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|dc.identifier.citation||Nature-inspired informatics for intelligent applications and knowledge discovery: implications in business, science, and engineering, 2009 / Raymond Chiong, (ed./s), pp.26-48||-|
|dc.description.abstract||<jats:p>There is a great need for accurate predictions of foreign exchange rates. Many industries participate in foreign exchange scenarios with little idea where the exchange rate is moving, and what the optimum decision to make at any given time is. Although current economic models do exist for this purpose, improvements could be made in both their flexibility and adaptability. This provides much room for models that do not suffer from such constraints. This chapter proposes the use of a genetic program (GP) to predict future foreign exchange rates. The GP is an extension of the DyFor GP tailored for forecasting in dynamic environments. The GP is tested on the Australian / US (AUD/USD) exchange rate and compared against a basic economic model. The results show that the system has potential in forecasting long term values, and may do so better than established models. Further improvements are also suggested.</jats:p>||-|
|dc.description.statementofresponsibility||Muneer Buckley and Zbigniew Michalewicz and Ralf Zurbruegg||-|
|dc.rights||Chapter: Copyright © 2010, IGI Global; Book (print): Copyright © 2009 by IGI Global||-|
|dc.title||An application of genetic programming to forecasting foreign exchanges rates||-|
|dc.identifier.orcid||Zurbrugg, R. [0000-0002-8652-0028]||-|
|Appears in Collections:||Aurora harvest|
Computer Science publications
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