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Financial Bubble Implosion

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Abstract

Expansion and collapse are two key features of a financial asset bubble. Bubble expansion may be modeled using a mildly explosive process. Bubble implosion may take several different forms depending on the nature of the collapse and therefore requires some flexibility in modeling. This paper develops analytics and studies the performance characteristics of the real time bubble monitoring strategy proposed in Phillips, Shi and Yu (2014b,c, PSY) under alternative forms of bubble implosion that can be represented in terms of mildly integrated processes which capture various return paths to market normalcy. We propose a new reverse sample use of the PSY procedure for detecting crises and estimating the date of market recovery. Consistency of the dating estimators is established and the limit theory addresses new complications arising from the alternative forms of bubble implosion and the endogeneity effects present in the reverse regression. Simulations explore the finite sample performance of the strategy for dating market recovery and an illustration to the Nasdaq stock market is provided. A real-time version of the strategy is provided that is suited for practical implementation.

Suggested Citation

  • Peter C.B. Phillips & Shu-Ping Shi, 2014. "Financial Bubble Implosion," Cowles Foundation Discussion Papers 1967, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:1967
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    File URL: http://cowles.yale.edu/sites/default/files/files/pub/d19/d1967.pdf
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    1. Peter C. B. Phillips & Shuping Shi & Jun Yu, 2014. "Specification Sensitivity in Right-Tailed Unit Root Testing for Explosive Behaviour," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(3), pages 315-333, June.
    2. Xi Chen & Michael Funke, 2013. "Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles," National Institute Economic Review, National Institute of Economic and Social Research, vol. 223(1), pages 39-48, February.
    3. Peter C. B. Phillips & Jun Yu, 2011. "Dating the timeline of financial bubbles during the subprime crisis," Quantitative Economics, Econometric Society, vol. 2(3), pages 455-491, November.
    4. Peter C. B. Phillips & Yangru Wu & Jun Yu, 2011. "EXPLOSIVE BEHAVIOR IN THE 1990s NASDAQ: WHEN DID EXUBERANCE ESCALATE ASSET VALUES?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(1), pages 201-226, February.
    5. Huang, Weihong & Zheng, Huanhuan & Chia, Wai-Mun, 2010. "Financial crises and interacting heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1105-1122, June.
    6. Shu-Ping Shi & Peter C. B. Phillips & Jun Yu, 2011. "Specification Sensitivities in Right-Tailed Unit Root Testing for Financial Bubbles," Working Papers 172011, Hong Kong Institute for Monetary Research.
    7. Sonali Das & Rangan Gupta & Patrick T Kanda, 2010. "Bubbles in South African House Prices and their Impact on Consumption," Working Papers 201017, University of Pretoria, Department of Economics.
    8. Bohl, Martin T. & Kaufmann, Philipp & Stephan, Patrick M., 2013. "From hero to zero: Evidence of performance reversal and speculative bubbles in German renewable energy stocks," Energy Economics, Elsevier, vol. 37(C), pages 40-51.
    9. Phillips, Peter C.B. & Magdalinos, Tassos, 2007. "Limit theory for moderate deviations from a unit root," Journal of Econometrics, Elsevier, vol. 136(1), pages 115-130, January.
    10. Diba, Behzad T & Grossman, Herschel I, 1988. "Explosive Rational Bubbles in Stock Prices?," American Economic Review, American Economic Association, vol. 78(3), pages 520-530, June.
    11. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    12. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, vol. 55(2), pages 277-301, March.
    13. Blanchard, Olivier Jean, 1979. "Speculative bubbles, crashes and rational expectations," Economics Letters, Elsevier, vol. 3(4), pages 387-389.
    14. Etienne, Xiaoli L. & Irwin, Scott H. & Garcia, Philip, 2014. "Bubbles in food commodity markets: Four decades of evidence," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 129-155.
    15. Phillips, Peter C.B. & Magdalinos, Tassos, 2009. "Unit Root And Cointegrating Limit Theory When Initialization Is In The Infinite Past," Econometric Theory, Cambridge University Press, vol. 25(6), pages 1682-1715, December.
    16. Efthymios Pavlidis & Ivan Paya & David Peel, 2012. "A New Test for Rational Speculative Bubbles using Forward Exchange Rates: The Case of the Interwar German Hyperinflation," Working Papers 18599597, Lancaster University Management School, Economics Department.
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    Cited by:

    1. Harvey, David I. & Leybourne, Stephen J. & Sollis, Robert & Taylor, A.M. Robert, 2016. "Tests for explosive financial bubbles in the presence of non-stationary volatility," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 548-574.
    2. Fantazzini, Dean, 2016. "The oil price crash in 2014/15: Was there a (negative) financial bubble?," Energy Policy, Elsevier, vol. 96(C), pages 383-396.
    3. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick, 2016. "The shine of precious metals around the global financial crisis," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 717-738.
    4. Phillips, Peter C.B., 2016. "Modeling speculative bubbles with diverse investor expectations," Research in Economics, Elsevier, vol. 70(3), pages 375-387.
    5. repec:eee:eneeco:v:72:y:2018:i:c:p:341-355 is not listed on IDEAS

    More about this item

    Keywords

    Bubble implosion; Dating algorithm; Limit theory; Market recovery; Nasdaq;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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