Each frame represents a month of time, each point is a stock ticker, and the positions of the tickers are the first two principal components of the covariance matrix of their volumes over that month (using day-resolution volume data).

I'm calling it a "squaredance plot" because you can see change in correlation over time by how the individual tickers "switch partners".