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suggest a superiority of the one-step method when the innovations are heavy-tailed. For standard GARCH models, the comparison …
Persistent link: https://www.econbiz.de/10011108575
the innovations are heavy-tailed. For standard GARCH models, the comparison only depends on characteristics of the …
Persistent link: https://www.econbiz.de/10011077602
We consider joint estimation of conditional Value-at-Risk (VaR) at several levels, in the framework of general conditional heteroskedastic models. The volatility is estimated by Quasi-Maximum Likelihood (QML) in a first step, and the residuals are used to estimate the innovations quantiles in a...
Persistent link: https://www.econbiz.de/10010796244
-maximum likelihood (QML) estimation of GARCH models. It relies on a reparameterization of the model and a first-step estimation of the … distribution of the estimators obtained by this method in univariate GARCH models. Comparisons with the standard QML are provided …
Persistent link: https://www.econbiz.de/10005014739
A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its...
Persistent link: https://www.econbiz.de/10010680448
A new model class for univariate asset returns is proposed which involves the use of mixtures of stable Paretian distributions, and readily lends itself to use in a multivariate context for portfolio selection. The model nests numerous ones currently in use, and is shown to outperform all its...
Persistent link: https://www.econbiz.de/10010608465
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer of many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011730304
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...
Persistent link: https://www.econbiz.de/10011674479
Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...
Persistent link: https://www.econbiz.de/10010281552
Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...
Persistent link: https://www.econbiz.de/10009651900