topic Re: Forecast the same date in SAS Forecasting and Econometrics

Forecast the same date

Sizzen — Thu, 04 May 2017 11:55:07 GMT

I have data :

date stock

2010 582

2011 685

2012 562

2013 684

2014 721

2015 653

2016 586

.............

It's is not stationarity, so i tried :

proc arima data=stock;
identify var=stock(1);
estimate p=1;
forecast ;
run;

And i get forecast in 2017, 2018 and etc.

But i need a program, which will forecast the same date .

I mean :

date stock forecasting

2010 582 ?

2011 685 ?

2012 562 ?

2013 684 ?

2014 721 ?

2015 653 ?

2016 586 ?

so first quesion: how to do it ?

second, how to do it with moving average ?

Re: Forecast the same date

Ksharp — Thu, 04 May 2017 12:31:39 GMT

Then you should not use PROC ARIMA or other forcast PROC,
Should use some predicted model like :
PROC REG
PROC ADAPTIVE
PROC LOESS
............

Re: Forecast the same date

dw_sas — Thu, 04 May 2017 13:52:16 GMT

If you add the PRINTALL option in the FORECAST statement, then the one-step-ahead predicted values for your historical data will also be displayed by PROC ARIMA. Note that the predicted value for 2010 cannot be computed since differencing is specified, but all other predicted values are displayed by PRINTALL for years 2011-2016, in addition to the multistep forecasts beyond the end of the data. If you want to save the one-step-ahead predicted values and multistep forecasts to a data set, then you can also add the OUT= option to the FORECAST statement.

Following, please find a modified version of your code which reads in the YEAR and STOCK, creates a SAS date variable from YEAR via the MDY function, fits your model and forecasts 4 years into the future. The ID= and INTERVAL= options in the FORECAST statement are used to extrapolate the values of the DATE variable for your LEAD= forecast horizon.

data stock;
  input year stock;
  date=mdy(1,1,year);  /* create SAS date variable from YEAR */
  format date year4.;
  datalines;
2010  582
2011  685
2012  562
2013  684
2014  721
2015  653
2016  586
;

proc arima data=stock;
  identify var=stock(1);
  estimate p=1;
  forecast printall lead=4 id=date interval=year out=stock_fcst;
run;
quit;

proc print data=stock_fcst;
run;

I hope this helps!