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Time and scale Hurst exponent analysis for financial markets

Author

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  • Matos, José A.O.
  • Gama, Sílvio M.A.
  • Ruskin, Heather J.
  • Sharkasi, Adel Al
  • Crane, Martin

Abstract

We use a new method of studying the Hurst exponent with time and scale dependency. This new approach allows us to recover the major events affecting worldwide markets (such as the September 11th terrorist attack) and analyze the way those effects propagate through the different scales. The time–scale dependence of the referred measures demonstrates the relevance of entropy measures in distinguishing the several characteristics of market indices: “effects” include early awareness, patterns of evolution as well as comparative behaviour distinctions in emergent/established markets.

Suggested Citation

  • Matos, José A.O. & Gama, Sílvio M.A. & Ruskin, Heather J. & Sharkasi, Adel Al & Crane, Martin, 2008. "Time and scale Hurst exponent analysis for financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3910-3915.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:15:p:3910-3915
    DOI: 10.1016/j.physa.2008.01.060
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    References listed on IDEAS

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    1. Grech, D & Mazur, Z, 2004. "Can one make any crash prediction in finance using the local Hurst exponent idea?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(1), pages 133-145.
    2. Matos, José A.O. & Gama, Sı́lvio M.A. & Ruskin, Heather J. & Duarte, José A.M.S., 2004. "An econophysics approach to the Portuguese Stock Index—PSI-20," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 342(3), pages 665-676.
    3. Sharkasi, Adel & Crane, Martin & Ruskin, Heather J. & Matos, Jose A., 2006. "The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(2), pages 511-521.
    4. Carbone, A. & Castelli, G. & Stanley, H.E., 2004. "Time-dependent Hurst exponent in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 267-271.
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