Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/58013
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Type: Conference paper
Title: Evaluation of Intelligent Quantitative Hedge Fund Management
Author: Buckley, M.
Ghandar, A.
Michalewicz, Z.
Zurbrugg, R.
Citation: Proceedings of the IEEE Congress on Evolutionary Computation, 2009: pp.2135-2142
Publisher: IEEE
Publisher Place: USA
Issue Date: 2009
Series/Report no.: IEEE Congress on Evolutionary Computation
ISBN: 9781424429585
Conference Name: IEEE Congress on Evolutionary Computation (2009 : Trondheim, Norway)
Statement of
Responsibility: 
Muneer Buckley, Adam Ghandar, Zbigniew Michalewicz, Ralf Zurbruegg
Abstract: This paper examines an intelligent recommendation strategy implementation for managing a long short hedge fund and reports on performance during market conditions at the onset of the liquidity crisis. A hedge fund utilizes long and short trading to manage an investment portfolio consisting of allocations to cash and share equity positions. This results in a combined long short portfolio that is leveraged to obtain a potentially greater market exposure with borrowed cash from short selling and is also hedged to protect against market downturns. The paper also examines effects of parameters for fuzzy rule base specification on trading performance.
Rights: © 2009 IEEE
RMID: 0020095933
DOI: 10.1109/CEC.2009.4983205
Published version: http://www.informatik.uni-trier.de/~ley/db/conf/cec/cec2009.html
Appears in Collections:Computer Science publications

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