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Long-range correlations in time series generated by time-fractional diffusion: A numerical study

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  • Barbieri, Davide
  • Vivoli, Alessandro

Abstract

Time series models showing power law tails in autocorrelation functions are common in econometrics. A special non-Markovian model for such kind of time series is provided by the random walk introduced by Gorenflo et al. as a discretization of time fractional diffusion. The time series so obtained are analyzed here from a numerical point of view in terms of autocorrelations and covariance matrices.

Suggested Citation

  • Barbieri, Davide & Vivoli, Alessandro, 2005. "Long-range correlations in time series generated by time-fractional diffusion: A numerical study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 190-198.
    • Handle: RePEc:eee:phsmap:v:355:y:2005:i:1:p:190-198
    DOI: 10.1016/j.physa.2005.02.083
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    References listed on IDEAS

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    1. Scalas, Enrico & Gorenflo, Rudolf & Mainardi, Francesco, 2000. "Fractional calculus and continuous-time finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 284(1), pages 376-384.
    2. Mainardi, Francesco & Raberto, Marco & Gorenflo, Rudolf & Scalas, Enrico, 2000. "Fractional calculus and continuous-time finance II: the waiting-time distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 468-481.
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