I am writing a paper about contagion effect on financial markets. I have fitted a DCC-GARCH model using dccfit
function from "rmgarch" package in R.
The results and the code are below:
library(rmgarch)
garch.spec<-ugarchspec(mean.model = list(armaOrder=c(0,0)),variance.model = list(garchOrder=c(1,1),model="sGARCH"),distribution.model = "std")
dcc_garch.spec<-dccspec(uspec = multispec(replicate(5,garch.spec)),dccOrder = c(1,1),distribution = "mvnorm",fixed.pars=(c(0,0)))
dcc.model<-dccfit(dcc_garch.spec,dane)
*---------------------------------*
* DCC GARCH Fit *
*---------------------------------*
Distribution : mvnorm
Model : DCC(1,1)
No. Parameters : 37
[VAR GARCH DCC UncQ] : [0+25+2+10]
No. Series : 5
No. Obs. : 2133
Log-Likelihood : 33040.77
Av.Log-Likelihood : 15.49
Optimal Parameters
-----------------------------------
Estimate Std. Error t value Pr(>|t|)
[set].mu -0.000463 0.000236 -1.963445 0.049594
[set].omega 0.000007 0.000010 0.707854 0.479036
[set].alpha1 0.159600 0.039701 4.020008 0.000058
[set].beta1 0.826963 0.060240 13.727911 0.000000
[set].shape 4.298032 1.091724 3.936920 0.000083
[jci].mu 0.000279 0.000186 1.504632 0.132419
[jci].omega 0.000004 0.000016 0.270505 0.786772
[jci].alpha1 0.286313 0.176156 1.625338 0.104091
[jci].beta1 0.712686 0.387752 1.837997 0.066063
[jci].shape 3.374667 1.137219 2.967474 0.003003
[klci].mu 0.000190 0.000163 1.162613 0.244987
[klci].omega 0.000002 0.000013 0.141293 0.887639
[klci].alpha1 0.115581 0.183842 0.628695 0.529549
[klci].beta1 0.883419 0.162858 5.424485 0.000000
[klci].shape 3.992326 1.539661 2.592990 0.009515
[kospi].mu -0.000017 0.000250 -0.067697 0.946027
[kospi].omega 0.000004 0.000005 0.758252 0.448300
[kospi].alpha1 0.118852 0.053993 2.201257 0.027718
[kospi].beta1 0.866701 0.062038 13.970540 0.000000
[kospi].shape 12.481904 3.682076 3.389909 0.000699
[psei].mu 0.000114 0.000199 0.570436 0.568382
[psei].omega 0.000004 0.000004 1.012793 0.311159
[psei].alpha1 0.123092 0.043843 2.807562 0.004992
[psei].beta1 0.871677 0.045946 18.971850 0.000000
[psei].shape 3.948307 0.367651 10.739287 0.000000
[Joint]dcca1 0.011300 0.004190 2.696611 0.007005
[Joint]dccb1 0.972213 0.015088 64.436650 0.000000
Information Criteria
---------------------
Akaike -30.946
Bayes -30.848
Shibata -30.946
Hannan-Quinn -30.910
Elapsed time : 10.4624
I need to test the total significance of parameters.
H0: alpha = beta = 0
H1: alpha =! 0 OR beta =! 0
To do that I need a test statistic:
$$D = -2(\ln Mz – \ln Mp),$$
where $\ln Mp$ is the log-likelihood of the full DCC model (in my case 33040.77) and $\ln Mz$ is the log-likelihood of the reduced DCC model, where alpha and beta equal 0.
I have no idea how I can built reduced DCC model and how to get log-likelihood of it. Do you have any idea how to do that?
Best Answer
You can set fixed parameters in the individual GARCH specifications: