Sorry one last question before I go do work. Is there a computationally efficient approach to doing pairwise correlation of a large amount of time series at discrete intervals (so given a time range T which can be broken into {t, t+e} intervals)?
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So for instance if you have 9000 stock price time series and I wanted to do Pearson's r to measure intraday correlation between two stocks over multiple days and how that evolves over a year
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Replying to @nope_its_lily
Are the intervals overlapping? If so, compute rolling covariances and variances (which is O(data pts) rather than O(data pts * pts per interval) and then divide appropriately to get correlations.
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Replying to @macrocephalopod @nope_its_lily
If they are not overlapping then you need to get more compute!
10:33 AM - 7 Feb 2021
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