Hi Li Guobin,
The MATLAB Financial Toolbox allows for the optimization of a financial portfolio with various constraints. By creating a `Portfolio` object, you can set up expected returns and covariances, enforce a budget constraint where the sum of weights equals one, and prevent short selling by setting bounds between zero and one. Sector-specific constraints, such as limiting the financial sector to a maximum of 10%, can be added using `addGroups`. Additionally, custom linear inequality constraints, like a carbon intensity cap, can be implemented with `setInequality`. The optimal portfolio weights that maximize the Sharpe ratio are then estimated using `estimateMaxSharpeRatio`.
Please have a look at the code below to understand How these functions could be used.
% Create a Portfolio object
p = Portfolio('AssetList', assetNames, 'RiskFreeRate', riskFreeRate);
% Set up the problem with expected returns and covariances
p = setAssetMoments(p, expReturns, expCovariances);
% Add a total budget constraint (sum of weights is 1)
p = setBudget(p, 1, 1);
% Add a no-short selling constraint
p = setBounds(p, 0, 1);
% Define the sector constraint for the financial sector
financialSectorUpperBound = 0.10;
p = addGroups(p, assetIndustries, 0, financialSectorUpperBound);
% Define the carbon intensity constraint using setInequality
carbonIntensityUpperBound = 10000;
Aineq = carbonIntensity';
bineq = carbonIntensityUpperBound;
p = setInequality(p, Aineq, bineq);
% Estimate the portfolio with the maximum Sharpe ratio
maxSharpeRatioWeights = estimateMaxSharpeRatio(p);
To understand more about the portfolio object of MATLAB, kindly refer to the below documentation:
I hope this helps,
Shivam.
