Provides a procedure to simulate BEKK processes.
simulateBEKK(series.count, T, order = c(1, 1), params = NULL)Simulated series and auxiliary information packaged as a
simulateBEKK class instance. Values are:
length of the series simulated
order of the BEKK model
a vector of the selected parameters
list of parameters in matrix form
computed eigenvalues for sum of Kronecker products
unconditional covariance matrix of the process
white noise series used for simulating the process
a list of simulated series
list of series of conditional correlations
list of series of conditional standard deviations
The number of series to be simulated.
The length of series to be simulated.
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.
A vector containing a sequence of parameter matrices' values.
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.
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., K.F. Kroner, Multivariate simultaneous generalized ARCH, Econometric Theory, 122-150, 1995 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
## Simulate series:
simulated = simulateBEKK(2, 1000, c(1,1))
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