Stock Price Prediction Based on Artificial Neural Network

Xuefei Kan, Miao Miao, Liangcheng Cao, Tianhao Xu, Yanqing Li, Jiyue Jiang

2020 · 13 citations · 3 references

Concepts

Abstract

At present, China's economy is undergoing continuous development and progress. With the emergence of new technologies, domestic emerging industries are showing a state of vigorous development, leading to strong volatility in the entire stock market, which brings complex challenges to stock price prediction. Therefore, this paper realizes the judgment of stock price based on artificial neural network and obtains more accurate prediction results. The results of the experiment show that the model proposed in this paper can accurately judge the future price trend of stocks, and the model runs faster, which fundamentally solves the defects of the traditional forecasting methods of slow operation efficiency and low forecast accuracy.

References

3