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Machine-Learning the Skill of Mutual Fund Managers / Ron Kaniel, Zihan Lin, Markus Pelger, Stijn Van Nieuwerburgh.
- Format:
- Book
- Author/Creator:
- Kaniel, Ron.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w29723.
- NBER working paper series no. w29723
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2022.
- Summary:
- We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, as well as identify funds with net-of-fees abnormal returns. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance, while characteristics of the stocks that funds hold are not predictive. Returns of predictive long-short portfolios are higher following a period of high sentiment or a good state of the macro-economy. Our estimation with neural networks enables us to uncover novel and substantial interaction effects between sentiment and both fund flow and fund momentum.
- Notes:
- Print version record
- February 2022.
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