Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) are good models to analyze and forecast volatility in time series. Arauto might use ARCH and GARCH models to:
- Model volatility;
- Use it as a way to reduce errors in ARIMA models. e.g.: by modeling the volatility, we could use it as a variable for ARIMA e deduce the forecasting values;
Autoregressive Conditional Heteroscedasticity (ARCH) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) are good models to analyze and forecast volatility in time series. Arauto might use ARCH and GARCH models to: