[R] Computing day-over-day log return for a matrix containingmultiple time series

[William Dunlap]

> -----Original Message-----
> From: r-help-bounces at r-project.org 
> [mailto:r-help-bounces at r-project.org] On Behalf Of sayan dasgupta
> Sent: Sunday, June 06, 2010 11:13 PM
> To: anyi.zhu at gmail.com
> Cc: r-help at r-project.org
> Subject: Re: [R] Computing day-over-day log return for a 
> matrix containingmultiple time series
> 
> Hope this helps
> 
> a <- matrix(runif(150),nrow=3,ncol=50)
> p2r <- function(x) 100 * diff(log(x))
>  t(apply(a,1,function(x){p2r(c(x))}))

The following expressions compute the same
thing as that t(apply(...)) does:
  100 * (log(a[,-1]) - log(a[,-ncol(a)]))
or
  100 * log(a[,-1]/a[,-ncol(a)])

The [,-1] (all but the first column) and
[,-ncol(a)] (all but the last column) is
a way to work with lagged data.

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com 

> 
> 
> 
> 
> On Mon, Jun 7, 2010 at 8:41 AM, Anyi Zhu <anyi.zhu at gmail.com> wrote:
> 
> > Hi all,
> >
> >
> >
> > Thanks a lot for anyone's help in advance.
> >
> >
> >
> > I am trying to find a way to compute the day-to-day return 
> (log return)
> > from
> > a n x r matrix containing, n different stocks and price 
> quotes over r days.
> > The time series of prices are already split by using 
> unstack function.
> >
> 
> >
> >
> > For the result, I would like to see a n x (r-1) matrix, 
> where by each entry
> > is the day-over-day return of each stock.
> >
> >
> >
> > I tried to look into the zoo package, however it seems to 
> give only the
> >
> plots but not the actual data.
> >
> take a look at
> vignette("zoo-quickref",package="zoo")
> It gives an exact solution to your problem
> 
> 
> 
> >
> >
> >
> > Would apply function work in this case?
> >
> >
> >
> > Thanks a lot!
> >
> >
> >        [[alternative HTML version deleted]]
> >
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> >
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
>