The class is returned by calling the function cgarchsim.
msim:Object of class "vector" Multivariate simulation list.
model:Object of class "vector" Model specification list.
Class "'>mGARCHsim", directly.
Class "'>GARCHsim", by class "mGARCHsim", distance 2.
Class "'>rGARCH", by class "mGARCHsim", distance 3.
signature(object = "cGARCHsim"):
The simulated conditional returns matrix given. Takes optional argument
“sim” indicating the simulation run to return (from the m.sim option
of the cgarchsim method.
signature(object = "cGARCHfit"):
The simulated conditional sigma matrix given. Takes optional argument
“sim” indicating the simulation run to return (from the m.sim option
of the cgarchsim method.
signature(object = "cGARCHsim"):
The simulated conditional correlation array (for DCC type). Takes optional
argument “sim” indicating the simulation run to return (from the
m.sim option of the cgarchsim method. A further argument
‘output’ allows to switch between “array”
and “matrix” returned object.
signature(object = "cGARCHsim"):
The simulated conditional covariance array. Takes optional argument
“sim” indicating the simulation run to return
(from the m.sim option of the cgarchsim method.
A further argument ‘output’ allows to switch between “array”
and “matrix” returned object.
signature(object = "cGARCHsim"):
Summary.
Joe, H. Multivariate Models and Dependence Concepts, 1997, Chapman \& Hall, London. Genest, C., Ghoudi, K. and Rivest, L. A semiparametric estimation procedure of dependence parameters in multivariate families of distributions, 1995, Biometrika, 82, 543-552.