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The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange

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  • Domino, Krzysztof
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    Abstract

    The local properties of the time series of the evolution of share prices of 126 significant companies traded on the Warsaw Stock Exchange during the period between 1991–2008 have been investigated. The analysis was applied to daily financial returns. I have used the local DFA to obtain the Hurst exponent (diffusion coefficient) while searching for negative correlations by which changes of long-term trends would be effected. A certain evidence, proving that after the signature of anti-correlation–the drop in the Hurst exponent–the change in the trend and in the return rate of an investment is probable, was pointed out. Hence after further investigation this method may be useful as a part of an investment strategy. As the Warsaw Stock Exchange is relatively smaller and younger than other significant world Stock Exchanges–and as the developing market is less efficient–the generalization for others markets needs further investigation.

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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 390 (2011)
    Issue (Month): 1 ()
    Pages: 98-109

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    Handle: RePEc:eee:phsmap:v:390:y:2011:i:1:p:98-109

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

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    Keywords: Econophysics; Time series; Warsaw Stock Exchange; Hurst exponent; Detrendet fluctuation analysis; Statistical research;

    References

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    Cited by:
    1. Domino, Krzysztof, 2012. "The use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 156-169.
    2. Caraiani, Petre, 2012. "Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(13), pages 3629-3637.
    3. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis And The Global Financial Crisis: Scaling, Investment Horizons And Liquidity," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 15(06), pages 1250065-1-1.
    4. Eder Lucio Fonseca & Fernando F. Ferreira & Paulsamy Muruganandam & Hilda A. Cerdeira, 2012. "Identifying financial crises in real time," Papers 1204.3136, arXiv.org, revised Nov 2012.
    5. da Fonseca, Eder Lucio & Ferreira, Fernando F. & Muruganandam, Paulsamy & Cerdeira, Hilda A., 2013. "Identifying financial crises in real time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1386-1392.

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