bayesline.api.equity.OptimizerSettings#
- model OptimizerSettings#
Optimizer settings to build an optimization problem.
Every enabled objective and constraint must have the inputs it requires, e.g. a factor exposure constraint needs a risk model; under-specified combinations are rejected at validation.
Fields# Field
Type
Required
Default
Constraints
No
factory
No
Nonestr|int|FactorRiskModelSettings|NoneNo
NoneNo
NoneYes
min_length=1
Yes
- field constraints: list[FactorExposureConstraint] [Optional]#
Hard restrictions on the feasible set
- field factor_cov_settings: FactorCovarianceSettings | None [Optional]#
Settings for the factor covariance matrix forecasts.
Noneunless an enabled objective or constraint is evaluated against covariance forecasts.
- field factor_model_settings: str | int | FactorRiskModelSettings | None [Optional]#
The factor risk model supplying exposures and risk: either inline settings or a reference (name or id) to saved factor risk model settings.
Nonefor problems that need no risk model, e.g. a mechanical rebalance back inside position limits.
- field idio_vol_settings: IdioVolSettings | None [Optional]#
Settings for the idiosyncratic volatility forecasts.
Noneunless an enabled objective or constraint is evaluated against idiosyncratic volatility forecasts.
- field objectives: list[MinimizeTradeVolumeObjective] [Required]#
Objectives combined into the weighted sum the optimizer minimizes
- Constraints:
min_length =
1
- field portfolio_hierarchy: str | int | PortfolioHierarchySettings [Required]#
The hierarchy of portfolios (with optional per-portfolio benchmarks) to optimize, each optimized independently against the same objectives and constraints: either inline settings or a reference (name or id) to saved settings.