Default Portfolio Problem
The default portfolio optimization problem has a risk and return
proxy associated with a given problem, and a portfolio set that specifies
portfolio weights to be nonnegative and to sum to 1
.
The lower bound combined with the budget constraint is sufficient
to ensure that the portfolio set is nonempty, closed, and bounded.
The default portfolio optimization problem characterizes a long-only
investor who is fully invested in a collection of assets.
For mean-variance portfolio optimization, it is sufficient to set up the default problem. After setting up the problem, data in the form of a mean and covariance of asset returns are then used to solve portfolio optimization problems.
For conditional value-at-risk portfolio optimization, the default problem requires the additional specification of a probability level that must be set explicitly. Generally, “typical” values for this level are 0.90 or 0.95. After setting up the problem, data in the form of scenarios of asset returns are then used to solve portfolio optimization problems.
For MAD portfolio optimization, it is sufficient to set up the default problem. After setting up the problem, data in the form of scenarios of asset returns are then used to solve portfolio optimization problems.
See Also
Portfolio
| PortfolioCVaR
| PortfolioMAD
Related Examples
- Creating the Portfolio Object
- Working with Portfolio Constraints Using Defaults
- Asset Allocation Case Study
- Portfolio Optimization Examples Using Financial Toolbox
- Portfolio Optimization with Semicontinuous and Cardinality Constraints
- Black-Litterman Portfolio Optimization Using Financial Toolbox
- Portfolio Optimization Using Factor Models
- Portfolio Optimization Using Social Performance Measure
- Diversify Portfolios Using Custom Objective
More About
Portfolio
- Supported Constraints for Portfolio Optimization Using Portfolio Objects
- Portfolio Object Workflow