IDEAS home Printed from https://ideas.repec.org/p/tin/wpaper/20130109.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://papers.tinbergen.nl/13109.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lakonishok, Josef & Shleifer, Andrei & Vishny, Robert W., 1992. "The impact of institutional trading on stock prices," Journal of Financial Economics, Elsevier, vol. 32(1), pages 23-43, August.
    2. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Papers cond-mat/0106520, arXiv.org.
    3. Beatriz Fernández & Teresa Garcia‐Merino & Rosa Mayoral & Valle Santos & Eleuterio Vallelado, 2011. "Herding, information uncertainty and investors' cognitive profile," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 3(1), pages 7-33, April.
    4. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 452-471.
    5. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    6. Sushil Bikhchandani & Sunil Sharma, 2001. "Herd Behavior in Financial Markets," IMF Staff Papers, Palgrave Macmillan, vol. 47(3), pages 1-1.
    7. Richard W. Sias, 2004. "Institutional Herding," Review of Financial Studies, Society for Financial Studies, vol. 17(1), pages 165-206.
    8. Petr Geraskin & Dean Fantazzini, 2013. "Everything you always wanted to know about log-periodic power laws for bubble modeling but were afraid to ask," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 366-391, May.
    9. Jeong-Ryeol Kurz-Kim, 2012. "Early warning indicator for financial crashes using the log periodic power law," Applied Economics Letters, Taylor & Francis Journals, vol. 19(15), pages 1465-1469, October.
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    11. Didier SORNETTE, 2009. "Dragon-Kings, Black Swans and the Prediction of Crises," Swiss Finance Institute Research Paper Series 09-36, Swiss Finance Institute.
    12. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    13. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    14. D. Sornette, "undated". "Dragon-Kings, Black Swans and the Prediction of Crises," Working Papers CCSS-09-005, ETH Zurich, Chair of Systems Design.
    15. Timmermann, Allan & Granger, Clive W. J., 2004. "Efficient market hypothesis and forecasting," International Journal of Forecasting, Elsevier, vol. 20(1), pages 15-27.
    16. repec:pri:cepsud:91malkiel is not listed on IDEAS
    17. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    18. Cajueiro, Daniel O. & Tabak, Benjamin M. & Werneck, Filipe K., 2009. "Can we predict crashes? The case of the Brazilian stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1603-1609.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Didier SORNETTE, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based Models," Swiss Finance Institute Research Paper Series 14-25, Swiss Finance Institute.
    2. D. Sornette, 2014. "Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based models," Papers 1404.0243, arXiv.org.
    3. Pasca Lucian, 2015. "A Critical Review of the Main Approaches on Financial Market Dynamics Modelling," Journal of Heterodox Economics, Sciendo, vol. 2(2), pages 151-167, December.
    4. Park, Cheol-Ho & Irwin, Scott H., 2004. "The Profitability Of Technical Trading Rules In Us Futures Markets: A Data Snooping Free Test," 2004 Conference, April 19-20, 2004, St. Louis, Missouri 19011, NCR-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    5. Taufiq Choudhry & Ranadeva Jayasekera, 2015. "Level of efficiency in the UK equity market: empirical study of the effects of the global financial crisis," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 213-242, February.
    6. Wosnitza, Jan Henrik & Leker, Jens, 2014. "Can log-periodic power law structures arise from random fluctuations?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 228-250.
    7. Basak, Suryoday & Kar, Saibal & Saha, Snehanshu & Khaidem, Luckyson & Dey, Sudeepa Roy, 2019. "Predicting the direction of stock market prices using tree-based classifiers," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 552-567.
    8. Romain Bocher, 2022. "The Intersubjective Markets Hypothesis," Journal of Interdisciplinary Economics, , vol. 34(1), pages 35-50, January.
    9. Imran Yousaf & Shoaib Ali & Syed Zulfiqar Ali Shah, 2018. "Herding behavior in Ramadan and financial crises: the case of the Pakistani stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 4(1), pages 1-14, December.
    10. Felicia Ramona Birau, 2011. "An Analysis Of Weak-Form Efficiency On The Bucharest Stock Exchange," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 3(39), pages 194-205.
    11. Roland Rothenstein, 2018. "Quantification of market efficiency based on informational-entropy," Papers 1812.02371, arXiv.org.
    12. Gabriel Frahm, 2015. "A theoretical foundation of portfolio resampling," Theory and Decision, Springer, vol. 79(1), pages 107-132, July.
    13. Kamal, Mona, 2014. "Studying the Validity of the Efficient Market Hypothesis (EMH) in the Egyptian Exchange (EGX) after the 25th of January Revolution," MPRA Paper 54708, University Library of Munich, Germany.
    14. Petr Geraskin & Dean Fantazzini, 2013. "Everything you always wanted to know about log-periodic power laws for bubble modeling but were afraid to ask," The European Journal of Finance, Taylor & Francis Journals, vol. 19(5), pages 366-391, May.
    15. Bernard Njindan Iyke, 2019. "A Test Of The Efficiency Of The Foreign Exchange Market In Indonesia," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 0(12th BMEB), pages 1-26, January.
    16. Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
    17. Rebecca Westphal & Didier Sornette, 2019. "Market Impact and Performance of Arbitrageurs of Financial Bubbles in An Agent-Based Model," Swiss Finance Institute Research Paper Series 19-29, Swiss Finance Institute.
    18. Ashok Chanabasangouda Patil & Shailesh Rastogi, 2019. "Time-Varying Price–Volume Relationship and Adaptive Market Efficiency: A Survey of the Empirical Literature," JRFM, MDPI, vol. 12(2), pages 1-18, June.
    19. Daniel Nicolae Militaru, 2011. "The Impact Of The Economic And Financial Crisis On Pension Systems In The European Union," Revista Tinerilor Economisti (The Young Economists Journal), University of Craiova, Faculty of Economics and Business Administration, vol. 1(17), pages 15-19, November.
    20. Min Shu & Ruiqiang Song & Wei Zhu, 2021. "The 2021 Bitcoin Bubbles and Crashes—Detection and Classification," Stats, MDPI, vol. 4(4), pages 1-21, November.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tin:wpaper:20130109. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tinbergen Office +31 (0)10-4088900 (email available below). General contact details of provider: https://edirc.repec.org/data/tinbenl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.