Thanks Paul, you are right; if the trend is stronger it's revealed by the
adfTest.

As a follow-up question:
Does anyone know if a test exists that would reveal a weaker trend in the
data?

Regards,

-Mark-

2011/1/19 Paul Teetor <[email protected]>

> Mark,
>
> The adfTest with type="nc" works for me. I think your trend time series is
> not "trendy" enough. When I change the assignment statement to this:
>
>     trend=notrend+(row(notrend)*.4)         # Change 0.04 to 0.4
>
> and execute this:
>
>     adfTest(coredata(trend), lag=0, type='nc')@test$p.value
>
> I get a p-value of 0.98.
>
>
> Paul Teetor, Elgin, IL USA
> http://quanttrader.info/public
>
>
> ------------------------------
> *From:* Mark Breman <[email protected]>
> *To:* [email protected]
> *Sent:* Wed, January 19, 2011 4:38:56 AM
> *Subject:* [R-SIG-Finance] Howto test for true stationarity with adfTest()
>
> Hi everyone,
>
> I want to test for true stationarity (not trend-stationarity) in my
> timeseries. I understand that i can't use the adf.test(), because it
> de-trends the series.
> Indeed, i can verify this:
>
> > notrend=xts(rnorm(100), Sys.Date()-100:1)
> > trend=notrend+(row(notrend)*.04)
> > adf.test(coredata(notrend), alternative="stationary", k=0)$p.value
> [1] 0.01
> > adf.test(coredata(trend), alternative="stationary", k=0)$p.value
> [1] 0.01
>
> The p-values are the same so it's not usable for my purpose.
>
> I'm told i can use the adfTest() from package fUnitRoots instead because
> this test does not de-trend the series.
> So i try:
>
> library(fUnitRoots)
>
> > adfTest(coredata(notrend), lag=0, type='c')@test$p.value
> 0.01
> > adfTest(coredata(trend), lag=0, type='c')@test$p.value
> 0.01
>
> Again, the p-values are the same!? Changing the type parameter (to 'ct' or
> 'nc') does not help either (it gives the same p-values).
> What am i doing wrong here?
>
> Thanks,
>
> -Mark-
>
>     [[alternative HTML version deleted]]
>
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