Machine-learning-enhanced systemic risk measure: a two-step supervised learning approach
This paper explores ways to improve the existing systemic risk measures by incorporating machine learning algorithms into the measurement. We aim to overcome the shortcomings of existing methods that rely on restricted modeling and are difficult to tap into various data resources. To this end, this...
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Main Authors: | , |
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格式: | Article |
語言: | English |
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2022
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在線閱讀: | https://hdl.handle.net/10356/161971 |
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