Predicting tail-related risk measures: The consequences of using GARCH filters for non-GARCH dataAmine Jalal and Michael Rockinger () Journal of Empirical Finance, 2008, vol. 15, issue 5, pages 868-877 Abstract: We investigate the consequences for Value-at-Risk and expected shortfall purposes of using a GARCH filter on various mis-specified processes. In general, we find that the McNeil and Frey (McNeil, A.J. and R. Frey, 2000, Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: An Extreme Value Approach, Journal of Empirical Finance 7, 271-300.) two step procedure has very good forecasting properties. Using an unconditional non-filtered tail estimate also appears to perform satisfactorily for expected shortfall measurements but less so for VaR computations. Methods assuming specific densities such as the Gaussian or Student-t may yield wrong predictions. Thus, the use of an adequacy test for filtered data to given densities appears relevant. The paper builds on recent techniques to obtain thresholds for extreme value computations. Statistical tests for the expected shortfall, based on the circular bootstrap, are developed. Keywords: Extreme; value; theory; Value-at-Risk; (VaR); Expected; shortfall; GARCH; Markov; switching; Jump; diffusion; Backtesting (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: http://EconPapers.repec.org/RePEc:eee:empfin:v:15:y:2008:i:5:p:868-877 Access Statistics for this article Journal of Empirical Finance is edited by R. T. Baillie, G. Bekaert, W. Ferson, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff More articles in Journal of Empirical Finance from Elsevier |
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