discuss their advantages and limitations. By using both VaR and TVaR to compute the loading, we see that only the latter …

Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually superior to Value-at-Risk (VaR … not to be elicitable which means that backtesting for ES is less straight-forward than, e.g., backtesting for VaR …. Expectiles have been suggested as potentially better alternatives to both ES and VaR. In this paper, we revisit commonly accepted …

In this paper we propose a new tool for backtesting that examines the quality of Value-at- Risk (VaR) forecasts. To …-choice model, e.g. Probit, Logit, links the sequence of violations to a set of explanatory variables including the lagged VaR and …

This paper proposes a new test of Value at Risk (VaR) validation. Our test exploits the idea that the sequence of VaR … dimension appreciably improves the power properties of the VaR validation test for reasonable sample sizes. …

-at-Risk (VaR) and a VaR de.ned at an extremely low coverage probability. We then formally test whether the sequences of exceptions … market, credit, operational, or systemic risk estimates (VaR, stressed VaR, expected shortfall, and CoVaR) or to assess the …

risque pour évaluer les risques extrêmes. Ces mesures de risques, telles que la VaR, sont devenues incontournables dans la …, sur des données longues américaines, une relation en U-inversé entre notre mesure du risque de modèle sur les VaR …

(specification and estimation risks) on VaR estimates. We find that integrating the model risk into the VaR computations implies a … substantial minimum correction of the order of 10-40% of VaR levels. We also present results of a practical method - based on a … backtesting framework - for incorporating the model risk into the VaR estimates. …