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Identification of speculative bubbles using state-space models with Markov-switching

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  • Al-Anaswah, Nael
  • Wilfling, Bernd

Abstract

In this paper we use a state-space model with Markov-switching to detect speculative bubbles in stock-price data. To this end we express a present-value stock-price model in state-space form which we estimate using the Kalman filter. This procedure enables us to estimate a two-regime Markov-switching specification of the unobservable bubble process. The respective Markov-regimes represent two distinct phases in the bubble process, namely one in which the bubble survives and one in which it collapses. We ultimately identify bursting stock-price bubbles by statistically separating both Markov-regimes from each other. In an empirical analysis we apply our methodology to a plethora of artificial and real-world data sets. Our study has two major findings. First, we find significant Markov-switching structures in real-world stock-price bubbles. Second, in the stock markets considered our identification procedure correctly detects most speculative periods which have been classified as such by economic historians.

Suggested Citation

  • Al-Anaswah, Nael & Wilfling, Bernd, 2011. "Identification of speculative bubbles using state-space models with Markov-switching," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1073-1086, May.
  • Handle: RePEc:eee:jbfina:v:35:y:2011:i:5:p:1073-1086
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    More about this item

    Keywords

    Stock market dynamics Detection of speculative bubbles Present-value models State-space models with Markov-switching;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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