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A new Fourier transform algorithm for value-at-risk

Author

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  • Claudio Albanese
  • Ken Jackson
  • Petter Wiberg

Abstract

In this paper, we introduce a new Fourier method for computing value-at-risk for a portfolio with derivatives and for return models with fat tails. The new method does not assume that the characteristic function for the return model is known explicitly. We define a class of admissible models for returns and present statistical evidence that supports our approach. We discuss the details of the algorithm. The paper concludes with two applications of value-at-risk. Both examples illustrate the effect that changes in the models for portfolio value and for risk factor returns have on the value-at-risk surface.

Suggested Citation

  • Claudio Albanese & Ken Jackson & Petter Wiberg, 2004. "A new Fourier transform algorithm for value-at-risk," Quantitative Finance, Taylor & Francis Journals, vol. 4(3), pages 328-338.
  • Handle: RePEc:taf:quantf:v:4:y:2004:i:3:p:328-338
    DOI: 10.1088/1469-7688/4/3/008
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    Citations

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    Cited by:

    1. Torben G. Andersen & Tim Bollerslev & Peter Christoffersen & Francis X. Diebold, 2007. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Chapters,in: The Risks of Financial Institutions, pages 513-548 National Bureau of Economic Research, Inc.
    2. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, Elsevier.
    3. Alessandro Ramponi, 2012. "Computing Quantiles in Regime-Switching Jump-Diffusions with Application to Optimal Risk Management: a Fourier Transform Approach," Papers 1207.6759, arXiv.org.
    4. Chen, Rongda & Yu, Lean, 2013. "A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions," Economic Modelling, Elsevier, vol. 35(C), pages 796-804.

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