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An Lppl Algorithm For Estimating The Critical Time Of A Stock Market Bubble

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  • Daniel T. Pele

    (Bucharest University of Economic Studies)

Abstract

LPPL models have been widely used to describe the behaviour of stock prices during an endogenous bubble and to predict the most probable time of the regime switching. Although their utility has been proved in many papers, there is still a lack of consensus on the statistical robustness, as the estimators are obtained through a nonlinear optimization algorithm and they are sensitive to the initial values. In this paper we propose an extension of the approach from Liberatore (2011), using a time series peak detection algorithm.

Suggested Citation

  • Daniel T. Pele, 2012. "An Lppl Algorithm For Estimating The Critical Time Of A Stock Market Bubble," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, vol. 1(2), pages 14-22, DECEMBER.
    • Handle: RePEc:aes:jsesro:v:1:y:2012:i:2:p:14-22
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    References listed on IDEAS

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    1. Vincenzo Liberatore, 2010. "Computational LPPL Fit to Financial Bubbles," Papers 1003.2920, arXiv.org, revised Jan 2011.
    2. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    3. 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.
    4. Cajueiro, Daniel O. & Tabak, Benjamin M. & Werneck, Filipe K., 2009. "Can we predict crashes? The case of the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1603-1609.
    5. Jeong-Ryeol Kurz-Kim, 2012. "Early warning indicator for financial crashes using the log periodic power law," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1465-1469, October.
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    Citations

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    Cited by:

    1. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and log-period power laws in the cryptocurrencies market," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 13, pages 1-26.
    2. Wątorek Marcin & Stawiarski Bartosz, 2016. "Log-Periodic Power Law and Generalized Hurst Exponent Analysis in Estimating an Asset Bubble Bursting Time," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 12(3), pages 49-58, October.
    3. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2019. "Metcalfe's law and herding behaviour in the cryptocurrencies market," Economics Discussion Papers 2019-16, Kiel Institute for the World Economy (IfW Kiel).
    4. Nathan Burks & Adetokunbo Fadahunsi & Ann Marie Hibbert, 2021. "Financial Contagion: A Tale of Three Bubbles," JRFM, MDPI, vol. 14(5), pages 1-14, May.
    5. Bingcun Dai & Fan Zhang & Domenico Tarzia & Kwangwon Ahn, 2018. "Forecasting Financial Crashes: Revisit to Log-Periodic Power Law," Complexity, Hindawi, vol. 2018, pages 1-12, August.
    6. Xiong, Jinwu & Liu, Qing & Zhao, Lei, 2020. "A new method to verify Bitcoin bubbles: Based on the production cost," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    7. MITRACHE, Mihai-Andrei & BOITOUT, Nicolas, 2017. "Tracking Financial Bubbles On Romania Stock Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 21(1), pages 41-62.
    8. Pele, Daniel Traian & Mazurencu-Marinescu-Pele, Miruna, 2018. "Cryptocurrencies, Metcalfe's law and LPPL models," IRTG 1792 Discussion Papers 2018-056, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

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    More about this item

    Keywords

    LPPL; stock market crash; speculative bubble;
    All these keywords.

    JEL classification:

    • G - Financial Economics
    • G01 - Financial Economics - - General - - - Financial Crises

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