Simulation methods for robust risk assessment and the distorted mix approach

Sojung Kim and Stefan Weber

European Journal of Operational Research, 2022, vol. 298, issue 1, 380-398

Abstract: Uncertainty requires suitable techniques for risk assessment. Combining stochastic approximation and stochastic average approximation, we propose an efficient algorithm to compute the worst case average value at risk in the face of tail uncertainty. Dependence is modelled by the distorted mix method that flexibly assigns different copulas to different regions of multivariate distributions. We illustrate the application of our approach in the context of financial markets and cyber risk.

Keywords: Risk management; Robustness; Risk measures; Simulation; Cyber risk (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:298:y:2022:i:1:p:380-398

DOI: 10.1016/j.ejor.2021.07.005

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