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Multiscale behavior of financial time series model from Potts dynamic system

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Abstract

A financial agent-based time series model is developed and investigated by the Potts model. Potts model, a generalization of the Ising model to more than two components, is a model of interacting spins on a crystalline lattice which describes the interaction strength among the agents. We present numerical research in conjunction with statistical analysis and correlation analysis in an attempt to study the volatilities of financial time series. The fluctuation behavior of logarithmic returns of the proposed model is investigated by multiscale entropy and time-dependent intrinsic correlation. Furthermore, in order to obtain a robust conclusion, the daily returns of Shanghai Composite Index and Shenzhen Component Index are considered, and the comparisons of return behaviors between the simulation data and the actual data are exhibited.

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Acknowledgments

The authors were supported in part by National Natural Science Foundation of China Grant No. 71271026 and Grant No. 10971010.

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  1. Institute of Financial Mathematics and Financial Engineering, School of Science, Beijing Jiaotong University, Beijing , 100044, People’s Republic of China

    Weijia Hong & Jun Wang

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  1. Weijia Hong
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  2. Jun Wang
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Correspondence to Jun Wang.

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Hong, W., Wang, J. Multiscale behavior of financial time series model from Potts dynamic system. Nonlinear Dyn 78, 1065–1077 (2014). https://doi.org/10.1007/s11071-014-1496-9

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