Thanks @RobPratt Now it goes through all the initials However, I am not able to get the right solution among these. For example, ticker 99999 must have solution: alpha=0.4, delta=0.5, mu=50, eta_B=eta_S=40. I can not find this in the output dataset When I run my old PROC NLP code, using only 1 set of initials for ticker 99999 (alpha=0.9, delta=0.7, mu=18.5, eta_B=45, eta_S=38.3), it gives me the right solution. So it confirms that the "true" solution lies in one of my initials After examining your PROC OPTMODEL, I think the issue might be: - The PROC NLP uses Newton-Ralphson technique; PROC OPTMODEL uses interior point technique. I searched but I can not find Newton-Ralphson technique or any equivalent in PROC OPTMODEL - eta_B, eta_S, mu are strictly > 0 (rather than >=0). However, when I change this constraint by using var alpha >= 0 <= 1, delta >= 0 <= 1;
var mu, eta_B, eta_S;
con mu>0, eta_B>0, eta_S>0; It gives me error: ERROR: The problem contains strict inequality or predicate constraints that reference non-integer variables. Could you please advise me on this? Thank you very much
... View more