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A Review on Applied Data Mining Techniques to Stock Market Prediction

A Review on Applied Data Mining Techniques to Stock Market Prediction

Neslihan Fidan, Beyza Ahlatcioglu Ozkok
Copyright: © 2013 |Pages: 19
ISBN13: 9781466639461|ISBN10: 1466639466|EISBN13: 9781466639478
DOI: 10.4018/978-1-4666-3946-1.ch009
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MLA

Fidan, Neslihan, and Beyza Ahlatcioglu Ozkok. "A Review on Applied Data Mining Techniques to Stock Market Prediction." Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems, edited by Petraq Papajorgji, et al., IGI Global, 2013, pp. 108-126. https://doi.org/10.4018/978-1-4666-3946-1.ch009

APA

Fidan, N. & Ozkok, B. A. (2013). A Review on Applied Data Mining Techniques to Stock Market Prediction. In P. Papajorgji, A. Guimarães, & M. Guarracino (Eds.), Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems (pp. 108-126). IGI Global. https://doi.org/10.4018/978-1-4666-3946-1.ch009

Chicago

Fidan, Neslihan, and Beyza Ahlatcioglu Ozkok. "A Review on Applied Data Mining Techniques to Stock Market Prediction." In Enterprise Business Modeling, Optimization Techniques, and Flexible Information Systems, edited by Petraq Papajorgji, Alaine Margarete Guimarães, and Mario R. Guarracino, 108-126. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3946-1.ch009

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Abstract

A portfolio manager considers forecasting the asset prices and measurement of the market risk of an underlying asset. Financial institutions produce datasets to handle their problems by using data mining tools. Recently new technologies have been developed for tracking, collecting, and processing financial data. From a data analysis point of view, this chapter reviews the published articles based upon predictive data mining applications to stock market index. It is observed that hybrid models that combine data mining techniques or integrate an algorithm to a method work efficiently. Finally, the chapter provides likely directions of future researches.

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