gogarchsim-methods {rmgarch}

function: GO-GARCH Simulation

Description

Method for simulation from a fitted GO-GARCH model.

Usage

gogarchsim(object, n.sim = 1, n.start = 0, m.sim = 1,
startMethod = c("unconditional", "sample"), prereturns = NA, preresiduals = NA,
presigma = NA, mexsimdata = NULL, rseed = NULL, cluster = NULL, ...)

Arguments

object

A GO-GARCH fit object of class goGARCHfit or goGARCHfilter.

n.sim

The simulation horizon.

n.start

The burn-in sample.

m.sim

The number of simulations.

startMethod

Starting values for the simulation. Valid methods are “unconditional” for the expected values given the density, and “sample” for the ending values of the actual data from the fit object.

prereturns

Allows the starting return data to be provided by the user.

preresiduals

Allows the starting factor residuals to be provided by the user.

presigma

Allows the starting conditional factor sigma to be provided by the user.

mexsimdata

A list of matrices with the simulated lagged external variables (if any). The list should be of size m.sim and the matrices each have n.sim + n.start rows.

rseed

Optional seeding value(s) for the random number generator.

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 (remember to stop the cluster on completion).

...

.

Value

A goGARCHsim object containing details of the GO-GARCH simulation.

Author(s)

Alexios Galanos