August 1, 2007

August 10, 2007 (the beginning)

December 20, 2007

January 15, 2008

May 15, 2008

July 10, 2008

September 15, 2008 (post-Lehman)

October 10, 2008 (biggest DJIA point drop in history)

With a short empirical investigation, Reginald Smith (MIT – Sloan School of Management) have come to some interesting complex networks (nodes in here are financial stocks) over time, since the beginning of the financial crisis in August 10, 2007, till today. His rather simple econophysics study (draft PDF link) somehow demonstrates that the losses in certain markets, in this case the US equity markets, follow a cascade or “epidemic” flow like model along the correlations of various stocks. His networks shows the correlation (similar rise and fall movements) among the stocks in the S&P 500 and NASDAQ-100 using the latest stocks in the index (as of 10/10/2008). The abbreviations are the ticker symbols. Network edges here connect stocks (nodes) based on their correlations. More then 500 tickers were used. After correlations among any two stocks were calculated (J.C. Gower, Biometrika, 1966), a distance metric is computed. Finally these distances are used to create a minimal spanning tree. For the graphics and animations Reginald have used the python-graph module, pydot and Graphviz. Extra details and a F.A.Q. is here as well as some movies. If the stock share price return had a return (minus dividends) greater than or equal to -10% the nodes are green, less than -10% but greater than -25% yellow, and less than or equal to -25% red.

In what relates red nodes over time, I now wonder what would be the probability distribution of vertex connectivity change (is it scale-free?!), the characteristic path length L as well as the clustering coefficient C. It would be quite funny to know.