Paper: Using Structured Events to Predict Stock Price Movement: An Empirical Investigation

ACL ID D14-1148
Title Using Structured Events to Predict Stock Price Movement: An Empirical Investigation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014
Authors

It has been shown that news events influ- ence the trends of stock price movements. However, previous work on news-driven stock market prediction rely on shallow features (such as bags-of-words, named entities and noun phrases), which do not capture structured entity-relation informa- tion, and hence cannot represent complete and exact events. Recent advances in Open Information Extraction (Open IE) techniques enable the extraction of struc- tured events from web-scale data. We propose to adapt Open IE technology for event-based stock price movement pre- diction, extracting structured events from large-scale public news without manual efforts. Both linear and nonlinear mod- els are employed to empirically investigate the hidden and complex relationships be- tween events and the stock marke...