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Financial bubbles: mechanisms and diagnostics

Author

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  • Didier Sornette

    (ETH Zurich)

  • Peter Cauwels

    (ETH Zurich)

Abstract

We define a financial bubble as a period of unsustainable growth, when the price of an asset increases ever more quickly, in a series of accelerating phases of corrections and rebounds. More technically, during a bubble phase, the price follows a faster-than-exponential power law growth process, often accompanied by log-periodic oscillations. This dynamic ends abruptly in a change of regime that may be a crash or a substantial correction. Because they leave such specific traces, bubbles may be recognised in advance, that is, before they burst. In this paper, we will explain the mechanism behind financial bubbles in an intuitive way. We will show how the log-periodic power law emerges spontaneously from the complex system that financial markets are, as a consequence of feedback mechanisms, hierarchical structure and specific trading dynamics and investment styles. We argue that the risk of a major correction, or even a crash, becomes substantial when a bubble develops towards maturity, and that it is therefore very important to find evidence of bubbles and to follow their development from as early a stage as possible. The tools that are explained in this paper actually serve that purpose. They are at the core of the Financial Crisis Observatory at the ETH Zurich, where tens of thousands of assets are monitored on a daily basis. This allow us to have a continuous overview of emerging bubbles in the global financial markets. The companion report available as part of the Notenstein white paper series (2014) with the title ``Financial bubbles: mechanism, diagnostic and state of the World (Feb. 2014)'' presents a practical application of the methodology outlines in this article and describes our view of the status concerning positive and negative bubbles in the financial markets, as of the end of January 2014.

Suggested Citation

  • Didier Sornette & Peter Cauwels, 2014. "Financial bubbles: mechanisms and diagnostics," Papers 1404.2140, arXiv.org.
    • Handle: RePEc:arx:papers:1404.2140
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    References listed on IDEAS

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    1. Didier Sornette & Ryan Woodard, & Wanfeng Yan & Wei-Xing Zhou, "undated". "Clarifications to Questions and Criticisms on the Johansen-Ledoit-Sornette bubble Model," Working Papers ETH-RC-11-004, ETH Zurich, Chair of Systems Design.
    2. K. Ronnie Sircar & George Papanicolaou, 1998. "General Black-Scholes models accounting for increased market volatility from hedging strategies," Applied Mathematical Finance, Taylor & Francis Journals, vol. 5(1), pages 45-82.
    3. Janeway,William H., 2012. "Doing Capitalism in the Innovation Economy," Cambridge Books, Cambridge University Press, number 9781107031258.
    4. Zhou, Wei-Xing & Sornette, Didier, 2006. "Is there a real-estate bubble in the US?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 361(1), pages 297-308.
    5. Gisler, Monika & Sornette, Didier & Woodard, Ryan, 2011. "Innovation as a social bubble: The example of the Human Genome Project," Research Policy, Elsevier, vol. 40(10), pages 1412-1425.
    6. Hyman P. Minsky, 1992. "The Financial Instability Hypothesis," Economics Working Paper Archive wp_74, Levy Economics Institute.
    7. Didier Sornette & Peter Cauwels, 2014. "1980–2008: The Illusion of the Perpetual Money Machine and What It Bodes for the Future," Risks, MDPI, vol. 2(2), pages 1-29, April.
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    Citations

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    Cited by:

    1. von der Becke Susanne & Sornette Didier, 2019. "An Asset-Based Framework of Credit Creation (applied to the Global Financial Crisis)," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 9(2), pages 1-21, July.
    2. Zhang, Yue-Jun & Yao, Ting, 2016. "Interpreting the movement of oil prices: Driven by fundamentals or bubbles?," Economic Modelling, Elsevier, vol. 55(C), pages 226-240.
    3. Ionuț Nica & Ștefan Ionescu & Camelia Delcea & Nora Chiriță, 2024. "Quantitative Modeling of Financial Contagion: Unraveling Market Dynamics and Bubble Detection Mechanisms," Risks, MDPI, vol. 12(2), pages 1-42, February.
    4. Martin Keller-Ressel, 2014. "Simple examples of pure-jump strict local martingales," Papers 1405.2669, arXiv.org, revised Jun 2015.
    5. Zura Kakushadze, 2016. "On Origins of Bubbles," Papers 1610.03769, arXiv.org, revised Jul 2017.
    6. Leiss, Matthias & Nax, Heinrich H. & Sornette, Didier, 2015. "Super-exponential growth expectations and the global financial crisis," LSE Research Online Documents on Economics 65434, London School of Economics and Political Science, LSE Library.
    7. Keller-Ressel, Martin, 2015. "Simple examples of pure-jump strict local martingales," Stochastic Processes and their Applications, Elsevier, vol. 125(11), pages 4142-4153.
    8. Ozkan Haykir & Ibrahim Yagli, 2022. "Speculative bubbles and herding in cryptocurrencies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-33, December.
    9. Geuder, Julian & Kinateder, Harald & Wagner, Niklas F., 2019. "Cryptocurrencies as financial bubbles: The case of Bitcoin," Finance Research Letters, Elsevier, vol. 31(C).
    10. Iliyasu, Jamilu & Rafindadi Sanusi, Aliyu & Suleiman, Dahiru, 2019. "Testing For Multiple Bubble Episodes In Nigerian Stock Exchange Market," Ilorin Journal of Economic Policy, Department of Economics, University of Ilorin, vol. 6(6), pages 13-26, June.
    11. Cerruti, Gianluca & Lombardini, Simone, 2022. "Financial bubbles as a recursive process lead by short-term strategies," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 555-568.

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