Usage
dccsim(fitORspec, n.sim = 1000, n.start = 0, m.sim = 1,
startMethod = c("unconditional", "sample"), presigma = NULL, preresiduals = NULL,
prereturns = NULL, preQ = NULL, preZ = NULL, Qbar = NULL, Nbar = NULL,
rseed = NULL, mexsimdata = NULL, vexsimdata = NULL, cluster = NULL,
VAR.fit = NULL, prerealized = NULL, ...)Arguments
fitORspec
A DCCspec or DCCfit
object created by calling either dccspec with fixed parameters
or 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 (for the dispatch method usin
presigma
Allows the starting sigma values to be provided by the user
for the univariate GARCH dynamics.
prereturns
Allows the starting return data to be provided by the
user for the conditional mean simulation.
preresiduals
Allows the starting residuals to be provided by the
user and used in the GARCH dynamics simulation.
preQ
Allows the starting DCC-Q value to be provided by the
user and though unnecessary for the first 1-ahead simulation using the
sample option in the startMethod, this is key to obtaining
a rolling n-ahea
preZ
Allows the starting standardized residuals to be provided by
the user and though unnecessary for the first 1-ahead simulation using
the sample option in the startMethod, this is key to
obtaining a rolling n-ahead for
Qbar
The DCC dynamics unconditional Q matrix, required for the
specification dispatch method.
Nbar
The aDCC dynamics unconditional asymmetry matrix, required for
the specification dispatch method.
rseed
Optional seeding value(s) for the random number generator.
For m.sim>1, it is possible to provide either a single seed to initialize
all values, or one seed per separate simulation (i.e. m.sim seeds). However,
in the latter case this may result i
mexsimdata
A list (equal to the number of asset) of matrices of
simulated external regressor-in-mean data with row length equal to
n.sim + n.start. If the fit object contains external regressors in the mean
equation, this must be provided else will be assum
vexsimdata
A list (equal to the number of asset) of matrices of
simulated external regressor-in-variance data with row length equal to
n.sim + n.start. If the fit object contains external regressors in the
variance equation, this must be provided else will
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).
VAR.fit
An VAR.fit list returned from calling the
varxfilter or varxfit function with postpad
set to constant. This is require prerealized
Allows the starting realized volatility values to be provided
by the user for the univariate GARCH dynamics.