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Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange

Author

Listed:
  • Daniel Traian Pele

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Miruna Mazurencu-Marinescu

    (Bucharest University of Economic Studies, Bucharest, Romania)

  • Peter Nijkamp

    (VU University Amsterdam)

Abstract

In this paper we investigate the herding behaviour of the Bucharest Stock Exchange (BSE), using log periodic power laws models. By analysing the behaviour of the most speculative index from the Bucharest Stock Exchange, the BET-FI, we are able to demonstrate that Log-Periodic Power Law (LPPL) models are a useful tool for recognizing the behaviour of a stock market bubble, and have good abilities for predicting the critical point of a bubble. From our statistical investigation, it turns out that an iterative calibration of the model for the BET-FI regime leads ex post to a rather accurate forecast of the stock market crash in January 2008. Next, by using the same methodology, the anti-bubble regime from 2008 is used for a statistical fit. We then find an accurate “prediction” of the local point of phase transition on 27 October 2008.

Suggested Citation

  • Daniel Traian Pele & Miruna Mazurencu-Marinescu & Peter Nijkamp, 2013. "Herding Behaviour, Bubbles and Log Periodic Power Laws in Illiquid Stock Markets. A Case Study on the Bucharest Stock Exchange," Tinbergen Institute Discussion Papers 13-109/VIII, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:20130109
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    References listed on IDEAS

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    Cited by:

    1. TRENCA Ioan & PETRIA Ioan & PECE Andreea Maria, 2015. "Empirical Inquiry Of Gregarious Behavior: Evidence From European Emerging Markets," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 67(2), pages 143-160.
    2. Andreea Pece, 2014. "The Herding Behavior On Small Capital Markets: Evidence From Romania," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 795-801, July.
    3. Cheng, Fangzheng & Fan, Tijun & Fan, Dandan & Li, Shanling, 2018. "The prediction of oil price turning points with log-periodic power law and multi-population genetic algorithm," Energy Economics, Elsevier, vol. 72(C), pages 341-355.

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    More about this item

    Keywords

    Log-periodic Power Law; Stock Market Bubble; Crash;
    All these keywords.

    JEL classification:

    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics

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