Lags analysis

The goal of lags analysis is to identify and quantify the relationship between a series and its lags. This relationship is typically measured by calculating the correlation between the two and with the use of data visualization tools. The level of correlation between a series and its lags is derived from the series characteristics. For instance, you should expect the series to have a strong correlation with its seasonal lags (for example, lags 12, 24, and 36 when the series frequency is monthly) when the series has strong seasonal patterns. This should make sense, as the direction of the series is impacted by its seasonal pattern. Another example is the price of a stock over time, which, in this case, should be correlated with the most recent lags. In the following examples, we will use the USgas, EURO_Brent, and USVSales series, each with different characteristics...