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Statistical bootstrapping methods in VaR calculation

Author

Listed:
  • Thomas Siegl
  • Ansgar West

Abstract

Monte Carlo methods are often applied to problems in finance especially in the area of risk calculation by the Value-atRisk (VaR) measure. Different applications of statistical resampling techniques are shown, specifically bootstrapping, to refine the computational results in different ways. Methods are provided for improving backtesting stability, acceleration of Monte Carlo VaR convergence by orders of magnitude, and incorporating covariance matrix uncertainty in VaR figures. Existing methods are applied and new solutions developed. Extensive numerical tests on large numbers of randomly generated portfolios prove the effectiveness of the suggested solutions.

Suggested Citation

  • Thomas Siegl & Ansgar West, 2001. "Statistical bootstrapping methods in VaR calculation," Applied Mathematical Finance, Taylor & Francis Journals, vol. 8(3), pages 167-181.
    • Handle: RePEc:taf:apmtfi:v:8:y:2001:i:3:p:167-181
    DOI: 10.1080/13504860110093504
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    References listed on IDEAS

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    1. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    2. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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    Cited by:

    1. Katleho Makatjane, 2022. "Forecasting Uncertainty Intervals for Return Period of Extreme Daily Electricity Consumption," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 217-225, July.

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