Research on Deep Learning and Its Application in Stock Price Prediction

Các tác giả

  • Hoang Van Hai Thai Nguyen University of Economics and Business Administration, Tan Thinh ward, Thai Nguyen city, Vietnam
  • Dang Thi Thu Hien Thuy Loi University, 175 Tay Son, Dong Da, Hanoi, Vietnam

Từ khóa

deep learning, stock price prediction, LSTM, BiLSTM, CNN

DOI:

https://doi.org/10.32913/mic-ict-research.v2023.n1.1136

Tóm tắt

The article studies the problem of forecasting the closing price of a stock based on historical data of a previous  day. The paper uses and compares algorithms based on deep learning such as LSTM, BiLSTM, and CNN. The dataset includes data on price, trading volume and some technical indicators related to VCB, MSN, and HPG shares. The results show that CNN performs better for predicting the next day’s closing price than the other architectures. 

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Đã Xuất bản

2023-09-26