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Scaling in the market of futures

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  • Scalas, Enrico

Abstract

The price time series of the Italian government bonds (BTP) futures is studied by means of scaling concepts originally developed for random walks in statistical physics. The series of overnight price differences is mapped onto a one-dimensional random walk: the bond walk. The analysis of the root mean square fluctuation function and of the auto-correlation function indicates the absence of both short- and long-range correlations in the bond walk. A simple Monte Carlo simulation of a random walk with trinomial probability distribution is able to reproduce the main features of the bond walk.

Suggested Citation

  • Scalas, Enrico, 1998. "Scaling in the market of futures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 253(1), pages 394-402.
    • Handle: RePEc:eee:phsmap:v:253:y:1998:i:1:p:394-402
    DOI: 10.1016/S0378-4371(97)00652-3
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    Cited by:

    1. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
    2. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.
    3. Ioannis P. Antoniades & Giuseppe Brandi & L. G. Magafas & T. Di Matteo, 2020. "The use of scaling properties to detect relevant changes in financial time series: a new visual warning tool," Papers 2010.08890, arXiv.org, revised Dec 2020.
    4. Zhuang, Xin-tian & Huang, Xiao-yuan & Sha, Yan-li, 2004. "Research on the fractal structure in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 293-305.
    5. Antoniades, I.P. & Brandi, Giuseppe & Magafas, L. & Di Matteo, T., 2021. "The use of scaling properties to detect relevant changes in financial time series: A new visual warning tool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    6. Kang, Sang Hoon & Yoon, Seong-Min, 2007. "Long memory properties in return and volatility: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 591-600.

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