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An Exotic Long-Term Pattern in Stock Price Dynamics

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  • Jianrong Wei
  • Jiping Huang

Abstract

Background: To accurately predict the movement of stock prices is always of both academic importance and practical value. So far, a lot of research has been reported to help understand the behavior of stock prices. However, some of the existing theories tend to render us the belief that the time series of stock prices are unpredictable on a long-term timescale. The question arises whether the long-term predictability exists in stock price dynamics. Methodology/Principal Findings: In this work, we analyze the price reversals in the US stock market and the Chinese stock market on the basis of a renormalization method. The price reversals are divided into two types: retracements (the downward trends after upward trends) and rebounds (the upward trends after downward trends), of which the intensities are described by dimensionless quantities, and , respectively. We reveal that for both mature and emerging markets, the distribution of either retracements or rebounds shows two characteristic values, 0.335 and 0.665, both of which are robust over the long term. Conclusions/Significance: The methodology presented here provides a way to quantify the stock price reversals. Our findings strongly support the existence of the long-term predictability in stock price dynamics, and may offer a hint on how to predict the long-term movement of stock prices.

Suggested Citation

  • Jianrong Wei & Jiping Huang, 2012. "An Exotic Long-Term Pattern in Stock Price Dynamics," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-5, December.
  • Handle: RePEc:plo:pone00:0051666
    DOI: 10.1371/journal.pone.0051666
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    1. Y. Shapira & D. Y. Kenett & E. Ben-Jacob, 2009. "The Index cohesive effect on stock market correlations," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 72(4), pages 657-669, December.
    2. Petre Caraiani, 2012. "Evidence of Multifractality from Emerging European Stock Markets," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    3. Miguel A. Fuentes & Austin Gerig & Javier Vicente, 2009. "Universal Behavior of Extreme Price Movements in Stock Markets," Papers 0912.5448, arXiv.org.
    4. Hsieh, David A, 1991. "Chaos and Nonlinear Dynamics: Application to Financial Markets," Journal of Finance, American Finance Association, vol. 46(5), pages 1839-1877, December.
    5. Sukanto Bhattacharya & Kuldeep Kumar, 2006. "A Computational Exploration of the Efficacy of Fibonacci Sequences in Technical Analysis and Trading," Annals of Economics and Finance, Society for AEF, vol. 7(1), pages 185-196, May.
    6. Kunyu Song & Kenan An & Guang Yang & Jiping Huang, 2012. "Risk-Return Relationship in a Complex Adaptive System," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-8, March.
    7. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    8. Dror Y Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2012. "Evolvement of Uniformity and Volatility in the Stressed Global Financial Village," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    9. Thomas Lux & Michele Marchesi, 2000. "Volatility Clustering In Financial Markets: A Microsimulation Of Interacting Agents," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 675-702.
    10. Pai, Ping-Feng & Lin, Chih-Sheng, 2005. "A hybrid ARIMA and support vector machines model in stock price forecasting," Omega, Elsevier, vol. 33(6), pages 497-505, December.
    11. Miguel A Fuentes & Austin Gerig & Javier Vicente, 2009. "Universal Behavior of Extreme Price Movements in Stock Markets," PLOS ONE, Public Library of Science, vol. 4(12), pages 1-4, December.
    12. J. Doyne Farmer & Duncan Foley, 2009. "The economy needs agent-based modelling," Nature, Nature, vol. 460(7256), pages 685-686, August.
    13. Dror Y. Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2010. "Dynamics of Stock Market Correlations," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 330-340, November.
    14. Mantegna, Rosario N & Palágyi, Zoltán & Stanley, H.Eugene, 1999. "Applications of statistical mechanics to finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 274(1), pages 216-221.
    15. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    16. Dror Y Kenett & Yoash Shapira & Asaf Madi & Sharron Bransburg-Zabary & Gitit Gur-Gershgoren & Eshel Ben-Jacob, 2011. "Index Cohesive Force Analysis Reveals That the US Market Became Prone to Systemic Collapses Since 2002," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-8, April.
    17. Johnson, Neil F. & Jefferies, Paul & Hui, Pak Ming, 2003. "Financial Market Complexity," OUP Catalogue, Oxford University Press, number 9780198526650.
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    Cited by:

    1. Lu Liu & Jianrong Wei & Jiping Huang, 2013. "Scaling and Volatility of Breakouts and Breakdowns in Stock Price Dynamics," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-6, December.
    2. Zhang, H.S. & Shen, X.Y. & Huang, J.P., 2016. "Pattern of trends in stock markets as revealed by the renormalization method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 340-346.

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