EconPapers    
Economics at your fingertips  
 

Financial market prediction system with Evolino neural network and Delphi method

Nijolė Maknickienė and Algirdas Maknickas

Journal of Business Economics and Management, 2013, vol. 14, issue 2, 403-413

Abstract: Use of artificial intelligence systems in forecasting financial markets requires a reliable and simple model that would ensure profitable growth. The model presented in the paper combines Evolino recurrent neural networks with orthogonal data inputs and the Delphi expert evaluation method for its investment portfolio decision making process. A statistical study demonstrates the reliability of the model and describes its accuracy. Capabilities of the model are demonstrated using a trading simulation.

Date: 2013
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.3846/16111699.2012.729532 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jbemgt:v:14:y:2013:i:2:p:403-413

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TBEM20

DOI: 10.3846/16111699.2012.729532

Access Statistics for this article

Journal of Business Economics and Management is currently edited by Izolda Joksiene, Romualdas Ginevicius and Ieva Meidute

More articles in Journal of Business Economics and Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:jbemgt:v:14:y:2013:i:2:p:403-413