PaperView: On the Importance of Text Analysis for Stock Price Prediction

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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.

Shayan Fazeli
Shayan Fazeli
Ph.D. Candidate in Computer Science

Ph.D. candidate researcher at the eHealth and Data Analytics Lab - CS [at] UCLA