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In this short report, we investigate the ability of the DCCA coefficient to measure correlation level between non-stationary series. Based on a wide Monte Carlo simulation study, we show that the DCCA coefficient can estimate the…

Statistical Finance · Quantitative Finance 2014-03-27 Ladislav Kristoufek

We focus on power-law coherency as an alternative approach towards studying power-law cross-correlations between simultaneously recorded time series. To be able to study empirical data, we introduce three estimators of the power-law…

Statistical Finance · Quantitative Finance 2018-10-30 Ladislav Kristoufek

The Detrending Moving Average (DMA) algorithm has been widely used in its several variants for characterizing long-range correlations of random signals and sets (one-dimensional sequences or high-dimensional arrays) either over time or…

Data Analysis, Statistics and Probability · Physics 2016-07-01 Anna Carbone , Ken Kiyono

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

The Hurst exponent $H$ of long range correlated series can be estimated by means of the Detrending Moving Average (DMA) method. A computational tool defined within the algorithm is the generalized variance $ \sigma_{DMA}^2={1}/{(N-n)}\sum_i…

Data Analysis, Statistics and Probability · Physics 2009-03-20 Sergio Arianos , Anna Carbone

The detrending moving average (DMA) algorithm is one of the best performing methods to quantify the long-term correlations in nonstationary time series. Many long-term correlated time series in real systems contain various trends. We…

Data Analysis, Statistics and Probability · Physics 2015-08-04 Ying-Hui Shao , Gao-Feng Gu , Zhi-Qiang Jiang , Wei-Xing Zhou

Detrended fluctuation analysis (DFA) and detrended moving average (DMA) are two scaling analysis methods designed to quantify correlations in noisy non-stationary signals. We systematically study the performance of different variants of the…

Other Condensed Matter · Physics 2009-11-10 L. Xu , P. Ch. Ivanov , K. Hu , Z. Chen , A. Carbone , H. E. Stanley

We examine several recently suggested methods for the detection of long-range correlations in data series based on similar ideas as the well-established Detrended Fluctuation Analysis (DFA). In particular, we present a detailed comparison…

Statistical Finance · Quantitative Finance 2009-11-13 Amir Bashan , Ronny Bartsch , Jan W. Kantelhardt , Shlomo Havlin

We study finite sample properties of estimators of power-law cross-correlations -- detrended cross-correlation analysis (DCCA), height cross-correlation analysis (HXA) and detrending moving-average cross-correlation analysis (DMCA) -- with…

Data Analysis, Statistics and Probability · Physics 2014-12-11 Ladislav Kristoufek

Distance correlation coefficient (DCC) can be used to identify new associations and correlations between multiple variables. The distance correlation coefficient applies to variables of any dimension, can be used to determine smaller sets…

Statistical Finance · Quantitative Finance 2023-01-13 J. E. Salgado-Hernández , Manan Vyas

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

We make the comparative study of scaling range properties for detrended fluctuation analysis (DFA), detrended moving average analysis (DMA) and recently proposed new technique called modified detrended moving average analysis (MDMA). Basic…

Data Analysis, Statistics and Probability · Physics 2013-11-05 Dariusz Grech , Zygmunt Mazur

Here we propose a method, based on detrended covariance which we call detrended cross-correlation analysis (DXA), to investigate power-law cross-correlations between different simultaneously-recorded time series in the presence of…

Statistical Finance · Quantitative Finance 2009-11-13 Boris Podobnik , H. Eugene Stanley

The strength of association between a pair of data vectors is represented by a nonnegative real number, called matching weight. For dimensionality reduction, we consider a linear transformation of data vectors, and define a matching error…

Machine Learning · Statistics 2015-12-15 Hidetoshi Shimodaira

We present a general framework of detrending methods of fluctuation analysis of which detrended fluctuation analysis (DFA) is one prominent example. Another more recently introduced method is detrending moving average (DMA). Both methods…

Statistical Mechanics · Physics 2019-04-03 Marc Höll , Ken Kiyono , Holger Kantz

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using classic detrended cross-correlation analysis (DCCA) without considering these common factors will bias…

Statistical Finance · Quantitative Finance 2015-06-29 Xi-Yuan Qian , Ya-Min Liu , Zhi-Qiang Jiang , Boris Podobnik , Wei-Xing Zhou , H. Eugene Stanley

It is ubiquitous in natural and social sciences that two variables, recorded temporally or spatially in a complex system, are cross-correlated and possess multifractal features. We propose a new method called multifractal detrended…

Data Analysis, Statistics and Probability · Physics 2008-12-02 Wei-Xing Zhou

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. The multifractal detrended cross-correlation analysis (MF-DCCA) approaches can…

Statistical Finance · Quantitative Finance 2015-03-19 Zhi-Qiang Jiang , Wei-Xing Zhou

In recent years it was shown both theoretically and experimentally that in certain systems exhibiting anomalous diffusion the time and ensemble average mean squared displacement are remarkably different. The ensemble average diffusivity is…

Statistical Mechanics · Physics 2017-12-20 Philipp Meyer , Eli Barkai , Holger Kantz

In this paper, we propose a novel framework for non-stationary time-series analysis that replaces conventional correlation-based statistics with direct estimation of statistical dependence in the normalized joint density of input and target…

Machine Learning · Computer Science 2026-04-09 Yao Sun , Bo Hu , Jose Principe
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