Multifractal analysis of financial markets: A review
Multifractality is ubiquitously observed in complex natural and socioeconomic systems.
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …
Multifractal analysis provides powerful tools to understand the complex nonlinear nature of …
Approaching complexity by stochastic methods: From biological systems to turbulence
This review addresses a central question in the field of complex systems: given a fluctuating
(in time or space), sequentially measured set of experimental data, how should one analyze …
(in time or space), sequentially measured set of experimental data, how should one analyze …
A multifractal approach for stock market inefficiency
In this paper, the multifractality degree in a collection of developed and emerging stock
market indices is evaluated. Empirical results suggest that the multifractality degree can be …
market indices is evaluated. Empirical results suggest that the multifractality degree can be …
MFDFA: Efficient multifractal detrended fluctuation analysis in python
Multifractal detrended fluctuation analysis (MFDFA) has become a central method to
characterise the variability and uncertainty in empiric time series. Extracting the fluctuations …
characterise the variability and uncertainty in empiric time series. Extracting the fluctuations …
Quantitative features of multifractal subtleties in time series
Abstract Based on the Multifractal Detrended Fluctuation Analysis (MFDFA) and on the
Wavelet Transform Modulus Maxima (WTMM) methods we investigate the origin of …
Wavelet Transform Modulus Maxima (WTMM) methods we investigate the origin of …
A modified multifractal detrended fluctuation analysis (MFDFA) approach for multifractal analysis of precipitation
Abstract Multifractal Detrended Fluctuation Analysis (MFDFA) is an efficient method to
investigate the long-term correlations of the power law of non-stationary time series, in which …
investigate the long-term correlations of the power law of non-stationary time series, in which …
Facilitating joint chaos and fractal analysis of biosignals through nonlinear adaptive filtering
Background Chaos and random fractal theories are among the most important for fully
characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis …
characterizing nonlinear dynamics of complicated multiscale biosignals. Chaos analysis …
Multifractal detrended cross-correlation analysis of temporal and spatial seismic data
S Shadkhoo, GR Jafari - The European Physical Journal B, 2009 - Springer
Abstract We use Multi-Fractal Detrended Cross-Correlation Analysis (MF-DXA) method to
investigate the cross-correlation of temporal and spatial inter-events seismic data, which …
investigate the cross-correlation of temporal and spatial inter-events seismic data, which …
Multifractal detrended fluctuation analysis of human gait diseases
S Dutta, D Ghosh, S Chatterjee - Frontiers in physiology, 2013 - frontiersin.org
In this paper multifractal detrended fluctuation analysis (MFDFA) is used to study the human
gait time series for normal and diseased sets. It is observed that long range correlation is …
gait time series for normal and diseased sets. It is observed that long range correlation is …
A modified multifractal detrended fluctuation analysis (MFDFA) approach for multifractal analysis of precipitation in dongting lake basin, China
X Zhang, G Zhang, L Qiu, B Zhang, Y Sun, Z Gui… - Water, 2019 - mdpi.com
Multifractal detrended fluctuation analysis (MFDFA) method can examine higher-
dimensional fractal and multifractal characteristics hidden in time series. However, removal …
dimensional fractal and multifractal characteristics hidden in time series. However, removal …