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Stock Market Prediction using Multi Expression
Programming
57. Crina Grosan, Ajith
Abraham, Sang Yong Han, Vitorino Ramos, Stock Market Prediction using
Multi Expression Programming, in ALEA´05, Workshop on
Artificial
Life and Evolutionary Algorithms at EPIA´05 - Proc. of the 12th
Portuguese Conference on Artificial Intelligence, C. Bento, A. Cardoso
and G. Dias (Eds.), IEEE Press,
pp. 73-78, 2005.
PDF
file: paper
(169 Kb)
Abstract: The use of intelligent systems
for stock market predictions has been widely established. In this paper
we introduce a genetic programming technique (called Multi-Expression
programming) for the prediction of two stock indices. The performance
is then compared with an artifcial neural network trained using
Levenberg-Marquardt algorithm, support vector machine, Takagi-Sugeno
neuro-fuzzy model, a difference boosting neural network. We considered
Nasdaq-100 index of Nasdaq Stock MarketSM and the S&P CNX NIFTY
stock index as test data.
Keywords: Stock Market Prediction, Multi Expression Programming,
Nasdaq-100, CNX NIFTY stock index.
Cited
by:
º
William
Wilson, Phil Birkin and Uwe Aickelin, "The Motif Tracking Algorithm",
in International Journal of Automation and Computing 04(1), January
2007.
º Zhang Jianwei, Zhang Yingjiang,
Wang Zongyue, Lin Zhiyi and Huang Zhang Can, "Study on Multi-Expression
Programming", in Journal of Wuhan University of Technology (Information
& Management Enginnering), Vol.29, No.2 pp. 57-61, 2007.
º William
O. Wilson, Phil Birkin and Uwe Aickelin, "Price Trackers Inspired by
Immune Memory", Proc.s of the 5th Int. Conf. on Artificial Immune
Systems (ICARIS 2006), LNCS, Springer-Verlag, Oeiras, Portugal, 2006.
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