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.
- Copyright © 2010 Deutsche Börse AG. All rights reserved. Not to be reproduced or redistributed without permission.
Don’t have access? Register today to begin unrestricted access to our database of research.