Hi Irfan, Yes R is a good one you can try.

I estimated a modified version of the multivariate CCC-EGARCH in GAUSS. Details are in my paper:

'Price and volatilty spillovers in the case of stock markets located in different time zones'

The estimation of the multivariate DCC-EGARCH is also possible.

Best Regards,

Joanna Olbrys

Thanks Joanna Olbrys,

Can you please send me your paper and if possible send me the codes of CCC-EGARCH model and your data as well

Best Regards 

IRfan

Dear Irfan,

Sorry, but the paper is quite new and it is available online only on the platform for Taylor&Francis Group content:

http://www.tandfonline.com/doi/abs/10.2753/REE1540-496X4902S208#.VNuyLOaG_6g

Best Regards,

Joanna

Neither univariate not multivariate EGARCH has an underlying stochastic process that leads to its derivation, no regularity conditions, no likelihood equation, no Jacobian or Hessian matrices, and hence no asymptotic properties of the QMLE.

In short, EGARCH has no statistical properties.

It might be useful to read the following short papers on EGARCH:

“A one line derivation of EGARCH”, Econometrics, 2(2), 2014, 92-97.

“The correct regularity condition and interpretation of asymmetry in EGARCH”, Economics Letters, 161, 2017, 52-55.

“On the invertibility of EGARCH(p,q)”, Econometric Reviews, 37(8), 2018, 824-849.

As for DCC, the following paper shows it has fatal flaws and should not be used:

“What they did not tell you about algebraic (non-)existence, mathematical (ir-)regularity and (non-)asymptotic properties of the dynamic conditional correlation (DCC) model”, Journal of Risk and Financial Management, 12(2:61), 2019, 1-9.