Stock market one-day ahead movement prediction using disparate data sources

By Bin Weng, Mohamed A. Ahmed, F. Megahed. 2017

203 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Signal Processing

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. Changjun Zhou
2. Weiwei Jiang
3. Jiayu Qiu
4. Bin Wang

In Management Science and Operations Research

1. Changjun Zhou
2. Weiwei Jiang
3. Jiayu Qiu
4. Bin Wang

In Signal Processing

1. Changjun Zhou
2. Weiwei Jiang
3. Jiayu Qiu
4. Bin Wang

Citations in the corpus

• Applications of deep learning in stock market prediction: recent progress (2020, methodology): “Link: https://doi.org/10.6084/m9. figshare.7976144.v1 Liu et al. (2019c) News headlines from Thomson Reuters and Ca- ble News Network for 6 stocks in US markets.”
• Forecasting stock prices with long-short term memory neural network based on attention mechanism (2020, background): “[1] For the stock market, its volatility is complicated and nonlinear.[2] It is obviously unreliable and inefficient to rely solely on a trader’s personal experience and intuition for analysis and judgment.”