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MEASURING MODEL RISK IN FINANCIAL RISK MANAGEMENT AND PRICING

Valeriane Jokhadze () and Wolfgang M. Schmidt
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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

International Journal of Theoretical and Applied Finance (IJTAF), 2020, vol. 23, issue 02, 1-37

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.

Keywords: Market risk measurement; model risk measurement; contingent claim pricing; robust representation; Bayesian analysis; DCC-GARCH (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0219024920500120

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