Working with 'Conditional'
BoundType, MinNumAssets, and
MaxNumAssets Constraints Using PortfolioCVaR Objects
When any one, or any combination of 'Conditional'
BoundType, MinNumAssets, or
MaxNumAssets constraints are active, the portfolio problem is
formulated by adding NumAssets binary variables, where
0 indicates not invested, and 1 is invested.
For example, to explain the 'Conditional'
BoundType and MinNumAssets and
MaxNumAssets constraints, assume that your portfolio has a
universe of 100 assets that you want to invest:
'Conditional'BoundType(also known as semicontinuous constraints), set bysetBounds, is often used in situations where you do not want to invest small values. A standard example is a portfolio optimization problem where many small allocations are not attractive because of transaction costs. Instead, you prefer fewer instruments in the portfolio with larger allocations. This situation can be handled using'Conditional'BoundTypeconstraints for aPortfolioCVaRobject.For example, the weight you invest in each asset is either
0or between[0.01, 0.5]. Generally, a semicontinuous variable x is a continuous variable between bounds [lb,ub] that also can assume the value0, wherelb>0,lb≤ub. Applying this to portfolio optimization requires that very small or large positions should be avoided, that is values that fall in (0,lb) or are more thanub.MinNumAssetsandMaxNumAssets(also known as cardinality constraints), set bysetMinMaxNumAssets, limit the number of assets in aPortfolioCVaRobject. For example, if you have 100 assets in your portfolio and you want the number of assets allocated in the portfolio to be from 40 through 60. UsingMinNumAssetsandMaxNumAssetsyou can limit the number of assets in the optimized portfolio, which allows you to limit transaction and operational costs or to create an index tracking portfolio.
Setting 'Conditional' BoundType Constraints Using the setBounds Function
Use setBounds with a
'conditional'
BoundType to set xi =
0 or 0.02 <= xi <= 0.5 for all i=1,...NumAssets:
p = PortfolioCVaR; p = setBounds(p, 0.02, 0.5,'BoundType', 'Conditional', 'NumAssets', 3)
p =
PortfolioCVaR with properties:
BuyCost: []
SellCost: []
RiskFreeRate: []
ProbabilityLevel: []
Turnover: []
BuyTurnover: []
SellTurnover: []
NumScenarios: []
Name: []
NumAssets: 3
AssetList: []
InitPort: []
AInequality: []
bInequality: []
AEquality: []
bEquality: []
LowerBound: [3×1 double]
UpperBound: [3×1 double]
LowerBudget: []
UpperBudget: []
GroupMatrix: []
LowerGroup: []
UpperGroup: []
GroupA: []
GroupB: []
LowerRatio: []
UpperRatio: []
MinNumAssets: []
MaxNumAssets: []
ConditionalBudgetThreshold: []
ConditionalUpperBudget: []
BoundType: [3×1 categorical]Setting the Limits on the Number of Assets Invested Using the setMinMaxNumAssets Function
You can also set the MinNumAssets and
MaxNumAssets properties to define a limit on the number of
assets invested using setMinMaxNumAssets. For example, by setting
MinNumAssets=MaxNumAssets=2,
only two of the three assets are invested in the
portfolio.
p = PortfolioCVaR; p = setBounds(p, 0.02, 0.5,'BoundType', 'Conditional', 'NumAssets', 3) p = setMinMaxNumAssets(p, 2, 2)
p =
PortfolioCVaR with properties:
BuyCost: []
SellCost: []
RiskFreeRate: []
ProbabilityLevel: []
Turnover: []
BuyTurnover: []
SellTurnover: []
NumScenarios: []
Name: []
NumAssets: 3
AssetList: []
InitPort: []
AInequality: []
bInequality: []
AEquality: []
bEquality: []
LowerBound: [3×1 double]
UpperBound: [3×1 double]
LowerBudget: []
UpperBudget: []
GroupMatrix: []
LowerGroup: []
UpperGroup: []
GroupA: []
GroupB: []
LowerRatio: []
UpperRatio: []
MinNumAssets: 2
MaxNumAssets: 2
ConditionalBudgetThreshold: []
ConditionalUpperBudget: []
BoundType: [3×1 categorical]
See Also
PortfolioCVaR | setBounds | setMinMaxNumAssets | setDefaultConstraints | setBounds | setBudget | setConditionalBudget | setGroups | setGroupRatio | setEquality | setInequality | setTurnover | setOneWayTurnover
Topics
- Creating the PortfolioCVaR Object
- Working with CVaR Portfolio Constraints Using Defaults
- Working with 'Simple' Bound Constraints Using PortfolioCVaR Object
- Troubleshooting for Setting 'Conditional' BoundType, MinNumAssets, and MaxNumAssets Constraints
- Validate the CVaR Portfolio Problem
- Estimate Efficient Portfolios for Entire Frontier for PortfolioCVaR Object
- Estimate Efficient Frontiers for PortfolioCVaR Object
- Asset Returns and Scenarios Using PortfolioCVaR Object
- Hedging Using CVaR Portfolio Optimization
- Compute Maximum Reward-to-Risk Ratio for CVaR Portfolio
- PortfolioCVaR Object
- Portfolio Optimization Theory
- PortfolioCVaR Object Workflow