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When bubbles burst: econometric tests based on structural breaks

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  • Jörg Breitung
  • Robinson Kruse

Abstract

Speculative bubbles have played an important role ever since in financial economics. During an ongoing bubble it is relevant for investors and policy-makers to know whether the bubble continues to grow or whether it is already collapsing. Prices are typically well approximated by a random walk in absence of bubbles, while periods of bubbles are characterised by explosive price paths. In this paper we first propose a conventional Chow-type testing procedure for a structural break from an explosive to a random walk regime. It is shown that under the null hypothesis of a mildly explosive process a suitably modified Chow-type statistic possesses a standard normal limiting distribution. Second, a monitoring procedure based on the CUSUM statistic is suggested. It timely indicates such a structural change. Asymptotic results are derived and small-sample properties are studied via Monte Carlo simulations. Finally, two empirical applications illustrate the merits and limitations of our suggested procedures. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Jörg Breitung & Robinson Kruse, 2013. "When bubbles burst: econometric tests based on structural breaks," Statistical Papers, Springer, vol. 54(4), pages 911-930, November.
    • Handle: RePEc:spr:stpapr:v:54:y:2013:i:4:p:911-930
    DOI: 10.1007/s00362-012-0497-3
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    2. Wegener, Christoph & Kruse, Robinson & Basse, Tobias, 2019. "The walking debt crisis," Journal of Economic Behavior & Organization, Elsevier, vol. 157(C), pages 382-402.
    3. Balcilar, Mehmet & Gupta, Rangan & Jooste, Charl & Wohar, Mark E., 2016. "Periodically collapsing bubbles in the South African stock market," Research in International Business and Finance, Elsevier, vol. 38(C), pages 191-201.
    4. Kruse, Yves Robinson & Kaufmann, Hendrik, 2015. "Bias-corrected estimation in mildly explosive autoregressions," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112897, Verein für Socialpolitik / German Economic Association.
    5. Kruse, Robinson & Kaufmann, Hendrik & Wegener, Christoph, 2018. "Bias-corrected estimation for speculative bubbles in stock prices," Economic Modelling, Elsevier, vol. 73(C), pages 354-364.
    6. Vicente Esteve & María A. Prats, 2021. "Testing for rational bubbles in Australian housing market from a long-term perspective," Working Papers 2113, Department of Applied Economics II, Universidad de Valencia.
    7. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert, 2017. "Improving the accuracy of asset price bubble start and end date estimators," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 121-138.
    8. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    9. Anton Skrobotov, 2022. "Testing for explosive bubbles: a review," Papers 2207.08249, arXiv.org.
    10. Riza Demirer & Guilherme Demos & Rangan Gupta & Didier Sornette, 2019. "On the predictability of stock market bubbles: evidence from LPPLS confidence multi-scale indicators," Quantitative Finance, Taylor & Francis Journals, vol. 19(5), pages 843-858, May.
    11. Esteve Vicente & Prats Maria A., 2021. "Structural Breaks and Explosive Behavior in the Long-Run: The Case of Australian Real House Prices, 1870–2020," Economics - The Open-Access, Open-Assessment Journal, De Gruyter, vol. 15(1), pages 72-84, January.
    12. Moreira, Afonso M. & Martins, Luis F., 2020. "A new mechanism for anticipating price exuberance," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 199-221.
    13. Hendrik Kaufmannz & Robinson Kruse, 2013. "Bias-corrected estimation in potentially mildly explosive autoregressive models," CREATES Research Papers 2013-10, Department of Economics and Business Economics, Aarhus University.
    14. Jin-young Choi & Myoung-jae Lee, 2017. "Regression discontinuity: review with extensions," Statistical Papers, Springer, vol. 58(4), pages 1217-1246, December.
    15. Franses, Philip Hans, 2016. "A simple test for a bubble based on growth and acceleration," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 160-169.
    16. Michaelides, Panayotis G. & Tsionas, Efthymios G. & Konstantakis, Konstantinos N., 2016. "Non-linearities in financial bubbles: Theory and Bayesian evidence from S&P500," Journal of Financial Stability, Elsevier, vol. 24(C), pages 61-70.

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    More about this item

    Keywords

    Speculative bubbles; Structural breaks; Mildly explosive processes; Monitoring; C12 (Hypothesis Testing); C22 (Time-Series Models); G10 (General Financial Markets);
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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