Log-periodic power law and Gene Lized Hurst exponent analysis in estimating an asset bubble bursting time
Log-periodic power law and Gene Lized Hurst exponent analysis in estimating an asset bubble bursting time

Summary/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.

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