Other tranforms

Differencing should be the first transform you try to make a time series stationary. But sometimes it isn't the best option.

A classic way of transforming stock time series is the log-return of the series. This is calculated as follows: $$log\_return ( y_t ) = log \left( \frac{y_t}{y_{t-1}} \right)$$

The Amazon stock time series has already been loaded for you as amazon. You can calculate the log-return of this DataFrame by substituting:

$y_t \rightarrow$ amazon
$y_{t-1} \rightarrow$ amazon.shift(1)
$log() \rightarrow$ np.log()

In this exercise you will compare the log-return transform and the first order difference of the Amazon stock time series to find which is better for making the time series stationary.

Calculate the first difference of the time series amazon to test for stationarity and drop the NaNs.

Exercise

Other tranforms

Instructions 1/2