LOG-PERIODIC POWER LAW AND GENE LIZED HURST EXPONENT ANALYSIS IN ESTIMATING AN ASSET BUBBLE BURSTING TIME

Marcin Wątorek and Bartosz Stawiarski
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Marcin Wątorek: Institute of Nuclear Physics, Polish Academy of Sciences
Bartosz Stawiarski: Cracow University of Technology Faculty of Physics

Financial Internet Quarterly, 2016, vol. 12, issue 3, 49-58

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.

Keywords: asset bubble; crash; Log-Periodic Power Law; Generalized Hurst Exponent; multiractality; forecasting; bursting time estimation (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:wsz:fiq000:v:12:y:2016:i:3:id:701

DOI: 10.1515/fiqf-2016-0001

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