code: def test_garch_11_forecast(self):
      vol = GARCH(p=1, o=0, q=1)
      params = np.array([10.0, 0.1, 0.85])
      backcast = vol.backcast(self.resid)
      var_bounds = vol.variance_bounds(self.resid)
      forecast = vol.forecast(
          params, self.resid, backcast, var_bounds, horizon=10, start=0
      )
      expected = _simple_direct_gjrgarch_forecaster(
          self.resid, params, 1, 0, 1, backcast, var_bounds, 10
      )
      assert_allclose(forecast.forecasts, expected)
  
      assert forecast.forecast_paths is None
      assert forecast.shocks is None
  
imports: import numpy
  from numpy.random import RandomState
  from numpy.testing import assert_allclose
  import pandas
  import pytest
  from arch.univariate import arch_model
  from arch.univariate.distribution import Normal, StudentsT
  from arch.univariate.mean import ConstantMean
  from arch.univariate.volatility import APARCH, EGARCH, FIGARCH, GARCH, HARCH, BootstrapRng, ConstantVariance, EWMAVariance, FixedVariance, MIDASHyperbolic, RiskMetrics2006
label_desc: Use image node_id 7 for calling the TestVarianceForecasts obj's underlying member method code with example usage: obj.test_garch_11_forecast() without return types