Robert P. Schumaker is an American academic and Professor of computer science at the University of Texas at Tyler, best known for creating AZFinText, a news-aware high-frequency stock trading system. Schumaker is also known as a Sports Analytics expert for his pioneering work using Twitter tweet sentiment to predict sports outcomes and is currently active in both prescription drug interactions and covid-19 vaccine allergies. Schumaker is also the founder and Director of the Data Analytics Lab.

Biography

Schumaker received a B.S. degree in Civil Engineering from the University of Cincinnati, an MBA in Management and International Business from the University of Akron and a Ph.D. in Management Information Systems from the University of Arizona.

While at the University of Arizona, Schumaker created the Arizona Financial Text (AZFinText) System which machine learns the words used 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[9] and NFL matches.[10] 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

  1. ↑ "AI That Picks Stocks Better Than the Pros". MIT Technology Review. June 10, 2010.
  2. ↑ "StreetDogs: Who Says You Cannot Beat the Markets by Reading the News". Business Day. Aug 5, 2010.
  3. ↑ Valentino-DeVries, Jennifer (June 21, 2010). "Using Artificial Intelligence to Digest News, Trade Stocks". WSJ Blogs. The Wall Street Journal. Retrieved January 20, 2017.
  4. ↑ "Algorithmic and Trading Products Newsletter". Dow Jones Newswire. Nov 24, 2010.
  5. ↑ Kroeker, Kirk L. (2010). "Computer Scientists Beat U.S. Stock Market". Communications of the ACM. 53 (8): 20. doi:10.1145/1787234.1787261.
  6. ↑ "Using Artificial Intelligence to Predict Short-term Stock Market Performance". Inside Tucson Business. July 2, 2010.
  7. ↑ "An Investigation of SVM Regression to Predict Longshot Greyhound Races". Communications of the International Information Management Association. 8 (2): 67–82.
  8. ↑ Schumaker, Robert P. (2013). "Machine Learning the Harness Track- Crowdsourcing and Varying Race History". Decision Support Systems. 54 (3): 1370–1379. doi:10.1016/j.dss.2012.12.013.
  9. ↑ Schumaker, Robert P.; Jarmoszko, A. Tomasz; Labedz, Chester S. (2016). "Predicting Wins and Spread in the Premier League Using a Sentiment Analysis of Twitter". Decision Support Systems. 88 (8): 76–84. doi:10.1016/j.dss.2016.05.010.
  10. ↑ Schumaker, Robert P.; Labedz, Chester S.; Brown, Leonard L.; Jarmoszko, A. Tomasz (2017). "Prediction from Regional Angst - A Study of NFL Sentiment in Twitter Using Stock Market Charting". Decision Support Systems. 98 (6): 80–88. doi:10.1016/j.dss.2017.04.010.


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.