bayesline.api.equity.FactorAttributionMeasureSettings#
- pydantic model bayesline.api.equity.FactorAttributionMeasureSettings#
Settings for factor attribution measure.
This class defines settings for a factor attribution measure, which provides factor attribution calculations for portfolio analysis.
Show JSON schema
{ "title": "FactorAttributionMeasureSettings", "description": "Settings for factor attribution measure.\n\nThis class defines settings for a factor attribution measure,\nwhich provides factor attribution calculations for portfolio analysis.", "type": "object", "properties": { "type": { "const": "FactorAttribution", "default": "FactorAttribution", "title": "Type", "type": "string" }, "rescale_bench": { "default": true, "description": "Rescale the benchmark holdings to sum to the sum of the holdings.", "title": "Rescale Bench", "type": "boolean" }, "normalize_holdings": { "default": true, "description": "Make holdings sum to one.", "title": "Normalize Holdings", "type": "boolean" }, "multiperiod_aggregation": { "default": "none", "enum": [ "none", "optimized" ], "title": "Multiperiod Aggregation", "type": "string" }, "return_aggregation_type": { "default": "geometric", "enum": [ "arithmetic", "geometric" ], "title": "Return Aggregation Type", "type": "string" } }, "additionalProperties": false }
- Config:
frozen: bool = True
extra: str = forbid
- Fields:
multiperiod_aggregation (Literal['none', 'optimized'])normalize_holdings (bool)rescale_bench (bool)return_aggregation_type (Literal['arithmetic', 'geometric'])type (Literal['FactorAttribution'])
- field type: Literal['FactorAttribution'] = 'FactorAttribution'#
- field rescale_bench: bool = True#
Rescale the benchmark holdings to sum to the sum of the holdings.
- field normalize_holdings: bool = True#
Make holdings sum to one.
- field multiperiod_aggregation: Literal['none', 'optimized'] = 'none'#
- field return_aggregation_type: Literal['arithmetic', 'geometric'] = 'geometric'#