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Long-range dependence and market structure

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  • Cajueiro, Daniel O.
  • Tabak, Benjamin M.

Abstract

In this paper, we have found that although the Dow Jones Average Industrial Index does not possess long-range dependence in mean returns, individual stocks that form the index do. These results were obtained using the Local Whittle estimation procedure. Most stocks seem to be anti-persistent with Hurst exponents below 0.5, which is in line with mean reversion in the long run. Furthermore, open–open returns possess a stronger degree of anti-persistence than close–close returns due to market structure effects.

Suggested Citation

  • Cajueiro, Daniel O. & Tabak, Benjamin M., 2007. "Long-range dependence and market structure," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 995-1000.
  • Handle: RePEc:eee:chsofr:v:31:y:2007:i:4:p:995-1000
    DOI: 10.1016/j.chaos.2005.10.077
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    References listed on IDEAS

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    Cited by:

    1. Takami, Marcelo Yoshio & Tabak, Benjamin Miranda, 2008. "Interest rate option pricing and volatility forecasting: An application to Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 38(3), pages 755-763.
    2. Cajueiro, Daniel O. & Tabak, Benjamin M., 2008. "Testing for time-varying long-range dependence in real state equity returns," Chaos, Solitons & Fractals, Elsevier, vol. 38(1), pages 293-307.
    3. Batten, Jonathan A. & Ellis, Craig A. & Fethertson, Thomas A., 2008. "Sample period selection and long-term dependence: New evidence from the Dow Jones index," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1126-1140.
    4. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    5. Sensoy, A., 2013. "Time-varying long range dependence in market returns of FEAS members," Chaos, Solitons & Fractals, Elsevier, vol. 53(C), pages 39-45.
    6. Wang, Xiao-Tian & Zhu, En-Hui & Tang, Ming-Ming & Yan, Hai-Gang, 2010. "Scaling and long-range dependence in option pricing II: Pricing European option with transaction costs under the mixed Brownian–fractional Brownian model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 445-451.
    7. Sensoy, A., 2013. "Effects of monetary policy on the long memory in interest rates: Evidence from an emerging market," Chaos, Solitons & Fractals, Elsevier, vol. 57(C), pages 85-88.
    8. Liu, Li, 2014. "Cross-correlations between crude oil and agricultural commodity markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 293-302.
    9. Foad Shokrollahi, 2017. "The valuation of European option with transaction costs by mixed fractional Merton model," Papers 1702.00152, arXiv.org.
    10. Harrouni, S. & Guessoum, A., 2009. "Using fractal dimension to quantify long-range persistence in global solar radiation," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1520-1530.
    11. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Contemporaneous aggregation and long-memory property of returns and volatility in the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4844-4854.
    12. 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.
    13. Cajueiro, Daniel O. & Tabak, Benjamin M., 2009. "Testing for long-range dependence in the Brazilian term structure of interest rates," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1559-1573.
    14. Kang, Sang Hoon & Cheong, Chongcheul & Yoon, Seong-Min, 2010. "Long memory volatility in Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1425-1433.
    15. A. Sensoy & Benjamin M. Tabak, 2013. "How much random does European Union walk? A time-varying long memory analysis," Working Papers Series 342, Central Bank of Brazil, Research Department.

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