Hi Adrian!

Well spotted! Indeed, the issue comes from the fact that diff.xts keeps the
first NA (as has na.pad=TRUE), while diff.zoo does not (na.pad=FALSE), as
well as na.ts ...

A simple solution seems to be to add then:
diff(y, na.pad=FALSE)
or simply:
y<- y[!is.na(y)]

which seems to lead to correct results in both cases, but I haven't tested
thoroughly...

Best


2013/5/4 Adrian Trapletti <[email protected]>

> Hi Matthieu
>
> For me it looks like adf.test does not correctly handle xts and/or zoo
> inputs due to the subsetting code:
>
> > adf.test(stock2[,1])
>
>         Augmented Dickey-Fuller Test
>
> data:  stock2[, 1]
> Dickey-Fuller = 2.7174, Lag order = 12, p-value = 0.99
> alternative hypothesis: stationary
>
> Warning message:
> In adf.test(stock2[, 1]) : p-value greater than printed p-value
> > adf.test(unclass(stock2[,1]))
>
>         Augmented Dickey-Fuller Test
>
> data:  unclass(stock2[, 1])
> Dickey-Fuller = -2.4579, Lag order = 12, p-value = 0.3845
> alternative hypothesis: stationary
>
> At the time when adf.test was written neither xts nor zoo existed. A quick
> fix is to revise the documentation of adf.test: "x: a numeric vector."
>
> Best regards
> Adrian
>
>  Date: Fri, 3 May 2013 10:25:31 +0200
>> From: Matthieu 
>> Stigler<matthieu.stigler@**gmail.com<[email protected]>
>> >
>> To: "Brian G. Peterson"<[email protected]>**,[email protected],
>>         [email protected]
>> Cc:"r-sig-finance@r-project.**org <[email protected]>"  <
>> [email protected]>
>> Subject: Re: [R-SIG-Finance] Using adf.test to test time series
>>         stationarity of stock price
>> Message-ID:
>>         <CAEYvig+hrDqKGXaetr=H=vy1FYsX**iuB60hSkZoDt6L3L31od8Q@mail.**
>> gmail.com <[email protected]>>
>> Content-Type: text/plain
>>
>> Hi
>>
>> With our stated background in stats, we should have realised that the
>> result you obtain is indeed surprising, since your t-stat is large, but
>> positive! A positive t-stat implies actually that your rho is bigger than
>> 1... So in this case, you will not reject the alternative of stationarity,
>> but that of explosivity, try:
>>
>> adf.test(stock2[,1], alternative="explosive")
>>
>> That said, we should have also realised that results in adf.test seem to
>> be
>> incorrect,  since they do not correspond to the ones in:
>> library(urca)
>> ur.df(stock2[,1], lags=12, type="trend")
>> # or the corresponding "ADF" regression from tsDyn:
>> library(tsDyn)
>> ar_ts <- linear(stock2[,1], m=12, include="both", type="ADF")
>> summary(ar_ts)$coef["phi.1",]
>>
>> Both urca and tsDyn agree closely on the t-stat, at -2.4578550 for urca,
>> and -2.466884912 for tsDyn (differences come from the way of counting
>> degrees of freedom, urca discards the initial values, while tsDyn does
>> not,
>> as in ar()). Looking closer at the code of adf.test(), it looks like the
>> regression is \Delta y_t = const + trend + y_t while I would have expected
>> a y_{t-1}. I guess code should be corrected as:
>>      xt1 <- x[(k-1):(n-1)]
>> instead of
>>      xt1 <- x[k:n]
>>
>> once this done, adf.test does correspond to the others. And now Brian's
>> point that prices are usually non-stationary holds.
>>
>> I am ccing the maintainer of tseries on this.
>>
>> Best
>>
>> Matthieu
>>
>>
>>
>>
>> 2013/4/22 Brian G. Peterson<[email protected]>
>>
>>  On 04/21/2013 06:28 PM, Yitao Zhang wrote:
>>>
>>>  Hey guys,
>>>>
>>>> I'm trying to do a augmented Dickey-Fuller test to test the stationarity
>>>> of a stock price.
>>>>
>>>>  With your stated economics background, one would assume that you'd
>>> realize
>>> that price is almost never stationary.
>>>
>>> Perhaps try on returns?
>>>
>>> --
>>> Brian G. Peterson
>>> http://braverock.com/brian/
>>> Ph: 773-459-4973
>>> IM: bgpbraverock
>>>
>>>
>>> ______________________________****_________________
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>>> >
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> --
> Dr. Adrian Trapletti
> Steinstrasse 9b
> CH-8610 Uster
> Switzerland
>
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>
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