BiCuDNNLSTM-1dCNN — A hybrid deep learning-based predictive model for stock price prediction

作者：

Highlights：

• BiCuDNNLSTM-1dCNN is a hybrid DL model based on Bidirectional CuDNNLSTM and CNN.

• BiCuDNNLSTM-1dCNN is efficient and scalable in developed and emerging stock market.

• BiCuDNNLSTM-1dCNN uses univariate time series data to predict stock price.

• Results confirm BiCuDNNLSTM-1dCNN is effective for volatility of stock price data.

• BiCuDNNLSTM-1dCNN predicts better than LSTM, LSTM-CNN, CuDNNLSTM and LSTM-DNN.

摘要

•BiCuDNNLSTM-1dCNN is a hybrid DL model based on Bidirectional CuDNNLSTM and CNN.•BiCuDNNLSTM-1dCNN is efficient and scalable in developed and emerging stock market.•BiCuDNNLSTM-1dCNN uses univariate time series data to predict stock price.•Results confirm BiCuDNNLSTM-1dCNN is effective for volatility of stock price data.•BiCuDNNLSTM-1dCNN predicts better than LSTM, LSTM-CNN, CuDNNLSTM and LSTM-DNN.

论文关键词：BiCuDNNLSTM-1dCNN,BiCuDNNLSTM,CNN,LSTM,Stock price prediction,Time series data

论文评审过程：Received 3 August 2021, Revised 9 December 2021, Accepted 28 March 2022, Available online 12 April 2022, Version of Record 6 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117123