simulateBEKK | R Documentation |
Provides a procedure to simulate BEKK processes.
simulateBEKK(series.count, T, order = c(1, 1), params = NULL)
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. |
params |
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.
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
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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