[R-SIG-Finance] [R-sig-finance] Aggregating tick by tick timeSeries [C1]
anass.mouhsine at sgcib.com
anass.mouhsine at sgcib.com
Fri Mar 21 13:53:39 CET 2008
Hi Jeff,
I used the xts package as you advised.
I have a timeSeries object called test
>test[1000:1005,]
V10 V7
2005-04-08 10:55:16 0.3202287 448
2005-04-08 10:55:16 0.3945675 552
2005-04-08 10:55:16 0.0000000 0
2005-04-08 10:55:18 0.0000000 0
2005-04-08 10:55:30 0.0000000 0
2005-04-08 10:55:35 0.0000000 0
the first column stand for the spread*volume and the second one for the
traded volume.
I want to calculate the Volume Weighted Spread hourly.
>test.xts=as.xts(test)
>ep<-endpoints(test.xts,'hours')
>VWAS<-period.apply(test.xts[,1],ep,sum)/period.apply(test.xts[,2],ep,sum)
>VWAS
[1] 0.0006517149 0.0011587963 0.0008660431 0.0007342648 0.0010022736
[6] 0.0009949343 0.0009114276 0.0009170628 0.0008334971
Here I have what I want but need to improve the result:
1) I do not know how to get back to a timeSeries object using reclass() and
have a timeDate object as an index.
2) Is it possible to do the same calculation from a timeSeries object of
two columns (spread,volume) whithout calculating a column spread* volume
and doing two univariate sums.
Could you give some hints on the subject?
regards,
Anass
|------------------------------
| jeff.a.ryan at gmail
| .com
|
| 03/05/2008 16:21
|
To
Anass
MOUHSINE/fr/socgen at socgen
cc
r-sig-finance at stat.math.eth
z.ch
Subject
Re: [R-SIG-Finance]
[R-sig-finance] Aggregating
tick by tick timeSeries
[C1]
Anass,
If you want the mean/sd/etc for each hour ?aggregate from zoo will do
the job very well. To get there from timeSeries you can use the new
'xts' package:
myTS [a timeSeries object]
as.xts(myTS) [ now an 'xts' object - which inherits from zoo]
--or--
as.zoo(myTS)
you can even put it back to a timeSeries with little information loss
if you use xts via 'reclass' (changing the series outside of xts
functions currently isn't perfect - but it is good)
If you want to just aggregate the data into OHLC per time period -
to.period in xts is fast and flexible:
to.period(myTS,'minutes',15)
to.period(myTS,'hours')
to.monthly(myTS)
All these work by converting and reconverting to an 'xts' class
internally - so most any (including timeSeries) class will just work
with the function. In addition it is all compiled code - so it works
well.
One caveat - you'll need to get the most recent xts from
http://r-forge.r-project.org/projects/xts - as there was a minor bug
in the transition of 'to.period' code from quantmod to xts.
Jeff
On Wed, Mar 5, 2008 at 8:21 AM, <anass.mouhsine at sgcib.com> wrote:
>
> Hi guys,
>
>
> I have a timeSeries object like this one
> V10
> 2005-04-08 17:31:41 0.01
> 2005-04-08 17:31:57 0.02
> 2005-04-08 17:32:00 0.02
> 2005-04-08 17:32:57 0.02
> 2005-04-08 17:38:34 0.02
> 2005-04-08 17:38:49 0.01
>
> and I would like to aggregate the timeSeries in hours or minutes in
order
> to apply whatever function on the aggregated data (e.g mean, standard
dev,
> etc...)
> I have seen some aggreagation functions like aggregate in the fSeries
> package but it aggregates only monthly or quaterly.
> I am sure some of you guys were faced to this kind of issue.
>
> Could anyone give me some hints on how to solve my problem?
>
> thanks in advance
>
> Anass
>
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