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A Consistent Model of ‘Explosive’Financial Bubbles With Mean-Reversing Residuals

Author

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  • Li LIN

    (ETH Zurich and Beihang University)

  • Ruo En REN

    (Beihang University)

  • Didier SORNETTE

    (ETH Zurich and Swiss Finance Institute)

Abstract

We present a self-consistent model for explosive financial bubbles, which combines a mean-reverting volatility process and a stochastic conditional return which reflects nonlinear positive feedbacks and continuous updates of the investors’ beliefs and sentiments. The conditional expected returns exhibit faster-than-exponential acceleration decorated by accelerating oscillations, called “log-periodic power law.” Tests on residuals show a remarkable low rate (0.2%) of false positives when applied to a GARCH benchmark. When tested on the S&P500 US index from Jan. 3, 1950 to Nov. 21, 2008, the model correctly identifies the bubbles ending in Oct. 1987, in Oct. 1997, in Aug. 1998 and the ITC bubble ending on the first quarter of 2000. Different unit-root tests confirm the high relevance of the model specification. Our model also provides a diagnostic for the duration of bubbles: applied to the period before Oct. 1987 crash, there is clear evidence that the bubble started at least 4 years earlier. We confirm the validity and universality of the volatility-confined LPPL model on seven other major bubbles that have occurred in the World in the last two decades. Using Bayesian inference, we find a very strong statistical preference for our model compared with a standard benchmark, in contradiction with Chang and Feigenbaum [2006] which used a unit-root model for residuals.

Suggested Citation

  • Li LIN & Ruo En REN & Didier SORNETTE, 2009. "A Consistent Model of ‘Explosive’Financial Bubbles With Mean-Reversing Residuals," Swiss Finance Institute Research Paper Series 09-14, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp0914
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    Citations

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    Cited by:

    1. Maximilian Brauers & Matthias Thomas & Joachim Zietz, 2014. "Are There Rational Bubbles in REITs? New Evidence from a Complex Systems Approach," The Journal of Real Estate Finance and Economics, Springer, vol. 49(2), pages 165-184, August.
    2. Jiang, Zhi-Qiang & Zhou, Wei-Xing & Sornette, Didier & Woodard, Ryan & Bastiaensen, Ken & Cauwels, Peter, 2010. "Bubble diagnosis and prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 74(3), pages 149-162, June.
    3. Siab Mamipour & Mahshid Sepahi, 2015. "Analysis of the Behavior of Amateur and Professional Investors’ Impact on the Formation of Bubbles in Tehran Stock Market," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 19(3), pages 341-358, Autumn.
    4. Petr Geraskin & Dean Fantazzini, 2013. "Everything you always wanted to know about log-periodic power laws for bubble modeling but were afraid to ask," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 366-391, May.
    5. David S. Br�e & Damien Challet & Pier Paolo Peirano, 2013. "Prediction accuracy and sloppiness of log-periodic functions," Quantitative Finance, Taylor & Francis Journals, vol. 13(2), pages 275-280, January.
    6. Hanousek, Jan & Novotný, Jan, 2012. "Price jumps in Visegrad-country stock markets: An empirical analysis," Emerging Markets Review, Elsevier, vol. 13(2), pages 184-201.
    7. Wanfeng Yan & Ryan Woodard & Didier Sornette, 2014. "Inferring fundamental value and crash nonlinearity from bubble calibration," Quantitative Finance, Taylor & Francis Journals, vol. 14(7), pages 1273-1282, July.
    8. Élise Alfieri & Radu Burlacu & Geoffroy Enjolras, 2019. "Was the 2017 Crash of the Crypto-currency Market Predictable?," Post-Print hal-02952123, HAL.

    More about this item

    Keywords

    Rational bubbles; mean reversal; positive feedbacks; finite-time singularity; superexponential growth; Bayesian analysis; log-periodic power law;
    All these keywords.

    JEL classification:

    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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