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Study of Speculative Bubbles: The Contribution of Approximate Entropy

Author

Listed:
  • Imen Mahmoud

    (Faculty of Economic Sciences and Management of Tunis, Tunisia)

  • Kamel Naoui

    (Business School of Tunis, Tunisia)

  • Hatem Jemmali

    (Faculty of Economic Sciences and Management of Tunis, Tunisia)

Abstract

The purpose of this article is to provide a survey of the presence of speculative bubbles. The empirical study uses a new technique borrowed from statistical physics suggested by Pincus (1991). We use approximate entropy to test the presence of bubbles in the Tunisian and French markets. To this end, weekly data of primary stock markets of the countries under study (Tunisia, France) were used. Since our aim is to study the crisis, data before and after the crash was also analyzed. The crisis decade has been identified as the sample period for our study. More specifically, we consider weekly data over the 2002 to 2012 period. The obtained results confirm the presence of a speculative bubble during the "subprime" crisis (2008) in the two markets.

Suggested Citation

  • Imen Mahmoud & Kamel Naoui & Hatem Jemmali, 2013. "Study of Speculative Bubbles: The Contribution of Approximate Entropy," International Journal of Economics and Financial Issues, Econjournals, vol. 3(3), pages 683-693.
  • Handle: RePEc:eco:journ1:2013-03-11
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    Citations

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    Cited by:

    1. Batra, Luckshay & Taneja, H.C., 2020. "Evaluating volatile stock markets using information theoretic measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    2. Zapart, Christopher A., 2015. "Econophysics: A challenge to econometricians," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 318-327.

    More about this item

    Keywords

    Speculative bubbles; approximate entropy; financial crashes; speculation.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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