[R] moving correlation coef ?

[davidr@rhotrading.com]

One common weighting scheme is exponentially weighted, i.e., wt =
L^(0:m) ,
where 0 < L <= 1 .

David L. Reiner

p.s.
If your question is coming from a financial application, you might be
interested in the R-sig-finance list, as well as reading the RiskMetrics
(r)
document "Return to RiskMetrics: The Evolution of a Standard", by Jorge
Mina and Jerry Yi Xiao (available at their site, after a free
registration) where exponentially weighted moving statistics are
discussed at length.

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-
> bounces at stat.math.ethz.ch] On Behalf Of vincent
> Sent: Wednesday, June 29, 2005 11:02 AM
> Cc: r-help at r-project.org
> Subject: Re: [R] moving correlation coef ?
> 
> Thank you for your answers.
> 
> In fact, i believe my question wasn't precise enough.
> I don't want to have a moving/sliding windows over the data
> to correlate (i am already doing that).
> 
> If I have 2 vectors
> X = (x1, x2, x3, ..., xt)
> Y = (y1, y2, x3, ..., yt)
> I want the most recent elements (t) to have a heavier weight
> in the correlation calculus than the older ones (1).
> 
> I think that one simple way to do that is for example to
> compute cor() over XP, YP where
> XP = (x1, x2, x2, x3, x3, x3, ..., xt, xt, xt)
> YP = (y1, y2, y2, y3, y3, y3, ..., yt, yt, yt)
> ie where each element is repeated several times according
> to its freshness.
> It's quite naive ! so if there is a cleaver idea, many thanks.
> 
> Thanks
> Vincent
> 
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