Sentiment-influenced trading system based on multimodal deep reinforcement learning
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Sentiment-influenced trading system based on multimodal deep reinforcement learning
Authors
Keywords
Finance, Multimodal learning, Reinforcement learning, Sentiment analysis, Stock trading
Journal
APPLIED SOFT COMPUTING
Volume 112, Issue -, Pages 107788
Publisher
Elsevier BV
Online
2021-08-11
DOI
10.1016/j.asoc.2021.107788
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Exploring the influence of multimodal social media data on stock performance: an empirical perspective and analysis
- (2021) Hui Yuan et al. Internet Research
- An application of deep reinforcement learning to algorithmic trading
- (2021) Thibaut Théate et al. EXPERT SYSTEMS WITH APPLICATIONS
- Event Study and Principal Component Analysis Based on Sentiment Analysis – A Combined Methodology to Study the Stock Market with an Empirical Study
- (2020) Qianwen Xu et al. INFORMATION SYSTEMS FRONTIERS
- Multimodal deep learning for finance: integrating and forecasting international stock markets
- (2019) Sang Il Lee et al. JOURNAL OF SUPERCOMPUTING
- Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine
- (2018) Rui Ren et al. IEEE Systems Journal
- Multimodal Machine Learning: A Survey and Taxonomy
- (2018) Tadas Baltrusaitis et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- On the risk prediction and analysis of soft information in finance reports
- (2017) Ming-Feng Tsai et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Applications of a multivariate Hawkes process to joint modeling of sentiment and market return events
- (2017) Steve Y. Yang et al. QUANTITATIVE FINANCE
- Deep Direct Reinforcement Learning for Financial Signal Representation and Trading
- (2017) Yue Deng et al. IEEE Transactions on Neural Networks and Learning Systems
- Stock market sentiment lexicon acquisition using microblogging data and statistical measures
- (2016) Nuno Oliveira et al. DECISION SUPPORT SYSTEMS
- A hybrid stock trading system using genetic network programming and mean conditional value-at-risk
- (2015) Yan Chen et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach
- (2015) Muxuan Liang et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
- (2014) Heung-Il Suk et al. NEUROIMAGE
- Techniques and applications for sentiment analysis
- (2013) Ronen Feldman COMMUNICATIONS OF THE ACM
- Multimodal freight transportation planning: A literature review
- (2013) M. SteadieSeifi et al. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
- Multimedia classification and event detection using double fusion
- (2013) Zhen-zhong Lan et al. MULTIMEDIA TOOLS AND APPLICATIONS
- Multimodal fusion for multimedia analysis: a survey
- (2010) Pradeep K. Atrey et al. MULTIMEDIA SYSTEMS
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started