StandardFactorToWeightFunctions

class sigtech.framework.strategies.equity_factor_basket.StandardFactorToWeightFunctions

Class containing references to standard factor to weight conversion functions.

CAP_WEIGHTED = <sigtech.framework.strategies.equity_factor_basket.CapWeightedFactorToWeight object>

DEFAULT(factor_weights: Optional[dict] = None, z_score: bool = False, proportion: Optional[float] = None, long_only: bool = False, **kwargs) → Series

Default factor to weight function - This creates a linear combination of factors.

If proportion is not passed, stock weights are proportional to the sum of the input factor loadings. If proportion is passed, the top proportion % of stocks are given weights of 1 and the bottom proportion % are given weights of -1. If long_only=True (default False) the negative weights are truncated.

Parameters:

• factors – Factor indexed pd.DataFrame of stock loadings. Stocks as columns.

• factor_weights – Optional dictionary of factor weights. Keys should match factors index.

• z_score – Boolean of whether to normalise stock-factor loadings before combination. This allows different factors to be put onto the same scale. Default is False.

• proportion – Optional, proportion for long/short allocations.

• long_only – If proportion is passed with long_only=True, only the top proportion % are returned with positive values and the negative mirror image is removed. If long_only=False both the positive and negative weights are returned. If proportion is not passed this parameter has no effect.

Returns:

Series of stock weights. Index will be (possibly subset of) columns of factors.

FACTOR_WEIGHTED(factor_weights: Optional[dict] = None, z_score: bool = False, proportion: Optional[float] = None, long_only: bool = False, **kwargs) → Series

Similar to default_factors_to_weight_function but weight the stocks proportionally to their summed factor scores.