Recurrence analysis near the NASDAQ crash of April 2000

  • Annalisa Fabretti
  • Marcel Ausloos


Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are signal numerical analysis methodologies able to work with non linear dynamical systems and non stationarity. Moreover they well evidence changes in the states of a dynamical system. It is shown that RP and RQA detect the critical regime in financial indices (in analogy with phase transitions) before a bubble bursts, whence allowing to estimate the bubble initial time. The analysis is made on NASDAQ daily closing price between Jan. 1998 and Nov. 2003. The NASDAQ bubble initial time has been estimated to be on Oct. 19, 1999.

Key words

Endogenous crash Financial bubble Recurrence Plot Recurrence Quantification Analysis Nonlinear Time Series Analysis NASDAQ 


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  1. 1.
    Sornette D, Johansen A, Bouchaud JP (1996) Stock Market Crashes, Precursors and Replicas. J Phys I France 6:167–175CrossRefGoogle Scholar
  2. 2.
    Feigenbaum JA, Freund PGO (1996) Discrete scale invariance in Stock Market before crashes. Int J Mod Phys B 10:3737–3745CrossRefADSGoogle Scholar
  3. 3.
    Vandewalle N, Boveroux Ph, Minguet A, Ausloos M (1998) The crash of October 1987 seen as a phase transition. Physica A 255:201–210CrossRefGoogle Scholar
  4. 4.
    Vandewalle N, Ausloos M, Boveroux Ph, Minguet A (1998) How the financial crash of October 1997 could have been predicted. Eur Phys J B 4:139–141CrossRefADSGoogle Scholar
  5. 5.
    Johansen A, Sornette D (2000) The Nasdaq crash of April 2000: yet another example of log-periodicity in a speculative bubble ending in a crash. Eur Phys J B 17:319–328CrossRefADSGoogle Scholar
  6. 6.
    Eckmann JP, Kamphorst SO, Ruelle D (1987) Recurrence Plot of dynamical system. Europhys Lett 4:973–977ADSCrossRefGoogle Scholar
  7. 7.
    Zbilut JP, Webber CL (1992) Embedding and delays as derived from quantification of Recurrence Plot. Phys Lett A 171:199–203CrossRefADSGoogle Scholar
  8. 8.
    Lambertz M, Vandenhouten R, Grebe R, Langhorst P (2000) Phase transition in the common brainstem and related systems investigated by nonstationary time series analysis. Journal of the Autonomic Nervous System 78:141–157PubMedCrossRefGoogle Scholar
  9. 9.
    Antoniou A, Vorlow CE (2000) Recurrence Plot and financial time series analysis. Neural Network World 10:131–145Google Scholar
  10. 10.
    Holyst JA, Zebrowska M (2000) Recurrence Plots and Hurst exponent for financial market and foreign exchange data. Int J Theoretical and Applied Finance 3:419CrossRefGoogle Scholar
  11. 11.
    Johansen A, Sornette D (1999) Financial ‘Anti-Bubbles’: Log Periodicity in Gold and Nikkei collapses. Int J Mod Phys C 10:563–575CrossRefADSGoogle Scholar
  12. 12.
    Fabretti A, Ausloos M (2005) Recurrence Plot and Recurrence Quantification Analysis techniques for detecting a critical regime. Examples from financial market indices. Int J Mod Phys C (to be printed)Google Scholar

Copyright information

© Springer-Verlag Tokyo 2006

Authors and Affiliations

  • Annalisa Fabretti
    • 1
  • Marcel Ausloos
    • 2
  1. 1.Department of Mathematics for Economy, Insurances and Finance ApplicationsUniversity of RomaRomeItaly
  2. 2.SUPRATECS, B5University of LiègeLiègeEuroland

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