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On the Predictability of Stock Market Bubbles: Evidence from LPPLS ConfidenceTM Multi-scale Indicators

Author

Listed:
  • Riza Demirer

    () (Department of Economics & Finance, Southern Illinois University Edwardsville, USA)

  • Guilherme Demos

    () (ETH Zürich, Dept. of Management, Technology and Economics, Zürich, Switzerland)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria, South Africa and IPAG Business School, Paris, France)

  • Didier Sornette

    () (ETH Zürich, Dept. of Management, Technology and Economics, Zürich, Switzerland and Swiss Finance Institute)

Abstract

We examine the predictive power of market-based indicators over the positive and negative stock market bubbles via an application of the LPPLS ConfidenceTM Multi-scale Indicators to the S&P500 index. We find that the LPPLS framework is able to successfully capture, ex-ante, some of the prominent bubbles across different time scales, such as the Black Monday, Dot-com, and Subprime Crisis periods. We then show that measures of short selling activity have robust predictive power over negative bubbles across both short and long time horizons, in line with the previous studies suggesting that short sellers have predictive ability over stock price crash risks. Market liquidity, on the other hand, is found to have robust predictive power over both the negative and positive bubbles, while its predictive power is largely limited to short horizons. Short selling and liquidity are thus identified as two important factors contributing to the LPPLS-based bubble indicators. The evidence overall points to the predictability of stock market bubbles using market-based proxies of trading activity and can be used as a guideline to model and monitor the occurrence of bubble conditions in financial markets.

Suggested Citation

  • Riza Demirer & Guilherme Demos & Rangan Gupta & Didier Sornette, 2017. "On the Predictability of Stock Market Bubbles: Evidence from LPPLS ConfidenceTM Multi-scale Indicators," Working Papers 201752, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201752
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    References listed on IDEAS

