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

<p>This article first uses the gray correlation analysis combined with the gravitational search algorithm model to model the time series linearly. In this way, the predicted value of the GEM stock price is obtained. The simulation analysis of the calculation example found that the average relative error of the prediction result of our proposed model is 0.095 and the operation efficiency is high.</p>
</abstract>

This article first uses the gray correlation analysis combined with the gravitational search algorithm model to model the time series linearly. In this way, the predicted value of the GEM stock price is obtained. The simulation analysis of the calculation example found that the average relative error of the prediction result of our proposed model is 0.095 and the operation efficiency is high.

Prediction and Analysis of ChiNext Stock Price Based on Linear and Non-linear Composite Model

Applied Mathematics and Nonlinear Sciences

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

This article first uses the gray correlation analysis combined with the gravitational search algorithm model to model the time series linearly. In this way,...

Prediction and Analysis of ChiNext Stock Price Based on Linear and Non-linear Composite Model

Publié en ligne: 15 juil. 2022

Pages: 689 - 696

Reçu: 07 févr. 2022

Accepté: 09 avr. 2022

DOI: https://doi.org/10.2478/amns.2022.2.0055

Mots clés
Error correction, nonlinear model, linear model, stock price forecast

© 2023 Yueting Jiang et al., published by Sciendo

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

Prediction and Analysis of ChiNext Stock Price Based on Linear and Non-linear Composite Model

Publié en ligne: 15 juil. 2022

Pages: 689 - 696

Reçu: 07 févr. 2022

Accepté: 09 avr. 2022

DOI: https://doi.org/10.2478/amns.2022.2.0055

Mots clésError correction, nonlinear model, linear model, stock price forecast

© 2023 Yueting Jiang et al., published by Sciendo

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

Mots clés
Error correction, nonlinear model, linear model, stock price forecast