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Research Article
Jie Wang
North China University of Technology
Corresponding Author
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To investigate the price fluctuation mechanism of stock markets, this research aims to develop a novel stochastic financial model based on Potts dynamics and compound Poisson process. The new model considers two aspects: information interaction among traders and the uncertain events outside the system. Then, three different volatility statistics (return series $r_t$, absolute return series $|r_t|$ and volatility duration average intensity $V_t$) are introduced to explore the volatility and complexity properties of the proposed model. The descriptive statistical methods, power-law analysis are studied to validate the practicable of the proposed stochastic financial model. The Permutation Lempel-Ziv complexity of moving average series are referred to different volatility sequences to evaluate the complexity of the simulative data from proposed model and the real data from stock market. Moreover, the complexity analysis of Fractional sample entropy and Multiscale fractional sample entropy method are improved to illustrate the complexity of volatility behaviors in different scales. Compared with the real stock data, the empirical results demonstrate that the new model could reproduce the fluctuation and volatility behaviors of real stock markets to some extent.
Keywords
Stochastic Potts dynamics, volatility statistic, permutation Lempel-Ziv complexity, multi-scale fractional sample entropy, volatility duration average intensity
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This preprint is under consideration at Nonlinear Dynamics. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research Article
Jie Wang
North China University of Technology
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Revision
Version 1
Posted 16 Mar, 2021
No community comments so far
Editor assigned
On 22 Feb, 2021
First submitted
On 22 Feb, 2021
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
To investigate the price fluctuation mechanism of stock markets, this research aims to develop a novel stochastic financial model based on Potts dynamics and compound Poisson process. The new model considers two aspects: information interaction among traders and the uncertain events outside the system. Then, three different volatility statistics (return series $r_t$, absolute return series $|r_t|$ and volatility duration average intensity $V_t$) are introduced to explore the volatility and complexity properties of the proposed model. The descriptive statistical methods, power-law analysis are studied to validate the practicable of the proposed stochastic financial model. The Permutation Lempel-Ziv complexity of moving average series are referred to different volatility sequences to evaluate the complexity of the simulative data from proposed model and the real data from stock market. Moreover, the complexity analysis of Fractional sample entropy and Multiscale fractional sample entropy method are improved to illustrate the complexity of volatility behaviors in different scales. Compared with the real stock data, the empirical results demonstrate that the new model could reproduce the fluctuation and volatility behaviors of real stock markets to some extent.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
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