Analysis of binary trading patterns in Xetra - Kai-Oliver Maurer; Carsten Schäfer (Goethe University Frankfurt, Center for Financial Studies (CFS), 2010)
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.
urn:nbn:de:hebis:30-78648
Keywords: C40; D0; G14; G15; G20; 330; Financial Markets; Electronic Markets; Algorithmic Trading; Order Entry; Equity Trading; Information Theory; Entropy Measure; Wertpapierhandel; Anlageverhalten; Informationsverbreitung; Entropie; Aktienmarkt; Elektronisches Handelssystem; Schätzung; Deutschland