What is the process to make data stationery from non-stationary time series?

The two most common ways to make a non-stationary time series stationary are:

• Differencing

• Transforming

Let us look at some details for each of them:

Differencing:

To make your series stationary, you take a difference between the data points. So let us say, your original time series was:

• X1, X2, X3,...........Xn

Your series with a difference of degree 1 becomes:

• (X2 - X1, X3 - X2, X4 - X3,.......Xn - X(n-1)

Once, you make the difference, plot the series and see if there is any improvement in the ACF curve.

If not, you can try a second or even a third-order differencing. Remember, the more you differentiate, the more complicated your analysis is becoming.

Transforming:

If we cannot make a time series stationary, you can try out transforming the variables.

• Log transform is probably the most commonly used transformation if we see the diverging time series.

• However, it is suggested that you use transformation only in case differencing is not working.