Rolling Correlation Matrixes

Hi,

I am fairly new to R and I was hoping some of the great geniuses could help
me with my problem. Basically, I have 5 time series of daily data. Let's
say:

####
x1=rnorm(200, 0,1)
x2=rnorm(200, 10, 2)
x3=rnorm(200, 1,5)
x4=rnorm(200, 2,1)
x5=rnorm(200, 9,2)
x=cbind(x1,x2,x3,x4,x5)
rt=zoo(x, as.Date("2004-01-01") + 0:199)

and I want to calculate weekly rolling matrices (pairwise) correlations (not
average pairwise correlations). And I am looking to output the very last
(window) correlation a.k.a. the last period correlation matrix. So I did
this:

pw <- rollapply(rt, width = 5, FUN = function(x)
y <- cor(x), by.column = FALSE, align='right')
p=tail(pw,1)

I get really messy output. Something like this:

2004-07-18 1 0.5276424 -0.05103385

2004-07-18 -0.0783848 0.1752491 0.5276424 1

2004-07-18 -0.4639914 0.4708166 0.1443911

2004-07-18 -0.05103385 -0.4639914 1

2004-07-18 -0.8756658 0.3756958 -0.0783848

2004-07-18 0.4708166 -0.8756658 1

2004-07-18 0.01812455 0.1752491 0.1443911

2004-07-18 0.3756958 0.01812455 1

It's not that messy but it may be more than you expected. Your 200x5 
series is transformed into a 196x25. The 196 is due to "losing" four 
observations with a five observation window. The 25 is due to the 5x5 
correlation matrix that you compute. But it would be sufficient to use 
something like

   mycor <- function(x) {
     rval <- cor(x)
     rval[lower.tri(rval)]
   }

and then to use FUN = mycor in your rollapply() call. Maybe you can also 
improve the labeling somewhat.

Can you help me with that please? In addition, if I want to calculate the
current percentile of each pair of this last period with respect to its
rolling correlation distribution how can I do that? I was reading that
rank() may do the job but I am not sure. Thank you. :)

Maybe something like this?

   apply(pw, 2, function(x) mean(x <= tail(x, 1)))

hth,
Z

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Hi Achim, 

Thanks for your prompt reply. Sounds R is a toy for you to play around with. 

 mycor <- function(x) {
     rval <- cor(x)
     rval[lower.tri(rval)]
   }

 I can see from the first code that you are suggesting a function for
calculating the lower triangle of the correlation matrix and the second
seems to apply a columnwise average somehow. I just don't see how it
calculates the empirical percentile to each entry of the last(pw) matrix.
maybe I misunderstand the function?

   apply(pw, 2, function(x) mean(x <= tail(x, 1))) 

Can you suggest me, if there is similar function as for pairs() that can be
customized. Once I calculate the last rolling correlation matrix and the
current percentiles I want to put in the lower half what your "mycor"
calculates and in the upper half the matched percentiles for the current
rolling cor matrix in a graphical way?

If anybody else can help me with it, I would totally appreciate it. :)

Thanks again. Seems that I have to learn this tool long way.

Best wishes, 

T



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