Negative Kelvin temperatures in stock markets

Abstract

A spin model relating physical to financial variables is presented. This work is the first to introduce the concept of negative absolute temperature into stock market dynamics by establishing a rigorous formal analogy between physical and financial variables. Based on this model, an algorithm evaluating negative temperatures was applied to an analysis of New York Stock Exchange quotations from November 2002 up to the present. We found that the magnitude of negative temperature peaks correlates with subsequent index movement. Moreover, a certain autocorrelation function decays as temperature increases. An effort was directed to the search for patterns similar to known physical processes, since the model hypotheses pointed to the possibility of such a similarity. A number of cases resembling known processes in phenomenological thermodynamics were found, namely, population inversion and the magneto-caloric effect.