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
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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 |
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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 |
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