An Automated Framework for Incorporating News into Stock Trading Strategies

In this paper we present a framework for automatic exploitation of news in stock trading strategies. Events are extracted from news messages presented in free text without annotations. We test the introduced framework by deriving trading strategies based on technical indicators and impacts of the ex...

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Vydáno v:IEEE transactions on knowledge and data engineering Ročník 26; číslo 4; s. 823 - 835
Hlavní autoři: Nuij, Wijnand, Milea, Viorel, Hogenboom, Frederik, Frasincar, Flavius, Kaymak, Uzay
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 01.04.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Companies
Computer applications
Context
Corporate acquisitions
evolutionary computing and genetic algorithms
Genetic programming
Indexes
Information retrieval
learning
natural language processing
Stock markets
web text analysis
ISSN:1041-4347, 1558-2191
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Shrnutí:In this paper we present a framework for automatic exploitation of news in stock trading strategies. Events are extracted from news messages presented in free text without annotations. We test the introduced framework by deriving trading strategies based on technical indicators and impacts of the extracted events. The strategies take the form of rules that combine technical trading indicators with a news variable, and are revealed through the use of genetic programming. We find that the news variable is often included in the optimal trading rules, indicating the added value of news for predictive purposes and validating our proposed framework for automatically incorporating news in stock trading strategies.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2013.133