Hello everyone, I am learning about copulas and also do some MATLAB/R coding to get better understanding of how copulas work. Recently I have started coding simple copula-GARCH models, that is I fit say AR(1)-GARCH(1,1)-normal models to univariate time series, and then I want to fit the copula (two-stage procedure).
What I have problem with is connecting these two estimation stages. After I have estimated AR-GARCH univariate models, what do I take from these models and put into log-likelihood estimation of the copula? Do I take residuals from AR-GARCH models, or do I use estimated parameters of these models to produce samples that I then use in copula estimation stage? I read a few papers that use copula-GARCH models, but it is not clear from them how to estimate copula model. In one of the papers it says: "Let u=F(x; theta(x)) and v=F(y; theta(y)), where theta(x) and theta(y) are the vectors of parameters of each marginal distribution..." and then one uses u and v in copula log-likelihood minimization. I am so embarassed, but I still do not get it. If I estimated the GARCH model parameters, how do I get these F(x; theta(x)) and F(y; theta(y))? Probably very simple and totally obvious thing, but I just do not get it. :-( Could you please help me understand? How do I do it in MATLAB or R? THanks in advance! -- Jonas Malmros ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.