rugarch (version 1.4-2)

multifit-methods: function: Univariate GARCH and ARFIMA Multiple Fitting

Description

Method for multiple fitting a variety of univariate GARCH and ARFIMA models.

Usage

multifit(multispec, data, out.sample = 0, solver = "solnp", solver.control = list(), 
fit.control = list(stationarity = 1, fixed.se = 0, scale = 0, rec.init = "all"), 
cluster = NULL, ...)

Arguments

multispec

A multiple GARCH or ARFIMA spec object of class '>uGARCHmultispec and '>ARFIMAmultispec.

out.sample

A positive integer indicating the number of periods before the last to keep for out of sample forecasting (see details).

data

A multivariate data object of class xts or coercible to such.

solver

One of either “nlminb” or “solnp”.

solver.control

Control arguments list passed to optimizer.

fit.control

Control arguments passed to the fitting routine. Stationarity (only for the GARCH case) explicitly imposes the variance stationarity constraint during optimization. The fixed.se argument controls whether standard errors should be calculated for those parameters which were fixed (through the fixed.pars argument of the ugarchspec or arfimaspec functions). The scale parameter controls whether the data should be scaled before being submitted to the optimizer, while the rec.init option controls the recursion initialization method and only valid for GARCH models.

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.

...

.

Value

A '>uGARCHmultifit or '>ARFIMAmultifit object containing details of the GARCH or ARFIMA fits.

Examples

# NOT RUN {
data(dji30ret)
spec = ugarchspec()
mspec = multispec( replicate(spec, n = 4) )
fitlist = multifit(multispec = mspec, data = dji30ret[,1:4])
# }