Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/62290
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dc.contributor.authorGhandar, A.en
dc.contributor.authorMichalewicz, Z.en
dc.contributor.authorZurbrugg, R.en
dc.date.issued2010en
dc.identifier.citationProceedings of the 2010 IEEE Congress on Evolutionary Computation, held in Barcelona, Spain, July 18-23 2010: pp.1-8en
dc.identifier.isbn9781424481262en
dc.identifier.urihttp://hdl.handle.net/2440/62290-
dc.description.abstractThis paper describes an approach to constructing fuzzy rules for predictive modeling that involves a local search heuristic and an evolutionary algorithm. This approach is applied for learning strategies to manage a portfolio that comprises positions in the share market. We provide experimental results comparing the approach to random strategies and the market index. A non-linear prediction model that relates asset performance to a large set of explanatory variables is represented with fuzzy rules. Rulebases are combined to build multi-criteria recommendations for trading decisions that consider different forecast horizons and both risk and return criteria.en
dc.description.statementofresponsibilityAdam Ghandar, Zbigniew Michalewicz and Ralf Zurbrueggen
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofseriesIEEE Congress on Evolutionary Computationen
dc.rights©2010 IEEEen
dc.source.urihttp://www.informatik.uni-trier.de/~ley/db/conf/cec/cec2010.htmlen
dc.titleInterpretable multi-criteria fuzzy rule based decision models for hedge fund managementen
dc.typeConference paperen
dc.identifier.rmid0020102019en
dc.contributor.conferenceCongress on Evolutionary Computation (2010 : Barcelona, Spain)en
dc.identifier.doi10.1109/CEC.2010.5586198en
dc.publisher.placeUSAen
dc.relation.granthttp://purl.org/au-research/grants/arc/DP1096053en
dc.identifier.pubid32716-
pubs.library.collectionBusiness School publicationsen
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidZurbrugg, R. [0000-0002-8652-0028]en
Appears in Collections:Business School publications

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