conditional variance models -凯发k8网页登录

conditional variance models attempt to address volatility clustering in univariate time series models to improve parameter estimates and forecast accuracy. to model volatility, econometrics toolbox™ supports the standard generalized autoregressive conditional heteroscedastic (arch/garch) model, the exponential garch (egarch) model, and the glosten, jagannathan, and runkle (gjr) model.

to convert from the previous conditional variance model analysis syntaxes, see .