I have been coming across several studies in top journals that use Copula technique in their analysis. I find them to be more technical and difficult to comprehend in full. My limited interactions with a few professors did not bear any positive results as they were also new to this technique.
While I totally understand that it is the objectives and data under study that should drive the methodology used, I am really keen to know as to what these Copula models are and why they are gaining high acceptance in finance literature in the recent past. When does one use them? What are its advantages over all the other GARCH family of models?
I would really appreciate if someone could share the codes (RATS/MatLab/R) for a trivariate Vine-GARCH analysis. Any useful reads to better learn and understand Copula models would also be a great help.
Thanks in advance.
See the links:
- GARCH Models, https://www.mathworks.com/discovery/garch-models.html,
- Dynamic Copula Toolbox 3.0, https://www.mathworks.com/matlabcentral/fileexchange/29303-dynamic-copula-toolbox-3-0
Hi Sir George Varghese ,
I hope they help you.
Article Vine-Copula GARCH Model with Dynamic Conditional Dependence
https://cran.r-project.org/web/packages/copula/vignettes/copula_GARCH.html
Simplified explanation and relevant references at this wiki link:
https://en.wikipedia.org/wiki/Copula_(probability_theory)
I've been learning that creating a copula for a series of data is better than using functions because in the end the copula creates a specific function for your information, that is, in a GARC model your copula will be built according to the distribution you have even assuming the stochastic process that these types of models have; This specificity that gives you the copula by means of the function created is undoubtedly much better than using functions that could simply be "adjusted" to your data. I have a useful bibliography applied to the health economy, maybe it will be helpful.
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