In the last post we have seen that auto-correlation function breaks when try to analyze random walk time series. We have used differencing technique which has allowed us to circumvent non-stationarity of the random walk series.
In the upcoming post in our ARFIMA series we will use another technique known as partial auto-correlation function (abbr., PACF). This new technique is discussed by ritvikmath in the video below. Watch in order to understand the new tool.