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Model Risk Measurement under Wasserstein Distance

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  • Yu Feng
  • Erik Schlogl

Abstract

The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust risk management. The proposed approach accounts for equivalent and non-equivalent probability measures and incorporates the economic reality of the fictitious adversary. It provides practically feasible results that overcome the restriction of considering only models implying probability measures equivalent to the reference model. The Wasserstein approach suits for various types of model risk problems, ranging from the single-asset hedging risk problem to the multi-asset allocation problem. The robust capital market line, accounting for the correlation risk, is not achievable with other non-parametric approaches.

Suggested Citation

  • Yu Feng & Erik Schlogl, 2018. "Model Risk Measurement under Wasserstein Distance," Papers 1809.03641, arXiv.org, revised Mar 2019.
    • Handle: RePEc:arx:papers:1809.03641
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    References listed on IDEAS

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    1. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
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    Cited by:

    1. Yu Feng & Ralph Rudd & Christopher Baker & Qaphela Mashalaba & Melusi Mavuso & Erik Schlögl, 2021. "Quantifying the Model Risk Inherent in the Calibration and Recalibration of Option Pricing Models," Risks, MDPI, vol. 9(1), pages 1-20, January.
    2. Yu Feng, 2019. "Theory and Application of Model Risk Quantification," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 3-2019, January-A.
    3. M. Andrea Arias-Serna & Jean-Michel Loubes & Francisco J. Caro-Lopera, 2020. "Risk Measures Estimation Under Wasserstein Barycenter," Papers 2008.05824, arXiv.org.

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