Journal ArticleDOI
Automated news reading: Stock price prediction based on financial news using context-capturing features
Michael Hagenau,Michael Liebmann,Dirk Neumann +2 more
- Vol. 55, Iss: 3, pp 685-697
Reads0
Chats0
TLDR
It is shown that a robust feature selection allows lifting classification accuracies significantly above previous approaches when combined with complex feature types and reduces the problem of over-fitting when applying a machine learning approach.Abstract:
We examine whether stock price prediction based on textual information in financial news can be improved as previous approaches only yield prediction accuracies close to guessing probability. Accordingly, we enhance existing text mining methods by using more expressive features to represent text and by employing market feedback as part of our feature selection process. We show that a robust feature selection allows lifting classification accuracies significantly above previous approaches when combined with complex feature types. This is because our approach allows selecting semantically relevant features and thus, reduces the problem of over-fitting when applying a machine learning approach. We also demonstrate that our approach is highly profitable for trading in practice. The methodology can be transferred to any other application area providing textual information and corresponding effect data.read more
Citations
More filters
Journal ArticleDOI
A hierarchical attention network for stock prediction based on attentive multi-view news learning
TL;DR: Zhang et al. as discussed by the authors proposed a hierarchical attention network based on attentive multi-view news learning (NMNL) to excavate more useful information from news and the stock market for stock prediction.
Journal ArticleDOI
Analysing forward-looking statements in initial public offering prospectuses: a text analytics approach
TL;DR: The study finds that FLS features are more predictive for pre-IPo as compared to post-IPO valuation prediction, and proposes an analytical pipeline for identifying FLSs using machine learning techniques.
Journal ArticleDOI
An interpretable decision-support systems for daily cryptocurrency trading
Hamidreza Ahady Dolatsara,Eyyüb Y. Kıbış,Musa Çağlar,Serhat Simsek,Ali Dag,Gelareh Ahadi Dolatsara,Dursun Delen +6 more
TL;DR: In this paper , a tri-level feature selection approach is proposed to address the complexities posed by the datasets, and selected features are then, fed into the Classification & Regression Tree (C&RT) to build a highly parsimonious, transparent, and interpretable prediction model.
Journal ArticleDOI
Financial Market Predictions with Factorization Machines: Trading the Opening Hour Based on Overnight Social Media Data
TL;DR: Varying profitability during the opening minutes can be explained by the effects of market efficiency and trading turmoils, and the AFM approach achieves the highest accuracy rate and generates statistically and economically remarkable returns after transaction costs without loading on any systematic risk exposure.
Journal ArticleDOI
The impact of word sense disambiguation on stock price prediction
TL;DR: An advanced natural language processing pipeline for event-based stock price prediction is proposed, that allows for word sense disambiguation to be incorporated in the event detection process, and modest improvements in the precision of buy and sell signals generated based on these predictions tend to lead to vast improvements on average in the associated excess returns.
References
More filters
Book
Artificial Intelligence: A Modern Approach
Stuart Russell,Peter Norvig +1 more
TL;DR: In this article, the authors present a comprehensive introduction to the theory and practice of artificial intelligence for modern applications, including game playing, planning and acting, and reinforcement learning with neural networks.
Journal ArticleDOI
A Tutorial on Support Vector Machines for Pattern Recognition
TL;DR: There are several arguments which support the observed high accuracy of SVMs, which are reviewed and numerous examples and proofs of most of the key theorems are given.
Book
Introduction to Modern Information Retrieval
Gerard Salton,Michael J. McGill +1 more
TL;DR: Reading is a need and a hobby at once and this condition is the on that will make you feel that you must read.
Book ChapterDOI
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
TL;DR: This paper explores the use of Support Vector Machines for learning text classifiers from examples and analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task.
Journal ArticleDOI
An algorithm for suffix stripping
TL;DR: An algorithm for suffix stripping is described, which has been implemented as a short, fast program in BCPL, and performs slightly better than a much more elaborate system with which it has been compared.