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Dynamics of a financial market index after a crash

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  • Lillo, Fabrizio
  • Mantegna, Rosario N

Abstract

We discuss the statistical properties of index returns in a financial market just after a major market crash. The observed non-stationary behavior of index returns is characterized in terms of the exceedances over a given threshold. This characterization is analogous to the Omori law originally observed in geophysics. By performing numerical simulations and theoretical modelling, we show that the non-linear behavior observed in real market crashes cannot be described by a GARCH(1,1) model. We also show that the time evolution of the Value at Risk observed just after a major crash is described by a power-law function lacking a typical scale.

Suggested Citation

  • Lillo, Fabrizio & Mantegna, Rosario N, 2004. "Dynamics of a financial market index after a crash," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 125-134.
  • Handle: RePEc:eee:phsmap:v:338:y:2004:i:1:p:125-134 DOI: 10.1016/j.physa.2004.02.034
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    1. Germano Mwabu, 2002. "Working Paper 38 - Health Development in Africa," Working Paper Series 172, African Development Bank.
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    Cited by:

    1. Viviana Fernandez & Brian M Lucey, 2006. "Portfolio management implications of volatility shifts: Evidence from simulated data," Documentos de Trabajo 219, Centro de Economía Aplicada, Universidad de Chile.
    2. Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
    3. Oh, Gabjin & Kim, Ho-yong & Ahn, Seok-Won & Kwak, Wooseop, 2015. "Analyzing the financial crisis using the entropy density function," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 464-469.
    4. Fernandez, Viviana & Lucey, Brian M., 2007. "Portfolio management under sudden changes in volatility and heterogeneous investment horizons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 612-624.
    5. Jiang, X.F. & Chen, T.T. & Zheng, B., 2013. "Time-reversal asymmetry in financial systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5369-5375.
    6. Hai-Chuan Xu & Wei Zhang & Yi-Fang Liu, 2013. "Short-term Market Reaction after Trading Halts in Chinese Stock Market," Papers 1309.1138, arXiv.org, revised Jun 2014.
    7. Xu, Hai-Chuan & Zhang, Wei & Liu, Yi-Fang, 2014. "Short-term market reaction after trading halts in Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 103-111.
    8. Tanya Araujo & Francisco Louca, 2007. "The geometry of crashes. A measure of the dynamics of stock market crises," Quantitative Finance, Taylor & Francis Journals, pages 63-74.
    9. Brée, David S. & Joseph, Nathan Lael, 2013. "Testing for financial crashes using the Log Periodic Power Law model," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 287-297.
    10. Mu, Guo-Hua & Zhou, Wei-Xing, 2008. "Relaxation dynamics of aftershocks after large volatility shocks in the SSEC index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5211-5218.
    11. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.
    12. Tanya Ara'ujo & Francisco Louc{c}~a, 2005. "The Geometry of Crashes - A Measure of the Dynamics of Stock Market Crises," Papers physics/0506137, arXiv.org, revised Jul 2005.

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