> Subject: [R] GARCH with t-innovations > Date: 21 Feb 2003 14:07:44 +0100 > From: Gorazd Brumen <[EMAIL PROTECTED]> > To: [EMAIL PROTECTED] > > Dear all, > > Can garch function fit also t-innovations or only Gaussian innovations? > > -- > With kind regards -- Lepo pozdravljeni -- Gr��e (Gr�ezi) -- > > Gorazd Brumen > ------------------------------- > Mail 1: [EMAIL PROTECTED] > Mail 2: [EMAIL PROTECTED] > Tel.: +41 (0)1 63 34906 > Homepage: valjhun.fmf.uni-lj.si/~brumen
The estimator provided by the garch function is the maximum likelihood estimator under conditional normality. Under conditional-nonnormality (e.g., t-distribution) the estimator is a quasi-maximum likelihood estimator which is still consistent under certain (more restrictive than Gaussian case) assumptions. However, the standard errors as computed by the garch function are in the latter case not any more consistent. For an overview see section 8 of the first citation in the help page of the garch function. For practical purposes, that means you can fit a garch model with the garch function, take the residuals and fit, e.g., a t-distribution. This might be a consistent estimation procedure, however unless the residuals are Gaussian not the ideal one. best Adrian -- Dr. Adrian Trapletti Phone : +41 (0) 1 994 5631 Trapletti Statistical Computing Mobile: +41 (0)76 370 5631 Wildsbergstrasse 31 Fax : +41 (0) 1 994 5631 CH-8610 Uster Email : mailto:[EMAIL PROTECTED] Switzerland WWW : http://trapletti.homelinux.com ______________________________________________ [EMAIL PROTECTED] mailing list http://www.stat.math.ethz.ch/mailman/listinfo/r-help
