% Portfolio Optimization:
% Parameter Definitions

N = 10;      % Number of assets in class.

r = 0.15*rand(N,1);      % Expected rates of return.

sigma = .2*rand(N,1);      % Expected standard deviations.

rho = -1+2*rand(N);
D = (eye(N)==1);
rho(D) = 1; 
rho = (rho+rho')/2;      % Correlation coefficients.

Sigma = repmat(sigma,[1,N]);
V = Sigma'.*(rho.*Sigma);      % Covariance matrix.

lambda = 25;      % Risk tolerance.

clear D Sigma