# How to fit a skew normal/t copula to data?

I want to use either the skew normal copula or the skew t copula with a time-varying correlation matrix. But so far I haven't found any way to implement this either in R or Matlab.

Would anyone be able to help, does anyone maybe have a code available from some previous work? Or maybe do you know someone who works with copulas for risk management purposes?

In the literature I see that there are a few definitions available for these distributions (the skew t for example is defined differently in Azzalini & Capitanio (2003), Demarta, S. and A. J. McNeil (2005) or Sahu, Dey & Branco (2003)). Any definition of the skew normal or t you find in the literature is fine with me.

Any help is appreciated!

• Can you check out Azzalini's webpage for resources on fitting skew normal to the data? azzalini.stat.unipd.it/SN/index.html. An extract from the page talks about R package 'sn' which seems relevant:- "Software: 'sn' package The 'sn' package (or library, here the term is used as a synonym) is a suite of functions for handling skew-normal and skew-t distributions, in the univariate and the multivariate case. The available facilities include various standard operations (density function, random number generation, etc), data fitting via MLE, plotting log-likelihood surfaces...." – NaN Jan 12 '17 at 14:56

Have you look at copula package! Maybe you could get ideias from it https://www.jstatsoft.org/article/view/v021i04/v21i04.pdf

http://finzi.psych.upenn.edu/R/library/copula/html/copula-package.html

• I've already looked at it but it doesn't include the implementation I'd like to use, i.e. the skew normal or t copula. Thanks for the reply anyway :) – Kondo Jul 16 '16 at 15:24