arch.univariate.ConstantVariance.forecast¶
-
ConstantVariance.forecast(parameters: ndarray | Series, resids: ndarray[Any, dtype[float64]], backcast: float | ndarray[Any, dtype[float64]], var_bounds: ndarray[Any, dtype[float64]], start: int | None =
None
, horizon: int =1
, method: 'analytic' | 'simulation' | 'bootstrap' ='analytic'
, simulations: int =1000
, rng: Callable[[int | tuple[int, ...]], ndarray[Any, dtype[float64]]] | None =None
, random_state: RandomState | None =None
) VarianceForecast ¶ Forecast volatility from the model
- Parameters:¶
- parameters: ndarray | Series¶
Parameters required to forecast the volatility model
- resids: ndarray[Any, dtype[float64]]¶
Residuals to use in the recursion
- backcast: float | ndarray[Any, dtype[float64]]¶
Value to use when initializing the recursion
- var_bounds: ndarray[Any, dtype[float64]]¶
Array containing columns of lower and upper bounds
- start: int | None =
None
¶ Index of the first observation to use as the starting point for the forecast. Default is len(resids).
- horizon: int =
1
¶ Forecast horizon. Must be 1 or larger. Forecasts are produced for horizons in [1, horizon].
- method: 'analytic' | 'simulation' | 'bootstrap' =
'analytic'
¶ Method to use when producing the forecast. The default is analytic.
- simulations: int =
1000
¶ Number of simulations to run when computing the forecast using either simulation or bootstrap.
- rng: Callable[[int | tuple[int, ...]], ndarray[Any, dtype[float64]]] | None =
None
¶ Callable random number generator required if method is ‘simulation’. Must take a single shape input and return random samples numbers with that shape.
- random_state: RandomState | None =
None
¶ NumPy RandomState instance to use when method is ‘bootstrap’
- Returns:¶
forecasts – Class containing the variance forecasts, and, if using simulation or bootstrap, the simulated paths.
- Return type:¶
- Raises:¶
If method is not supported
If the method is not known
Notes
The analytic
method
is not supported for all models. Attempting to use this method when not available will raise a ValueError.