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Correlations in the Bond–Future Market

Author

Listed:
  • Gianaurelio Cuniberti

    (MPI fuer Physik Komplexer Systeme, Dresden, Germany)

  • Marco Raberto

    (Universita' di Genova, Genova, Italy)

  • Enrico Scalas

    (Universita' del Piemonte Orientale, Alessandria, Italy)

Abstract

We analyze the time series of overnight returns for the bund and btp futures exchanged at liffe (London). The overnight returns of both assets are mapped onto a one–dimensional symbolic–dynamics random walk: The “bond walk”. During the considered period (October 1991—January 1994) the bund–future market opened earlier than the btp–future one. The cross correlations between the two bond walks, as well as estimates of the conditional probability, show that they are not independent; however each walk can be modeled by means of a trinomial probability distribution. Monte Carlo simulations confirm that it is necessary to take into account the bivariate dependence in order to properly reproduce the statistical properties of the real–world data. Various investment strategies have been devised to exploit the “prior” information obtained by the aforementioned analysis.

Suggested Citation

  • Gianaurelio Cuniberti & Marco Raberto & Enrico Scalas, 2004. "Correlations in the Bond–Future Market," Finance 0411005, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0411005
    Note: Type of Document - pdf; pages: 10. Preprint pdf version of a paper published in Physica A, vol.269, no.1, p.90-7, 1 July 1999.
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    Cited by:

    1. Zheng, Zhiyong & Lu, Yunfan & Zhang, Junhuan, 2022. "Multiscale complexity fluctuation behaviours of stochastic interacting cryptocurrency price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    2. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.

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    JEL classification:

    • G - Financial Economics

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