simulateBEKK(series.count, T, order = c(1, 1), params = NULL)
Arguments
series.count
The number of series to be simulated.
T
The length of series to be simulated.
order
BEKK(p, q) order. An integer vector of length 2
giving the orders of the model to fit. order[2] refers
to the ARCH order and order[1] to the GARCH order.
params
A vector containing a sequence of parameter
matrices' values.
Details
simulateBEKK simulates an N dimensional BEKK(p,q)
model for the given length, order list, and initial parameter list
where N is also specified by the user.
Value
Simulated series and auxiliary information packaged as a
simulateBEKK class instance. Values are:
length
length of the series simulated
order
order of the BEKK model
params
a vector of the selected parameters
true.params
list of parameters in matrix form
eigenvalues
computed eigenvalues for sum of Kronecker products
uncond.cov.matrix
unconditional covariance matrix of the process
white.noise
white noise series used for simulating the process
eps
a list of simulated series
cor
list of series of conditional correlations
sd
list of series of conditional standard deviations
References
Bauwens L., S. Laurent, J.V.K. Rombouts, Multivariate GARCH models: A survey, April, 2003
Bollerslev T., Modelling the coherence in short-run nominal exchange rate: A multivariate generalized ARCH approach, Review of Economics and Statistics, 498–505, 72, 1990
Engle R.F., Dynamic conditional correlation: A new simple class of multivariate GARCH models, Journal of Business and Economic Statistics, 339–350, 20, 2002
Tse Y.K., A.K.C. Tsui, A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations, Journal of Business and Economic Statistics, 351-362, 20, 2002