Abstract & Overview
Atoms and molecules are important conceptual entities we invented to understand the physical world around us. The key to their usefulness lies in the organization of nuclear and electronic degrees of freedom into a single dynamical variable whose time evolution we can better imagine. The use of such effective variables in place of the true microscopic variables is possible because of the separation between nuclear/electronic and atomic/molecular time scales. Where separation of time scales occurs, identification of analogous objects in financial markets can help advance our understanding of their dynamics. To detect separated time scales and identify their associated effective degrees of freedom in financial markets, we devised a two-stage statistical clustering scheme to analyze the price movements of stocks in several equity markets. Through this two-time-scale clustering analysis, we discovered a hierarchy of levels of self-organization in real financial markets. We call these statistically robust self-organized dynamical structures financial atoms, financial molecules, and financial supermolecules. In general, the detailed compositions of these dynamical structures cannot be deduced based on raw financial intuition alone, and must be explained in terms of the underlying portfolios, and investment strategies of market players. More interestingly, we find that major market events such as the Chinese Correction and the Subprime Crisis leave many tell-tale signs within the correlational structures of financial molecules.