The class is returned by calling the function dccforecast.
mforecast:Object of class "vector" Multivariate
forecast list.
model:Object of class "vector" Model specification
list.
Class mGARCHforecast, directly.\
Class GARCHforecast object from the rugarch package, by class mGARCHforecast, distance 2.\
Class rGARCH object from the rugarch package, by class mGARCHforecast, distance 3.
signature(object = "DCCforecast"):
The multivariate distribution shape parameter(s).
signature(object = "DCCforecast"):
The multivariate distribution skew parameter(s).
signature(object = "DCCforecast"):
The conditional mean forecast array of dimensions n.ahead x n.assets
by (n.roll+1). The third dimension of the array has the T+0 index label.
signature(object = "DCCforecast"):
The conditional sigma forecast array of dimensions n.ahead x n.assets
by (n.roll+1). The third dimension of the array has the T+0 index label.
signature(x = "DCCforecast", y = "missing"):
Plot method, given additional arguments ‘series’ and ‘which’.
signature(object = "DCCforecast"):
The forecast dynamic conditional correlation list of arrays of length
(n.roll+1), with each array of dimensions n.assets x n.assets x n.ahead.
The method takes one additional argument ‘type’ (either “R”
for the correlation else will return the DCC Q matrix). A further argument
‘output’ allows to switch between “array”
and “matrix” returned object.
signature(object = "DCCforecast"):
The forecast dynamic conditional covariance list of arrays of length
(n.roll+1), with each array of dimensions n.assets x n.assets x n.ahead.
A further argument ‘output’ allows to switch between “array”
and “matrix” returned object.
signature(object = "DCCforecast"):
Summary.
Alexios Galanos
Engle, R.F. and Sheppard, K. 2001, Theoretical and empirical properties of
dynamic conditional correlation multivariate GARCH, NBER Working Paper.