Over the last 12+ months, metrics such as open interest, volume, cumulative volume, deltas, funding rates, etc. have become more popular. I have written about these metrics more extensively in many of our Market Notes as well as in our Markets Framework Series. Using any of these metrics in isolation is likely largely useless (just like many charting/TA indicators that people use).

In order for these metrics to mean something, we need to combine them with other pieces of the puzzle. For example, if we want a more meaningful way of viewing Open Interest data or changes, we may want to combine it with other metrics such as the funding rate, or cumulative volume in order to better ascertain market positioning.

Another way of adding more meaning to something like Open Interest would be comparing it to total transacted volume, and looking for large anomalous data prints. Going one step further, we can compare these things across exchanges to see where the pertinent and significant activity is happening (as seen in this tweet).

This is similar in practice to comparing OI changes to overall price % changes/movements. Knowing how much open interest was added and how much price moved can be provide structural clues.

A simple example: OI increasing by several hundred million, prices move 10%. One week later, OI increases by one billion, prices move 2%. Looking for things like this can often be early signals on various timeframes.