bayesline.api.equity.RollingHuberBetaSettings

pydantic model bayesline.api.equity.RollingHuberBetaSettings

Robust Huber rolling beta (univariate per factor, with intercept).

Show JSON schema

{
   "title": "RollingHuberBetaSettings",
   "description": "Robust Huber rolling beta (univariate per factor, with intercept).",
   "type": "object",
   "properties": {
      "method": {
         "const": "huber",
         "default": "huber",
         "title": "Method",
         "type": "string"
      },
      "max_iter": {
         "default": 10,
         "minimum": 1,
         "title": "Max Iter",
         "type": "integer"
      },
      "level": {
         "anyOf": [
            {
               "type": "number"
            },
            {
               "type": "null"
            }
         ],
         "default": null,
         "description": "Student t-test level for shrinking insignificant betas to zero.",
         "title": "Level"
      },
      "epsilon": {
         "default": 1.35,
         "exclusiveMinimum": 0,
         "title": "Epsilon",
         "type": "number"
      },
      "alpha": {
         "default": 0.0001,
         "minimum": 0,
         "title": "Alpha",
         "type": "number"
      }
   }
}

Config:

• frozen: bool = True

Fields:

• alpha (float)

• epsilon (float)

• level (float | None)

• max_iter (int)

• method (Literal['huber'])

field method: Literal['huber'] = 'huber'

field max_iter: int = 10

Constraints:

• ge = 1

field level: float | None = None

Student t-test level for shrinking insignificant betas to zero.

field epsilon: float = 1.35

Constraints:

• gt = 0

field alpha: float = 0.0001

Constraints:

• ge = 0