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Custom Portfolio Optimization

Estimate optimal portfolio, specify user-defined objective function, define constraints

Use a Portfolio object with the estimateCustomObjectivePortfolio function to compute the solution to a custom objective problem. The estimateCustomObjectivePortfolio function receives a function handle with the user-defined objective function and returns a vector of portfolio weights. Also, you can use constraints for the Portfolio object, such as linear equality and inequality, bound, budget, group, group ratio, turnover, and tracking error constraints.

Objects

Portfolio Create Portfolio object for mean-variance portfolio optimization and analysis

Functions

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Portfolio Constraints Functions

`setBounds`	Set up bounds for portfolio weights for portfolio
`setGroups`	Set up group constraints for portfolio weights
`setMinMaxNumAssets`	Set cardinality constraints on the number of assets invested in a portfolio
`setGroupRatio`	Set up group ratio constraints for portfolio weights
`setEquality`	Set up linear equality constraints for portfolio weights
`setInequality`	Set up linear inequality constraints for portfolio weights
`setBudget`	Set up budget constraints for portfolio
`setOneWayTurnover`	Set up one-way portfolio turnover constraints
`setTurnover`	Set up maximum portfolio turnover constraint
`setTrackingError`	Set up maximum portfolio tracking error constraint

Custom Objective Function

estimateCustomObjectivePortfolio Estimate optimal portfolio for user-defined objective function for Portfolio object (Since R2022b)

Topics

Risk Parity or Budgeting with Constraints
This example shows how to solve risk parity or budgeting problems with constraints using estimateCustomObjectivePortfolio.
Solve Robust Portfolio Maximum Return Problem with Ellipsoidal Uncertainty
This example shows a robust formulation of portfolio optimization with uncertainty in the assets returns.
Solve Problem for Minimum Tracking Error with Net Return Constraint
This example shows how to use estimateCustomObjectivePortfolio to solve a portfolio problem for minimum tracking error with a net return constraint using a custom objective.
Solve Problem for Minimum Variance Portfolio with Tracking Error Penalty
This example shows how to compute a portfolio that minimizes the tracking error subject to a benchmark portfolio.
Portfolio Optimization Against a Benchmark
This example demonstrates optimizing a portfolio to maximize the information ratio relative to a market benchmark.
Portfolio Optimization Using Social Performance Measure
Use a Portfolio object to minimize the variance, maximize return, and maximize the average percentage of women on a company's board.
Diversify Portfolios Using Custom Objective
This example shows three techniques of asset diversification in a portfolio using the estimateCustomObjectivePortfolio function with a Portfolio object.
Single Period Goal-Based Wealth Management
This example shows a method for goal-based wealth management (GBWM).
Dynamic Portfolio Allocation in Goal-Based Wealth Management for Multiple Time Periods
This example shows a dynamic programming strategy to maximize the probability of obtaining an investor's wealth goal at the end of the investment horizon.
Role of Convexity in Portfolio Problems
Characteristics of convexity, concavity, and nonconvexity in portfolio problems.
When to Use Portfolio Objects Over Optimization Toolbox
The three cases for using Portfolio, PortfolioCVaR, PortfolioMAD object are: always use, preferred use, and use Optimization Toolbox.
Choosing and Controlling the Solver for Mean-Variance Portfolio Optimization
The default solver for mean-variance portfolio optimization is lcprog.
Choose MINLP Solvers for Portfolio Problems
Tables listing types of MINLP solvers that you can select to find the solution to different portfolio problems.
Troubleshooting Portfolio Optimization Results
Resources for troubleshooting portfolio optimization results.