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The Computation of Risk Budgets under the Lévy Process Assumption

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  • Olivier Le Courtois

    (EM - EMLyon Business School)

  • Christian Walter

Abstract

This paper revisits the computation of Value-at-Risk and other risk indicators based on the use of Lévy processes. We first provide a new presentation of Variance Gamma Processes with Drift: we reconstruct them in an original way, starting from the exponential distribution. Then, we derive general Fourier formulas that allow us to compute VaR quickly and efficiently, but also other typical indicators like Tail Conditional Expectation (TCE). Based on such a formula, we conduct a study of the term structure of VaR, and provide a discussion of the Basle 2 and Solvency II agreements.
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Suggested Citation

  • Olivier Le Courtois & Christian Walter, 2014. "The Computation of Risk Budgets under the Lévy Process Assumption," Post-Print hal-02313172, HAL.
    • Handle: RePEc:hal:journl:hal-02313172
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    Cited by:

    1. Silvia Faroni & Olivier Le Courtois & Krzysztof Ostaszewski, 2022. "Equivalent Risk Indicators: VaR, TCE, and Beyond," Risks, MDPI, vol. 10(8), pages 1-19, July.
    2. Salem, Marwa Belhaj & Fouladirad, Mitra & Deloux, Estelle, 2022. "Variance Gamma process as degradation model for prognosis and imperfect maintenance of centrifugal pumps," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    3. Gian P. Cervellera & Marco P. Tucci, 2017. "A note on the Estimation of a Gamma-Variance Process: Learning from a Failure," Computational Economics, Springer;Society for Computational Economics, vol. 49(3), pages 363-385, March.
    4. Bertrand Tavin & Lorenz Schneider, 2018. "From the Samuelson volatility effect to a Samuelson correlation effect : An analysis of crude oil calendar spread options," Post-Print hal-02311970, HAL.
    5. Olivier Courtois, 2018. "Some Further Results on the Tempered Multistable Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(2), pages 87-109, June.

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