Correct. You might need to experiment with the scale on FXX and the degrees of freedom, but the process is the same.Jules89 wrote:Dear Tom,
I have two questions regarding MCMC estimation of the BEKK model:
1)
I went through the MCMC code for the DCC-GARCH. Wouldn't it be possible to estimate a BEKK model with the similar procedure? I start with the ML estimates, then I generate candidate draws with the t-distribution and evaluate it using:
The rest should be the same.Code: Select all
compute btest=blast+%ranmvt(fxx,nuxx) garch(p=1,q=1,mv=bekk,initial=btest,method=eval,$ rvectors=rv,hmatrices=htest) / xjpn xfra xsui compute logptest=%logl
If an independence chain works, it's generally superior to random walk---if the asymptotic distribution is fairly accurate (which is likely if you have enough data), independent draws use that while the RW draws ignore it.Jules89 wrote: 2)
Above would be Random Walk MH, why do you think that independence MH is better suited?