ugarchdistribution-methods: function: Univariate GARCH Parameter Distribution via...

In rugarch: Univariate GARCH Models

function: Univariate GARCH Parameter Distribution via Simulation

Description

Method for simulating and estimating the parameter distribution from a variety of univariate GARCH models as well as the simulation based consistency of the estimators given the data size.

Usage

ugarchdistribution(fitORspec, n.sim = 2000, n.start = 1, 
m.sim = 100,  recursive = FALSE, recursive.length = 6000, recursive.window = 1000,
presigma = NA, prereturns = NA, preresiduals = NA, rseed = NA,
custom.dist = list(name = NA, distfit = NA), mexsimdata = NULL, vexsimdata = NULL, 
fit.control = list(), solver = "solnp", solver.control = list(), cluster = NULL, ...)

Arguments

fitORspec	Either a univariate GARCH fit object of class uGARCHfit or alternatively a univariate GARCH specification object of class uGARCHspec with valid parameters supplied via the setfixed<- function in the specification.
n.sim	The simulation horizon.
n.start	The burn-in sample.
m.sim	The number of simulations.
recursive	Whether to perform a recursive simulation on an expanding window.
recursive.length	If recursive is TRUE, this indicates the final length of the simulation horizon, with starting length n.sim.
recursive.window	If recursive is TRUE, this indicates the increment to the expanding window. Together with recursive.length, it determines the total number of separate and increasing length windows which will be simulated and fitted.
presigma	Allows the starting sigma values to be provided by the user.
prereturns	Allows the starting return data to be provided by the user.
preresiduals	Allows the starting residuals to be provided by the user.
rseed	Optional seeding value(s) for the random number generator.
custom.dist	Optional density with fitted object from which to simulate.
mexsimdata	Matrix of simulated external regressor-in-mean data. If the fit object contains external regressors in the mean equation, this must be provided.
vexsimdata	Matrix of simulated external regressor-in-variance data. If the fit object contains external regressors in the variance equation, this must be provided.
solver	One of either “nlminb” or “solnp”.
solver.control	Control arguments list passed to optimizer.
fit.control	Control arguments passed to the fitting routine (as in the ugarchfit method).
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).
...	.

Details

This method facilitates the simulation and evaluation of the uncertainty of GARCH model parameters. The recursive option also allows the evaluation of the simulation based consistency (in terms of sqrt(N) ) of the parameters as the length (n.sim) of the data increases, in the sense of the root mean square error (rmse) of the difference between the simulated and true (hypothesized) parameters.
This is a very expensive function, particularly if using the recursive option, both on memory and cpu resources, performing many re-fits of the simulated data in order to generate the parameter distribution and it is therefore suggested that, if available, the parallel functionality should be used (in a system with ideally many cores and at least 4GB of RAM for the recursion option...).

Value

A uGARCHdistribution object containing details of the GARCH simulated parameters distribution.

Author(s)

Alexios Ghalanos

See Also

For specification ugarchspec, fitting ugarchfit, filtering ugarchfilter, forecasting ugarchforecast, simulation ugarchsim, rolling forecast and estimation ugarchroll, bootstrap forecast ugarchboot.

rugarch documentation built on Sept. 30, 2024, 9:30 a.m.