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https://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 |
DOI: | 10.1109/CEC.2010.5586198 |
Grant ID: | http://purl.org/au-research/grants/arc/DP1096053 http://purl.org/au-research/grants/arc/DP1096053 |
Published version: | http://dx.doi.org/10.1109/cec.2010.5586198 |
Appears in Collections: | Aurora harvest Business School publications |
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