[R-SIG-Finance] adf.test.help

[mat]

Arnaud Battistella a écrit :
> Hi,
>
> I am trying to test whether a return series is stationary, but before
> proceeding I wanted to make sure I understand correctly how to use the
> adf.test function and interpret its output... Could you please let me
> know whether I am correct in my interpretations?
>
> ex: I take x such as I know it doesn't have a unit root, and is
> therefore stationary
>
> 1/
>   
>> x <- rnorm(1000)
>> adf.test(x, "stationary", k=0)
>>     
>
> Augmented Dickey-Fuller Test
>
> data: x
> Dickey-Fuller = -31.8629, Lag order = 0, p-value = 0.01
> alternative hypothesis: stationary
>
> Warning message:
> In adf.test(x, "stationary", k = 0) : p-value smaller than printed p-value
>
> If I understand correctly, I am told that the probability of x having
> a unit root and therefore being non-stationary is 0.01, so the test
> tells me that there is a very high probability that x is stationary.
> Then I can conclude that x is mean-reverting. Am I correct?
>
>   
yes
> 2/ I would like to see critical values also, so I tried with ur.df
>
>   
>> summary(ur.df(x, "trend", lag=0))
>>     
>
> <snip>
>
> Value of test-statistic is: -31.8629 338.4156 507.6231
>
> Critical values for test statistics:
> 1pct 5pct 10pct
> tau3 -3.96 -3.41 -3.12
> phi2 6.09 4.68 4.03
> phi3 8.27 6.25 5.34
>
> Here if I understand correctly, as my first critical value is
> significantly less than the 1% critical value I reject the null
> hypothesis that x has a unit root, so x is stationary and then mean
> reverting.
>
>   
yes


> Thanks,
>
> -Arnaud
>
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