TY - JOUR A1 - Vilk, Ohad A1 - Aghion, Erez A1 - Avgar, Tal A1 - Beta, Carsten A1 - Nagel, Oliver A1 - Sabri, Adal A1 - Sarfati, Raphael A1 - Schwartz, Daniel K. A1 - Weiß, Matthias A1 - Krapf, Diego A1 - Nathan, Ran A1 - Metzler, Ralf A1 - Assaf, Michael T1 - Unravelling the origins of anomalous diffusion BT - from molecules to migrating storks JF - Physical Review Research N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1103/PhysRevResearch.4.033055 SN - 2643-1564 VL - 4 IS - 3 SP - 033055-1 EP - 033055-16 PB - American Physical Society CY - College Park, MD ER - TY - GEN A1 - Vilk, Ohad A1 - Aghion, Erez A1 - Avgar, Tal A1 - Beta, Carsten A1 - Nagel, Oliver A1 - Sabri, Adal A1 - Sarfati, Raphael A1 - Schwartz, Daniel K. A1 - Weiß, Matthias A1 - Krapf, Diego A1 - Nathan, Ran A1 - Metzler, Ralf A1 - Assaf, Michael T1 - Unravelling the origins of anomalous diffusion BT - from molecules to migrating storks T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1303 Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-577643 SN - 1866-8372 IS - 1303 ER - TY - JOUR A1 - Cherstvy, Andrey G. A1 - Vinod, Deepak A1 - Aghion, Erez A1 - Chechkin, Aleksei V. A1 - Metzler, Ralf T1 - Time averaging, ageing and delay analysis of financial time series JF - New journal of physics N2 - 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. KW - time averaging KW - diffusion KW - geometric Brownian motion KW - financial time series Y1 - 2017 U6 - https://doi.org/10.1088/1367-2630/aa7199 SN - 1367-2630 VL - 19 SP - 1 EP - 11 PB - IOP CY - London ER - TY - GEN A1 - Cherstvy, Andrey G. A1 - Vinod, Deepak A1 - Aghion, Erez A1 - Chechkin, Aleksei V. A1 - Metzler, Ralf T1 - Time averaging, ageing and delay analysis of financial time series N2 - 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 347 KW - diffusion KW - financial time series KW - geometric Brownian motion KW - time averaging Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-400541 ER - TY - JOUR A1 - Cherstvy, Andrey G. A1 - Vinod, Deepak A1 - Aghion, Erez A1 - Chechkin, Aleksei V. A1 - Metzler, Ralf T1 - Time averaging, ageing and delay analysis of financial time series JF - New journal of physics : the open-access journal for physics N2 - 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. KW - time averaging KW - diffusion KW - geometric Brownian motion KW - financial time series Y1 - 2017 U6 - https://doi.org/10.1088/1367-2630/aa7199 SN - 1367-2630 VL - 19 SP - 135 EP - 147 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Cherstvy, Andrey G. A1 - Vinod, Deepak A1 - Aghion, Erez A1 - Sokolov, Igor M. A1 - Metzler, Ralf T1 - Scaled geometric Brownian motion features sub- or superexponential ensemble-averaged, but linear time-averaged mean-squared displacements JF - Physical review : E, Statistical, nonlinear and soft matter physics N2 - Various mathematical Black-Scholes-Merton-like models of option pricing employ the paradigmatic stochastic process of geometric Brownian motion (GBM). The innate property of such models and of real stock-market prices is the roughly exponential growth of prices with time [on average, in crisis-free times]. We here explore the ensemble- and time averages of a multiplicative-noise stochastic process with power-law-like time-dependent volatility, sigma(t) similar to t(alpha), named scaled GBM (SGBM). For SGBM, the mean-squared displacement (MSD) computed for an ensemble of statistically equivalent trajectories can grow faster than exponentially in time, while the time-averaged MSD (TAMSD)-based on a sliding-window averaging along a single trajectory-is always linear at short lag times Delta. The proportionality factor between these the two averages of the time series is Delta/T at short lag times, where T is the trajectory length, similarly to GBM. This discrepancy of the scaling relations and pronounced nonequivalence of the MSD and TAMSD at Delta/T << 1 is a manifestation of weak ergodicity breaking for standard GBM and for SGBM with s (t)-modulation, the main focus of our analysis. The analytical predictions for the MSD and mean TAMSD for SGBM are in quantitative agreement with the results of stochastic computer simulations. Y1 - 2021 U6 - https://doi.org/10.1103/PhysRevE.103.062127 SN - 2470-0045 SN - 2470-0053 VL - 103 IS - 6 PB - American Physical Society CY - College Park ER - TY - JOUR A1 - Meyer, Philipp A1 - Aghion, Erez A1 - Kantz, Holger T1 - Decomposing the effect of anomalous diffusion enables direct calculation of the Hurst exponent and model classification for single random paths JF - Journal of physics / Institute of Physics. A, Mathematical, nuclear and general N2 - Recently, a large number of research teams from around the world collaborated in the so-called 'anomalous diffusion challenge'. Its aim: to develop and compare new techniques for inferring stochastic models from given unknown time series, and estimate the anomalous diffusion exponent in data. We use various numerical methods to directly obtain this exponent using the path increments, and develop a questionnaire for model selection based on feature analysis of a set of known stochastic processes given as candidates. Here, we present the theoretical background of the automated algorithm which we put for these tasks in the diffusion challenge, as a counter to other pure data-driven approaches. KW - time-series analysis KW - decomposing anomalous diffusion KW - anomalous KW - diffusion exponent KW - process inference Y1 - 2022 U6 - https://doi.org/10.1088/1751-8121/ac72d4 SN - 1751-8113 SN - 1751-8121 VL - 55 IS - 27 PB - IOP Publ. Ltd. CY - Bristol ER -