Application of Higher-Order Ordinary Differential Equation Model in Financial Investment Stock Price Forecast

Zhang, Liqin
Tian, Xiaojing
Chabani, Zakariya
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In order to improve the efficiency of dynamic system prediction modelling, this paper proposes a predictive model based on high-order normal differential equations to obtain an explicit model. The high-order constant differential equation model is reduced, and the numerical method is used to solve the predictive value. The results show that the method achieves the synchronisation of model establishment and parameter optimisation, in addition to greatly enhancing the modelling efficiency. © 2021 Zhang et al., published by Sciendo.
This article is licensed under Creative Commons License and full text is openly accessible in CUD Digital Repository. The version of the scholarly record of this article is published in Applied Mathematics and Nonlinear Sciences (2022), available online at:
03-00, dynamic system modelling, financial investment, High-order constant differential equation model, stock price
Zhang, L., Tian, X., & Chabani, Z. (2022). Application of higher-order ordinary differential equation model in financial investment stock price forecast. Applied Mathematics and Nonlinear Sciences,