@inproceedings{6df61a933b0a49a0912c3de32e0c06f4,
title = "On the importance of text analysis for stock price prediction",
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.",
keywords = "8-K text analysis, Financial events, Stock price forecasting",
author = "Heeyoung Lee and Mihai Surdeanu and Bill MacCartney and Dan Jurafsky",
note = "Funding Information: This work was supported by a Google Faculty Research Award, by the NSF via award IIS-1159679, and by the Center for Advanced Study in the Behavioral Sciences at Stanford. Thanks to the Stanford NLP Group for sharing ideas. We also thank Di Wu for providing their sentiment lexicon.; 9th International Conference on Language Resources and Evaluation, LREC 2014 ; Conference date: 26-05-2014 Through 31-05-2014",
year = "2014",
language = "English (US)",
series = "Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014",
publisher = "European Language Resources Association (ELRA)",
pages = "1170--1175",
editor = "Nicoletta Calzolari and Khalid Choukri and Sara Goggi and Thierry Declerck and Joseph Mariani and Bente Maegaard and Asuncion Moreno and Jan Odijk and Helene Mazo and Stelios Piperidis and Hrafn Loftsson",
booktitle = "Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014",
}