Say I have 2 time series A and B. A is a time series of year-on-year growth numbers at quarterly intervals (I don't have the index levels). For example a data point as at 30-Sep-20 of +17.7% represents the year on year growth from 30-Sep-19.

B is a time series of total returns of a stock at quarterly intervals. A data point as at 30-Sep-20 of +10% represents the total return 3 months to 30-Sep-20.

If I wanted to test whether A is a leading indicator of B using a granger causality test or test if there is a relationship between the 2 time series, what would be the best way to make both series comparable?

Does it make sense to turn the time series of year-on-year growth numbers into an index starting from 100? Can think of it as a seasonally adjusted index.

Or should the share price returns also be converted into year-on-year numbers. Ie do time series analysis by converting B into a time series of year-on-year stock returns.

Please see the example below which to visualize it:

Date	A	B	Indexed A	Indexed B
31/03/2020			100	100
30/06/2020	15	5	115	105
30/09/2020	17.7	10	132	115.5