Getting forecast values using DCC GARCH fit

Hi,
I am completely new to GARCH models and trying to fit a multivariate time
series model using DCC GARCH model and forecast it.

The data looks like this:

head(datax)

x   vibration_x     Speed
1 2017-05-16 17:53:00      -0.132  421.4189
2 2017-05-16 17:54:00      -0.296 1296.8882
3 2017-05-16 17:55:00      -0.572    0.0000
4 2017-05-16 17:56:00      -0.736 1254.2695
5 2017-05-16 17:57:00       0.000    0.0000
6 2017-05-16 17:58:00       0.000    0.0000

garch11.spec = ugarchspec(mean.model = list(armaOrder = c(1,1)),

variance.model = list(garchOrder = c(1,1),
                                          model = "sGARCH"),
distribution.model = "norm")

dcc.garch11.spec = dccspec(uspec = multispec( replicate(2, garch11.spec)

),
                  dccOrder = c(1,1), distribution = "mvnorm")

fit.a = dccfit(dcc.garch11.spec, data = datax[,c(2,3)], out.sample = 100,

fit.control = list(eval.se=T))

dcc.focast=dccforecast(fit.a, n.ahead = 100)

May I know how to get the forecast values from 'dcc.focast' ? when i plot
the model using,

plot(dcc.focast, which = 1)

I get different plots such as.
Make a plot selection (or 0 to exit):

1:   Conditional Mean (vs Realized Returns)
2:   Conditional Sigma (vs Realized Absolute Returns)
3:   Conditional Covariance
4:   Conditional Correlation
5:   EW Portfolio Plot with conditional density VaR limits

May i know what i should do with "Conditional covariance" and "conditional
correlation" forecast. I know this is for volatility prediction. I am
interested to know what things i can interpret from this conditional
covariance ?

 Any help is much appreciated. Thanks.,

Regards
Dhivya