Financial Market Analysis Using a Kinetics Model

Abstract

Over the past several decades physicists have used models and techniques that were developed in the sciences in order to analyze the price and volume behavior of financial markets. These models and techniques include the application of nonextensive thermodynamic statistics, information entropy, and detrended fluctuation analysis. This thesis extends the aforementioned approaches to include the use of chemical kinetics concepts. We create two-state models of stock market trading records - models where the stock is treated as being in either an increasing (I) state or a decreasing (D) state. We then treat the transition from one state to the other using standard reaction kinetic methodologies. We supplement the kinetic analysis with analysis of the autocorrelation function. We apply this approach to both closing prices and to trading volumes. In both the closing price and the volume models, we find that that the processes are not strictly Markovian but instead exhibit some perturbation due to memory effects. The closing price model shows evidence of momentum effects in stock pricing while the volume model captures autocorrelations centered around the quarterly earnings report cycle.