How do I assess whether two time series change together?

Question

In this example, at timepoint 5, both signals move up together. I would like to quantify these similar movements, and ideally disregard the parts where the signals are almost constant.
What correlation or similarity measures would be best here?

Brian Spiering · Accepted Answer

One option is a Granger causality test which a statistical hypothesis test for determining whether one time series is useful in forecasting another. One time series is said to Granger-cause another time series if the lagged values of one times series provide statistically significant information about future values of another time series.

Correct answer by Brian Spiering on September 4, 2021

Hagbard · Answer

This looks like a job for Dynamic Time Warping (DTW), as this algorithm calculates an optimal match between two given sequences. If you would like to implement it in Python (for example), I can recommend DTAIDistance. The documentation of this project is also very helpful if you want to understand this method in detail.

Answered by Hagbard on September 4, 2021

How do I assess whether two time series change together?

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