DCC GARCH implementation

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Tesero on 13 Jan 2012
Answered: RP on 13 Jan 2018
Hello, here's my problem.
I have a matrix with 3194 observations for 52 stock series [3194,52]. I need to calculate the conditional correlation between all the series... I tried to use the DCC model (function dcc_mvgarch of the UCSD GARCH package) as shown in my notes:
[p, lik, h]=dcc_mvgarch(LRDATASET,1,1,1,1);
Of course the notes were for a different dataset, and I knew I could expect some kind of error. I was hoping to understand the problem from the error, however I get a series of long warning message (always the same):
Warning: Matrix is singular, close to singular or badly scaled. Results may be inaccurate. RCOND = NaN. > In dcc_mvgarch_full_likelihood at 79 In dcc_mvgarch at 114
At the end I get a message error:
??? Error using ==> mpower Input to EIG must not contain NaN or Inf.
Error in ==> dcc_mvgarch at 122 stdresid(i,:)=data(i,:)*Ht(:,:,i)^(-0.5);
The first errors is really bothering me, since in LRDATASET there are no value inf or nan...
I have serious problems to understand the entire formula, so probably I'm doing something of very stupid, like mixing apple with orange. Any help would very much appreciated.
Thank you very much!
Angelos Pazaitis
Angelos Pazaitis on 15 Nov 2016
Edited: Angelos Pazaitis on 15 Nov 2016
what do you mean by "Step 1) Estimate Return Series" exactly?
Compute the returns from the price series? Like the simple returns or log-returns?

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Answers (1)

RP on 13 Jan 2018
I am using matlab 2017 version. I have 1 query that is MFE-toolbox additionally installed in matlab 2017 version?
Please suggest.


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