How to interpret the outputs of DCC Multivariate GARCH
16 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Hello everybody,
I want to run a dcc.m code of the MFE Kevin Sheppard toolbox by giving the following code:
[PARAMETERS,LL,HT,VCV,SCORES]= dcc(DATA,[],1,0,1)
I've got 4 variables (see attached file). By runing the code, everything goes well and I get the estimated parameters in "PARAMETERS". But I'm having difficulties in understanding the outputs "VCV" and "SCORES". The explanations in the code are not sufficient.
I know that a DCC Multivariate GARCH is designed as follows:
DATA=H(t)^1/2*epsilon(t)
H(t)=D(t)*R(t)*D(t) and R(t)= diag[Q(t)^1/2] * Q(t) * diag[Q(t)^1/2]
where R(t) peresents the conditional correlation matrix.
I want finally to plot the dynamic correlations, in other words I have to plot the values of the R(t) matrix. But where is the R(t) in the outputs of this code?
Can anybody help me please?
0 comentarios
Respuestas (3)
Lorenzo Orlando
el 12 de Jun. de 2017
Editada: Lorenzo Orlando
el 21 de Jun. de 2017
VCV is the correlation matrix of parameters, needed to calculate standard errors as sqrt(diag(VCV)).
0 comentarios
Weidong Lin
el 12 de En. de 2018
Actually the Rt is in the output of the function dcc_likelihood(), which is used inside of the dcc(). If you want to display the Rt, just simply add 'Rt' into the output option, i.e., [parameters, ll ,Ht, Rt, VCV, scores, diagnostics]=dcc(...)
Hope it works for you.
1 comentario
Zhitao Zhou
el 28 de Jul. de 2018
Hi, I am doing CCC GARCH model forecasting. Do you know How could I do the one-step-ahead forecasting after I fitting the model with ccc_mmvgarch.m file?
RP
el 13 de En. de 2018
Hi,
I am using matlab 2017 version. I have 1 query that is MFE-toolbox additionally installed in matlab 2017 version?
Please suggest.
2 comentarios
Weidong Lin
el 13 de En. de 2018
Just download the toolbox from Kevin's page. Then open your Matlab and type 'pathtool' in the command window, add the folder and subfolder of the MFE toolbox into the path.
Always check the path every time you see any errors when you use the toolbox.
Ver también
Categorías
Más información sobre Conditional Variance Models en Help Center y File Exchange.
Productos
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!