finance_risk.execution¶
Classes¶
!!! abstract "Usage Documentation" |
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!!! abstract "Usage Documentation" |
Functions¶
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Simple Almgren-Chriss style spread, temporary, and permanent cost estimate. |
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Monotone liquidation trajectory with risk-aversion controlled front-loading. |
Module Contents¶
- class finance_risk.execution.MarketImpactEstimate(/, **data: Any)[source]¶
Bases:
pydantic.BaseModel- !!! abstract “Usage Documentation”
[Models](../concepts/models.md)
A base class for creating Pydantic models.
- __class_vars__¶
The names of the class variables defined on the model.
- __private_attributes__¶
Metadata about the private attributes of the model.
- __signature__¶
The synthesized __init__ [Signature][inspect.Signature] of the model.
- __pydantic_complete__¶
Whether model building is completed, or if there are still undefined fields.
- __pydantic_core_schema__¶
The core schema of the model.
- __pydantic_custom_init__¶
Whether the model has a custom __init__ function.
- __pydantic_decorators__¶
Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
- __pydantic_generic_metadata__¶
A dictionary containing metadata about generic Pydantic models. The origin and args items map to the [__origin__][genericalias.__origin__] and [__args__][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the parameter item maps to the __parameter__ attribute of generic classes.
- __pydantic_parent_namespace__¶
Parent namespace of the model, used for automatic rebuilding of models.
- __pydantic_post_init__¶
The name of the post-init method for the model, if defined.
- __pydantic_root_model__¶
Whether the model is a [RootModel][pydantic.root_model.RootModel].
- __pydantic_serializer__¶
The pydantic-core SchemaSerializer used to dump instances of the model.
- __pydantic_validator__¶
The pydantic-core SchemaValidator used to validate instances of the model.
- __pydantic_fields__¶
A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
- __pydantic_computed_fields__¶
A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
- __pydantic_extra__¶
A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.
- __pydantic_fields_set__¶
The names of fields explicitly set during instantiation.
- __pydantic_private__¶
Values of private attributes set on the model instance.
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- model_config¶
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- spread_cost: float¶
- temporary_impact: float¶
- permanent_impact: float¶
- total_cost: float¶
- class finance_risk.execution.ExecutionTrajectory(/, **data: Any)[source]¶
Bases:
pydantic.BaseModel- !!! abstract “Usage Documentation”
[Models](../concepts/models.md)
A base class for creating Pydantic models.
- __class_vars__¶
The names of the class variables defined on the model.
- __private_attributes__¶
Metadata about the private attributes of the model.
- __signature__¶
The synthesized __init__ [Signature][inspect.Signature] of the model.
- __pydantic_complete__¶
Whether model building is completed, or if there are still undefined fields.
- __pydantic_core_schema__¶
The core schema of the model.
- __pydantic_custom_init__¶
Whether the model has a custom __init__ function.
- __pydantic_decorators__¶
Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.
- __pydantic_generic_metadata__¶
A dictionary containing metadata about generic Pydantic models. The origin and args items map to the [__origin__][genericalias.__origin__] and [__args__][genericalias.__args__] attributes of [generic aliases][types-genericalias], and the parameter item maps to the __parameter__ attribute of generic classes.
- __pydantic_parent_namespace__¶
Parent namespace of the model, used for automatic rebuilding of models.
- __pydantic_post_init__¶
The name of the post-init method for the model, if defined.
- __pydantic_root_model__¶
Whether the model is a [RootModel][pydantic.root_model.RootModel].
- __pydantic_serializer__¶
The pydantic-core SchemaSerializer used to dump instances of the model.
- __pydantic_validator__¶
The pydantic-core SchemaValidator used to validate instances of the model.
- __pydantic_fields__¶
A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.
- __pydantic_computed_fields__¶
A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.
- __pydantic_extra__¶
A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.
- __pydantic_fields_set__¶
The names of fields explicitly set during instantiation.
- __pydantic_private__¶
Values of private attributes set on the model instance.
Create a new model by parsing and validating input data from keyword arguments.
Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.
self is explicitly positional-only to allow self as a field name.
- model_config¶
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- remaining: numpy.ndarray¶
- trades: numpy.ndarray¶
- finance_risk.execution.vwap_schedule(*, total_quantity: float, volume_curve: Any) numpy.ndarray[source]¶
- finance_risk.execution.almgren_chriss_market_impact(*, quantity: float, volatility: float, daily_volume: float, spread: float = 0.0, temporary_impact: float = 0.1, permanent_impact: float = 0.1) MarketImpactEstimate[source]¶
Simple Almgren-Chriss style spread, temporary, and permanent cost estimate.
- finance_risk.execution.optimal_execution_trajectory(*, total_quantity: float, periods: int, risk_aversion: float = 1.0) ExecutionTrajectory[source]¶
Monotone liquidation trajectory with risk-aversion controlled front-loading.