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- W3170605874 abstract "This paper conducts a supervised machine learning algorithm under the guidance of an existing costly signaling model, and shows that traditional machine learning techniques can be applied successfully in the asset management industry combined with appropriate economic theory. This paper shows that the supervised machine learning algorithm can separate high- and low-skill corporate bond mutual fund managers by reading risk-related information in funds' prospectus. Other empirical evidence such as risk taking profile of fund managers shows that the results from the supervised machine learning algorithm are consistent with the model predictions." @default.
- W3170605874 created "2021-06-22" @default.
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- W3170605874 date "2019-07-05" @default.
- W3170605874 modified "2023-10-01" @default.
- W3170605874 title "Using Supervised Machine Learning to Detect High-Skill Mutual Fund Managers" @default.
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- W3170605874 doi "https://doi.org/10.1109/cybconf47073.2019.9436581" @default.
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