Reading news from the Internet and predicting the stock market – algorithm trading by natural language processing

Speaker: Prof. Yue Zhang (SUTD)

Time and Date: 9:00-10:30, Sep. 12, 2014

Place: Room B415, Building of Computing Center, Handan Campus

Abstract

It has been shown that news events influence the trends of stock price movements. However, previous work on news-driven stock market prediction relies on shallow features (such as bags-of-words, named entities and noun phrases), which do not capture structured entity-relation information, and hence cannot represent completeand exact events. Recent advances in Open Information Extraction (Open IE) techniques enable the extraction of structured events from web-scale data. We propose to adapt Open IE technology for event-based stock price movement prediction, extracting structured events from large-scale public news without manual efforts. Both linear and nonlinear models are employed to empirically investigate the hidden and complex relationships between events and the stock market. Large-scale experiments show that the accuracy of S&P 500 index prediction is 60%, and thatof individual stock prediction can be over 70%. Our event-based system out-performs bags-of-words-based baselines, and previously reported systems trained on S&P 500 stock historical data.

Biography

Yue Zhang is currently an assistant professor at Singapore University of Technology and Design. Before joining SUTD in July 2012, he worked as a postdoctoral research associate in University of Cambridge, UK. Yue Zhang received his DPhil and MSc degrees from University of Oxford, UK, and his BEng degree from Tsinghua University, China. His research interests include natural language processing, machine learning and artificial intelligence.