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Exact inference in diagnosing value-at-risk estimates: A Monte Carlo device

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Author Info
Herwartz, Helmut
Abstract

In this note a Monte Carlo approach is suggested to determine critical values for diagnostic tests of Value-at-Risk models that rely on binary random variables. Monte Carlo testing offers exact significance levels in finite samples. Conditional on exact critical values the dynamic quantile test suggested by Engle and Manganelli (2004) turns out more powerful than a recently proposed Portmanteau type test (Hurlin and Tokpavi 2006). --

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File URL: http://econstor.eu/bitstream/10419/27671/1/EWP-2008-16.pdf
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Publisher Info
Paper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2008,16.

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Date of creation: 2008
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Handle: RePEc:zbw:cauewp:7411

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Web page: http://www.wiso.uni-kiel.de/econ/

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Related research
Keywords: Value-at-Risk; Monte Carlo test;

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Find related papers by JEL classification:
G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions

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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. [Downloadable!] (restricted)
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  2. 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. [Downloadable!] (restricted)
    Other versions:
  3. Christophe Hurlin & Sessi Tokpavi, 2006. "Backtesting VaR Accuracy: A New Simple Test," Working Papers halshs-00068384_v1, HAL. [Downloadable!]
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