Log-periodic power law and genelized hurst exponent analysis in estimating an asset bubble bursting time

Artikel

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: e-Finanse: Financial Internet Quarterly ; ISSN: 1734-039X ; Volume: 12 ; Year: 2016 ; Issue: 3 ; Pages: 49-58 ; Rzeszów: University of Information Technology and Management

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Forecasting Models; Simulation Methods ; Optimization Techniques; Programming Models; Dynamic Analysis
• Subject: asset bubble ; crash ; Log-Periodic Power Law ; Generalized Hurst Exponent ; multiractality ; forecasting ; bursting time estimation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Wątorek, Marcin ; Stawiarski, Bartosz
• Event: Veröffentlichung
• (who): University of Information Technology and Management
• (where): Rzeszów
• (when): 2016

Further information

• DOI: doi:10.1515/fiqf-2016-0001
• Handle: http://hdl.handle.net/10419/197439
• Last update: 10.03.2025, 11:42 AM CET