When we refer to a time series as stationary, we mean to say that its mean, variance and autocorrelation are all consistent over time. Cointegration, on the other hand, is when we have two time series that are non-stationary, but a linear combination of them results in a stationary time series. So, why is the concept of stationarity important? Well, a large purpose of time series modelling is to be able to predict future values from current data.

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