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Exact inference in diagnosing Value-at-Risk estimates -- A Monte Carlo device

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  • Herwartz, Helmut

Abstract

A Monte Carlo approach is suggested for correctly sized backtesting of Value-at-Risk estimates by means of the dynamic quantile test and a Portmanteau statistic. The latter shows preferable power features but fails in case of unconditional VaR misspecification.

Suggested Citation

  • Herwartz, Helmut, 2009. "Exact inference in diagnosing Value-at-Risk estimates -- A Monte Carlo device," Economics Letters, Elsevier, vol. 103(3), pages 160-162, June.
    • Handle: RePEc:eee:ecolet:v:103:y:2009:i:3:p:160-162
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    References listed on IDEAS

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    1. Dufour, Jean-Marie, 2006. "Monte Carlo tests with nuisance parameters: A general approach to finite-sample inference and nonstandard asymptotics," Journal of Econometrics, Elsevier, vol. 133(2), pages 443-477, August.
    2. Christophe Hurlin & Sessi Tokpavi, 2006. "Backtesting VaR Accuracy: A New Simple Test," Working Papers halshs-00068384, HAL.
    3. Robert F. Engle & Simone Manganelli, 2004. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 367-381, October.
    4. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    5. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
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    Cited by:

    1. Tarasov, Arthur, 2011. "Coherent Quantitative Analysis of Risks in Agribusiness: Case of Ukraine," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 3(4), pages 1-7, December.
    2. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    3. Díaz, Antonio & Esparcia, Carlos & Huélamo, Diego, 2023. "Stablecoins as a tool to mitigate the downside risk of cryptocurrency portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

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    Value-at-Risk Monte Carlo test;

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