Testing and comparing Value-at-Risk measures
AbstractValue-at-Risk (VaR) has emerged as the standard tool for measuring and reporting financial market risk. Currently, more than eighty commercial vendors offer enterprise or trading risk management systems which report VaR-like measures. Risk managers are therefore often left with the daunting task of having to choose from this plethora of risk models. Accordingly, this paper develops a framework for asking, first, how a risk manager can test that the VaR measure at hand is properly specified. And second, given two different VaR measures, how can the risk manager compare the two and pick the best in a statistically meaningful way? In the application, competing VaR measures are calculated from either historical or option-price based volatility measures, and the VaRs are tested and compared. La valeur exposÃ©e au risque (value at risk - VaR) est devenue un outil standard de mesure et de communication des risques associÃ©s aux marchÃ©s financiers. Plus de quatre-vingts fournisseurs commerciaux proposent actuellement des systÃ¨mes de gestion d'entreprise ou de gestion des risques commerciaux fournissant des mesures de type VaR. C'est donc souvent aux gestionnaires des risques qu'incombe la tÃ¢che difficile d'opÃ©rer un choix parmi cette plÃ©thore de modÃ¨les de risques. Cet article propose un cadre utile pour dÃ©terminer par quel moyen le gestionnaire des risques peut s'assurer que la mesure de VaR dont il dispose est bien dÃ©finie, et, dans un deuxiÃ¨me temps, comparer deux mesures de VaR diffÃ©rentes et choisir la meilleure en s'appuyant sur des donnÃ©es statistiques utiles. Dans l'application, diffÃ©rentes mesures de VaR sont calculÃ©es Ã partir soit de mesures de volatilitÃ© historiques ou de mesures de volatilitÃ© implicites dans le prix des options; les VaR sont Ã©galement vÃ©rifiÃ©es et comparÃ©es.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Empirical Finance.
Volume (Year): 8 (2001)
Issue (Month): 3 (July)
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Web page: http://www.elsevier.com/locate/jempfin
Other versions of this item:
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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