dccroll-methods: function: DCC-GARCH Rolling Forecast
In rmgarch: Multivariate GARCH Models

Description Usage Arguments Value Author(s)

Method for creating a DCC-GARCH rolling forecast object.

dccroll(spec, data, n.ahead = 1, forecast.length = 50, refit.every = 25, 
n.start = NULL, refit.window = c("recursive", "moving"), window.size = NULL, 
solver = "solnp", solver.control = list(), 
fit.control = list(eval.se = TRUE, stationarity = TRUE, scale = FALSE), 
cluster = NULL, save.fit = FALSE, save.wdir = NULL, realizedVol = NULL, 
clusterOnAssets=FALSE, ...)

`spec`	A `DCCspec` object with fixed parameters.
`data`	A multivariate xts dataset or one which can be coerced to such.
`n.ahead`	The number of periods to forecast.
`forecast.length`	The length of the total forecast for which out of sample data from the dataset will be used for testing.
`n.start`	Instead of forecast.length, this determines the starting point in the dataset from which to initialize the rolling forecast.
`refit.every`	Determines every how many periods the model is re-estimated.
`refit.window`	Whether the refit is done on an expanding window including all the previous data or a moving window where all previous data is used for the first estimation and then moved by a length equal to refit.every (unless the window.size option is used instead).
`window.size`	If not NULL, determines the size of the moving window in the rolling estimation, which also determines the first point used.
`solver`	The solver to use.
`fit.control`	Control parameters parameters passed to the fitting function.
`solver.control`	Control parameters passed to the solver.
`cluster`	A cluster object created by calling `makeCluster` from the parallel package. If it is not NULL, then this will be used for parallel estimation of the refits (remember to stop the cluster on completion).
`save.fit`	Whether to save the fitted objects of class `DCCfit` during the estimation of each (“refit.every”). If true, the directory to save must be provided. The function will not save this by default for reasons of memory management, but can save it as an “.rda” file in the user's chosen directory for further analysis.
`save.wdir`	If “save.fit” is true, the directory in which to save the `DCCfit` objects (1 for each “refit.every”).
`realizedVol`	Required xts matrix for the realGARCH model.
`clusterOnAssets`	If a cluster object is provided, use parallel resources on the univariate estimation (TRUE) else on the rolling windows (FALSE).
`...`	.