Description

This version better exploits the symmetry of a quadratic form.
Additional information can be found at:

http://www.gams.com/modlib/adddocs/qp2doc.htm

Small Model of Type : NLP

Category : GAMS Model library

Main file : qp2.gms   includes :  qpdata.inc

$title Standard QP Model - Symmetry Exploitations (QP2,SEQ=172)

$onText
This version better exploits the symmetry of a quadratic form.
Additional information can be found at:

http://www.gams.com/modlib/adddocs/qp2doc.htm


Kalvelagen, E, Model Building with GAMS. forthcoming

de Wetering, A V, private communication.

Keywords: nonlinear programming, quadratic programming, symmetry exploitation, finance
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$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) < 31;
s(stocks) = ord(stocks) < 51;

Parameter
   mean(stocks)          'mean of daily return'
   dev(stocks,days)      'deviations'
   covar(stocks,sstocks) 'covariance matrix of returns (upper)'
   totmean               'total mean return';

mean(s)  = sum(d, return(s,d))/card(d);
dev(s,d) = return(s,d) - mean(s);

* calculate covariance
* to save memory and time we only compute the uppertriangular
* part as the covariance matrix is symmetric
covar(upper(s,t)) = 2*sum(d, dev(s,d)*dev(t,d))/(card(d) - 1);
covar(s,s)        = covar(s,s)/2;
totmean           = sum(s, mean(s))/(card(s));

Variable
   z         'objective variable'
   x(stocks) 'investments';

Positive Variable x;

Equation
   obj    'objective'
   budget
   retcon 'return constraint';

obj..    z =e= sum((s,t), x(s)*covar(s,t)*x(t));

budget.. sum(s, x(s)) =e= 1.0;

retcon.. sum(s, mean(s)*x(s)) =g= totmean*1.25;

Model qp2 / all /;

* Some solvers need more memory
qp2.workFactor = 6;

solve qp2 using nlp minimizing z;

display x.l;