bayesline.api.equity.VolForecastMeasureSettings

pydantic model bayesline.api.equity.VolForecastMeasureSettings

Settings for volatility forecast measure.

This class defines settings for a volatility forecast measure, which provides volatility forecasting calculations and metrics.

Show JSON schema

{
   "title": "VolForecastMeasureSettings",
   "description": "Settings for volatility forecast measure.\n\nThis class defines settings for a volatility forecast measure,\nwhich provides volatility forecasting calculations and metrics.",
   "type": "object",
   "properties": {
      "type": {
         "const": "VolForecast",
         "default": "VolForecast",
         "title": "Type",
         "type": "string"
      },
      "window": {
         "default": "6mo",
         "description": "The size of the rolling window",
         "title": "Window",
         "type": "string"
      },
      "metric": {
         "default": "qlike",
         "description": "The metric to use",
         "enum": [
            "qlike",
            "mse",
            "mae",
            "bias"
         ],
         "title": "Metric",
         "type": "string"
      },
      "ddof": {
         "default": 1,
         "description": "The degrees of freedom to use for the stability",
         "title": "Ddof",
         "type": "integer"
      }
   },
   "additionalProperties": false
}

Config:

• frozen: bool = True

• extra: str = forbid

Fields:

• ddof (int)

• metric (Literal['qlike', 'mse', 'mae', 'bias'])

• type (Literal['VolForecast'])

• window (str)

field type: Literal['VolForecast'] = 'VolForecast'

field window: str = '6mo'

The size of the rolling window

field metric: Literal['qlike', 'mse', 'mae', 'bias'] = 'qlike'

The metric to use

field ddof: int = 1

The degrees of freedom to use for the stability

property columns: list[str]

Get the column names for this measure.

Returns

list[str]

The column names for this measure.