if you check the code you can see that he used the data "MSFT" and "GSPC".
He calculates the returns
MSFT.ret = CalculateReturns(MSFT, method="log")
GSPC.ret = CalculateReturns(GSPC, method="log")
creates the combined series
MSFT.GSPC.ret = merge(MSFT.ret,GSPC.ret)
and fits an univariate GARCH and then the DCC GARCH model
# univariate normal GARCH(1,1) for each series
garch11.spec = ugarchspec(mean.model = list(armaOrder = c(0,0)),
variance.model = list(garchOrder = c(1,1),
model = "sGARCH"),
distribution.model = "norm")
# dcc specification - GARCH(1,1) for conditional correlations
dcc.garch11.spec = dccspec(uspec = multispec( replicate(2, garch11.spec) ),
dccOrder = c(1,1),
distribution = "mvnorm")
dcc.garch11.spec
dcc.fit = dccfit(dcc.garch11.spec, data = MSFT.GSPC.ret)
Here you can change "MSFT" and "GSPC" and if you need help to write for example a loop to iterate over all combinations, post a simple code with your data.frame or matrix with the data and a simple example.