Time series stationarity Dickey Fuller

[Pelox]

I have a time series with prices.  And i need to check if it stationary or not ?And if not, i need to make it stationary.

So i think, i have to do a Dickey Fuller test.

So i tried this code

proc ARIMA data=prices;
identify var=price stationarity=(adf=(0)) ;
run;

Is it correct ?

[Ksharp]

ACF is decreasing very slowly, therefore price could not be stationarity.

Difference it .

identify var=price(1)

[Pelox]

i see that's the same like:

newprice=price-lag1(price);

It is stationary now, but some prices are negative.

[Ksharp]

Use SAS syntax (forecast statement), and SAS will take care of it.

identify var=price(1);
estimate p=2;
forecast lead=12 

[Ksharp]

If you want constraint price be positive , Try PROC ESM .

Or "Forecasting Log Transformed Data" , check it in PROC ARIMA's documentation.

[Pelox]

I have very small variables. It's gas prices.

So after difference i get for example some prices like -0.0568, -0.2654

I tried this

data new;
set newprices;
ylog = log( newprices );
run;

But  after this i get :

-2.356,-2.0325  etc.

i don't understand

[Ksharp · Accepted solution]

Sorry . mislead you.

newprice=price-lag1(price);

are supposed to get negative value like -0.0568, -0.2654.

if you put model on newprice ,you will get difference of price 's forecast,

therefore suggest you to use PROC ARIMA syntax, not calculated it by hand .