Fluctuation patterns in high-frequency financial asset returnsT. Preis1, 2, W. Paul1 and J. J. Schneider1
1 Institute of Physics, Johannes Gutenberg University of Mainz - Staudinger Weg 7, D-55099 Mainz, Germany, EU
2 Artemis Capital Asset Management GmbH - Gartenstr. 14, D-65558 Holzheim, Germany, EU
received 31 January 2008; accepted in final form 30 April 2008; published June 2008
published online 4 June 2008
We introduce a new method for quantifying pattern-based complex short-time correlations of a time series. Our correlation measure is 1 for a perfectly correlated and 0 for a random walk time series. When we apply this method to high-frequency time series data of the German DAX future, we find clear correlations on short time scales. In order to subtract trivial autocorrelation parts from the pattern conformity, we introduce a simple model for reproducing the antipersistent regime and use alternatively level 1 quotes. When we remove the pattern conformity of this stochastic process from the original data, remaining pattern-based correlations can be observed.
89.65.Gh - Economics; econophysics, financial markets, business and management.
05.10.Ln - Monte Carlo methods.
02.50.Ey - Stochastic processes.
© EPLA 2008