Abstract
We investigate the importance of text analysis for stock price prediction. In particular, we introduce a system that forecasts companies stock price changes (UP, DOWN, STAY) in response to financial events reported in 8-K documents. Our results indicate that using text boosts prediction accuracy over 10% (relative) over a strong baseline that incorporates many financially-rooted features. This impact is most important in the short term (i.e., the next day after the financial event) but persists for up to five days.- Anthology ID:
- L14-1048
- Volume:
- Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
- Month:
- May
- Year:
- 2014
- Address:
- Reykjavik, Iceland
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 1170–1175
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/1065_Paper.pdf
- DOI:
- Cite (ACL):
- Heeyoung Lee, Mihai Surdeanu, Bill MacCartney, and Dan Jurafsky. 2014. On the Importance of Text Analysis for Stock Price Prediction. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 1170–1175, Reykjavik, Iceland. European Language Resources Association (ELRA).
- Cite (Informal):
- On the Importance of Text Analysis for Stock Price Prediction (Lee et al., LREC 2014)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/1065_Paper.pdf