-based Predictive Model (EFPM). Then, we combine it with the Copula-GARCH simulation model and the Mean-Conditional Value at Risk (Mean-CVaR …, Sharpe ratio, maximum drawdown, and 99% CVaR. …

with risk measured by CVaR and additional sophisticated constraints. The cash outflow shortages are penalized in the …

–regime and Markov-switching GARCH (MSGARCH) models, from a risk management perspective. I find that, for daily, weekly, and ten … étude à grande échelle empirique pour comparer la` performance de prévision de modèle GARCH sans changement de régime et de … modèle GARCH à changement de régimes Markovien (MSGARCH) du point de vue d’un gestionnaire des risques. Les résultats …

for main indices from stock exchanges was conducted. The VaR forecasts from GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH … volatility trend. However, GARCH-st (1,1) and QML-GARCH(1,1) were found to be the most robust models in the different volatility …

several different multivariate GARCH models (dynamic conditional correlation (DCC), asymmetric DCC (ADCC), generalized … orthogonal GARCH (GO-GARCH)) to estimate minimum variance equity portfolios. Both long and short portfolios are considered. An …

Theory. We utilise the GARCH-EVT approach in combination with a novel algorithm to automatically determine the optimal …

employed in a bivariate GARCH model, where the joint distribution of the disturbances is split into its marginals and its …-dependent distribution. -- value-at-risk ; copula ; non-normal bivariate GARCH ; asymmetric dependence ; profile likelihood-ratio test …