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Nonlinearities and tests of asset price bubbles

Author

Listed:
  • Vipin Arora

    (U.S. Energy Information Administration)

  • Shuping Shi

    (Macquarie University
    The Centre for Applied Macroeconomic Analysis (CAMA))

Abstract

We find that incorporating nonlinearities into tests of asset price bubbles has important consequences for the results. We show this by comparing four tests using S&P 500 data. Our results indicate that the modification which incorporates nonlinear probabilities outperforms the other models in terms of select information criteria and a likelihood-based test. In addition, the coefficients associated with the nonlinear terms have the expected sign and the estimated probabilities display larger movements during the late 1910s, early 1930s/1940s, and the 2000s.

Suggested Citation

  • Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    • Handle: RePEc:spr:empeco:v:50:y:2016:i:4:d:10.1007_s00181-015-0976-1
    DOI: 10.1007/s00181-015-0976-1
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    References listed on IDEAS

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    Cited by:

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    3. 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.

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    More about this item

    Keywords

    Regime switching; Bubble; Linear approximation; Nonlinear specification;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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