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

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.

Keywords

• error correction
• nonlinear model
• linear model
• stock price forecast
• 62j05