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Date-stamping multiple bubble regimes

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  • Harvey, David I.
  • Leybourne, Stephen J.
  • Whitehouse, Emily J.

Abstract

Identifying the start and end dates of explosive bubble regimes has become a prominent issue in the econometric literature. Recent research has demonstrated the advantage of a model-based minimum sum of squared residuals estimator, combined with Bayesian Information Criterion model selection, over recursive unit root testing methods in providing accurate date estimates for a single explosive regime. However, in the context of multiple bubbles, a large number of models are possible, making such a model-based method unappealing. In this paper, we propose a two-step procedure for dating multiple explosive regimes. First, recursive unit root tests are used to identify a ‘date window’ in which an explosive episode starts and ends. Second, a model-based BIC approach is used to precisely estimate the regime change points within each date window. In addition, our method allows us to distinguish between different types of explosive episode, such as whether or not each explosive regime crashes before reverting back to a unit root process, and date any crash regimes. Monte Carlo simulations highlight the effectiveness of our procedure when compared to existing methods of dating. The value of the new methodology is also demonstrated through an empirical application to housing markets.

Suggested Citation

  • Harvey, David I. & Leybourne, Stephen J. & Whitehouse, Emily J., 2020. "Date-stamping multiple bubble regimes," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 226-246.
  • Handle: RePEc:eee:empfin:v:58:y:2020:i:c:p:226-246
    DOI: 10.1016/j.jempfin.2020.06.004
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    References listed on IDEAS

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    Cited by:

    1. Yang, Bingduo & Long, Wei & Yang, Zihui, 2022. "Testing predictability of stock returns under possible bubbles," Journal of Empirical Finance, Elsevier, vol. 68(C), pages 246-260.
    2. Horváth, Lajos & Li, Hemei & Liu, Zhenya, 2022. "How to identify the different phases of stock market bubbles statistically?," Finance Research Letters, Elsevier, vol. 46(PA).
    3. Skrobotov Anton, 2023. "Testing for explosive bubbles: a review," Dependence Modeling, De Gruyter, vol. 11(1), pages 1-26, January.
    4. Hansen, Jacob H. & Møller, Stig V. & Pedersen, Thomas Q. & Schütte, Christian M., 2024. "House price bubbles under the COVID-19 pandemic," Journal of Empirical Finance, Elsevier, vol. 75(C).
    5. Eiji Kurozumi & Anton Skrobotov, 2021. "On the asymptotic behavior of bubble date estimators," Papers 2110.04500, arXiv.org, revised Sep 2022.

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    More about this item

    Keywords

    Explosive autoregression; Break date estimation; Multiple bubbles;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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