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Backtesting Parametric Value-at-Risk with Estimation Risk

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Author Info

  • Juan Carlos Escanciano

    ()
    (Indiana University Bloomington)

  • Jose Olmo

    ()
    (City University, London)

Abstract

One of the implications of the creation of Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk. Since then, the capital requirements of commercial banks with trading activities are based on VaR estimates. Therefore, appropriately constructed tests for assessing the out-of-sample forecast accuracy of the VaR model (backtesting procedures) have become of crucial practical importance. In this paper we show that the use of the standard unconditional and independence backtesting procedures to assess VaR models in out-of-sample composite environments can be misleading. These tests do not consider the impact of estimation risk and therefore may use wrong critical values to assess market risk. The purpose of this paper is to quantify such estimation risk in a very general class of dynamic parametric VaR models and to correct standard backtesting procedures to provide valid inference in out-of-sample analyses. A Monte Carlo study illustrates our theoretical findings in finite-samples and shows that our corrected unconditional test can provide more accurately sized and more powerful tests than the uncorrected one. Finally, an application to S&P500 Index shows the importance of this correction and its impact on capital requirements as imposed by Basel Accord.

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File URL: http://www.iub.edu/~caepr/RePEc/PDF/2007/CAEPR2007-005_updated.pdf
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Bibliographic Info

Paper provided by Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington in its series Caepr Working Papers with number 2007-005_updated.

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Length: 39 pages
Date of creation: Mar 2007
Date of revision:
Handle: RePEc:inu:caeprp:2007005updated

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Keywords: Backtesting; Basel Accord; Conditional Quantile; Estimation Risk; Forecast evaluation; Fixed; rolling and recursive forecasting scheme; Risk management; Value at Risk;

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References

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  1. Raffaella Giacomini & Ivana Komunjer, 2003. "Evaluation and Combination of Conditional Quantile Forecasts," Boston College Working Papers in Economics 571, Boston College Department of Economics.
  2. Joan Jasiak & C. Gourieroux, 2006. "Dynamic Quantile Models," Working Papers 2006_4, York University, Department of Economics.
  3. Martins-Filho Carlos & Yao Feng, 2006. "Estimation of Value-at-Risk and Expected Shortfall based on Nonlinear Models of Return Dynamics and Extreme Value Theory," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(2), pages 1-43, May.
  4. Christoffersen, Peter & Hahn, Jinyong & Inoue, Atsushi, 2001. "Testing and comparing Value-at-Risk measures," Journal of Empirical Finance, Elsevier, vol. 8(3), pages 325-342, July.
  5. Jianqing Fan & Juan Gu, 2003. "Semiparametric estimation of Value at Risk," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 261-290, December.
  6. Oliver Linton & Yoon-Jae Whang, 2004. "A Quantilogram Approach to Evaluating Directional Predictability," Cowles Foundation Discussion Papers 1454, Cowles Foundation for Research in Economics, Yale University.
  7. Norman Swanson & Valentina Corradi, 2006. "Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes," Departmental Working Papers 200618, Rutgers University, Department of Economics.
  8. Durlauf, Steven N., 1991. "Spectral based testing of the martingale hypothesis," Journal of Econometrics, Elsevier, vol. 50(3), pages 355-376, December.
  9. Escanciano, J. C. & Olmo, J., 2007. "Estimation risk effects on backtesting for parametric value-at-risk models," Working Papers 07/11, Department of Economics, City University London.
  10. repec:cup:cbooks:9780521496032 is not listed on IDEAS
  11. Li, W K & Ling, Shiqing & McAleer, Michael, 2002. " Recent Theoretical Results for Time Series Models with GARCH Errors," Journal of Economic Surveys, Wiley Blackwell, vol. 16(3), pages 245-69, July.
  12. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value-at-Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, vol. 57(3), pages 1093-1111, 06.
  13. Delgado, Miguel A. & Carlos Escanciano, J., 2007. "Nonparametric tests for conditional symmetry in dynamic models," Journal of Econometrics, Elsevier, vol. 141(2), pages 652-682, December.
  14. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 53-89.
  15. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
  16. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
  17. Mc Cracken, Michael W., 2000. "Robust out-of-sample inference," Journal of Econometrics, Elsevier, vol. 99(2), pages 195-223, December.
  18. Koenker, Roger & Zhao, Quanshui, 1996. "Conditional Quantile Estimation and Inference for Arch Models," Econometric Theory, Cambridge University Press, vol. 12(05), pages 793-813, December.
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Cited by:
  1. Candelon Bertrand & Colletaz Gilberg & Hurlin Christophe & Tokpavi Sessi, 2009. "Backtesting Value-at-Risk: A GMM Duration-based Test," Research Memorandum 051, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  2. Sylvain Benoit & Christophe Hurlin & Christophe Pérignon, 2013. "Implied Risk Exposures," Working Papers halshs-00836280, HAL.
  3. Syed Adeel Hussain, 2013. "Differentiation of Market Risk Characteristics among Sharia Compliant and Conventional Equities listed on the Pakistani Capital Market - KSE 100 Index over a selective time period," 2013 Papers phu395, Job Market Papers.
  4. Lönnbark, Carl, 2013. "On the role of the estimation error in prediction of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 37(3), pages 847-853.
  5. Gourieroux, Christian & Zakoïan, Jean-Michel, 2013. "Estimation-Adjusted Var," Econometric Theory, Cambridge University Press, vol. 29(04), pages 735-770, August.
  6. Escanciano, Juan Carlos & Pei, Pei, 2012. "Pitfalls in backtesting Historical Simulation VaR models," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2233-2244.

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