TypeError                                 Traceback (most recent call last)
<ipython-input-12-22a2564d592f> in <module>
     16 
     17 # Forecast 2020
---> 18 dgfor = dgf.forecast('2020-01-01', horizon=1)
     19 

~\Desktop\education\test\varfxi\modules\distGARCH.py in forecast(self, start_date, horizon, fmethod, sample_size)
    328     def forecast(self, start_date, horizon=1, fmethod='analytic',
    329                  sample_size=10000):
--> 330         return(DistGARCHForecast(self, start_date, horizon, fmethod,
    331                                  sample_size))
    332 

~\Desktop\education\test\varfxi\modules\distGARCH.py in __init__(self, DistGARCHFit, start_date, horizon, fmethod, sample_size)
    672 
    673         # Run the forecasts from the arch package
--> 674         self.forecasts = self.res.forecast(horizon=self.horizon, 
    675                                            start=self.start_date,
    676                                            method=self.fmethod)

c:\users\oleg\appdata\local\programs\python\python38\lib\site-packages\arch\univariate\base.py in forecast(self, params, horizon, start, align, method, simulations, rng, random_state, reindex, x)
   1504         if not isinstance(horizon, (int, np.integer)) or horizon < 1:
   1505             raise ValueError("horizon must be an integer >= 1.")
-> 1506         return self.model.forecast(
   1507             params,
   1508             horizon,

c:\users\oleg\appdata\local\programs\python\python38\lib\site-packages\arch\univariate\mean.py in forecast(self, params, horizon, start, align, method, simulations, rng, random_state, reindex, x)
    946         constant = arp[0] if self.constant else 0.0
    947         dynp = arp[int(self.constant) :]
--> 948         expected_x = self._reformat_forecast_x(x, horizon, start_index)
    949         mean_fcast = _ar_forecast(
    950             self._y, horizon, start_index, constant, dynp, expected_x, exog_p

c:\users\oleg\appdata\local\programs\python\python38\lib\site-packages\arch\univariate\mean.py in _reformat_forecast_x(self, x, horizon, start)
    799                 return np.empty(0)
    800             else:
--> 801                 raise TypeError(
    802                     "x is None but the model contains exogenous variables. You must "
    803                     "provide expected values to use for the exogenous variables to "

TypeError: x is None but the model contains exogenous variables. You must provide expected values to use for the exogenous variables to construct forecasts.