{"id":4829,"date":"2025-04-25T10:07:09","date_gmt":"2025-04-25T01:07:09","guid":{"rendered":"https:\/\/www.waseda.jp\/fcom\/riba\/?p=4829"},"modified":"2025-04-25T10:29:06","modified_gmt":"2025-04-25T01:29:06","slug":"2025%e5%b9%b45%e6%9c%8826%e6%97%a5%e6%9c%88-%e3%81%ab%e7%94%a3%e7%a0%94%e8%ac%9b%e6%bc%94%e4%bc%9a%e3%80%8cwaseda-organizational-and-financial-economics-seminar-value-of-machine-learning-in-mutual","status":"publish","type":"post","link":"https:\/\/www.waseda.jp\/fcom\/riba\/news\/4829","title":{"rendered":"2025\u5e745\u670826\u65e5(\u6708) \u306b\u7523\u7814\u8b1b\u6f14\u4f1a\u300cWaseda Organizational and Financial Economics Seminar : Value of Machine Learning in Mutual Fund Trades\u300d\u304c\u958b\u50ac\u3055\u308c\u307e\u3059\u3002"},"content":{"rendered":"

\u300cWaseda Organizational and Financial Economics Seminar:
\nValue of Machine Learning in Mutual Fund Trades\u300d<\/h3>\n
\n\n\n\n\n\n\n\n\n\n
\u65e5\u6642<\/th>\n2025\u5e745\u670826\u65e5\uff08\u6708\uff0913:10\uff5e14:50<\/td>\n<\/tr>\n
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\n\u2461Zoom\uff0a\u304a\u7533\u8fbc\u307f\u5b8c\u4e86\u306e\u81ea\u52d5\u8fd4\u4fe1\u30e1\u30fc\u30eb\u306b\u3066\u3001\u53c2\u52a0\u7528URL\u3092\u304a\u77e5\u3089\u305b\u3044\u305f\u3057\u307e\u3059\u3002<\/td>\n<\/tr>\n
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\u8b1b\u6f14\u8005<\/th>\nHsiu-Lang Chen \u6c0f
\n\uff08Associate Professor, Department of Finance, University of Illinois Chicago\uff09<\/td>\n<\/tr>\n
\u8981\u65e8<\/th>\nInterest in Artificial Intelligence (AI), especially machine learning, and its applications in finance, has grown tremendously in both academia and industry. Machine learning provides a powerful framework to accommodate high-dimensional predictor sets and flexible functional forms, enabling the discovery of complex patterns and underlying relationships.
\nAmong machine learning techniques, Artificial Neural Networks (ANNs) have shown capability to predict stock returns and select better-performing mutual funds. Can actively managed mutual funds still provide value to Main Street investors in the era of AI? We aim to answer this question by presenting evidence that mutual fund managers continue to demonstrate human wisdom beyond the reach of AI.
\nOur findings suggest that ANNs can utilize mutual fund holdings disclosures, firm characteristics, and macroeconomic variables to learn fund managers\u2019 stock trading strategies and deliver desirable performance. Nevertheless, fund managers still possess critical skills that AI cannot replicate.
\nFunds with higher levels of non-AI skills consistently generate significantly higher alphas for at least two quarters after these skills are identified. Funds persist in their non-AI skills over time.
\nFunds likely exhibit higher non-AI skill levels if they have larger assets under management, charge higher fees, and do not primarily invest in large-cap stocks.<\/td>\n<\/tr>\n
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