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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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Author details:Andrey G. CherstvyORCiD, Deepak Vinod, Erez Aghion, Aleksei V. ChechkinORCiDGND, Ralf MetzlerORCiDGND
DOI:https://doi.org/10.1088/1367-2630/aa7199
ISSN:1367-2630
Title of parent work (English):New journal of physics : the open-access journal for physics
Publisher:IOP Publ. Ltd.
Place of publishing:Bristol
Publication type:Article
Language:English
Year of first publication:2017
Publication year:2017
Release date:2020/04/20
Tag:diffusion; financial time series; geometric Brownian motion; time averaging
Volume:19
Number of pages:11
First page:135
Last Page:147
Funding institution:DAAD fellowship; KoUP grant of the University of Potsdam; MINERVA Short-Term Research Grant; Deutsche Forschungsgemeinschaft [ME 1535/6-1]; Potsdam University
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Physik und Astronomie
Peer review:Referiert
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