I think I sended it to R-Sig-Finance (r-sig-finance@stat.math.ethz.ch)...

Well... I analyzed the series with the Augmented Dickey Fuller test. I used the procedure from Dolado, Jenkinson and Rivero (1990) to identify the unit root.

Some idea:
Can I model the non-stationary time series with the Augmented Dickey Fuller model and use the intercept and the standard error of the intercept as proxies for the mean of the series? That would be something like a conditional mean "given the series is stationary"...
Can I calculate then robust standard errors with the sandwich-package of that Augmented Dickey Fuller-Intercept? -> vcovHC(ADFmodel, type="HC0") or NeweyWest(ADFmodel)


Andy






--- markleeds@verizon.net <markleeds@verizon.net> schrieb am So, 16.5.2010:

Von: markleeds@verizon.net <markleeds@verizon.net>
Betreff: Re: [R-SIG-Finance] Robust standard error for a time series mean.
An: klein82517@yahoo.de
Datum: Sonntag, 16. Mai, 2010 01:27 Uhr

Hi: i'm not sure what you mean by "non-stationary" ( there are many versions of non-stationarity ) but, if you mean non-constant mean , then I don't think the standard error has any meaning and you need to get stationary first.  But , if it's returns, I'm not sure
how you would do that because I thought returns were generally stationary ( !~zero mean ).

The book by Jan Beran, "statistics for long memory processes"  has some  material on calculating the standard error for the mean of a time series when the values are not independent but it may be similar to the Newey West estimator. I'm not sure abut that but the book may be worth looking at. Hopefully someone will else will say more. Another thing: it may be better to send that question to R-Sig-Finance because you may get more responses. good luck.









hi: I'
On May 15, 2010, Andreas Klein <klein82517@yahoo.de> wrote: Hello.

I have a non-stationary time series of returns and I would like to calculate the standard error for the mean of that series.

When I use the White-estimator or assume constant variance I got the same results. When I use the Newey-West-estimator, which also cares about autocorrelation, the standard errors increase a lot.

1. What is the right estimator?
2. Is the Newey West estimator strongly affected by the non-stationarity?


Does anyone have any literature source or a link to a paper or something like that? 


I hope someone can help me.


Thank you in advance.


Sincerely,
Andy.



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