Berlin 2008 – scientific programme

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AKSOE: Arbeitskreis Physik sozio-ökonomischer Systeme

AKSOE 3: Financial Markets and Risk Management I

AKSOE 3.1: Talk

Monday, February 25, 2008, 10:15–10:45, EW 203

Modeling and predicting financial data — •Joachim Peinke and Andreas P. Nawroth — Institute of Physics, Carl von Ossietzky University of Oldenburg, D 26111 Oldenburg, Germany

It is shown how based on given financial data stochastic equations can be extracted. Based on these equation a new method is proposed which allows a reconstruction of time series based on higher order multiscale statistics given by the hierarchical process. This method is able to model the time series not only on a specific scale but for a range of scales. It is possible to generate complete new time series, or to model the next steps for a given sequence of data. The method itself is based on the joint probability density which can be extracted directly from given data, thus no estimation of parameters is necessary. The results of this approach are shown for financial data. The unconditional and conditional probability densities of the original and reconstructed time series are compared and the ability to reproduce both is demonstrated. Therefore in the case of Markov properties the method proposed here is able to generate artificial time series with correct n-point statistics.