BacktestForecasterConfig

class openstef_beam.backtesting.backtest_forecaster.BacktestForecasterConfig(**data: Any) → None

Bases: BaseConfig

Configuration parameters for backtesting forecasting models.

Defines the operational constraints and requirements for a forecasting model during backtesting simulations. Controls data availability requirements, prediction horizons, and training schedules.

Parameters:

data (Any)

requires_training: bool

predict_sample_interval: timedelta

predict_length: timedelta

predict_min_length: timedelta

predict_context_length: timedelta

predict_context_min_coverage: float

training_context_length: timedelta

training_context_min_coverage: float

model_config: ClassVar[ConfigDict] = {'arbitrary_types_allowed': False, 'extra': 'ignore', 'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].