<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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. </p></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.

Log-Periodic Power Law and Generalized Hurst Exponent Analysis in Estimating an Asset Bubble Bursting Time

Institute of Nuclear Physics, Polish Academy of Sciences,

Cracow University of Technology Faculty of Physics, Mathematics and Computer Science,

Financial Internet Quarterly

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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...

Log-Periodic Power Law and Generalized Hurst Exponent Analysis in Estimating an Asset Bubble Bursting Time

Online veröffentlicht: 09. Feb. 2017

Seitenbereich: 49 - 58

Eingereicht: 31. Okt. 2015

Akzeptiert: 14. Sept. 2016

DOI: https://doi.org/10.1515/fiqf-2016-0001

Schlüsselwörter
asset bubble, crash, Log-Periodic Power Law, Generalized Hurst Exponent, multifractality, forecasting, bursting time estimation

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Log-Periodic Power Law and Generalized Hurst Exponent Analysis in Estimating an Asset Bubble Bursting Time

Online veröffentlicht: 09. Feb. 2017

Seitenbereich: 49 - 58

Eingereicht: 31. Okt. 2015

Akzeptiert: 14. Sept. 2016

DOI: https://doi.org/10.1515/fiqf-2016-0001

Schlüsselwörterasset bubble, crash, Log-Periodic Power Law, Generalized Hurst Exponent, multifractality, forecasting, bursting time estimation

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
asset bubble, crash, Log-Periodic Power Law, Generalized Hurst Exponent, multifractality, forecasting, bursting time estimation