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On spurious anti-persistence in the US stock indices

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  • Kristoufek, Ladislav

Abstract

We reexamine the results of Serletis and Rosenberg [Serletis A, Rosenberg A. Mean reversion in the US stock market. Chaos, Solitons and Fractals 2009;40:2007–2015.] who claim that the returns of the most important US stock indices (DJI, NASDAQ, NYSE and S&P500) are strongly anti-persistent and thus mean reverting. We apply various methods to detect long-range dependence – detrending moving average, detrended fluctuation analysis, generalized Hurst exponent approach, classical rescaled range analysis and modified rescaled range analysis. We show that there are no signs of anti-persistence in any of the indices. Moreover, we discuss that the authors did not find any anti-persistence but rather showed returns of the said assets do not follow the scaling power law around their moving average with varying window length. Anti-persistence is thus spurious and due to wrong application of detrending moving average method.

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  • Kristoufek, Ladislav, 2010. "On spurious anti-persistence in the US stock indices," Chaos, Solitons & Fractals, Elsevier, vol. 43(1), pages 68-78.
    • Handle: RePEc:eee:chsofr:v:43:y:2010:i:1:p:68-78
    DOI: 10.1016/j.chaos.2010.09.001
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    References listed on IDEAS

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    Cited by:

    1. Dilip Kumar & S. Maheswaran, 2015. "Long memory in Indian exchange rates: an application of power-law scaling analysis," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 8(1-2), pages 90-107, July.
    2. Kristoufek, Ladislav, 2012. "How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(17), pages 4252-4260.

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