The Wasserstein Metric and Robustness in Risk Management

Rüdiger Kiesel, Robin Rühlicke, Gerhard Stahl and Jinsong Zheng
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Rüdiger Kiesel: Chair for Energy Trading and Finance, University of Duisburg-Essen, Campus Essen, Universitätsstraße 12, Essen 45141, Germany
Robin Rühlicke: Chair for Energy Trading and Finance, University of Duisburg-Essen, Campus Essen, Universitätsstraße 12, Essen 45141, Germany
Gerhard Stahl: Group Risk Management, Talanx AG, Riethorst 2, Hannover 30659, Germany
Jinsong Zheng: Group Risk Management, Talanx AG, Riethorst 2, Hannover 30659, Germany

Risks, 2016, vol. 4, issue 3, 1-14

Abstract: In the aftermath of the financial crisis, it was realized that the mathematical models used for the valuation of financial instruments and the quantification of risk inherent in portfolios consisting of these financial instruments exhibit a substantial model risk. Consequently, regulators and other stakeholders have started to require that the internal models used by financial institutions are robust. We present an approach to consistently incorporate the robustness requirements into the quantitative risk management process of a financial institution, with a special focus on insurance. We advocate the Wasserstein metric as the canonical metric for approximations in robust risk management and present supporting arguments. Representing risk measures as statistical functionals, we relate risk measures with the concept of robustness and hence continuity with respect to the Wasserstein metric. This allows us to use results from robust statistics concerning continuity and differentiability of functionals. Finally, we illustrate our approach via practical applications.

Keywords: risk management; Wasserstein metric; robustness; risk measures (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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