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", by class "mGARCHforecast", distance 2.
Class "'>rGARCH", 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 thirds 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 thirds 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 on 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 correlation 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.
Engle, R.F. and Sheppard, K. 2001, Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH, NBER Working Paper.