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Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range

  • Cathy W. S. Chen

    (Graduate Institute of Statistics and Actuarial Science, Feng Chia University)

  • Richard Gerlach

    (University of Sydney Business School)

  • Bruce B. K. Hwang

    (Graduate Institute of Statistics and Actuarial Science, Feng Chia University)

  • Michael McAleer

    (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, Complutense University of Madrid, and Institute of Economic Research, Kyoto University)

Value-at-Risk (VaR) is commonly used for financial risk measurement. It has recently become even more important, especially during the 2008-09 global financial crisis. We pro- pose some novel nonlinear threshold conditional autoregressive VaR (CAViaR) models that incorporate intra-day price ranges. Model estimation and inference are performed using the Bayesian approach via the link with the Skewed-Laplace distribution. We examine how a range of risk models perform during the 2008-09 financial crisis, and evaluate how the crisis affects the performance of risk models via forecasting VaR. Empirical analysis is conducted on five Asia-Pacific Economic Cooperation stock market indices as well as two exchange rate series. We examine violation rates, back-testing criteria, market risk charges and quantile loss function values to measure and assess the forecasting performance of a variety of risk models. The proposed threshold CAViaR model, incorporating range information, is shown to forecast VaR more efficiently than other models, across the series considered, which should be useful for financial practitioners.

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File URL: http://www.kier.kyoto-u.ac.jp/DP/DP775.pdf
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Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 775.

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Length: 40pages
Date of creation: May 2011
Date of revision:
Handle: RePEc:kyo:wpaper:775
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  2. Michael McAleer & Juan-Ángel Jiménez-Martín & Teodosio Pérez Amaral, 2012. "Has the Basel Accord Improved Risk Management During the Global Financial Crisis?," Documentos de Trabajo del ICAE 2012-26, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Oct 2012.
  3. Richard H. Gerlach & Cathy W. S. Chen & Nancy Y. C. Chan, 2011. "Bayesian Time-Varying Quantile Forecasting for Value-at-Risk in Financial Markets," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 481-492, October.
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  5. Engle, Robert F & Manganelli, Simone, 1999. "CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles," University of California at San Diego, Economics Working Paper Series qt06m3d6nv, Department of Economics, UC San Diego.
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  7. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
  8. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.
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  16. Michael McAleer & Bernardo da Veiga, 2008. "Single-index and portfolio models for forecasting value-at-risk thresholds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(3), pages 217-235.
  17. Juan-Ángel Jiménez-Martín & Michael McAleer & Teodosio Pérez-Amaral, 2009. "Has the Basel II Accord Encouraged Risk Management During the 2008-09 Financial Crisis?," Documentos de Trabajo del ICAE 0918, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  18. McAleer, M.J. & Jimenez-Martin, J-A. & Perez-Amaral, T., 2009. "What Happened to Risk Management During the 2008-09 Financial Crisis?," Econometric Institute Research Papers EI 2009-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  19. Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
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