Hi Shantanu,

The problem is that the time series is asynchronous. All these tests seem
fine for synchronous series.
Also for the same, stationarity is also not well defined.

Thanks

On Thu, Apr 19, 2012 at 10:18 PM, Shantanu Sharma
<shantanusharma@gmail.com>wrote:

> Hey Gaurav,
>
> Did you look at the vars package:
> http://cran.r-project.org/web/packages/vars/index.html ?
>
> Prof. Etheber had suggested computing vector autoregression on
> variablesand testing for Granger non-causality [vars::causality()
> function]. However, you may need to look at transforming non-stationary
> price time series into a stationary series.
>
> With sincere regards,
> Shantanu
> *
> *
> *--*
> *Shantanu Sharma, Ph. D.*
> Web: www.shantanusharma.com
>
>
>
> On Thu, Apr 19, 2012 at 8:43 AM, Gaurav Raizada <graizada@gmail.com>wrote:
>
>> Hi,
>>
>> I am trying to test lead/lag relationships between exchange data of 2
>> instruments.
>> The hypothesis is that one of the instruments leads the other.
>>
>> I have data for both symbols to the microseconds.
>>
>> <Time to Microseconds> <Symbol> <MidPrice>
>>
>> 2012-04-17 15:00:02.00395 "Symbol1" "100.1"
>> 2012-04-17 15:00:02.00891 "Symbol2" "300.0"
>> 2012-04-17 15:00:02.01941 "Symbol1" "100.3"
>> 2012-04-17 15:00:02.01974 "Symbol1" "100.4"
>> 2012-04-17 15:00:03.01048 "Symbol2" "300.5"
>> 2012-04-17 15:00:03.05090 "Symbol2" "300.6"
>>
>>
>> I have looked at RTAQ package and also tried applying VECM.
>> RTAQ is more on a univariate time series while VECM is not significant on
>> these timescales.
>>
>> Is there any package that can provide an analysis ?
>> --
>> Regards
>> Shoonya
>>
>>        [[alternative HTML version deleted]]
>>
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>>
>
>


-- 
Regards
Gaurav Raizada
iRage Capital
+91-9769379242

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