DCCforecast-class {rmgarch}

class: DCC Forecast Class

Description

The class is returned by calling the function dccforecast.

Slots

mforecast:

Object of class "vector" Multivariate forecast list.

model:

Object of class "vector" Model specification list.

Extends

Class "mGARCHforecast", directly. Class "GARCHforecast", by class "mGARCHforecast", distance 2. Class "rGARCH", by class "mGARCHforecast", distance 3.

Methods

rshape

signature(object = "DCCforecast"): The multivariate distribution shape parameter(s).

rskew

signature(object = "DCCforecast"): The multivariate distribution skew parameter(s).

fitted

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.

sigma

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.

plot

signature(x = "DCCforecast", y = "missing"): Plot method, given additional arguments ‘series’ and ‘which’.

rcor

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.

rcov

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.

show

signature(object = "DCCforecast"): Summary.

Author(s)

Alexios Galanos

References

Engle, R.F. and Sheppard, K. 2001, Theoretical and empirical properties of dynamic conditional correlation multivariate GARCH, NBER Working Paper.