Empirical analysis: stock market prediction via extreme learning machine

By Xiaodong Li, Haoran Xie, Ran Wang, Yi Cai, Jingjing Cao, Feng Wang, Huaqing Min, Xiaotie Deng. 2014

161 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Management Science and Operations Research

How researchers see this paper

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

In Artificial Intelligence

1. Weiwei Jiang
2. Juho Kanniainen
3. Moncef Gabbouj
4. Zhaoqing Pan
5. Xiaodong Li
6. Dat Thanh Tran
7. Alexandros Iosifidis
8. Martin Magris

In Electrical and Electronic Engineering

1. Weiwei Jiang
2. Zhaoqing Pan
3. Xiaodong Li
4. Juho Kanniainen
5. Alexandros Iosifidis
6. Martin Magris
7. Jingjing Cao
8. Moncef Gabbouj

In Management Science and Operations Research

1. Weiwei Jiang
2. Adamantios Ntakaris
3. Zhaoqing Pan
4. Xiaodong Li
5. Dat Thanh Tran
6. Juho Kanniainen
7. Alexandros Iosifidis
8. Martin Magris

Citations in the corpus

• Tensor representation in high-frequency financial data for price change prediction (2017, methodology): “The provided data was extracted based on event inflow [30] which aggregates to approximately 4 .”
• Market impact analysis via deep learned architectures (2018, methodology): “We follow the guideline in [35] and set the number between the number of output features of PCA and the number of the instances.”
• Applications of deep learning in stock market prediction: recent progress (2020, methodology): “…Chai (2018) LSTM MA, EMA, ARMA, GARCH, SVM, FFNN, and LSTM Hollis et al. (2018) Attention LSTM LSTM Huang et al. (2018) SMC+LSTM SVM, PCA+SVM, TeSIA (Li et al., 2016a), SMC+TeSIA Jiang et al. (2018) RNN with attention RNN Liu et al. (2018) HCAN BoW (Joachims, 1998), Fast- Text (Joulin et al.,…”
• Benchmark Dataset for Mid-Price Prediction of Limit Order Book data (2017, methodology): “Finally, the most common source of data is through platforms requiring a subscription fee, like those in [28], [31], [49].”