Abstract
Complexity-entropy causality plane analysis and large deviations spectrums theory are proposed to study time series. The entropy plane analysis depicts the complexity of a system in two-dimensional plane, while large deviations theory shows the spectral structure of time series in the way of multifractal. In this paper, we combine the characteristics of these two popular methods and propose a generalized entropy plane model based on the large deviation theory. The methodology is applied to both synthetic data and financial markets. We discuss the impact of the parameters on the results in detail. Besides, the modified model can distinguish different time series. Meanwhile, we compare our results with the original complexity-entropy causality plane and large deviations spectrums, and the consistency of these results is confirmed. The method can provide abundant dynamical properties of complex systems.
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