Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment

Abstract

This chapter presents a market microstructure model, which investigates the behavior dynamics in financial markets. We are especially interested in examining whether the markets’ behavior is non-stationary, because this implies that strategies from the past cannot be applied to future time periods, unless they have co-evolved with the markets. In order to test this, we employ Genetic Programming, which acts as an inference engine for trading rules, and Self-Organizing Maps, which is used for clustering the above rules into types of trading strategies. The results on four empirical financial markets show that their behavior constantly changes; thus, agents’ trading strategies need to continuously adapt to the changes taking place in the market, in order to remain effective.