returns. For multivariate density and portfolio risk forecasting, a drawback of these models is the underlying assumption of …. An extensive empirical study confirms the COMFORT model’s superiority in terms of multivariate density and Value-at-Risk …

financial returns and port-folio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and …, especially the Frank-GARCH models provide most conservative risk forecasts and out-perform all rival models. -- Copula … distributions ; expected shortfall ; GARCH ; model selection ; non-Gaussian innovations ; risk forecasting ; value-at-risk …

financial returns and portfolio risk. In this paper, we propose an adjustment of GARCH implied conditional value-at-risk and …, especially the Frank-GARCH models provide most conservative risk forecasts and out-perform all rival models …

Beyond their importance from the regulatory policy point of view, Value-at-Risk (VaR) and Expected Shortfall (ES) play … an important role in risk management, portfolio allocation, capital level requirements, trading systems, and hedging …

This study contrasts GARCH models with diverse combined forecast techniques for Commodities Value at Risk (VaR …

In this study we consider the risk estimation as a stochastic process based on the Sample Quantile Process (SQP …) - which is a generalization of the Value-at-Risk calculated on a rolling sample. Using SQP's, we are able to show and quantify … the pro-cyclicality of the current way financial institutions measure their risk. Analysing 11 stock indices, we show that …

We define the Multidimensional Value at Risk (MVaR) as a natural generalization of VaR. This generalization makes a …

Multidimensional Value at Risk (MVaR) generalises VaR in a natural way as the intersection of univariate VaRs. We …