Black-Box Model Risk in Finance

Samuel N. Cohen, Derek Snow, L. Szpruch
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引用次数: 8

Abstract

Machine learning models are increasingly used in a wide variety of financial settings. The difficulty of understanding the inner workings of these systems, combined with their wide applicability, has the potential to lead to significant new risks for users; these risks need to be understood and quantified. In this sub-chapter, we will focus on a well studied application of machine learning techniques, to pricing and hedging of financial options. Our aim will be to highlight the various sources of risk that the introduction of machine learning emphasises or de-emphasises, and the possible risk mitigation and management strategies that are available.
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金融中的黑箱模型风险
机器学习模型越来越多地用于各种各样的金融环境。很难理解这些系统的内部工作原理,再加上它们的广泛适用性,有可能给用户带来重大的新风险;这些风险需要被理解和量化。在本分章中,我们将重点研究机器学习技术在金融期权定价和对冲方面的应用。我们的目标是强调引入机器学习所强调或淡化的各种风险来源,以及可用的可能的风险缓解和管理策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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