A new Fourier transform algorithm for value-at-risk
AbstractIn 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.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Quantitative Finance.
Volume (Year): 4 (2004)
Issue (Month): 3 ()
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Web page: http://www.tandfonline.com/RQUF20
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- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005.
"Practical volatility and correlation modeling for financial market risk management,"
CFS Working Paper Series
2005/02, Center for Financial Studies (CFS).
- 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.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," NBER Working Papers 11069, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Practical Volatility and Correlation Modeling for Financial Market Risk Management," PIER Working Paper Archive 05-007, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- 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.
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