Time averaging, ageing and delay analysis of financial time series

  • We introduce three strategies for the analysis of financial time series based on time averaged observables. These comprise the time averaged mean squared displacement (MSD) as well as the ageing and delay time methods for varying fractions of the financial time series. We explore these concepts via statistical analysis of historic time series for several Dow Jones Industrial indices for the period from the 1960s to 2015. Remarkably, we discover a simple universal law for the delay time averaged MSD. The observed features of the financial time series dynamics agree well with our analytical results for the time averaged measurables for geometric Brownian motion, underlying the famed Black–Scholes–Merton model. The concepts we promote here are shown to be useful for financial data analysis and enable one to unveil new universal features of stock market dynamics.

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Metadaten
Author:Andrey G. Cherstvy, Deepak Vinod, Erez Aghion, Aleksei V. Chechkin, Ralf MetzlerORCiD
URN:urn:nbn:de:kobv:517-opus4-400541
Series (Serial Number):Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (347)
Document Type:Postprint
Language:English
Date of first Publication:2017/09/01
Year of Completion:2017
Publishing Institution:Universität Potsdam
Release Date:2017/09/01
Tag:diffusion; financial time series; geometric Brownian motion; time averaging
Pagenumber:11
Source:New journal of physics 19 (2017) 063045. - DOI: 10.1088/1367-2630/aa7199
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Peer Review:Referiert
Publication Way:Open Access
Licence (English):License LogoCreative Commons - Attribution 3.0 unported
Licence (German):License LogoKeine Nutzungslizenz vergeben - es gilt das deutsche Urheberrecht
Notes extern:Bibliographieeintrag der Originalveröffentlichung/Quelle