Deep learning for stock market prediction from financial news articles

By Manuel R. Vargas, B. Lima, Alexandre Evsukoff. 2017

218 citations recorded by the source corpus.

Subfields: Natural Language 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 Natural Language Processing

1. A. Ozbayoglu
2. Omer Berat Sezer
3. M. Ugur Gudelek
4. Weiwei Jiang
5. Mark Dras
6. Leonardo dos Santos Pinheiro

In Time-Series & Forecasting

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. Weiwei Jiang
4. A. Ozbayoglu
5. Mark Dras
6. Leonardo dos Santos Pinheiro
7. Longbing Cao
8. Ze Hu

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “[115] S&P500 index news from Reuters 2006-2013 Financial news titles, Technical indicators 1d 1d RCNN Accuracy -”
• Deep Learning for Financial Applications : A Survey (2020, methodology): “[170] S&P500 index news from Reuters 2006-2013 Financial news titles, Technical indicators SI-RCNN (LSTM + CNN) Accuracy -”
• Stock Market Prediction with Deep Learning: A Character-based Neural Language Model for Event-based Trading (2017, methodology): “This work was followed by Vargas et al. (2017) who combined recurrent and convolution layers with pre-trained word vectors to also predict changes to the S&P 500 index.”
• Applications of deep learning in stock market prediction: recent progress (2020, background): “…Huynh et al. (2017); Li & Tam (2017); Liu & Song (2017); Nelson et al. (2017); Selvin et al. (2017); Singh & Srivastava (2017); Sun et al. (2017); Vargas et al. (2017); Weng et al. (2017); Yang et al. (2017); Zhang et al. (2017a); Zhao et al. (2017); Assis et al. (2018); Chen et al.…”