Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/43245
Authors: 
Maurer, Kai-Oliver
Schäfer, Carsten
Year of Publication: 
2010
Series/Report no.: 
CFS Working Paper 2010/12
Abstract: 
This paper proposes the Shannon entropy as an appropriate one-dimensional measure of behavioural trading patterns in financial markets. The concept is applied to the illustrative example of algorithmic vs. non-algorithmic trading and empirical data from Deutsche Börse's 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 non-algorithmic trading tends towards either very regular or very irregular trading patterns.
Subjects: 
Financial Markets
Electronic Markets
Algorithmic Trading
Order Entry
Equity Trading
Information Theory
Entropy Measure
JEL: 
C40
D0
G14
G15
G20
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

Files in This Item:
File
Size
254.3 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.