[R-SIG-Finance] Copula in R

[alexios]

No, first fit the standardized residuals with the distribution you want
(e.g. the spd), then apply the cdf transform on those residuals(i.e.
pspd(std.resids, fit) ) to get the pseudo-uniform
numbers, then collect into a matrix and fit using the copula.

Once you have fitted, use the random number generator of copula to get a
correlated sample which you then transform back by using the quantile
function (qspd), and then reintroduce them into the univariate garch
fit from stage 1 from which you can now simulate.

HTH.

Alexios

Yana Roth wrote:
> Yes, I filtered the residuals with GARCH. You mean, I should apply
> fit.copula.rank to standardised residuals directly?
> I thought, I should estimate CDFs before....
>  
> Thank you
> 
> --- On *Fri, 1/30/09, alexios /<alexios at 4dscape.com>/* wrote:
> 
>     From: alexios <alexios at 4dscape.com>
>     Subject: Re: [R-SIG-Finance] Copula in R
>     To: yana.roth at yahoo.com
>     Cc: r-sig-finance at stat.math.ethz.ch
>     Date: Friday, January 30, 2009, 3:05 PM
> 
>     The QRMlib function "fit.tcopula.rank" with method="kendall"
>     will accept
>      the uniform data from the cdf transformation.
> 
>     It is more commonplace to first filter the data with a process like
>     garch, and then apply the fit to the standardized residuals.
> 
>     There is also a package on r-forge for the semi-parametric distribution
>     with pareto tail which implements density, distribution, quantile and
>     sampling (http://r-forge.r-project.org/projects/spd/).
> 
>     -Alexios
> 
>     Yana Roth wrote:
>     > Hello,
>     > I try to reproduce copula fitting from Matlab by R. I constructed pieswise
>     distribution: Generalised Pareto at the tails and empirical distribution
>     estimated with Gaussian Kernel. Like this I obtain 15 CDF. However, I dont find
>     my way to convert them to uniforms and fit copula.
>     >  
>     > If you could provide some help, I would be thanjful
>     >  
>     > Thank You
>     > Yana
>     > 
>     > 
>     >       
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>     > 
>     > 
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