Stock Market Prediction with Deep Learning: A Character-based Neural Language Model for Event-based Trading

By Leonardo dos Santos Pinheiro, Mark Dras. 2017

48 citations recorded by the source corpus.

Subfields: Large Language Models, 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 Large Language Models

1. Ze Hu
2. A. Ozbayoglu
3. Omer Berat Sezer
4. M. Ugur Gudelek
5. Matloob Khushi
6. Yiqi Zhao

In Natural Language Processing

1. Ze Hu
2. A. Ozbayoglu
3. Omer Berat Sezer
4. M. Ugur Gudelek
5. Matloob Khushi
6. Yiqi Zhao

In Time-Series & Forecasting

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Ze Hu
5. Matloob Khushi
6. Yiqi Zhao
7. Weiwei Jiang
8. Longbing Cao

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “The authors of [206] proposed a novel method that used character-based neural language model using financial news and LSTM for trend prediction.”
• Deep Learning for Financial Applications : A Survey (2020, methodology): “[181] Reuters, Bloomberg News, S&P500 price 2006-2013 News and sentences LSTM Accuracy -”
• A Survey of Forex and Stock Price Prediction Using Deep Learning (2021, methodology): “The results showed that the proposed model performed better than some model proposed in other papers such as WI-RCNN and SI-RCNN[43] .”