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

[Patrick Burns]

Actually the 'apply' is not necessary.

The original poster has stocks as rows
rather than the customary columns, so
the following should suffice:

retmat <- diff(log(t(pricemat)))

Questions that are specifically financial
should be sent to r-sig-finance (you need
to subscribe before posting).

On 07/06/2010 07:12, sayan dasgupta wrote:
> 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))}))
>
>
>
>
> 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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>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

-- 
Patrick Burns
pburns at pburns.seanet.com
http://www.burns-stat.com
(home of 'Some hints for the R beginner'
and 'The R Inferno')