An automated framework for incorporating news into stock trading strategies

W. Nuij, D.V. Milea, F.P. Hogenboom, F. Frasincar, U. Kaymak

Research output: Contribution to journalArticleAcademicpeer-review

43 Citations (Scopus)
4 Downloads (Pure)

Abstract

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.
Original languageEnglish
Pages (from-to)823-835
Number of pages13
JournalIEEE Transactions on Knowledge and Data Engineering
Volume26
Issue number4
DOIs
Publication statusPublished - 2014

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