Author(s)

Chenhao Wei ¹, Hong Rao ¹

Affiliation(s)

¹ Sun Yueqi Honors College, China University of Mining and Technology, Xuzhou, 221116, China

Corresponding Author

Chenhao Wei

ABSTRACT

In the rapid development of China’s socialist market economy, stock investment has become a focal point of public attention, and the accuracy of stock market predictions is crucial for investors. This study employs a Bidirectional Long Short-Term Memory (Bi-LSTM) network model to conduct an in-depth predictive analysis of a representative Chinese stock. The research initially selected stock data from 2010 to 2020, which underwent meticulous cleaning and normalization processes, and was prepared for model training through feature engineering and data segmentation. Subsequently, a Bi-LSTM model was constructed and trained, and its performance was evaluated using a validation set. Ultimately, the model’s predictive capability was comprehensively assessed through key indicators such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared (R2). The study demonstrates the high application potential of the Bi-LSTM model in stock market prediction.

KEYWORDS

Chinese stock market, Stock prediction, Bidirectional Long Short-Term Memory network, Investment analysis, Deep learning

CITE THIS PAPER

Chenhao Wei, Hong Rao, Stock Prediction System Based on Bi-directional LSTM Model. Advances in Computer, Signals and Systems (2024) Vol. 8: 105-112. DOI: http://dx.doi.org/10.23977/acss.2024.080415.

REFERENCES

[1] Guan Jian. Research on Stock Price Prediction Method Based on RNN-CNN Model[D]. Nanjing University of Information Science & Technology, 2023.
[2] Li Junhao. Stock Price Prediction Model Based on Improved Multiple Linear Regression[J]. Science Technology and Economy Market, 2019, (08): 61-62+64.
[3] Sun Chenhao, Wang Lin. Prediction and Analysis of Shanghai Composite Index Based on ARIMA and LSTM[J]. Information and Computer (Theoretical Edition), 2023, 35(02):29-31.
[4] Peng Yan, Liu Yuhong, Zhang Rongfen. Modeling and Analysis of Stock Price Prediction Based on LSTM[J]. Computer Engineering and Applications, 2019, 55(11):209-212.
[5] Qiao Zhongxue. Comparative Study of Shenzhen Component Index Based on Bi-directional LSTM[J]. Industrial Innovation Research, 2020, (14): 83-84.

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