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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
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