Mastering Python for Finance - Second Edition

Forecasting and predicting a time series

In the previous section, we identified non-stationarity in time series data and discussed techniques for making time series data stationary. With stationary data, we can proceed to perform statistical modeling such as prediction and forecasting. Prediction involves generating best estimates of in-sample data. Forecasting involves generating best estimates of out-of-sample data. Predicting future values is based on previously observed values. One such commonly used method is the Autoregressive Integrated Moving Average.