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Waiting time distributions of the volatility in the Italian MIB30 index: Clustering or Poisson functions?

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  • Greco, Antonella
  • Sorriso-Valvo, Luca
  • Carbone, Vincenzo
  • Cidone, Stefano

Abstract

We investigate the time behaviour of the Italian MIB30 stock index collected every minute during two months in the period from May 17, 2006, up to July 24, 2006. We find short-range correlations in the price returns and, on the contrary, a long persistent time lag and slow decay in the autocorrelation functions of volatility. Besides, we find that the probability density functions (PDFs) of returns show fat tails, which are well fit by the log-normal model of Castaing [B. Castaing, Y. Gagne, E.J. Hopfinger, Physica D 46 (1990) 177], and a convergence toward a normal distribution for large time scales; we also find that the PDFs of volatility, for short time horizons, fit better with a log-normal distribution than with a Gaussian. Most of these features characterize the indexes and stocks of the largest American, European and Asian markets.

Suggested Citation

  • Greco, Antonella & Sorriso-Valvo, Luca & Carbone, Vincenzo & Cidone, Stefano, 2008. "Waiting time distributions of the volatility in the Italian MIB30 index: Clustering or Poisson functions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4272-4284.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:16:p:4272-4284
    DOI: 10.1016/j.physa.2008.03.007
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    References listed on IDEAS

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    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
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    2. Zhi-Qiang Jiang & Gang-Jin Wang & Askery Canabarro & Boris Podobnik & Chi Xie & H. Eugene Stanley & Wei-Xing Zhou, 2018. "Short term prediction of extreme returns based on the recurrence interval analysis," Quantitative Finance, Taylor & Francis Journals, vol. 18(3), pages 353-370, March.
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    4. Zhi-Qiang Jiang & Askery Canabarro & Boris Podobnik & H. Eugene Stanley & Wei-Xing Zhou, 2016. "Early warning of large volatilities based on recurrence interval analysis in Chinese stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 16(11), pages 1713-1724, November.
    5. Xie, Wen-Jie & Jiang, Zhi-Qiang & Zhou, Wei-Xing, 2014. "Extreme value statistics and recurrence intervals of NYMEX energy futures volatility," Economic Modelling, Elsevier, vol. 36(C), pages 8-17.
    6. Zhou, Weijie & Wang, Zhengxin & Guo, Haiming, 2016. "Modelling volatility recurrence intervals in the Chinese commodity futures market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 514-525.

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