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Improving the accuracy of asset price bubble start and end date estimators

Author

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  • Harvey, David I.
  • Leybourne, Stephen J.
  • Sollis, Robert

Abstract

Recent research has proposed using recursive right-tailed unit root tests to date the start and end of asset price bubbles. In this paper an alternative approach is proposed that utilises model-based minimum sum of squared residuals estimators combined with Bayesian Information Criterion model selection. Conditional on the presence of a bubble, the dating procedures suggested are shown to offer consistent estimation of the start and end dates of a fixed magnitude bubble, and can also be used to distinguish between different types of bubble process, i.e. a bubble that does or does not end in collapse, or a bubble that is ongoing at the end of the sample. Monte Carlo simulations show that the proposed dating approach out-performs the recursive unit root test methods for dating periods of explosive autoregressive behaviour in finite samples, particularly in terms of accurate identification of a bubble's end point. An empirical application involving Nasdaq stock prices is discussed.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:empfin:v:40:y:2017:i:c:p:121-138
    DOI: 10.1016/j.jempfin.2016.11.001
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    References listed on IDEAS

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    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2015. "Testing For Multiple Bubbles: Historical Episodes Of Exuberance And Collapse In The S&P 500," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56, pages 1043-1078, November.
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    Cited by:

    1. repec:eee:ecmode:v:73:y:2018:i:c:p:354-364 is not listed on IDEAS
    2. repec:bla:jtsera:v:39:y:2018:i:6:p:863-891 is not listed on IDEAS
    3. Sam Astill & David I. Harvey & Stephen J. Leybourne & A. M. Robert Taylor, 2017. "Tests for an end-of-sample bubble in financial time series," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 651-666, October.
    4. repec:ris:apltrx:0319 is not listed on IDEAS
    5. Pang, Tianxiao & Tai-Leung Chong, Terence & Zhang, Danna & Liang, Yanling, 2018. "Structural Change In Nonstationary Ar(1) Models," Econometric Theory, Cambridge University Press, vol. 34(05), pages 985-1017, October.
    6. Pang, Tianxiao & Du, Lingjie & Chong, Terence Tai Leung, 2018. "Estimating Multiple Breaks in Nonstationary Autoregressive Models," MPRA Paper 92074, University Library of Munich, Germany.
    7. David Harvey & Stephen Leybourne & Yang Zu, 2018. "Testing explosive bubbles with time-varying volatility," Discussion Papers 18/05, University of Nottingham, Granger Centre for Time Series Econometrics.

    More about this item

    Keywords

    Rational bubble; Explosive autoregression; Regime change; Break date estimation;

    JEL classification:

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

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