DocumentCode :
1640431
Title :
Evaluation of intelligent quantitative hedge fund management
Author :
Buckley, Muneer ; Ghandar, Adam ; Michalewicz, Zbigniew ; Zurbruegg, Ralf
Author_Institution :
Sch. of Comput. Sci., Univ. of Adelaide, Adelaide, SA
fYear :
2009
Firstpage :
2135
Lastpage :
2142
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.
Keywords :
financial management; fuzzy set theory; investment; equity positions; fuzzy rule base specification; intelligent quantitative hedge fund management; intelligent recommendation strategy implementation; investment portfolio; liquidity crisis; market downturns; Australia; Computer science; Costs; Crisis management; Information technology; Investments; Marketing and sales; Portfolios; Protection; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
Type :
conf
DOI :
10.1109/CEC.2009.4983205
Filename :
4983205
Link To Document :
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