Scale dependence of the directional relationships between coupled time series

Shirazi, Amir Hossein Masnadi; Aghamohammadi, Cina; Anvari, Mehrnaz; Bahraminasab, Alireza; Tabar, M. Reza Rahimi; Peinke, Joachim; Sahimi, Muhammad; Marsili, Matteo

doi:10.1088/1742-5468/2013/02/p02042

Cited by 4 publications

(5 citation statements)

References 35 publications

(31 reference statements)

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“…This means that price changes are random, and the variety of patterns are at the maximum level. Financial time series may behave differently on different time scales [28][29][30][31][32]. We investigate the variety of patterns in a financial time series on different time scales.…”

Section: High Frequency Trading and Its Effect On Fading Patternsmentioning

confidence: 99%

Permutation approach, high frequency trading and variety of micro patterns in financial time series

Aghamohammadi

Ebrahimian

Tahmooresi

2014

Physica A: Statistical Mechanics and its Applications

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Permutation approach is suggested as a method to investigate financial time series in micro scales. The method is used to see how high frequency trading in recent years has affected the micro patterns which may be seen in financial time series. Tick to tick exchange rates are considered as examples. It is seen that variety of patterns evolve through time; and that the scale over which the target markets have no dominant patterns, have decreased steadily over time with the emergence of higher frequency trading. 1

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Section: High Frequency Trading and Its Effect On Fading Patternsmentioning

confidence: 99%

Permutation approach, high frequency trading and variety of micro patterns in financial time series

Aghamohammadi

Ebrahimian

Tahmooresi

2014

Physica A: Statistical Mechanics and its Applications

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“…The same fluctuation theory has recently been used to identify fluctuations in macroscopic thermodynamic functioning in Maxwellian Demons [50]. Moreover, the method can be applied to many stochastic systems to explore their rare behaviors, from natural processes observed in fluid turbulence [51,52], physiology [53,54], surface science [55,56], meteorological processes [57], cosmic microwave background radiation [58], seismic time series [59] to designed systems found in finance [60][61][62][63], renewable energy [64,65], and traffic [66,67]. It gives a full description of a process, from its typical to its rare behaviors.…”

Section: Discussionmentioning

confidence: 99%

Minimum memory for generating rare events

Aghamohammadi

Crutchfield

2017

Phys. Rev. E

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We classify the rare events of structured, memoryful stochastic processes and use this to analyze sequential and parallel generators for these events. Given a stochastic process, we introduce a method to construct a new process whose typical realizations are a given process' rare events. This leads to an expression for the minimum memory required to generate rare events. We then show that the recently discovered classical-quantum ambiguity of simplicity also occurs when comparing the structure of process fluctuations.

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“…There are a number of alternative formulations for ρ XY (s, τ ), such as the one recently proposed by Shirazi et al [2013], and based on the amplitudes instead of the real part of the coefficients. This neglects the information about temporal asymmetries to focus only on the amplitude of correlations across diverse scales.…”

Section: Continuous Wavelet Filtering: Generalitiesmentioning

confidence: 99%

Wavelet correlations to reveal multiscale coupling in geophysical systems

Casagrande,

Mueller,

Miralles

et al. 2015

Preprint

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The interactions between climate and the environment are highly complex. Due to this complexity, process-based models are often preferred to estimate the net magnitude and directionality of interactions in the Earth System. However, these models are based on simplifications of our understanding of nature, thus are unavoidably imperfect. Conversely, observationbased data of climatic and environmental variables are becoming increasingly accessible over large scales due to the progress of space-borne sensing technologies and data-assimilation techniques. Albeit uncertain, these data enable the possibility to start unraveling complex multivariable, multiscale relationships if the appropriate statistical methods are applied.Here, we investigate the potential of the wavelet cross-correlation method as a tool for identifying multiscale interactions, feedback and regime shifts in geophysical systems. The ability of wavelet cross-correlation to resolve the fast and slow components of coupled systems is tested on synthetic data of known directionality, and then applied to observations to study one of the most critical interactions between land and atmosphere: the coupling between soil moisture and near-ground air temperature. Results show that our method is not only able to capture the dynamics of the soil moisture-temperature coupling over a wide range of temporal scales (from days to several months) and climatic regimes (from wet to dry), but also to consistently identify the magnitude and directionality of the coupling. Consequently, wavelet crosscorrelations are presented as a promising tool for the study of multiscale in-D R A F T May 15, 2018, 11:04am D R A F T X -4 CASAGRANDE ET AL.: MULTISCALE COUPLING IN THE EARTH SYSTEMteractions, with the potential of being extended to the analysis of causal relationships in the Earth system.

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Scale dependence of the directional relationships between coupled time series

Cited by 4 publications

References 35 publications

Permutation approach, high frequency trading and variety of micro patterns in financial time series

Permutation approach, high frequency trading and variety of micro patterns in financial time series

Minimum memory for generating rare events

Wavelet correlations to reveal multiscale coupling in geophysical systems

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