Stock market prediction based on neural network

Chang Huang; Zhihui Hou; Yanchu Liu; Yanlin Wu

doi:10.1117/12.2623098

1 December 2021 Stock market prediction based on neural network

Chang Huang, Zhihui Hou, Yanchu Liu, Yanlin Wu

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120792J (2021) https://doi.org/10.1117/12.2623098
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

With the advent of the information age, the development of science and technology has reached an unprecedented speed, especially computer science, and machine learning has been a hot topic among scientists and researchers. Stock market prediction lies in this area that helps investors understand what stocks they should purchase or when to purchase. More importantly, they can earn money by successfully predicting the trends of the stock market. In this work, we use relevant theoretical knowledge of machine learning and neural networks and set up neural network models in Python's programming language. At first, we collect stock prices data of Apple and Tesla from 2020 to 2021. Later, we compute them by using the models we build to analyze and predict the trend of stock prices from these two companies. At last, we find out that our models work nicely before day 340. However, the models fail to predict the trends of stock prices of these two companies starting from day 340 to day 360.

Citation Download Citation

Chang Huang, Zhihui Hou, Yanchu Liu, and Yanlin Wu "Stock market prediction based on neural network", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120792J (1 December 2021); https://doi.org/10.1117/12.2623098

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