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Are Critical Slowing Down Indicators Useful to Detect Financial Crises?

Author

Listed:
  • Hayette Gatfaoui

    (IÉSEG School Of Management [Puteaux], LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Isabelle Nagot

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Philippe de Peretti

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this article, we consider financial markets as complex dynamical systems, and check whether the critical slowing down indicators can be used as early warning signals to detect a phase transition. Using various rolling windows, we analyze the evolution of three indicators: i) First-order autocorrelation, ii) Variance, and iii) Skewness. Using daily data for ten European stock exchanges plus the United States, and focusing on the Global Financial Crisis, our results are mitigated and depend both on the series used and the indicator. Using the main log-indices, critical slowing down indicators seem weak to predict the Global Financial Crisis. Using cumulative returns, for almost all countries, an increase in variance and skewness does precede the crisis. However, first-order autocorrelations of both log-indices and cumulative returns do not provide any useful information about the Global Financial Crisis. Thus, only some of the reported critical slowing down indicators may have informational content, and could be used as early warnings.

Suggested Citation

  • Hayette Gatfaoui & Isabelle Nagot & Philippe de Peretti, 2016. "Are Critical Slowing Down Indicators Useful to Detect Financial Crises?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01505202, HAL.
  • Handle: RePEc:hal:cesptp:halshs-01505202
    DOI: 10.2139/ssrn.2861258
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    References listed on IDEAS

    as
    1. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 905-939.
    2. Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
    3. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
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    Cited by:

    1. Haoyu Wen & Massimo Pica Ciamarra & Siew Ann Cheong, 2018. "How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-22, March.
    2. Chengyi Tu & Paolo DOdorico & Samir Suweis, 2018. "Critical slowing down associated with critical transition and risk of collapse in cryptocurrency," Papers 1806.08386, arXiv.org, revised Nov 2019.

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    More about this item

    Keywords

    Skewness; Variance; Phase transition; Critical slowing down; Autocorrelation; Crisis;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics

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