Robert P. Schumaker
Robert P. Schumaker is an American academic and Associate Professor of CIS at the University of Texas at Tyler, best known for creating the AZFinText textual financial prediction system and is also a Sports Analytics expert.
Biography
Schumaker received a B.S. degree from the University of Cincinnati in Civil Engineering, an MBA from the University of Akron and Ph.D. in Management Information Systems from University of Arizona.
While at the University of Arizona, Schumaker created the Arizona Financial Text System (AZFinText) which is a stock selection research project that utilizes the terms in financial news articles to predict future stock prices.[1][2][3][4][5][6]
Schumaker also works in the field of Sports Analytics authoring numerous papers on greyhound[7] and harness racing prediction[8] as well as using Twitter sentiment to predict Premier League matches.[9] He has also authored a book on the subject, Sports Data Mining (2010; ISBN 978-1-4419-6729-9).
He is the Past Editor of the Communications of the International Information Management Association journal (2010-2015), Associate Editor of Decision Support Systems and is a Fellow of the International Information Management Association (IIMA).
References
- ↑ "AI That Picks Stocks Better Than the Pros". MIT Technology Review. June 10, 2010.
- ↑ "StreetDogs: Who Says You Cannot Beat the Markets by Reading the News". Business Day. Aug 5, 2010.
- ↑ http://blogs.wsj.com/digits/2010/06/21/using-artificial-intelligence-to-digest-financial-news/
- ↑ "Algorithmic and Trading Products Newsletter". Dow Jones Newswire. Nov 24, 2010.
- ↑ "Computer Scientists Beat U.S. Stock Market". Communications of the ACM. 53 (8): 20. doi:10.1145/1787234.1787261.
- ↑ "Using Artificial Intelligence to Predict Short-term Stock Market Performance". Inside Tucson Business. July 2, 2010.
- ↑ "An Investigation of SVM Regression to Predict Longshot Greyhound Races". Communications of the International Information Management Association. 8 (2): 67–82.
- ↑ "Machine Learning the Harness Track- Crowdsourcing and Varying Race History". Decision Support Systems. 54 (3): 1370–1379.
- ↑ "Predicting Wins and Spread in the Premier League Using a Sentiment Analysis of Twitter". Decision Support Systems. 88 (8): 76–84.