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Scale-adjusted volatility and the Dow Jones index

Author

Listed:
  • Ellis, Craig
  • Hudson, Christopher

Abstract

This paper extends research by Batten and Ellis [Econ. Lett. 72 (2001) 291] to propose a simple model of scale-adjusted volatility which measures the extent to which the Gaussian scaling law mis-estimates long-horizon volatility. Applied to the Dow Jones industrial average, the results of our model show a dramatic improvement over the Gaussian scaling law in predicting long-horizon volatility. Our model provides a general framework for estimating scaled volatility that may be also applied to other fields of study where the Hurst exponent is commonly used.

Suggested Citation

  • Ellis, Craig & Hudson, Christopher, 2007. "Scale-adjusted volatility and the Dow Jones index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 374-386.
    • Handle: RePEc:eee:phsmap:v:378:y:2007:i:2:p:374-386
    DOI: 10.1016/j.physa.2006.12.008
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    Cited by:

    1. Auer, Benjamin R., 2016. "On time-varying predictability of emerging stock market returns," Emerging Markets Review, Elsevier, vol. 27(C), pages 1-13.
    2. Benjamin Rainer Auer, 2018. "Are standard asset pricing factors long-range dependent?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 42(1), pages 66-88, January.
    3. Jonathan A. Batten & Cetin Ciner & Brian M. Lucey & Peter G. Szilagyi, 2013. "The structure of gold and silver spread returns," Quantitative Finance, Taylor & Francis Journals, vol. 13(4), pages 561-570, March.

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