mgarch is an R package for simulating and estimating multivariate GARCH models. Currently, only BEKK, GJR and DCC specifications are implemented.
After you install the package, you can load the library:
> library(mgarch)
Probably, you are interested in the following functions:
mvBEKK.sim: Simulates an MGARCH-BEKK processmvBEKK.est: Estimates an MGARCH-BEKK modelmvBEKK.diag: Provides diagnostics for an estimated MGARCH-BEKK model
You can get help from the embedded documentation by issuing:
> ?mvBEKK.sim
> ?mvBEKK.est
> ?mvBEKK.diag
As an example, you can simulate an MGARCH-BEKK process as follows:
> sim <- mvBEKK.sim(series.count=2, T=1200)
This will give you two vectors of 2500 observations along with many other objects. Checkout the help for further details.
Now create a data frame with the given two vectors:
> eps <- data.frame(s1=sim$eps[[1]], s2=sim$eps[[2]])
The first and last few rows of the resulting data frame looks like as follows:
> head(eps)
s1 s2
1 -0.7302 -0.9066
2 -1.0601 -0.9100
3 -2.0181 0.8561
4 1.1678 0.9071
5 -0.1927 0.2441
6 0.9193 -0.0993
> tail(eps)
s1 s2
2495 -1.0160 -0.9626
2496 1.5960 -0.5020
2497 -1.6413 1.1664
2498 2.0670 -1.9811
2499 0.6587 0.1838
2500 1.0310 1.2592
When you need to supply your own data, make sure that it follows the same convention as above.
Now, we will estimate a model:
> est <- mvBEKK.est(eps)
The estimation may take longer depending on the number of series and the length of series. The result contains quite a lot of information:
> names(est)
[1] "eps" "series.length"
[3] "estimation.time" "total.time"
[5] "order" "estimation"
[7] "aic" "asy.se.coef"
[9] "est.params" "cor"
[11] "sd" "H.estimated"
[13] "eigenvalues" "uncond.cov.matrix"
[15] "residuals"
Check the documentation for details.
You can see a summary by using the mvBEKK.diag command:
> mvBEKK.diag(est)
Number of estimated series : 2
Length of estimated series : 1200
Estimation Time : 3.971
Total Time : 4.788
BEKK order : 1 1
Eigenvalues : 0.9371 0.5384 0.5016 0.3784
aic : 5592
unconditional cov. matrix : 3.821 -0.5761 -0.5761 11.3
var(resid 1 ) : 0.9996
mean(resid 1 ) : 0.0005716
var(resid 2 ) : 0.9922
mean(resid 2 ) : 0.04112
Estimated parameters :
C estimates:
[,1] [,2]
[1,] 1.16 0.2905
[2,] 0.00 0.9404
ARCH estimates:
[,1] [,2]
[1,] -0.5225 0.14426
[2,] 0.3576 -0.09822
GARCH estimates:
[,1] [,2]
[1,] -0.5358 -0.07182
[2,] -0.2370 0.90391
asy.se.coef :
C estimates, standard errors:
[,1] [,2]
[1,] 0.1767 0.7308
[2,] 0.0000 0.2853
ARCH estimates, standard errors:
[,1] [,2]
[1,] 0.03618 0.03759
[2,] 0.03326 0.03972
GARCH estimates, standard errors:
[,1] [,2]
[1,] 0.0519 0.09403
[2,] 0.1336 0.03051
Called from: mvBEKK.diag(est)
Browse[1]>
This command will also produce some helpful plots.
This software is licensed under the GPLv3::
Copyright (C) 2005-2014 Harald Schmidbauer <[email protected]>,
Angi Roesch <[email protected]>,
Vehbi Sinan Tunalioglu <[email protected]>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
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