Research on investment portfolio model based on neural network and genetic algorithm in big data era

EURASIP Journal on Wireless Communications and Networking

Weiwei Chen¹  Wei Zhou²  Rongjun Yang²  Yuanjun Zhao³  Yanghui Liu⁴  Zheng Liu⁵ 

[1] College of Business Administration, Hunan University of Technology and Business, 410205, Changsha, China;Department of Economy and Management, Zaozhuang University, 277100, Zaozhuang, China;School of Business Administration, Shanghai Lixin University of Accounting and Finance, 201209, Shanghai, China;School of Economics and Management, East China Jiaotong University, 330000, Nanchang, China;School of Management, Shanghai University of Engineering Science, 201620, Shanghai, China;

关键词: Neural network;    Genetic algorithm;    Stock investment;    Big data;   

DOI  :  10.1186/s13638-020-01850-x

来源: Springer

【 摘 要 】

With the maturity of neural network theory, it provides new ideas and methods for the prediction and analysis of stock market investment. The purpose of this paper is to improve the accuracy of stock market investment prediction, we build neural network model and genetic algorithm model, study the law of stock market operation, and improve the effectiveness of neural network and genetic algorithm. Through the empirical research, it is found that the neural network model can make up for the shortcomings of the traditional algorithm through the optimization of genetic algorithm.

【 授权许可】

CC BY