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A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and…

Physics and Society · Physics 2017-07-13 Yanguang Chen

Multifractals are inhomogeneous measures (or functions) which are typically described by a full spectrum of real dimensions, as opposed to a single real dimension. Results from the study of fractal strings in the analysis of their geometry,…

Mathematical Physics · Physics 2008-10-07 Michel L. Lapidus , John A. Rock

Detrended Fluctuation Analysis (DFA) is the most popular fractal analytical technique used to evaluate the strength of long-range correlations in empirical time series in terms of the Hurst exponent, $H$. Specifically, DFA quantifies the…

Quantitative Methods · Quantitative Biology 2023-01-27 Aaron D. Likens , Madhur Mangalam , Aaron Y. Wong , Anaelle C. Charles , Caitlin Mills

We investigate how simultaneously recorded long-range power-law correlated multi-variate signals cross-correlate. To this end we introduce a two-component ARFIMA stochastic process and a two-component FIARCH process to generate coupled…

Statistical Finance · Quantitative Finance 2009-11-13 Boris Podobnik , Davor Horvatic , Alfonso Lam Ng , H. Eugene Stanley , Plamen Ch. Ivanov

Multifractal scaling (MFS) refers to structures that can be described as a collection of interwoven fractal subsets which exhibit power-law spatial scaling behavior with a range of scaling exponents (concentration, or singularity,…

Astrophysics · Physics 2009-10-30 David W. Chappell , John Scalo

For many complex systems the interaction of different scales is among the most interesting and challenging features. It seems not very successful to extract the physical properties in different scale regimes by the existing approaches, such…

Fluid Dynamics · Physics 2015-05-14 L. P. Wang , Y. X. Huang

Multifractal detrended fluctuation analysis (MFDFA) has become a central method to characterise the variability and uncertainty in empiric time series. Extracting the fluctuations on different temporal scales allows quantifying the strength…

Computational Physics · Physics 2022-01-05 Leonardo Rydin Gorjão , Galib Hassan , Jürgen Kurths , Dirk Witthaut

We study quantitatively the level of false multifractal signal one may encounter while analyzing multifractal phenomena in time series within multifractal detrended fluctuation analysis (MF-DFA). The investigated effect appears as a result…

Data Analysis, Statistics and Probability · Physics 2015-06-16 Dariusz Grech , Grzegorz Pamuła

We propose a fully multivariate generalization of multifractal detrended fluctuation analysis (MFDFA) and leverage it to develop a fault diagnosis framework for multichannel machine vibration data. We introduce a novel covariance-weighted…

Signal Processing · Electrical Eng. & Systems 2025-11-27 Khuram Naveed , Naveed ur Rehman

Multifractal analysis is a forecasting technique used to study the scaling regularity properties of financial returns, to analyze the long-term memory and predictability of financial markets. In this paper, we propose a novel structural…

Statistical Finance · Quantitative Finance 2023-04-18 Foued Saâdaoui

Multifractal time series analysis is a approach that shows the possible complexity of the system. Nowadays, one of the most popular and the best methods for determining multifractal characteristics is Multifractal Detrended Fluctuation…

Statistical Finance · Quantitative Finance 2015-10-20 Rafal Rak , Pawel Zięba

We examine the scaling regime for the detrended fluctuation analysis (DFA) - the most popular method used to detect the presence of long memory in data and the fractal structure of time series. First, the scaling range for DFA is studied…

Data Analysis, Statistics and Probability · Physics 2015-06-05 Dariusz Grech , Zygmunt Mazur

The detrending moving average (DMA) algorithm is a widely used technique to quantify the long-term correlations of non-stationary time series and the long-range correlations of fractal surfaces, which contains a parameter $\theta$…

Statistical Finance · Quantitative Finance 2010-08-03 Gao-Feng Gu , Wei-Xing Zhou

Multifractal detrended cross-correlation methodology is described and applied to Foreign exchange (Forex) market time series. Fluctuations of high frequency exchange rates of eight major world currencies over 2010-2018 period are used to…

Statistical Finance · Quantitative Finance 2019-12-17 Robert Gębarowski , Paweł Oświęcimka , Marcin Wątorek , Stanisław Drożdż

We present a novel method, Fractal Space-Curve Analysis (FSCA), which combines Space-Filling Curve (SFC) mapping for dimensionality reduction with fractal Detrended Fluctuation Analysis (DFA). The method is suitable for multidimensional…

In the canonical framework, we propose an alternative approach for the multifractal analysis based on the detrending moving average method (MF-DMA). We define a canonical measure such that the multifractal mass exponent $\tau(q)$ is related…

Statistical Finance · Quantitative Finance 2019-02-13 Hai-Chuan Xu , Gao-Feng Gu , Wei-Xing Zhou

Angular x-ray cross-correlation analysis (XCCA) is an approach to study the structure of disordered systems using the results of coherent x-ray scattering experiments. Here, we present the results of simulations that validate our…

Disordered Systems and Neural Networks · Physics 2012-06-07 R. P. Kurta , M. Altarelli , E. Weckert , I. A. Vartanyants

The detrended cross-correlation coefficient $\rho_{\rm DCCA}$ has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, non-stationary time series. It is based on the detrended…

Data Analysis, Statistics and Probability · Physics 2015-12-09 Jaroslaw Kwapien , Pawel Oswiecimka , Stanislaw Drozdz

Correlations in multifractal series have been investigated, extensively. Almost all approaches try to find scaling features of a given time series. However, the analysis of such scaling properties has some difficulties such as finding a…

Data Analysis, Statistics and Probability · Physics 2020-02-03 Pouya Manshour

While scale invariance is commonly observed in each component of real world multivariate signals, it is also often the case that the inter-component correlation structure is not fractally connected, i.e., its scaling behavior is not…

Statistics Theory · Mathematics 2017-09-13 Herwig Wendt , Gustavo Didier , Sébastien Combrexelle , Patrice Abry