Abstract
In this work the system of agents is applied to establish a model of the nonlinear distributed signal processing. The evolution of the system of the agents – by the prediction time scale diversified trend followers, has been studied for the stochastic time-varying environments represented by the real currency-exchange time series. The time varying population and its statistical characteristics have been analyzed in the non-interacting and interacting cases. The outputs of our analysis are presented in the form of the mean life-times, mean utilities and corresponding distributions. They show that populations are susceptible to the strength and form of inter-agent interaction. We believe that our results will be useful for the development of the robust adaptive prediction systems.
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© 2012 Springer-Verlag Berlin Heidelberg
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Tokár, T., Horváth, D., Hnatič, M. (2012). Multi-agent Based Analysis of Financial Data. In: Adam, G., Buša, J., Hnatič, M. (eds) Mathematical Modeling and Computational Science. MMCP 2011. Lecture Notes in Computer Science, vol 7125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28212-6_39
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DOI: https://doi.org/10.1007/978-3-642-28212-6_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28211-9
Online ISBN: 978-3-642-28212-6
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