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Measuring Model Risk In Financial Risk Management And Pricing

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  • VALERIANE JOKHADZE

    (Frankfurt School of Finance & Management, Adickesalee 32-34, 60322, Frankfurt am Main, Germany)

  • WOLFGANG M. SCHMIDT

    (Frankfurt School of Finance & Management, Adickesalee 32-34, 60322, Frankfurt am Main, Germany)

Abstract

Risk measurement and pricing of financial positions are based on modeling assumptions, which are common assumptions on the probability distribution of the position’s outcomes. We associate a model with a probability measure and investigate model risk by considering a model space. First, we incorporate model risk into market risk measures by introducing model weighted and superposed market risk measures. Second, we quantify model risk itself and propose axioms for model risk measures. We introduce superposed model risk measures that quantify model risk relative to a reference model, which is the financial institution’s model of choice. Several risk measures that we propose require a probability distribution on the model space, which can be obtained from data by applying Bayesian analysis. Examples and a case study illustrate our approaches.

Suggested Citation

  • Valeriane Jokhadze & Wolfgang M. Schmidt, 2020. "Measuring Model Risk In Financial Risk Management And Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 23(02), pages 1-37, April.
    • Handle: RePEc:wsi:ijtafx:v:23:y:2020:i:02:n:s0219024920500120
    DOI: 10.1142/S0219024920500120
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    2. Roman Tikhonov & Aleksey Masyutin & Vadim Anpilogov, 2021. "The Relationship Between the Financial Performance of Banks and the Quality of Credit Scoring Models," Russian Journal of Money and Finance, Bank of Russia, vol. 80(2), pages 76-95, June.
    3. Berthine Nyunga Mpinda & Jules Sadefo-Kamdem & Salomey Osei & Jeremiah Fadugba, 2021. "Accuracies of Model Risks in Finance using Machine Learning," Working Papers hal-03191437, HAL.

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