Join Graham School master of science in analytics students as they present capstone projects on deriving investor sentiment from social media to predict stock market direction.
Event Details
This research project is a study of investor sentiment as derived from social media content and its ability to predict short-term stock market direction. The team choose S&P 500 and Russell 2000 indices to represent the stock market for this project. The study involves using cutting edge, Text Analytics/ Natural Language processing techniques to analyze articles posted on financial social media websites and derive daily 'Sentiment Measures' from it. The results indicate that these 'Sentiment Measures' have strong short term relationship with Russell 2000 Index. On the other hand, there were no strong evidence of short term relationship between sentiment measures and S&P 500 Index. Using these Sentiment measures, the research team was able to predict the Russell index direction for the next trading day with an 80% accuracy rate.
Team:
Benedict Augustine
Baodan Zhang
Kads Bennurkar
Supervisor:
Yuri G Balasanov, Ph. D
$10 until 11/05/15 at 12 p.m.
$15 at the door
Registration
Register Online
6:30 - 7:00 - Networking w/hors d'oeuvres and cash bar
7:00 - 8:00 - Program
8:00 - 8:30 - Continued networking w/hors d'oeuvres and cash bar
Deadline: 11/5/2015
Speaker Profiles
Benedict Augustine (Speaker)
Baodan Zhang (Speaker)
Kads Bennurkar (Speaker)
Questions
Roger Moore, '92
Senior Director / Gartner
312-543-1319