40054
2017
2017
eng
11
postprint
1
--
2017-09-01
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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.
urn:nbn:de:kobv:517-opus4-400541
online registration
New journal of physics 19 (2017) 063045. - DOI: 10.1088/1367-2630/aa7199
<a href="http://publishup.uni-potsdam.de/opus4-ubp/frontdoor/index/index/docId/40053">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
Keine öffentliche Lizenz: Unter Urheberrechtsschutz
Andrey G. Cherstvy
Deepak Vinod
Erez Aghion
Aleksei V. Chechkin
Ralf Metzler
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
347
eng
uncontrolled
diffusion
eng
uncontrolled
financial time series
eng
uncontrolled
geometric Brownian motion
eng
uncontrolled
time averaging
Physik
open_access
Institut für Physik und Astronomie
Referiert
Open Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/40054/pmn347_online.pdf
57764
2022
2022
eng
16
1303
postprint
1
2022-07-18
2022-07-18
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Unravelling the origins of anomalous diffusion
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
from molecules to migrating storks
10.25932/publishup-57764
urn:nbn:de:kobv:517-opus4-577643
1866-8372
Version of record
<a href="http://publishup.uni-potsdam.de/57765">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
CC-BY - Namensnennung 4.0 International
Ohad Vilk
Erez Aghion
Tal Avgar
Carsten Beta
Oliver Nagel
Adal Sabri
Raphael Sarfati
Daniel K. Schwartz
Matthias Weiß
Diego Krapf
Ran Nathan
Ralf Metzler
Michael Assaf
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
1303
Physik
open_access
Institut für Physik und Astronomie
Referiert
Green Open-Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/57764/pmnr1303.pdf