Welcome to the InfoSci Platform
Predicting Stock Price Movement from Financial News Articles

Predicting Stock Price Movement from Financial News Articles

Robert P. Schumaker, Hsinchun Chen
Copyright: © 2012 |Pages: 33
ISBN13: 9781613501627|ISBN10: 1613501625|EISBN13: 9781613501634
DOI: 10.4018/978-1-61350-162-7.ch006
Cite Chapter Cite Chapter

MLA

Schumaker, Robert P., and Hsinchun Chen. "Predicting Stock Price Movement from Financial News Articles." Information Systems for Global Financial Markets: Emerging Developments and Effects, edited by Alexander Y. Yap, IGI Global, 2012, pp. 96-128. https://doi.org/10.4018/978-1-61350-162-7.ch006

APA

Schumaker, R. P. & Chen, H. (2012). Predicting Stock Price Movement from Financial News Articles. In A. Yap (Ed.), Information Systems for Global Financial Markets: Emerging Developments and Effects (pp. 96-128). IGI Global. https://doi.org/10.4018/978-1-61350-162-7.ch006

Chicago

Schumaker, Robert P., and Hsinchun Chen. "Predicting Stock Price Movement from Financial News Articles." In Information Systems for Global Financial Markets: Emerging Developments and Effects, edited by Alexander Y. Yap, 96-128. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-162-7.ch006

Export Reference

Mendeley
Favorite

Abstract

However, using computational approaches to predict stock prices using financial data is not unique. In recent years, interest has increased in Quantitative funds, or Quants, that automatically sift through numeric financial data and issue stock recommendations. While these systems are based on proprietary technology, they do differ in the amount of trading control they have, ranging from simple stock recommenders to trade executors. Using historical market data and complex mathematical models, these methods are constrained to make assessments within the scope of existing information. This weakness means that they are unable to react to unexpected events falling outside of historical norms. However, this disadvantage has not stopped fund managers at Federated, Janus, Schwab, and Vanguard from trusting billions of dollars of assets to the decisions of these computational systems.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.