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qp7.gms : Standard QP Model - conic programming formulation

Illustrates the use of conic formulation for quadratic
programs by implementing rotated quadratic cones.

For the original model in quadratic programming format

   http://www.gams.com/modlib/adddocs/qp1doc.htm

The quadratic component x^T*CoVar(s,t)*x is modeled as:

(|d|-1)*x^T*CoVar(s,t)*x = x^Tdev(s,d)^T*dev(t,d)*x = ||Dx||^2
                         = sum(d, w_i^2) with w = Dx
                        := 2*p*q

which leads to the formulation in this model whose last constraint is
a rotated quadratic cone.

 Optional inputs:
   --numdays    investment period in number of days (default: 31).
                Days: 1-100
   --numstocks  number of stocks invested (default: 51)
                Stocks: 1-170
References:
Small Model of Type: LP    Includes:  qpdata.inc
$TITLE Standard QP Model - conic formulation (QP7,SEQ=271) $ONTEXT Illustrates the use of conic formulation for quadratic programs by implementing rotated quadratic cones. For the original model in quadratic programming format http://www.gams.com/modlib/adddocs/qp1doc.htm The quadratic component x^T*CoVar(s,t)*x is modeled as: (|d|-1)*x^T*CoVar(s,t)*x = x^Tdev(s,d)^T*dev(t,d)*x = ||Dx||^2 = sum(d, w_i^2) with w = Dx := 2*p*q which leads to the formulation in this model whose last constraint is a rotated quadratic cone. Optional inputs: --numdays investment period in number of days (default: 31). Days: 1-100 --numstocks number of stocks invested (default: 51) Stocks: 1-170 Andersen, E, MOSEK Optimization Tools Manual, online at http://www.mosek.com/documentation.html Kalvelagen, E, Model Building with GAMS. forthcoming $OFFTEXT *=== Set default number of days and number of stocks $if not set numdays $set numdays 31 $if not set numstocks $set numstocks 51 $include qpdata.inc set d(days) selected days s(stocks) selected stocks alias(s,t); *=== Select subset of stocks and periods d(days) = ord(days) >1 and ord(days) < %numdays%; s(stocks) = ord(stocks) < %numstocks%; parameter mean(stocks) Mean of daily return dev(stocks,days) Deviations totmean Total mean return; mean(s) = sum(d, return(s,d))/card(d); dev(s,d) = return(s,d) - mean(s); totmean = sum(s, mean(s))/(card(s)); variables z objective variable x(stocks) investments w(days) intermediate variable for rotated cone p intermediate variable for rotated cone q intermediate variable for rotated cone positive variables x, p, q equations obj objective budget retcon return constraint wcone(days) qone conic constraint rcone rotated quadratic cone constraint; obj.. z =e= 2/(card(d)-1)*p; wcone(d).. w(d) =e= sum(s, x(s)*dev(s,d)); * This is really awful: qone.. q =e= 1; rcone.. p + q =c= sum(d, w(d)); budget.. sum(s, x(s)) =E= 1.0; retcon.. sum(s, mean(s)*x(s)) =G= totmean*1.25; model qp7 /all/; * Mosek and Conopt are currently the only cone solvers available *Option lp=mosek; solve qp7 using lp minizing z; Display x.l;