Hello,
I have a few questions concerning the DCC-GARCH model and its programming in
R.
So here is what I want to do:
I take quotes of two indices - S&P500 and DJ. And the aim is to estimate
coefficients of the DCC-GARCH model for them. This is how I do it:


library(tseries)
p1 = get.hist.quote(instrument = "^gspc",start = "2005-01-07",end =
"2009-09-04",compression = "w", quote="AdjClose")
p2 = get.hist.quote(instrument = "^dji",start = "2005-01-07",end =
"2009-09-04",compression = "w", quote="AdjClose")
p = cbind(p1,p2)
y = diff(log(p))*100
y[,1] = y[,1]-mean(y[,1])
y[,2] = y[,2]-mean(y[,2])
T = length(y[,1])

library(ccgarch)
library(fGarch)

f1 = garchFit(~ garch(1,1), data=y[,1],include.mean=FALSE)
f1 = f1@fit$coef
f2 = garchFit(~ garch(1,1), data=y[,2],include.mean=FALSE)
f2 = f2@fit$coef

a = c(f1[1], f2[1])
A = diag(c(f1[2],f2[2]))
B = diag(c(f1[3], f2[3]))
dccpara = c(0.2,0.6)
dccresults = dcc.estimation(inia=a, iniA=A, iniB=B, ini.dcc=dccpara,dvar=y,
model="diagonal")

dccresults$out
DCCrho = dccresults$DCC[,2]
matplot(DCCrho, type='l')


dccresults$out deliver me the estimated coefficients of the DCC-GARCH model.
And here is my first question:
How can I check if these coefficients are significant or not? How can I test
them for significance?

second question would be:
Is this true that matplot(DCCrho, type='l') shows conditional correlation
between the two indices in question?

and the third one:
What is actually dccpara and why do I get totally different DCC-alpha and
DCC-beta coefficients if I change dccpara from c(0.2,0.6) to, let's say,
c(0.01, 0.98) ? What determines which values should be chosen?


Hopefully someone will find time to give me a hand.

Thank you very much in advance, people of good will, for looking at/checking
what I wrote and helping me.

Best regards
Marcin

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