| DCCroll-class {rmgarch} | R Documentation |
class: DCC Roll Class
Description
The class is returned by calling the function dccroll.
Slots
mforecast:Object of class
"vector"Multivariate forecast list.model:Object of class
"vector"Model specification list.
Extends
Class "mGARCHroll", directly.
Class "GARCHroll", by class "mGARCHroll", distance 2.
Class "rGARCH", by class "mGARCHroll", distance 3.
Methods
- coef
signature(object = "DCCroll"): The coefficient array across the rolling estimations with a T+0 3rd dimension index label.- fitted
signature(object = "DCCroll"): The conditional mean forecast xts object (with the actual T+i forecast dates as index).- likelihood
signature(object = "DCCroll"): The log-likelihood across rolling estimations.- plot
signature(x = "DCCroll", y = "missing"): Plot method, given additional arguments ‘series’ and ‘which’.- rcor
signature(object = "DCCroll"): The forecast dynamic conditional correlation array, with the T+i forecast index in the 3rd dimension label. Optional argument ‘type’ determines whether to return “R” for the correlation else will the DCC Q matrix. A further argument ‘output’ allows to switch between “array” and “matrix” returned object.- rcov
signature(object = "DCCroll"): The forecast dynamic conditional covariance array, with the T+i forecast index in the 3rd dimension label. A further argument ‘output’ allows to switch between “array” and “matrix” returned object.- rshape
signature(object = "DCCroll"): The multivariate distribution shape parameter(s).- rskew
signature(object = "DCCroll"): The multivariate distribution skew parameter(s).- show
signature(object = "DCCroll"): Summary.- sigma
signature(object = "DCCroll"): The conditional sigma forecast xts object (with the actual T+i forecast dates as index).
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.