Codifference can detect ergodicity breaking and non-Gaussianity

  • We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.

Download full text files

  • pmnr748.pdfeng

    SHA-1: 75e24aea31e6fd342b71beac91bcd6e395ac296d

Export metadata

Additional Services

Share in Twitter Search Google Scholar Statistics
Author:Jakub ŚlęzakORCiD, Ralf MetzlerORCiD, Marcin MagdziarzORCiD
Parent Title (German):Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (748)
Document Type:Postprint
Date of first Publication:2019/10/09
Year of Completion:2019
Publishing Institution:Universität Potsdam
Release Date:2019/10/09
Tag:anomalous diffusion; diffusion; stochastic time series
Source:New Journal of Physics 21 (2019) DOI: 10.1088/1367-2630/ab13f3
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Peer Review:Referiert
Publication Way:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, 3.0 Deutschland
Notes extern:Bibliographieeintrag der Originalveröffentlichung/Quelle