Using Off-The-Shelf Constraint Models

Usage

Like cost models, using constraint models is also easy!

You simply pass instantiated models into your desired convex optimization investment strategy:

from investos.portfolio.strategy import SPO

strategy = SPO(
    actual_returns = actual_returns,
    ...,
    constraints=[
        ConstraintModelA(*args, **kwargs),
        ConstraintModelB(*args, **kwargs)
    ],
)

and that's it!

Optional Arguments

All constraint models take the following optional arguments:

• exclude_assets: [str]
• include_assets: [str]
  • Can't be used alongside exclude_assets

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InvestOS provides the following constraint models:

Leverage Constraints

MaxLeverageConstraint

MaxLeverageConstraint enforces a limit on the (absolute) leverage of the portfolio.

E.g. For leverage of 2.0x, a portfolio with 100MM net value (i.e. the portfolio value if it were converted into cash, ignoring liquidation / trading costs) could have 200MM of (combined long and short) exposure.

To instantiate MaxLeverageConstraint you will need to set the following argument:

• limit: float = 1.0

MaxShortLeverageConstraint

MaxShortLeverageConstraint enforces a limit on the short leverage of the portfolio.

To instantiate MaxShortLeverageConstraint you will need to set the following argument:

• limit: float = 1.0

MaxLongLeverageConstraint

MaxLongLeverageConstraint enforces a limit on the long leverage of the portfolio.

To instantiate MaxLongLeverageConstraint you will need to set the following argument:

• limit: float = 1.0

Long Constraints

LongOnlyConstraint

LongOnlyConstraint enforces no short positions.

LongCashConstraint

LongCashConstraint enforces no short cash positions.

To instantiate LongCashConstraint you will need to set the following argument:

• include_assets: [str] = ["cash"]

EqualLongShortConstraint

EqualLongShortConstraint enforces equal long and short exposure.

To instantiate EqualLongShortConstraint you will need to set the following argument:

• exclude_assets: [str] = ["cash"]

Weight Constraints

MaxWeightConstraint

MaxWeightConstraint enforces a limit (as a percentage) on the weight of each asset in your portfolio.

To instantiate MaxWeightConstraint you will need to set the following arguments:

• limit: float = 0.025
• exclude_assets: [str] = ["cash"]

MinWeightConstraint

MinWeightConstraint enforces a limit (as a percentage) on the weight of each asset in your portfolio.

To instantiate MinWeightConstraint you will need to set the following arguments:

• limit: float = -0.025
• exclude_assets: [str] = ["cash"]

A Quick Note

If you aren't using a convex optimization based investment strategy (like SPO), constraint models don't do anything.

Next: Custom Constraint Models

Next, let's explore building our own constraint models: Custom Constraint Models.