Analysis of Binary Trading Patterns in Xetra

Abstract

Maurer and Schäfer propose the Shannon entropy as an appropriate one-dimensional measure of behavioral trading patterns in financial markets. The concept is applied to the illustrative example of algorithmic versus non-algorithmic trading and empirical data from the Deutsche Börse electronic cash equity trading system, Xetra. The results reveal pronounced differences between algorithmic and non-algorithmic traders. In particular, trading patterns of algorithmic traders exhibit a medium degree of regularity, while nonalgorithmic trading tends towards either very regular or very irregular trading patterns.