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


  • 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)


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

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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


    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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