Hello Sven, Thank You. Actually I had a gig user manual downloaded from internet that does not have the section 3.5 on forecasting.
Now, I retrieved the gig.pdf file file you mentioned. Based on the example provided I was able to replicate the example for b-g.gdt dataset but not for my dataset. My dataset consists of 1489 observations of 6 years daily stock index log return series. I want to generate 150 days out of sample forecast. The script I used is : include gig.gfn egarch = gig_setup(Y, 7, const) gig_set_dist(&egarch,1) gig_estimate(&egarch) series h = egarch.h series uhat = egarch.uhat matrix theta = egarch.coeff scalar omega = theta[2] scalar alpha = theta[3] scalar beta = theta[5] dataset addobs 150 scalar latest = $nobs - 1000 smpl latest ; series fore = h[latest] series fore = omega + beta * fore(-1) + alpha * (ok(uhat(-1)) ? uhat(-1)^2 : fore(-1)) But the forecast generated by the above script was in range from -10 to negative values in millions. Please let me know how to correct this and also I want to know how to measure the forecast performance using loss functions like Mean square error, Root mean square error etc. Thank You. Regards, Karthik Sven Schreiber wrote on 2014-09-27 01:10 PM +0530: >> No, I'm referring to the "gig" manual, because you mentioned gig. >> gig.pdf is a separate file, for example click "help" on the gig dialog >> window when you launch gig. >> >> -sven >> Am 27.09.2014 um 07:20 schrieb Karthik Raju: >> Hello Sven, >> >> Thank you for your response. >> >> I think you refer to Chapter 29 - Forecasting in "Gnu Regression, >> Econometrics and Time-series Library" by Allin Cottrell. But I cannot >> replicate to what is explained there. >> >>_______________________________________________ >> Gretl-users mailing list >> Gretl-users(a)lists.wfu.edu >> http://lists.wfu.edu/mailman/listinfo/gretl-users
