Stock Market Prediction via Deep Learning Techniques: A Survey

Existing surveys on stock market prediction often focus on traditional machine learning methods instead of deep learning methods. This motivates us to provide a structured and comprehensive overview of the research on stock market prediction. We present four elaborated subtasks of stock market predi...

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Bibliographic Details
Published in:arXiv.org 2023-02
Main Authors: Zou, Jinan, Zhao, Qingying, Jiao, Yang, Cao, Haiyao, Liu, Yanxi, Qingsen Yan, Abbasnejad, Ehsan, Liu, Lingqiao, Shi, Javen Qinfeng
Format: Article
Language:English
Subjects:
Artificial neural networks
Chaos theory
Deep learning
Domains
Machine learning
Securities markets
Taxonomy
Online Access:Get full text
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Summary:Existing surveys on stock market prediction often focus on traditional machine learning methods instead of deep learning methods. This motivates us to provide a structured and comprehensive overview of the research on stock market prediction. We present four elaborated subtasks of stock market prediction and propose a novel taxonomy to summarize the state-of-the-art models based on deep neural networks. In addition, we also provide detailed statistics on the datasets and evaluation metrics commonly used in the stock market. Finally, we point out several future directions by sharing some new perspectives on stock market prediction.
ISSN:2331-8422