The following sequence of examples highlights features of the Portfolio object in the Financial Toolbox™. Specifically, the examples use the Portfolio object to show how to set up mean-variance portfolio optimization problems that focus on the two-fund theorem, the impact of transaction costs and turnover constraints, how to obtain portfolios that maximize the Sharpe ratio, and how to set up two popular hedge-fund strategies — dollar-neutral and 130-30 portfolios.

Demonstrates optimizing a portfolio to maximize the information ratio relative to a market benchmark.

Perform backtesting of portfolio strategies using a backtesting framework implemented in MATLAB®. Backtesting is a useful tool to compare how investment strategies perform over historical or simulated market data. This example develops five different investment strategies and then compares their performance after running over a one-year period of historical stock data. The backtesting framework is implemented in two MATLAB® classes: backtestStrategy and backtestEngine.