R: Simulate from a multivariate log-GARCH(1,1) model
mlgarchSim
R Documentation
Simulate from a multivariate log-GARCH(1,1) model
Description
Simulate the y series (typically a collection of financial returns or regression errors) from a log-GARCH model. Optionally, the conditional standard deviation and the standardised error, together with their logarithmic transformations, are also returned.
vector with the values of the intercepts in the log-volatility specification
arch
matrix with the arch coefficients
garch
matrix with the garch coefficients
xreg
a vector (of length n) or matrix (with rows n) with the values of the conditioning variables. The first column enters the first equation, the second enters the second equation, and so on
backcast.values
backcast values for the recursion (chosen automatically if NULL)
check.stability
logical. If TRUE (default), then the system is checked for stability
innovations
Either NULL (default) or a vector or matrix of length n with the standardised errors. If NULL, then the innovations are multivariate N(0,1) with correlations equal to zero
innovations.vcov
numeric matrix, the variance-covariance matrix of the standardised multivariate normal innovations. Only applicable if innovations = NULL
verbose
logical. If FALSE (default), then only the matrix with the y series is returned. If TRUE, then also additional information is returned
Sucarrat, Gronneberg and Escribano (2013), 'Estimation and Inference in Univariate and Multivariate Log-GARCH-X Models When the Conditional Density is Unknown', MPRA Paper 49344: http://mpra.ub.uni-muenchen.de/49344/
See Also
lgarchSim, mlgarch and zoo
Examples
##simulate 1000 observations from a multivariate
##ccc-log-garch(1,1) w/default parameter values:
set.seed(123)
y <- mlgarchSim(1000)
##simulate the same series, but with more output:
set.seed(123)
y <- mlgarchSim(1000, verbose=TRUE)
head(y)
##plot the simulated values:
plot(y)