Stock market's price movement prediction with LSTM neural networks

By David M. Q. Nelson, Adriano César Machado Pereira, Renato A. de Oliveira. 2017

813 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Signal Processing, Time-Series & Forecasting

How researchers see this paper

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

In Economics and Econometrics

1. Weiwei Jiang
2. Stephen J. Roberts
3. Zihao Zhang
4. Saibal Kar
5. Saman Haratizadeh
6. Ehsan Hoseinzade
7. Stefan Zohren

In Management Science and Operations Research

1. Weiwei Jiang
2. Stefan Zohren
3. Stephen J. Roberts
4. Zihao Zhang
5. Saman Haratizadeh
6. Ehsan Hoseinzade
7. Bryan Lim

In Signal Processing

1. Stefan Zohren
2. Stephen J. Roberts
3. Weiwei Jiang
4. Saman Haratizadeh
5. Jerry Chun-Wei Lin
6. Ehsan Hoseinzade

In Time-Series & Forecasting

1. Stefan Zohren
2. Stephen J. Roberts
3. Zihao Zhang
4. Weiwei Jiang
5. Saman Haratizadeh
6. Ehsan Hoseinzade
7. Bryan Lim

Citations in the corpus

• Applications of deep learning in stock market prediction: recent progress (2020, methodology): “…Type Huynh et al. (2017) BGRU LSTM, GRU, DNN (Ding et al., 2014), DNN (Peng & Jiang, 2016) Li & Tam (2017) WT+LSTM LSTM Li et al. (2017a) LSTM SVM Nelson et al. (2017) LSTM MLP, RF Tsantekidis et al. (2017b) LSTM SVM, MLP Zhang et al. (2017a) GRU SVM Zhang et al. (2017b) SFM AR, LSTM Zhao et al.…”
• Predicting the direction of stock market prices using tree-based classifiers (2019, background): “Neural networks with short term memory is not appropriate for the same reasons (Nelson et al. 2017).”
• A graph-based CNN-LSTM stock price prediction algorithm with leading indicators (2021, background): “In [44], they provide technical indicators to LSTM to achieve the forecast of the stock price direction of the Brazilian stock market.”
• DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2018, background): “markets, the LSTM has been popular in recent years, [20], [28], [42]–[47] all utilising LSTMs to analyse financial data.”
• CNNpred: CNN-based stock market prediction using a diverse set of variables (2019, methodology): “In (Nelson et al., 2017), technical indicators were fed to an LSTM in order to predict the direction of stock prices in the Brazilian stock market.”