Publication: Validation of aggregated risks models
Validation of aggregated risks models
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Dacorogna, M., Elbahtouri, L., & Kratz, M. (2018). Validation of aggregated risks models. Annals of Actuarial Science, 12(2), 433–454. https://doi.org/10.1017/S1748499517000227
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Validation of risk models is required by regulators and demanded by management and shareholders. Those models rely in practice heavily on Monte Carlo (MC) simulations. Given their complexity, the convergence of the MC algorithm is difficult to prove mathematically. To circumvent this problem and nevertheless explore the conditions of convergence, we suggest an analytical approach. Considering standard models, we compute, via mixing techniques, closed form formulas for risk measures as VaR or TVaR on a portfolio of risks, and consequen
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- Kratz, Marie
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Dacorogna, M., Elbahtouri, L., & Kratz, M. (2018). Validation of aggregated risks models. Annals of Actuarial Science, 12(2), 433–454. https://doi.org/10.1017/S1748499517000227
