I am struggling to compute my out-of-sample results for R^2os. This is out-of-sample R^2 as done by Campbell and Thompson (2008), as
1 - sum[(r_t - rhat_t)^2] / sum[(r_t - rbar_t)^2] , where rhat is the fitted value from a predictive regression, rbar is the historical average return.

I have tried this code so far but my results do not match those I am trying to replicate.

My initial period is t<205 to forecast from t= 205 to 504.

regress r1 DPs if t<205
predict fittedDPs
gen feDPs = r1 - fittedDPs if t>=205
gen sfeDPs = feDPs^2
gen sumsfeDPs = sum(sfeDPs)

regress r1 if t<205
predict historic
gen fehist = r1 - historic if t>=205
gen sfehist = fehist^2
gen sumsfehist = sum(sfehist)


I then compare the last values at t=504 of the summed variables as the R^2os states as = 1 - sum[(r_t - rhat_t)^2] / sum[(r_t - rbar_t)^2]
so 1 - sumsfeDPs/sumsfehist, at t=504.

However I am not producing the correct results.

Any help would be greatly appreciated.