A hybrid model for high-frequency stock market forecasting

By Ricardo de A. Araújo, Adriano Oliveira, Silvio Romero Lemos de Meira. 2015

47 citations recorded by the source corpus.

How researchers see this paper

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

1. Siqi Tang
2. Guyu Hu
3. Zhisong Pan
4. Cheng Zhao
5. Xingyu Zhou
6. Weiwei Jiang
7. Mojtaba Nabipour

Citations in the corpus

• Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018, background): “Some literatures have established various models based on deep neural networks to improve the prediction ability of high-frequency financial time series [32, 33].”