Stock Price Movement Prediction from Financial News with Deep Learning and Knowledge Graph Embedding
By Yang Liu, Qingguo Zeng, Huanrui Yang, Adrian Carrio. 2018
44 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Finance, Management Science and Operations Research, Knowledge Graphs & Representation, 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 Electrical and Electronic Engineering
- A. Ozbayoglu
- M. Ugur Gudelek
- Omer Berat Sezer
- Ze Hu
- Matloob Khushi
- Yiqi Zhao
- Longbing Cao
- Weiwei Jiang
In Finance
- M. Ugur Gudelek
- A. Ozbayoglu
- Omer Berat Sezer
- Ze Hu
- Matloob Khushi
- Yiqi Zhao
- Weiwei Jiang
- Longbing Cao
In Management Science and Operations Research
- M. Ugur Gudelek
- Omer Berat Sezer
- A. Ozbayoglu
- Ze Hu
- Matloob Khushi
- Yiqi Zhao
- Weiwei Jiang
- Longbing Cao
In Knowledge Graphs & Representation
In Time-Series & Forecasting
- M. Ugur Gudelek
- Omer Berat Sezer
- A. Ozbayoglu
- Ze Hu
- Matloob Khushi
- Yiqi Zhao
- Weiwei Jiang
- Longbing Cao
Citations in the corpus
- Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “The authors of [208] proposed a method that used two separate LSTM networks to construct an ensemble network.”
- A Survey of Forex and Stock Price Prediction Using Deep Learning (2021, methodology): “0–50% [56,89] 50–60% [19,25,34,53,58,74] 60–70% [16,23,28,29,45,50,54,67,87] 70–80% [3,13,22,26,62–64,92] 80–90% [52,61,68] 90–100% [36]”