On a Transform Method for the Efficient Computation of Conditional V@R (and V@R) with Application to Loss Models with Jumps and Stochastic Volatility

Alessandro Ramponi

Methodology and Computing in Applied Probability, 2016, vol. 18, issue 2, 575-596

Abstract: Abstract In this paper we consider Fourier transform techniques to efficiently compute the Value-at-Risk and the Conditional Value-at-Risk of an arbitrary loss random variable, characterized by having a computable generalized characteristic function. We exploit the property of these risk measures of being the solution of an elementary optimization problem of convex type in one dimension. An application to univariate loss models driven by Lévy or stochastic volatility risk factors dynamic is finally reported.

Keywords: V@R; CV@R; Fourier transform methods; Stochastic volatility; Jump-diffusion models; 91G60; 91B30; 60E10 (search for similar items in EconPapers)
Date: 2016
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Working Paper: On a Transform Method for the Efficient Computation of Conditional VaR (and VaR) with Application to Loss Models with Jumps and Stochastic Volatility (2014)
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DOI: 10.1007/s11009-015-9446-7

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