# arch.univariate.FIGARCH.forecast¶

FIGARCH.forecast(parameters, resids, backcast, var_bounds, start=None, horizon=1, method='analytic', simulations=1000, rng=None, random_state=None)

Forecast volatility from the model

Parameters
• parameters ({ndarray, Series}) – Parameters required to forecast the volatility model

• resids (ndarray) – Residuals to use in the recursion

• backcast (float) – Value to use when initializing the recursion

• var_bounds (ndarray, 2-d) – Array containing columns of lower and upper bounds

• start ({None, int}) – Index of the first observation to use as the starting point for the forecast. Default is len(resids).

• horizon (int) – Forecast horizon. Must be 1 or larger. Forecasts are produced for horizons in [1, horizon].

• method ({'analytic', 'simulation', 'bootstrap'}) – Method to use when producing the forecast. The default is analytic.

• simulations (int) – Number of simulations to run when computing the forecast using either simulation or bootstrap.

• rng (callable) – 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, optional) – 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

VarianceForecast

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.