Hi
I am trying to implement a typical GARCH-Copula with DCC for dynamic
correlations. Is there someone could give me an example codes how it can be
done? I have implemented this in Matlab, but don't know how to get a start
in R. I have googled around and found rmgarch package can give it a go.
Below is what I did:
> library(rmgarch)
> data(dji30ret)
> Data <- dji30ret[, 1:3, drop = FALSE]
> uspec <- ugarchspec(mean.model = list(armaOrder = c(0,0), include.mean =
> FALSE), variance.model = list(garchOrder = c(1,1), model = "sGARCH"),
> distribution.model = "std")
> cspec <- cgarchspec(uspec = multispec( replicate(3, uspec) ), VAR = FALSE,
> robust = FALSE, lag = 1, lag.max = NULL, lag.criterion =
> c("AIC", "HQ", "SC", "FPE"), external.regressors = NULL, robust.control =
> list(gamma = 0.25, delta = 0.01, nc = 10, ns = 500), dccOrder = c(1, 1),
> asymmetric = FALSE, distribution.model = list(copula = "mvt", method =
> "ML", time.varying = TRUE, transformation = "parametric"), start.pars =
> list(), fixed.pars = list())
> cfit <- cgarchfit(cspec, data =Data, spd.control = list(lower = 0.1, upper
> = 0.9, type = "pwm", kernel = "epanech"),fit.control = list(eval.se =
> TRUE, trace = TRUE, stationarity = TRUE),solver = "solnp", solver.control
> = list(), out.sample = 0, parallel = FALSE, parallel.control = list(pkg =
> c("multicore", "snowfall"), cores = 2), fit = NULL, VAR.fit = NULL)
my questions are:
1) (very silly) how to get the estimated parameters (incl. s.e. p-value)?
2) how to plot the dynamics of correlation?
3) how to perform goodness-of-fit tests for marginal estimations?
4) how to perform goodness-of-fit tests for copula?
I will appreciate for any help! Thank you
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