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On the Importance of Text Analysis for Stock Price Prediction

Heeyoung Lee · Mihai Surdeanu · Bill MacCartney · Dan Jurafsky

101 citations0/0 files storedLanguage Resources and Evaluation Conference (LREC)

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Financial Analysis and Corporate Governance

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.

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2011Twitter mood predicts the stock market 2015Assessing asset pricing models using revealed preference 2013Word power: A new approach for content analysis 2008Costly Information Processing: Evidence from Earnings Announcements 2009Predicting risk from financial reports with regression 2011Identifying and Following Expert Investors in Stock Microblogs 2011Event-Driven Trading and the “New News”

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