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Strategy Change and Wealth Accumulation: An Analysis of S&P 500 Data

Author

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  • Weihong HUANG

    (Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, 14 Nanyang Drive, Singapore 637332)

  • Yu ZHANG

    (Division of Economics, School of Humanities and Social Sciences, Nanyang Technological University, 14 Nanyang Drive, Singapore 637332)

Abstract

This paper studies investors' strategy change frequency and their wealth accumulation by financial investments. Artificial investors are put into a real stock market. They trade S&P 500 following common strategies in practice. Fundamental analysis generally surpasses technical analysis in all market situa- tions except boom periods. Though investors' strategy change behavior, which is driven by the past performance of strategies, seems reasonable, a faster strat- egy change does not guarantee a higher final wealth. Active strategy change hurts investor' wealth in bear markets and in markets with major trend rever- sals. In bull markets, both fast and slow strategy change behaviors work better than a moderate speed of strategy change. A detailed decomposition of wealth accumulation via financial investment shows the dependence of wealth on in- vestors' past transactions. This may explain the relation between investors' strategy change frequency and their wealth.

Suggested Citation

  • Weihong HUANG & Yu ZHANG, 2015. "Strategy Change and Wealth Accumulation: An Analysis of S&P 500 Data," Economic Growth Centre Working Paper Series 1502, Nanyang Technological University, School of Social Sciences, Economic Growth Centre.
    • Handle: RePEc:nan:wpaper:1502
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    References listed on IDEAS

    as
    1. Day, Richard H. & Huang, Weihong, 1990. "Bulls, bears and market sheep," Journal of Economic Behavior & Organization, Elsevier, vol. 14(3), pages 299-329, December.
    2. Chiarella, Carl & He, Xue-Zhong & Hommes, Cars, 2006. "A dynamic analysis of moving average rules," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1729-1753.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    5. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    6. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    7. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    8. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    9. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
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    More about this item

    Keywords

    Financial Investment Strategy; Strategy Change Frequency; Wealth Accumulation; Standard & Poor's 500;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G19 - Financial Economics - - General Financial Markets - - - Other

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