It's a lot
more complicated than what you're doing. Because the DCC correlation is associated with the specific ordering of the original data, you have to bootstrap a data set, which needs to have the proper mean model as well, use it to estimate a new set of GARCH coefficients, then evaluate the DCC GARCH model on the original data set with the bootstrapped coefficients. I would recommend doing the Metropolis-Hastings method shown in:http://www.estima.com/forum/viewtopic.php?f=8&t=1591
It will probably be over 100 times faster since it just has to do one function evaluation per sweep rather than needing full estimation of the GARCH model for each bootstrap sample.