hi: the paired t-test is used when you want to reduce variance ( by
differencing the
same observational unit ) or reduce the amount of confounding. in this
case, I think it's more appropriate to use a regular t-test on two
populations. that will also get rid of the autocorrelation problem. of
course, if the variances of the 2 series differs greatly,
then you have a new problem ( and should use welch t-test).
mark
On Fri, Jul 8, 2011 at 6:23 AM, tonyp <petro...@gmail.com> wrote:
> Hi,
>
> I am trying to test for differences in means between two return (time)
> series. However, the Ljung-Box test is significant due to the long-memory
> structure of the series ie. autocorrelation is present. I tried to
> difference twice which is standard (didn't want to overdifference) and still
> I have, as expected, series correlation.
>
> Is there any function in R or a technique some of you guys can suggest me to
> filter the autocorrelation in order to apply my test?
>
> t.test(ts1, ts2 ,alternative='greater',
> paired=TRUE,var.equal=FALSE, conf.level=0.95)
>
> I would totally appreciate if any of you quant minds outthere has done work
> on that. Thank you in advance.
>
> Best,
> TP
>
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