Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/62290
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Type: Conference paper
Title: Interpretable multi-criteria fuzzy rule based decision models for hedge fund management
Author: Ghandar, A.
Michalewicz, Z.
Zurbrugg, R.
Citation: Proceedings of the 2010 IEEE Congress on Evolutionary Computation, held in Barcelona, Spain, July 18-23 2010: pp.1-8
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
Series/Report no.: IEEE Congress on Evolutionary Computation
ISBN: 9781424481262
Conference Name: Congress on Evolutionary Computation (2010 : Barcelona, Spain)
Statement of
Responsibility: 
Adam Ghandar, Zbigniew Michalewicz and Ralf Zurbruegg
Abstract: This 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.
Rights: ©2010 IEEE
RMID: 0020102019
DOI: 10.1109/CEC.2010.5586198
Grant ID: http://purl.org/au-research/grants/arc/DP1096053
Published version: http://www.informatik.uni-trier.de/~ley/db/conf/cec/cec2010.html
Appears in Collections:Business School publications

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