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来源类型Working Paper
规范类型报告
DOI10.3386/w29723
来源IDWorking Paper 29723
Machine-Learning the Skill of Mutual Fund Managers
Ron Kaniel; Zihan Lin; Markus Pelger; Stijn Van Nieuwerburgh
发表日期2022-02-07
出版年2022
语种英语
摘要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.
主题Financial Economics ; Portfolio Selection and Asset Pricing ; Financial Institutions
URLhttps://www.nber.org/papers/w29723
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/587397
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GB/T 7714
Ron Kaniel,Zihan Lin,Markus Pelger,et al. Machine-Learning the Skill of Mutual Fund Managers. 2022.
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