Hello Sekar,
I understand that you are having errors while implementing the MALAB Code you have written.
Variable ‘z’ is not defined before using in line 47 of ‘PO_BD.m’. Assign it to the desired value and try to run the code again.
In my opinion the following code might also help you :
clc;
tic
% Load data
Data = readtable("INPUT DATA - SEKAR.xlsx", 'ReadRowNames', true);
data = [Data.UNVR Data.ADMR Data.INKP Data.ARGO Data.SMAR Data.TFCO Data.TPIA];
[rData, cData] = size(data);
% Calculate returns
returns = diff(data) ./ data(1:end-1, :);
% Calculate mean returns
meanReturns = mean(returns);
% Calculate covariance matrix
covMatrix = cov(returns);
% Define parameters
a = 0.15 * ones(cData, 1);
b = 0.85 * ones(cData, 1);
l = zeros(cData, 1);
rho = 0.0001;
% Create optimization problems
masterProblem = optimproblem;
subProblem = cell(cData, 1);
% Define decision variables
x = optimvar('x', cData, 'LowerBound', l, 'UpperBound', b);
y = optimvar('y', cData, 'Type', 'integer', 'LowerBound', 0, 'UpperBound', 1);
t = optimvar('t', 'LowerBound', -inf, 'UpperBound', 0);
% Define master problem constraints
masterProblem.Constraints.cons1 = t <= 0;
masterProblem.Constraints.cons2 = a .* y <= x;
masterProblem.Constraints.cons3 = x <= b .* y;
% Solve subproblems and add optimality cuts to master problem
for i = 1:cData
subProblem{i} = optimproblem;
subProblem{i}.Objective = -t;
subProblem{i}.Constraints.cons1 = sum(x) <= 1;
subProblem{i}.Constraints.cons2 = -meanReturns * x <= -rho;
subProblem{i}.Constraints.cons3 = t + norm(chol(covMatrix) * x, 2) <= 0;
subProblem{i}.Constraints.cons4 = a(i) * y(i) <= x(i);
subProblem{i}.Constraints.cons5 = x(i) <= b(i) * y(i);
subObjective = subProblem{i}.Objective;
masterProblem.Constraints.(['cons2_' num2str(i)]) = [x(i); y(i)] >= subObjective;
end
% Solve master problem
[xSol, fval] = solve(masterProblem);
% Calculate portfolio returns
portfolioReturns = returns * xSol.x;
fprintf('Optimal portfolio:\n');
disp(xSol.x);
fprintf('Objective value: %f\n', fval);
toc
Hope it helps.
