Mastering Python for Finance - Second Edition

About the Autoregressive Integrated Moving Average

The Autoregressive Integrated Moving Average (ARIMA) is a forecasting model for stationary time series based on linear regression. As its name suggests, it is based on three components:

• Autoregression (AR): A model that uses the dependency between an observation and its lagged values
• Integrated (I): The use of differencing an observation with an observation from a previous time stamp in making the time series stationary
• Moving average (MA): A model that uses the dependency between an observed error term and a combination of previous error terms, e_t

ARIMA models are referenced by the notation ARIMA(p, d, q), which corresponds to the parameters of the three components. Non-seasonal ARIMA ...