Abstract

Stock market news and investing tips are popular topics in Twitter. In this paper, first we utilize a 5-year financial news corpus comprising over 50,000 articles collected from the NASDAQ website for the 30 stock symbols in Dow Jones Index (DJI) to train a directional stock price prediction system based on news content. Then we proceed to prove that information in articles indicated by breaking Tweet volumes leads to a statistically significant boost in the hourly directional prediction accuracies for the prices of DJI stocks mentioned in these articles. Secondly, we show that using document-level sentiment extraction does not yield to a statistically significant boost in the directional predictive accuracies in the presence of other 1-gram keyword features.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages523-530
Number of pages8
Volume1
ISBN (Electronic)9781467396172
DOIs
StatePublished - Feb 2 2016
Event2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015 - Singapore, Singapore
Duration: Dec 6 2015Dec 9 2015

Other

Other2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015
CountrySingapore
CitySingapore
Period12/6/1512/9/15

Fingerprint

Websites
Financial markets

Keywords

  • Breaking news
  • Stock prediction
  • Stock trading
  • Text mining
  • Twitter analysis
  • Twitter volume spike

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Alostad, H., & Davulcu, H. (2016). Directional prediction of stock prices using breaking news on twitter. In Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015 (Vol. 1, pp. 523-530). [7396858] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WI-IAT.2015.82

Directional prediction of stock prices using breaking news on twitter. / Alostad, Hana; Davulcu, Hasan.

Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015. Vol. 1 Institute of Electrical and Electronics Engineers Inc., 2016. p. 523-530 7396858.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Alostad, H & Davulcu, H 2016, Directional prediction of stock prices using breaking news on twitter. in Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015. vol. 1, 7396858, Institute of Electrical and Electronics Engineers Inc., pp. 523-530, 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015, Singapore, Singapore, 12/6/15. https://doi.org/10.1109/WI-IAT.2015.82
Alostad H, Davulcu H. Directional prediction of stock prices using breaking news on twitter. In Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015. Vol. 1. Institute of Electrical and Electronics Engineers Inc. 2016. p. 523-530. 7396858 https://doi.org/10.1109/WI-IAT.2015.82
Alostad, Hana ; Davulcu, Hasan. / Directional prediction of stock prices using breaking news on twitter. Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015. Vol. 1 Institute of Electrical and Electronics Engineers Inc., 2016. pp. 523-530
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