| Using GAs to balance technical indicators on stock picking for financial portfolio composition |
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Genetic And Evolutionary Computation Conference
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Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
table of contents
Montreal, Québec, Canada
SESSION: Late-breaking papers
table of contents
Pages: 2041-2046
Year of Publication: 2009
ISBN:978-1-60558-505-5
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Authors
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António Gorgulho
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Instituto de Telecomunicações, Lisboa, Portugal
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Rui Neves
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Instituto de Telecomunicações, Lisboa, Portugal
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Nuno Horta
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Instituto de Telecomunicações, Lisboa, Portugal
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ABSTRACT
The building of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market's domain. The presented paper proposes a potential system, based on those techniques, which aims to generate a profitable portfolio by using technical analysis indicators. In order to validate the designed application we performed a comparison against the Buy & Hold strategy and a purely random one. The preliminary results are promising once; the developed approach easily beats the remaining methodologies during Bull Market periods.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Branke, J., et al., Portfolio optimization with an envelope-based multi-objective evolutionary algorithm. European Journal of Operational Research, 2008.
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3
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Canegrati, E., A Non-Random Walk down Canary Wharf, in MPRA Paper. 2008, University Library of Munich.
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4
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Coello, C., A survey of constraint handling techniques used with evolutionary algorithms. 1999, Laboratorio Nacional de Informática Avanzada.
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5
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Coello, C.A.C. and N.C. Cortés, Use of Emulations of the Immune System to Handle Constraints in Evolutionary Algorithms, in Intelligent Engineering Systems through Artificial Neural Networks. 2001. p. 141--146.
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6
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Pablo Fernández-Blanco , Diego J. Bodas-Sagi , Francisco J. Soltero , J. Ignacio Hidalgo, Technical market indicators optimization using evolutionary algorithms, Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation, July 12-16, 2008, Atlanta, GA, USA
[doi> 10.1145/1388969.1388989]
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Irwin, S.H. and C.H. Park, What do we know about the profitability of technical analysis? Journal of Economic Surveys, 2007. 21: p. 786--826.
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8
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Maginn, J.L., et al., Managing Investment Portfolios: A Dynamic Process. 3rd ed, ed. C.I.I. Series. 2007: Wiley.
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9
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Malkiel, B., A Random Walk Down Wall Street. 1973: W. W. Norton & Company.
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10
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Markowitz, H., Portfolio Selection. The Journal of Finance, 1952. 7: p. 77--91.
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11
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Murphy, J.J., Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications. 1999: Prentice Hall Press.
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12
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13
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Skolpadungket, P., K. Dahal, and N. Harnpornchai, Portfolio optimization using multi-objective genetic algorithms, in IEEE Congress on Evolutionary Computation. 2007.
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14
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Sumathi, S., T. Hamsapriya, and P. Surekha, Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab. 2008: Springer Verlag.
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15
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Wagman, L., Stock Portfolio Evaluation: An Application of Genetic-Programming-Based Technical Analysis, in Genetic Algorithms and Genetic Programming at Stanford. 2003, Standford Bookstore. p. 213--220.
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