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Log-Periodic Power Law And Gene Lized Hurst Exponent Analysis In Estimating An Asset Bubble Bursting Time

Author

Listed:
  • MARCIN WĄTOREK

    (Institute of Nuclear Physics, Polish Academy of Sciences)

  • BARTOSZ STAWIARSKI

    (Cracow University of Technology Faculty of Physics)

Abstract

We closely examine and compare two promising techniques helpful in estimating the moment an asset bubble bursts. Namely, the Log-Periodic Power Law model and Generalized Hurst Exponent approaches are considered. Sequential LPPL fitting to empirical financial time series exhibiting evident bubble behavior is presented. Estimating the critical crash-time works satisfactorily well also in the case of GHE, when substantial „decorrelation” prior to the event is visible. An extensive simulation study carried out on empirical data: stock indices and commodities, confirms very good performance of the two approaches.

Suggested Citation

  • Marcin Wątorek & Bartosz Stawiarski, 2016. "Log-Periodic Power Law And Gene Lized Hurst Exponent Analysis In Estimating An Asset Bubble Bursting Time," Financial Internet Quarterly, University of Information Technology and Management in Rzeszów, vol. 12(3), pages 49-58, January.
    • Handle: RePEc:wsz:fiq000:v:12:y:2016:i:3:id:701
    DOI: 10.1515/fiqf-2016-0001
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