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A note on pivotal Value-at-Risk estimates

Author

Listed:
  • Pflug Georg Ch.
  • Schaller Peter

    (Bank Austria, Vienna, Österreich)

Abstract

Inspired by the practice of risk management in the financial industry, we introduce the notion of pivotal quantile estimates, and relate it to the theory of structural statistical models. This framework gives a mathematical foundation to unbiased estimation of exceedance probabilities. The application to Value at Risk calculations is illustrated by an operational risk example.

Suggested Citation

  • Pflug Georg Ch. & Schaller Peter, 2009. "A note on pivotal Value-at-Risk estimates," Statistics & Risk Modeling, De Gruyter, vol. 27(3), pages 201-209, December.
    • Handle: RePEc:bpj:strimo:v:27:y:2009:i:3:p:201-209:n:4
    DOI: 10.1524/stnd.2009.1059
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    References listed on IDEAS

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    1. Marco Moscadelli, 2004. "The modelling of operational risk: experience with the analysis of the data collected by the Basel Committee," Temi di discussione (Economic working papers) 517, Bank of Italy, Economic Research and International Relations Area.
    2. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
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