Usage
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, ...)Arguments
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 in
window.size
If not NULL, determines the size of the moving window in the rolling estimation,
which also determines the first point used.
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
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.