[R-SIG-Finance] Correlation on Tick Data

Tue Jul 22 21:51:23 CEST 2008

I forgot to mention that my former Phd student Scott Payseur wrote the Realized R package that has functions to compute realized variance and covariance using all of the latest techniques.

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*  Eric Zivot                  			               *
*  Professor and Gary Waterman Distinguished Scholar           *
*  Department of Economics                                     *
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On Tue, 22 Jul 2008 markleeds at verizon.net wrote:

>
>  gotcha. so what you are saying is that you need normality for
> hypothesis testing, statistical inference purposes. that's fine and
> thanks again
> for pointing that out.
>
>
>
>
> On Tue, Jul 22, 2008 at  1:21 PM, BOB SAMOHYL wrote:
>
>
> Mark,
>
> To reject the null of no correlation, an hypothsis test based on the
> normal distribution. If normality is not the base assumption your
> working from then p-values, significance tests and conf. intervals dont
> mean much (the value of the coefficient is not reliable) or youll have
> to find a more appropriate distribution for your data. Or transform the
> data to normal. ThereÂ´s a box-cox transformation in R that can resolve
> this. Normality may represent returns data most of the time (maybe not)
> but imagine  that it doesnt in a specific case and this discrepancy
> finds its way into a portfolio. Bob
>
>
> --- Em ter, 22/7/08, markleeds at verizon.net <markleeds at verizon.net>
> escreveu:
> De:  markleeds at verizon.net <markleeds at verizon.net>
> Assunto: Re: [R-SIG-Finance] Correlation on Tick Data
> Para: samohyl at yahoo.com
> Cc: r-sig-finance at stat.math.ethz.ch
> Data: TerÃ§a-feira, 22 de Julho de 2008, 13:43
>
> Thanks for pointing that out. I understand the linearity ( you're
> saying i think that correlation will only pick up linear relation ) but
> why normality ?
>
> On Tue, Jul 22, 2008 at 12:29 PM, BOB SAMOHYL wrote:
>
>> I would go farther than just stationarity and include normality, and
>> linearity in the relation, three suppositions for the correlation
>> coefficient that are rarely examined. Robert Wayne Samohyl, Ph.D.
>> www.qualimetria.ufsc.br fones: 55-48-3721-7001 University
>> 55-48-9608-5056 celular  ï¿½ï¿½
>> --- Em ter, 22/7/08, markleeds at verizon.net <markleeds at verizon.net>
>> escreveu: De: markleeds at verizon.net
>  <markleeds at verizon.net>
>> Assunto: Re: [R-SIG-Finance] Correlation on Tick Data Para: "Matthieu
>> Stigler" <Matthieu.Stigler at gmail.com> Cc:
>> r-sig-finance at stat.math.ethz.ch Data: Terï¿½ï¿½a-feira, 22 de Julho de
>> 2008, 12:38
>> just to elaborate a bit more on what matt said.
>> you need to make sure you time series are stationary before you
>> correlate them.  usually one does this by using a unit root test but,
>> in your case, since you are dealing with currencies, as long as you
>> are dealing with the returns streamsand not the prices themselves,
>> there's really no need to use the unit root test.  returns should be
>> stationary ( in general ).   if you're dealing with prices, then
>> correlations don't make sense because prices aren't ( in general ), or
>> atleast i've never seen prices that were.
>>
>>
>> On
>  Tue, Jul 22, 2008 at 10:14 AM, Matthieu Stigler wrote:
>>
>>> Hello
>>> If ES and YM are time series, you maybe should first test for
>>> auto-correlation of the series. High auto-correlated series can lead
>>> to the phenomen called as spurious regression, and then the
>>> correlation coefficient is "too high".
>>> Hope this helps
>>> Mat
>>> Neil Gupta a ï¿½ï¿½crit :
>>>> Hello R users.
>>>> I was using R to calculate correlation of midquote returns on ES
> and
>>>> YM. ES and YM are highly correlated at close to .97. However when I
>>>> run
> the
>>>> correlation on the MQ returns the correlation is close to 0.
> Should
>>>> I be expecting this or am I doing something wrong? Others have told
>>>> me this
>  should happen, but I do not understand why. If anyone can please
>>>> explain I would really appreciate.
>>>> Many Thanks, Neil
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