Last Updated on August 21, 2019 A change in the variance or volatility over time can cause problems when modeling time series with classical methods like ARIMA. The ARCH or Autoregressive Conditional Heteroskedasticity method provides a way to model a change in variance in a time series that is time dependent, such as increasing or decreasing … Continue reading How to Model Volatility with ARCH and GARCH for Time Series Forecasting in Python