自定义投资组合优化

This example shows how to solve risk parity or budgeting problems with constraints using estimateCustomObjectivePortfolio.

This example shows a robust formulation of portfolio optimization with uncertainty in the assets returns.

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.

This example shows how to compute a portfolio that minimizes the tracking error subject to a benchmark portfolio.

This example demonstrates optimizing a portfolio to maximize the information ratio relative to a market benchmark.

Use a Portfolio object to minimize the variance, maximize return, and maximize the average percentage of women on a company's board.

This example shows three techniques of asset diversification in a portfolio using the estimateCustomObjectivePortfolio function with a Portfolio object.

This example shows a method for goal-based wealth management (GBWM).

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.

Characteristics of convexity, concavity, and nonconvexity in portfolio problems.

The three cases for using Portfolio, PortfolioCVaR, PortfolioMAD object are: always use, preferred use, and use Optimization Toolbox.

The default solver for mean-variance portfolio optimization is lcprog.

Tables listing types of MINLP solvers that you can select to find the solution to different portfolio problems.

Resources for troubleshooting portfolio optimization results.