ai%3A3%3As0304405x23001770
featured: 2023-12-20
citations: unknown
topic: Portfolio & Allocation
---


# ML Methods for Selecting Mutual Funds with Positive Alpha

Machine-learning methods can help select profitable mutual fund portfolios, with the study indicating that past performance predicts future performance for active funds, benefiting investors with access to advanced prediction methods.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0304405X23001770%3Bh%3Drepec%3Aeee%3Ajfinec%3Av%3A150%3Ay%3A2023%3Ai%3A3%3As0304405x23001770
- Identifier: RePEc:eee:jfinec:v:150:y:2023:i:3:s0304405x23001770
- Released: 2023-12-20
- First featured: Quant Letter No. 30 (2023-12-20): https://www.ml-quant.com/issues/2023-12-20/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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