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Ordinary Shares, Exotic Methods:Financial Forecasting Using Data Mining Techniques

Author

Listed:
  • Francis Eng-Hock Tay

    (National University of Singapore)

  • Lixiang Shen

    (National University of Singapore)

  • Lijuan Cao

    (Institute of High Performance Computing, Singapore)

Abstract

Exotic methods refer to specific functions within general soft computing methods such as genetic algorithms, neural networks and rough sets theory. They are applied to ordinary shares for a variety of financial purposes, such as portfolio selection and optimization, classification of market states, forecasting of market states and data mining. This is in contrast to the wide spectrum of work done on exotic financial instruments, wherein advanced mathematics is used to construct financial instruments for hedging risks and for investment.

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Suggested Citation

  • Francis Eng-Hock Tay & Lixiang Shen & Lijuan Cao, 2003. "Ordinary Shares, Exotic Methods:Financial Forecasting Using Data Mining Techniques," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 5027, December.
    • Handle: RePEc:wsi:wsbook:5027
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    Cited by:

    1. Tangian, Andranik, 2008. "Predicting DAX trends from Dow Jones data by methods of the mathematical theory of democracy," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1632-1662, March.
    2. Valeriy V. Gavrishchaka, 2006. "Boosting-Based Framework For Portfolio Strategy Discovery And Optimization," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 315-330.

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