IEEE Transactions on Knowledge and Data Engineering Article Appeared on An Automated Framework for Incorporating News into Stock Trading Strategies

Dr. Viorel Milea, Frederik Hogenboom, dr. Flavius Frasincar, and prof. dr. Uzay Kaymak, members of ECBI, have published an article in IEEE Transactions on Knowledge and Data Engineering on an automated framework for incorporating news into stock trading strategies. The article appears in volume 26, issue 4 (pages 823-835) of the P-ranked ISI 2nd decile journal.

The paper discusses a framework for automatic exploitation of news in stock trading strategies. Events are extracted from news messages presented in free text without annotations. The authors 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. It is concluded 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.

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