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Return performance volatility and adaptation in an automated technical analysis approach to portfolio management

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Listed:
  • Adam Ghandar
  • Zbigniew Michalewicz
  • Ralf Zurbruegg

Abstract

This paper discusses the design of a quantitative computational intelligence portfolio management system and evaluates the advantages of some adaptive mechanisms to enable the system to adjust its management approach as market conditions change. A detailed analysis of the performance of the system outside is also provided. It is found that an adaptive methodology where trading rules are able to adjust to market conditions performs better, having greater excess returns and lower volatility than a fixed rule approach. We consider several performance metrics, including portfolio alpha and information content. Copyright © 2009 John Wiley & Sons, Ltd.

Suggested Citation

  • Adam Ghandar & Zbigniew Michalewicz & Ralf Zurbruegg, 2009. "Return performance volatility and adaptation in an automated technical analysis approach to portfolio management," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(1‐2), pages 127-146, January.
    • Handle: RePEc:wly:isacfm:v:16:y:2009:i:1-2:p:127-146
    DOI: 10.1002/isaf.297
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    References listed on IDEAS

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    1. Fama, Eugene F, 1972. "Components of Investment Performance," Journal of Finance, American Finance Association, vol. 27(3), pages 551-567, June.
    2. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    3. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    4. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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