SOFT COMPUTING APROACHES TO STOCK FORECASTING: A SURVEY

Ifebanjo, Temitope M. and Ogunleye, Olawole M. and Abiodun, Theresa Nkechi and Adebiyi, A. A. (2017) SOFT COMPUTING APROACHES TO STOCK FORECASTING: A SURVEY. Global Journal of Engineering Science and Research Management, 4 (5). pp. 107-131. ISSN 2349-4506

[img] Text
SurveyPaper_2017.pdf - Published Version

Download (657kB)
Official URL: http://www.gjesrm.com

Abstract

Soft computing techniques has been effectively applied in business, engineering, medical domain to solve problems in the past decade. However, this paper focuses on censoring the application of soft computing techniques for stock market prediction in the last decade (2010 -todate). Over a hundred published articles on stock price prediction were reviewed. The survey is done by grouping these published articles into: the stock market surveyed, input variable choices, summary of modelling technique applied, comparative studies, and summary of performance measures. This survey aptly shows that soft computing techniques are widely used and it has demonstrated widely acceptability to accurately use for predicting stock price andstock index behavior worldwide

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Depositing User: Mr DIGITAL CONTENT CREATOR LMU
Date Deposited: 24 Apr 2019 09:01
Last Modified: 24 Apr 2019 09:01
URI: https://eprints.lmu.edu.ng/id/eprint/2112

Actions (login required)

View Item View Item