    as
    1. Balcilar, Mehmet & Gupta, Rangan & Jooste, Charl & Wohar, Mark E., 2016. "Periodically collapsing bubbles in the South African stock market," Research in International Business and Finance, Elsevier, vol. 38(C), pages 191-201.
    2. V. Filimonov & G. Demos & D. Sornette, 2017. "Modified profile likelihood inference and interval forecast of the burst of financial bubbles," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1167-1186, August.
    3. Maximilian Seyrich & Didier Sornette, 2016. "Micro-Foundation Using Percolation Theory of the Finite-Time Singular Behavior of the Crash Hazard Rate in a Class of Rational Expectation Bubbles," Swiss Finance Institute Research Paper Series 16-03, Swiss Finance Institute.
    4. John Y. Campbell & Sanford J. Grossman & Jiang Wang, 1993. "Trading Volume and Serial Correlation in Stock Returns," The Quarterly Journal of Economics, Oxford University Press, vol. 108(4), pages 905-939.
    5. Didier SORNETTE & Guilherme DEMOS & Zhang QUN & Peter CAUWELS & Vladimir FILIMONOV & Qunzhi ZHANG, 2015. "Real-Time Prediction and Post-Mortem Analysis of the Shanghai 2015 Stock Market Bubble and Crash," Swiss Finance Institute Research Paper Series 15-32, Swiss Finance Institute.
    6. 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.
    7. Pastor, Lubos & Stambaugh, Robert F., 2003. "Liquidity Risk and Expected Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 111(3), pages 642-685, June.
    8. Anderson, Keith & Brooks, Chris & Katsaris, Apostolos, 2010. "Speculative bubbles in the S&P 500: Was the tech bubble confined to the tech sector?," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 345-361, June.
    9. 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.
    10. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Papers cond-mat/0106520, arXiv.org.
    11. Robert J. Shiller, 2014. "Speculative Asset Prices (Nobel Prize Lecture)," Cowles Foundation Discussion Papers 1936, Cowles Foundation for Research in Economics, Yale University.
    12. Chordia, Tarun & Subrahmanyam, Avanidhar & Anshuman, V. Ravi, 2001. "Trading activity and expected stock returns," Journal of Financial Economics, Elsevier, vol. 59(1), pages 3-32, January.
    13. Didier Sornette & Ryan Woodard, & Wanfeng Yan & Wei-Xing Zhou, "undated". "Clarifications to Questions and Criticisms on the Johansen-Ledoit-Sornette bubble Model," Working Papers ETH-RC-11-004, ETH Zurich, Chair of Systems Design.
    14. 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.
    15. Vipin Arora & Shuping Shi, 2016. "Nonlinearities and tests of asset price bubbles," Empirical Economics, Springer, vol. 50(4), pages 1421-1433, June.
    16. Roger E. A. Farmer, 2015. "The Stock Market Crash Really Did Cause the Great Recession," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(5), pages 617-633, October.
    17. Jiang, Zhi-Qiang & Zhou, Wei-Xing & Sornette, Didier & Woodard, Ryan & Bastiaensen, Ken & Cauwels, Peter, 2010. "Bubble diagnosis and prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 74(3), pages 149-162, June.
    18. G. Demos & D. Sornette, 2017. "Birth or burst of financial bubbles: which one is easier to diagnose?," Quantitative Finance, Taylor & Francis Journals, vol. 17(5), pages 657-675, May.
    19. Rapach, David E. & Ringgenberg, Matthew C. & Zhou, Guofu, 2016. "Short interest and aggregate stock returns," Journal of Financial Economics, Elsevier, vol. 121(1), pages 46-65.
    20. Nneji, Ogonna, 2015. "Liquidity shocks and stock bubbles," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 35(C), pages 132-146.
    21. David S. Brée & Damien Challet & Pier Paolo Peirano, 2013. "Prediction accuracy and sloppiness of log-periodic functions," Quantitative Finance, Taylor & Francis Journals, vol. 13(2), pages 275-280, January.
    22. Sornette, Didier & Cauwels, Peter, 2015. "Financial Bubbles: Mechanisms and Diagnostics," Review of Behavioral Economics, now publishers, vol. 2(3), pages 279-305, October.
    23. Chris Brooks & Apostolos Katsaris, 2005. "A Three-Regime Model of Speculative Behaviour: Modelling the Evolution of the S&P 500 Composite Index," Economic Journal, Royal Economic Society, vol. 115(505), pages 767-797, July.
    24. Sornette, Didier & Woodard, Ryan & Yan, Wanfeng & Zhou, Wei-Xing, 2013. "Clarifications to questions and criticisms on the Johansen–Ledoit–Sornette financial bubble model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4417-4428.
    25. T. Kaizoji & D. Sornette, 2008. "Market bubbles and crashes," Papers 0812.2449, arXiv.org.
    26. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 452-471.
    27. Ulrich Homm & Jörg Breitung, 2010. "Testing for Speculative Bubbles in Stock Markets: A Comparison of Alternative Methods," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 10(1), pages 198-231, 2012 10 1.
    28. Jörg Breitung & Robinson Kruse, 2013. "When bubbles burst: econometric tests based on structural breaks," Statistical Papers, Springer, vol. 54(4), pages 911-930, November.
    29. Jones, Charles M & Kaul, Gautam & Lipson, Marc L, 1994. "Transactions, Volume, and Volatility," Review of Financial Studies, Society for Financial Studies, vol. 7(4), pages 631-651.
    30. Doron Avramov & Tarun Chordia & Amit Goyal, 2006. "Liquidity and Autocorrelations in Individual Stock Returns," Journal of Finance, American Finance Association, vol. 61(5), pages 2365-2394, October.
    31. Callen, Jeffrey L. & Fang, Xiaohua, 2015. "Short interest and stock price crash risk," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 181-194.
    32. Maximilian Seyrich & Didier Sornette, 2016. "Micro-foundation using percolation theory of the finite-time singular behavior of the crash hazard rate in a class of rational expectation bubbles," Papers 1601.07707, arXiv.org.
    33. Karpoff, Jonathan M., 1987. "The Relation between Price Changes and Trading Volume: A Survey," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(1), pages 109-126, March.
    34. Robert J. Shiller, 2014. "Speculative Asset Prices," American Economic Review, American Economic Association, vol. 104(6), pages 1486-1517, June.
    35. Shu-Ping Shi, 2013. "Specification sensitivities in the Markov-switching unit root test for bubbles," Empirical Economics, Springer, vol. 45(2), pages 697-713, October.
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    Cited by:

    1. 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.

    More about this item

    Keywords

    Financial bubble indicators; LPPL method; Markov switching; Predictability; Short interest;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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