Summary
In this chapter, we've talked about time-series forecasting based on moving averages and autoregression. This topic comprises a large set of models that are very popular in different disciplines, such as econometrics and statistics. These models constitute a mainstay in time-series modeling and provide state-of-the-art forecasts.
We've discussed autoregression and moving averages models, and others that combine these two, including ARMA, ARIMA, VAR, GARCH, and others. In the practice session, we've applied a few models to a dataset of stock ticker prices.
