Principal component analysis can be a powerful tool for detecting similarity between time series, and whether a series ceases to resemble one group of signals and begins to resemble another. I extract three principal components and create a three-dimensional dot plot. My function `msPCABoxNF3[]`

used to label each dot with an `Epilog`

, but with Mathematica 11.3 it became possible to use `Callout[]`

s instead.

`msPCABoxNF3[allChNF3sA, "names" -> "names", ImageSize -> Large]`

We can show the evolution of these relationships over time using Manipulate[] (a snapshot of the tool is shown below)

`msEvolvingPCABoxNF3[allChNF3sA, 20, "spacing" -> 200, "names" -> "tickers", ImageSize -> Large]`

Mathematica can also export videos of these things, as shown below. The following runs a bit quicker than I would like but I’m not going to solve the problem for the sake of this post.