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Log-Periodic Crashes Revisited

Author

Listed:
  • Raul Matsushita

    (University of Brasilia)

  • Iram Gleria

    (Federal University of Alagoas)

  • Annibal Figueiredo

    (University of Brasilia)

  • Sergio Da Silva

    (Federal University of Santa Catarina)

Abstract

We revisit the finding that crashes can be deterministic and governed by log-periodic formulas [D. Sornette, A. Johansen, Significance of log-periodic precursors to financial crashes, Quant. Finance 1 (2001) 452–471; D. Sornette, W.X. Zhou, The US 2000–2002 market descent: how much longer and deeper?, Quant. Finance 2 (2002) 468–481]. One- and two-harmonic equations are usually employed to fit daily data during bubble episodes. But a three-harmonics has been shown to fit anti-bubbles [A. Johansen, D. Sornette, Financial “anti-bubbles”: log-periodicity in gold and Nikkei collapses, Int. J. Mod. Phys. C 10 (1999) 563–575]. Here we show that the three-harmonic formula can work for bubble episodes as well as anti-bubbles. This is illustrated with daily data from the Brazilian real-US dollar exchange rate. And we also show that the three-harmonics can fit an intraday data set from that foreign exchange rate.
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Suggested Citation

  • Raul Matsushita & Iram Gleria & Annibal Figueiredo & Sergio Da Silva, 2005. "Log-Periodic Crashes Revisited," Finance 0508005, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpfi:0508005
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    References listed on IDEAS

    as
    1. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Papers cond-mat/0106520, arXiv.org.
    2. Didier Sornette & Wei-Xing Zhou, 2002. "The US 2000-2002 market descent: How much longer and deeper?," Quantitative Finance, Taylor & Francis Journals, vol. 2(6), pages 468-481.
    3. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 452-471.
    4. A. Johansen & D. Sornette, 1999. "Financial ``Anti-Bubbles'': Log-Periodicity in Gold and Nikkei collapses," Papers cond-mat/9901268, arXiv.org.
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    Citations

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    Cited by:

    1. Li Lin & Didier Sornette, 2018. "“Speculative Influence Network” during financial bubbles: application to Chinese stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(2), pages 385-431, July.
    2. Pawel Dlotko & Simon Rudkin, 2019. "The Topology of Time Series: Improving Recession Forecasting from Yield Spreads," Working Papers 2019-02, Swansea University, School of Management.
    3. Sornette, Didier & Woodard, Ryan & Yan, Wanfeng & Zhou, Wei-Xing, 2013. "Clarifications to questions and criticisms on the Johansen–Ledoit–Sornette financial bubble model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4417-4428.
    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. Wosnitza, Jan Henrik & Denz, Cornelia, 2013. "Liquidity crisis detection: An application of log-periodic power law structures to default prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3666-3681.
    6. Wosnitza, Jan Henrik & Leker, Jens, 2014. "Can log-periodic power law structures arise from random fluctuations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 228-250.
    7. Li Lin & Didier Sornette, 2015. ""Speculative Influence Network" during financial bubbles: application to Chinese Stock Markets," Papers 1510.08162, arXiv.org.
    8. Filimonov, V. & Sornette, D., 2013. "A stable and robust calibration scheme of the log-periodic power law model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3698-3707.
    9. Matsushita, Raul & Figueiredo, Annibal & Da Silva, Sergio, 2012. "A suggested statistical test for measuring bivariate nonlinear dependence," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4891-4898.

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