Stock closing price prediction based on sentiment analysis and LSTM

By Zhigang Jin, Yang Yang, Yuhong Liu. Neural computing & applications (Print), 2019

401 citations recorded by the source corpus.

Subfields: Building and Construction, Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2ebcff63660dd5bf5b09c9b8457c258cfeece24f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Weiwei Jiang

In Electrical and Electronic Engineering

1. Weiwei Jiang

In Management Science and Operations Research

1. Weiwei Jiang
2. Jiazheng Li
3. Aijun Sun
4. Yifan Li
5. Wenjie Lu
6. Jingyang Wang

Citations in the corpus

• Applications of deep learning in stock market prediction: recent progress (2020, methodology): “…Prediction Model Baselines Guang et al. (2019) MSTD-RCNN SVM, RF, FDNN, TreNet (Lin et al., 2017), SFM RNN (Hu & Qi, 2017), MS-CNN (Cui et al., 2016) Jin et al. (2019) CNN+LSTM+Attention LSTM Kim & Kim (2019) CNN+LSTM CNN, LSTM Liu & Chen (2019) SRCGUs MGUs, GRUs and LSTMs Long et al. (2019)…”
• A CNN-LSTM-Based Model to Forecast Stock Prices (2020, methodology): “However, four of the LSTM modules are similar to the standard RNN modules, and they operate in a special interactive manner [33, 34].”