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

Date
2022-01-01
Authors
Zhang, Liqin
Tian, Xiaojing
Chabani, Zakariya
Journal Title
Journal ISSN
Volume Title
Publisher
Sciendo
Abstract
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.
Description
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: https://doi.org/10.2478/amns.2021.1.00074
Keywords
dynamic system modelling, financial investment, High order constant differential equation model, stock price
Citation
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, 7(1), 893-900. https://doi.org/10.2478/amns.2021.1.00074
DOI