[R-SIG-Finance] Irregular time series and tick data

Jeff Ryan jeff.a.ryan at gmail.com
Sat Apr 16 02:36:38 CEST 2011

Hi Noah. 

Take a look through the list archives, you'll find this is a very common question. 

My (biased) reply is use xts. Highly optimized for tick data, very fast (mostly C) and widely used/depended upon. 

Aside from that, zoo is stellar - though might be tougher with tick data and will also complain about duplicate times. 

fts and timeSeries are quite good as well, though different (fts is actually a wrapper to a C++ library by the same author). timeSeries is part of rmetrics, and is nice, though not really built for big/high freq data. 

ts, its, irts, are really quite old and exist only for particular legacy reasons best I can tell. 

data.table isn't a time series per se, but is quite a cool replacement for data.frames. 

Check the list (as recently as the last few posts even!), and give them all a test - that's the best part of OSS. 


Jeffrey Ryan    |    Founder    |    jeffrey.ryan at lemnica.com


On Apr 15, 2011, at 6:32 PM, Noah Silverman <noah at smartmediacorp.com> wrote:

> Hi,
> I have some tick data that I want to analyze.
> The file given to me has date and time in separate columns.
> There may be multiple transactions with the same date and time stamps
> I tried using the its package to convert them into a nice time series object, but it complains about multiple items with the same index.
> Does anyone have any guidance as to how to best do this in R??
> Below are a few lines of the data
>  symbol as_of_date as_of_time close_price volume
> 1  WCH07 2007-01-01   18:32:01      882.50     20
> 2  WCH07 2007-01-01   18:32:01      882.50      5
> 3  WCH07 2007-01-01   18:32:06      882.75      2
> 4  WCH07 2007-01-01   18:32:06      883.00      1
> 5  WCH07 2007-01-01   18:32:06      883.00      2
> 6  WCH07 2007-01-01   18:32:07      883.00      1
> Thanks!
> -N
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