GARCH models are useful to estimate daily volatility in financial return series. When intra-day return data are available realized volatility may be used for the same purpose. We formulate a new model ...
We consider a class of semiparametric GARCH models with additive autoregressive components linked together by a dynamic coefficient. We propose estimators for the additive components and the dynamic ...
We discuss the relative performances of value-at-risk (VaR) models using generalized autoregressive conditional heteroscedasticity (GARCH), Glosten-Jagannathan-Runkle GARCH and integrated GARCH ...
There are several approaches to dealing with heteroscedasticity. If the error variance at different times is known, weighted regression is a good method. If, as is ...
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