The Wasserstein Metric and Robustness in Risk Management
| Autor: | Jinsong Zheng, Rüdiger Kiesel, Robin Rühlicke, Gerhard Stahl |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Mathematical optimization
Wasserstein metric Financial institution Strategy and Management Economics Econometrics and Finance (miscellaneous) Robust statistics robustness risk management lcsh:HG8011-9999 01 natural sciences lcsh:Insurance 010104 statistics & probability Accounting 0502 economics and business Econometrics 0101 mathematics Risk management Valuation (finance) Mathematics 050208 finance business.industry Financial instrument 05 social sciences risk measures Wirtschaftswissenschaften Financial crisis Model risk business |
| Zdroj: | Risks; Volume 4; Issue 3; Pages: 32 Risks, Vol 4, Iss 3, p 32 (2016) |
| ISSN: | 2227-9091 |
| DOI: | 10.3390/risks4030032 |
| Popis: | OA gold 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. |
| Databáze: | OpenAIRE |
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