# Estimating joint distributions using copula package in R

I am trying to estimate the joint distribution of stock returns using the copula package. I have read a couple of papers on copulae, but alas my lack of math knowledge prevents me from understanding beyond the basics if that! I am thinking of estimating the joint distribution using the following steps and have a couple of questions about the process in general:

2. Convert prices to continuous returns
3. Transform returns to marginal uniform distribution.
1. How do I do this??
4. Create the copula object
1. When creating the Copula object using ellipCopula() or archmCopula(), I need to specifiy the type of copula and the parameters. How do I know which copula to use? And how do I obtain the parameters... I thought the point of fitting a copula to the data was to obtain the estimated parameters, so why do I need to specify here? Am I just providing initial estimates of the parameters which are then corrected in the actual fitting?
5. Specifiy the bivariate distribution
1. When specifying the bivariate distribution, I need to specify the margins in mvdc(), since, according to a number of sources, I should convert the data (returns) to uniform distributions, do I specify the margins as 'unif' in the function?
6. Define the data to be fitted
1. I am assuming the will be a matrix with 2 columns in this case, each column being the uniforms
7. Fit the data

As you can see I am very new at this and any help would be greatly appreciated!

• could you please share the s-plus or the R code? I am facing the same problem at the moment... Many thanks in advance!
– user8239
Dec 28, 2011 at 21:46