Predicting Stock Price Movement from Financial News ArticlesRobert P. Schumaker (Cleveland State University, USA) and Hsinchun Chen (University of Arizona, USA)
Copyright © 2012. 33 pages.
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DOI: 10.4018/978-1-61350-162-7.ch006 Sample PDFCite
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. IGI Global, 2012. 96-128. Web. 21 May. 2013. doi: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). Hershey, PA: Business Science Reference. doi: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, ed. Alexander Y. Yap, 96-128 (2012), accessed May 21, 2013. doi:10.4018/978-1-61350-162-7.ch006
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 Favorite  | | TopAbstractHowever, 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. TopComplete Chapter List
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