「Waseda Organizational and Financial Economics Seminar:
Value of Machine Learning in Mutual Fund Trades」
| 日時 | 2025年5月26日（月）13:10～14:50 |
|---|---|
| 開催方法 | ①対面 ＊11号館504教室にお越しください。 ②Zoom＊お申込み完了の自動返信メールにて、参加用URLをお知らせいたします。 |
| 対象 | 学生・教職員・一般 |
| 講演者 | Hsiu-Lang Chen 氏 （Associate Professor, Department of Finance, University of Illinois Chicago） |
| 要旨 | Interest 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. Among 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. Our findings suggest that ANNs can utilize mutual fund holdings disclosures, firm characteristics, and macroeconomic variables to learn fund managers’ stock trading strategies and deliver desirable performance. Nevertheless, fund managers still possess critical skills that AI cannot replicate. Funds 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. Funds 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. |
| 世話人 | 宮島 英昭 （早稲田大学商学学術院 教授） |
| 参加申し込み方法 | 参加はこちらからお申込みください。※5月22日（木）17:00締切 |
| その他 | 早稲田大学商学部・産業経営研究所・谷川寧彦分科会 |
