Evaluating Value-at-Risk Models with Desk-Level Data
AbstractWe present new evidence on disaggregated profit and loss (P/L) and value-at-risk (VaR) forecasts obtained from a large international commercial bank. Our data set includes the actual daily P/L generated by four separate business lines within the bank. All four business lines are involved in securities trading and each is observed daily for a period of at least two years. Given this unique data set, we provide an integrated, unifying framework for assessing the accuracy of VaR forecasts. We use a comprehensive Monte Carlo study to assess which of these many tests have the best finite-sample size and power properties. Our desk-level data set provides importance guidance for choosing realistic P/L-generating processes in the Monte Carlo comparison of the various tests. The conditional autoregressive value-at-risk test of Engle and Manganelli (2004) performs best overall, but duration-based tests also perform well in many cases. This paper was accepted by John Birge, focused issue editor.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by INFORMS in its journal Management Science.
Volume (Year): 57 (2011)
Issue (Month): 12 (December)
risk management; backtesting; volatility; disclosure;
Other versions of this item:
- Peter Christoffersen & Jeremy Berkowitz & Denis Pelletier, 2008. "Evaluating Value-at-Risk Models with Desk-Level Data," CREATES Research Papers 2009-35, School of Economics and Management, University of Aarhus.
- Jeremy Berkowitz & Peter Christoffersen & Denis Pelletier, 2005. "Evaluating Value-at-Risk models with desk-level data," Working Paper Series 010, North Carolina State University, Department of Economics, revised Dec 2006.
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Elena-Ivona Dumitrescu & Christophe Hurlin & Jaouad Madkour, 2011.
"Testing interval forecasts: a GMM-based approach,"
- Krenar Avdulaj & Jozef Barunik, 2013. "Can we still benefit from international diversification? The case of the Czech and German stock markets," Papers 1308.6120, arXiv.org, revised Sep 2013.
- Chen, C.W.S. & Gerlach, R. & Hwang, B.B.K. & McAleer, M.J., 2011.
"Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intraday Range,"
Econometric Institute Report
EI 2011-17, Erasmus University Rotterdam, Econometric Institute.
- Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," Working Papers in Economics 11/22, University of Canterbury, Department of Economics and Finance.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," Documentos del Instituto Complutense de AnÃ¡lisis EconÃ³mico 2011-16, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
- Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
- Bertrand Candelon & Marc Joëts & Sessi Tokpavi, 2012. "Testing for crude oil markets globalization during extreme price movements," EconomiX Working Papers 2012-28, University of Paris West - Nanterre la Défense, EconomiX.
- Ales Kresta & Tomas Tichy, 2012. "International Equity Portfolio Risk Modeling: The Case of the NIG Model and Ordinary Copula Functions," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 62(2), pages 141-161, May.
- Sylvain Benoit & Christophe Hurlin & Christophe Pérignon, 2013. "Implied Risk Exposures," Working Papers halshs-00836280, HAL.
- El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.
- Gourieroux, Christian & Zakoïan, Jean-Michel, 2013.
Cambridge University Press, vol. 29(04), pages 735-770, August.
- J. Carlos Escanciano & Carlos Velasco, 2010.
"Specification tests of parametric dynamic conditional quantiles,"
- Escanciano, Juan Carlos & Velasco, Carlos, 2010. "Specification tests of parametric dynamic conditional quantiles," Journal of Econometrics, Elsevier, vol. 159(1), pages 209-221, November.
- Juan Carlos Escanciano & Carlos Velasco, 2008. "Specification Tests of Parametric Dynamic Conditional Quantiles," Caepr Working Papers 2008-021, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
- repec:syb:wpbsba:01/2012 is not listed on IDEAS
- Filip Zikes & Jozef Barunik, 2013. "Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility," Papers 1308.4276, arXiv.org.
- Dumitrescu, Elena-Ivona, 2012. "Econometric methods for financial crises," Open Access publications from Maastricht University urn:nbn:nl:ui:27-29274, Maastricht University.
- Escanciano, Juan Carlos & Pei, Pei, 2012.
"Pitfalls in backtesting Historical Simulation VaR models,"
Journal of Banking & Finance,
Elsevier, vol. 36(8), pages 2233-2244.
- Juan Carlos Escanciano & Pei Pei, 2012. "Pitfalls in Backtesting Historical Simulation VaR Models," Caepr Working Papers 2012-003, Center for Applied Economics and Policy Research, Economics Department, Indiana University Bloomington.
- Krenar Avdulaj & Jozef Barunik, 2013. "Are benefits from oil - stocks diversification gone? A new evidence from a dynamic copulas and high frequency data," Papers 1307.5981, arXiv.org.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc).
If references are entirely missing, you can add them using this form.