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Erscheinungsjahr: 
2016
Quellenangabe: 
[Journal:] e-Finanse: Financial Internet Quarterly [ISSN:] 1734-039X [Volume:] 12 [Issue:] 3 [Publisher:] University of Information Technology and Management [Place:] Rzeszów [Year:] 2016 [Pages:] 49-58
Verlag: 
University of Information Technology and Management, Rzeszów
Zusammenfassung: 
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.
Schlagwörter: 
asset bubble
crash
Log-Periodic Power Law
Generalized Hurst Exponent
multiractality
forecasting
bursting time estimation
JEL: 
C22
C53
C61
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