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The underlying coherent behavior in intraday dynamic market equilibrium

Leilei Shi (School of Management, International Institute of Finance, University of Science and Technology of China (USTC), Hefei, P. R. China) (Beijing Fuwaidajie Office, Haitong Securities Co Ltd, Xicheng District, Beijing, P. R. China)
Xinshuai Guo (School of Management, International Institute of Finance, University of Science and Technology of China (USTC), Hefei, P. R. China)
Andrea Fenu (Boston University, Boston, Massachusetts, USA) (University of Cagliari, Cagliari, Italy)
Bing-Hong Wang (Department of Modern Physics, University of Science and Technology of China (USTC), Hefei, P. R. China)

China Finance Review International

ISSN: 2044-1398

Article publication date: 9 January 2023




This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.


The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.


The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

Research limitations/implications

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

Practical implications

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Social implications

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.


It uncovers subjects' intelligent interactively trading behaviors.



The authors appreciate the opportunity provided by Wenfeng Wu, Managing Editor-in-Chief for China Finance Review International (CFRI) and anonymous reviews' reports from CFRI, International Review of Economics and Finance, Review of Asset Pricing Studies, and Review of Finance. The authors gratefully acknowledge comments by and discussions with Hui-Xia Lu (CFRI), Yancheng Qiu, Justin Mohr, Xinran Zhang, Xiao Li, Huaiyu Wang, Qiubin Huang, Ijaz Younis, Shen Lin, Zhenxi Chen, Zhifang Su, Tao Bing, Shouyu Yao and participants from 2022 China National Conference on Game Theory and Experimental Economics (Shanghai), 2022 The Chinese Economists Society Annual Conference (Guiyang), Economics of Financial Technology Conference (Edinburgh Business School, UK 2022), 2022 China Fin-Tech Research Conference (Tianjin, China), Future Finance Conference Nanchang 2021 (Nanchang, China), IFABS 2021 Oxford Conference (Oxford, UK), 2021 AEA Annual Meetings (Chicago, USA), the 19th China Economics Annual Conference (Tianjin, 2019), 3rd International Workshop on Financial Market and Nonlinear Dynamics (2017, Paris, France), 2017 China Finance Review International Conference (Shanghai, China). Shi thanks technical assistance from Huaiyu Wang, and Wang thanks the support from the National Natural Science Foundation of China (Grant No: 71874172). This work is supported by the National Natural Science Foundation of China (Grant No: 71874172).


Shi, L., Guo, X., Fenu, A. and Wang, B.-H. (2023), "The underlying coherent behavior in intraday dynamic market equilibrium", China Finance Review International, Vol. ahead-of-print No. ahead-of-print.



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