I am using an arima model to forecast sales of a given product in python, using
statsmodels.tsa.arima.model.ARIMA Sales are daily, with a history of 2019 until today.
The model is adjusting correctly to the past, however when performing the forecast, it returns a flat line, as in the image shown.
Is there a way for forecasting to follow the same trend as in the past?
model = ARIMA(df_log, order=(2,1,1), seasonal_order=(1,1,1,7), freq = 'D') results = model.fit() forecast_arima = np.exp(results.predict(start = 0, end = len(group)+1, dynamic = False)).to_frame(g)