Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions

Yu Feng

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arXiv · 1903.00590

Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions

Yu Feng

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Abstract

Understanding and measuring model risk is important to financial practitioners. However, there lacks a non-parametric approach to model risk quantification in a dynamic setting and with path-dependent losses. We propose a complete theory generalizing the relative-entropic approach by Glasserman and Xu to the dynamic case under any $f$-divergence. It provides an unified treatment for measuring both the worst-case risk and the $f$-divergence budget that originate from the model uncertainty of an underlying state process.

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Yu Feng. 2019-03-02. Non-Parametric Robust Model Risk Measurement with Path-Dependent Loss Functions. https://arxiv.org/abs/1903.00590

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