<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to improve the modelling efficiency in dynamic system prediction, this paper proposes a predictive model based on high-order normal differential equations to model high-order differential data 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 realises the synchronisation of model establishment and parameter optimisation, and greatly enhances the modelling efficiency.</p>
</abstract>

In order to improve the modelling efficiency in dynamic system prediction, this paper proposes a predictive model based on high-order normal differential equations to model high-order differential data 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 realises the synchronisation of model establishment and parameter optimisation, and greatly enhances the modelling efficiency.

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

Department of International Business, Faculty of Management

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In order to improve the modelling efficiency in dynamic system prediction, this paper proposes a predictive model based on high-order normal differential...

Parameter Name	Parameter declaration
Dgeneration times	20000
Function set
{+ − − /^∧2} The Symbol Set
Chromosomes number	30
Number of genes	3
Connection function	+
Head length	8
Variability rate	0.044
IS string rate	0.1
RIS insertion rate	0.1
Gene insertion rate	0.1
Single-point reorganisation rate	0.3
Two-point reorganisation rate	0.3
Gene recombinant rate	0.1

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

Published Online: Dec 15, 2021

Page range: 893 - 900

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00074

Keywords
High order constant differential equation model, dynamic system modelling, financial investment, stock price

© 2021 Liqin Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Parameter setting table

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

Published Online: Dec 15, 2021

Page range: 893 - 900

Received: Jun 16, 2021

Accepted: Sep 24, 2021

DOI: https://doi.org/10.2478/amns.2021.1.00074

KeywordsHigh order constant differential equation model, dynamic system modelling, financial investment, stock price

© 2021 Liqin Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Parameter setting table

Keywords
High order constant differential equation model, dynamic system modelling, financial investment, stock price