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Identifying financial crises in real time

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  • Eder Lucio Fonseca
  • Fernando F. Ferreira
  • Paulsamy Muruganandam
  • Hilda A. Cerdeira
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    Abstract

    Following the thermodynamic formulation of multifractal measure that was shown to be capable of detecting large fluctuations at an early stage, here we propose a new index which permits us to distinguish events like financial crisis in real time . We calculate the partition function from where we obtain thermodynamic quantities analogous to free energy and specific heat. The index is defined as the normalized energy variation and it can be used to study the behavior of stochastic time series, such as financial market daily data. Famous financial market crashes - Black Thursday (1929), Black Monday (1987) and Subprime crisis (2008) - are identified with clear and robust results. The method is also applied to the market fluctuations of 2011. From these results it appears as if the apparent crisis of 2011 is of a different nature from the other three. We also show that the analysis has forecasting capabilities.

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    File URL: http://arxiv.org/pdf/1204.3136
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1204.3136.

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    Date of creation: Apr 2012
    Date of revision: Nov 2012
    Publication status: Published in Physica A (2012)
    Handle: RePEc:arx:papers:1204.3136

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    Web page: http://arxiv.org/

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    1. Benoit Mandelbrot, 1963. "The Variation of Certain Speculative Prices," The Journal of Business, University of Chicago Press, vol. 36, pages 394.
    2. Sun, Xia & Chen, Huiping & Yuan, Yongzhuang & Wu, Ziqin, 2001. "Predictability of multifractal analysis of Hang Seng stock index in Hong Kong," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 473-482.
    3. O. A. Rosso & C. Masoller, 2009. "Detecting and quantifying temporal correlations in stochastic resonance via information theory measures," The European Physical Journal B - Condensed Matter and Complex Systems, Springer, vol. 69(1), pages 37-43, May.
    4. Domino, Krzysztof, 2011. "The use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(1), pages 98-109.
    5. Ivanova, K. & Shirer, H.N. & Clothiaux, E.E. & Kitova, N. & Mikhalev, M.A. & Ackerman, T.P. & Ausloos, M., 2002. "A case study of stratus cloud base height multifractal fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 518-532.
    6. Dion Harmon & Marcus A. M. de Aguiar & David D. Chinellato & Dan Braha & Irving R. Epstein & Yaneer Bar-Yam, 2011. "Predicting economic market crises using measures of collective panic," Papers 1102.2620, arXiv.org.
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