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Asymmetric Multifractal Detrended Fluctuation Analysis (A-MFDFA)
2018The presence of multifractality suggests the inefficiency (Cajueiro and Tabak 2004, 2004, 2008; Cajueiro et al. 2009; Tabak and Cajueiro 2007; Wang et al. 2010), volatility predictability (Wei and Wang 2008), crash predictions (Wei and Wang 2008; Grech and Pamula 2008), and complexity (Matia et al. 2003; Kumar and Deo 2009; Norouzzadeh and Jafari 2005)
Guangxi Cao, Ling-Yun He, Jie Cao
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Applications of Multifractal Detrended Fluctuation Analysis
Journal of Information and Computing ScienceIn recent years, multifractal detrended fluctuation analysis (MF-DFA) has become an important tool for detecting the scale and long correlation of non-stationary time series. With the continuous development of multifractal theory, researchers have widely applied it in physics, chemistry, biology, economy, etc.
Dongxu Dai +8 more
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Characterizing Detrended Fluctuation Analysis of multifractional Brownian motion
Physica A: Statistical Mechanics and its Applications, 2015Abstract The Hurst exponent ( H ) is widely used to quantify long range dependence in time series data and is estimated using several well known techniques. Recognizing its ability to remove trends the Detrended Fluctuation Analysis (DFA) is used extensively to estimate a Hurst exponent in non-stationary data. Multifractional Brownian motion (mBm)
V.A. Setty, A.S. Sharma
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Chinese Physics B, 2011
Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series.
Zhou, Yu, Yee, Leung, Yu, Zuguo
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Multifractal detrended fluctuation analysis (MF-DFA) is a relatively new method of multifractal analysis. It is extended from detrended fluctuation analysis (DFA), which was developed for detecting the long-range correlation and the fractal properties in stationary and non-stationary time series.
Zhou, Yu, Yee, Leung, Yu, Zuguo
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Relationships of exponents in two-dimensional multifractal detrended fluctuation analysis
Physical Review E, 2013Multifractal detrended fluctuation analysis (MF-DFA) is a generalization of the conventional multifractal analysis. It is extended from the detrended fluctuation analysis (DFA) which is developed for the purpose of detecting long-range correlation and fractal property in stationary and nonstationary time series.
Zhou, Yu, Yee, Leung, Yu, Zuguo
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Are Islamic stock markets efficient? A multifractal detrended fluctuation analysis
Finance Research Letters, 2018Abstract In this paper, we use the methods of Multifractal Detrended Fluctuation Analysis (MF-DFA) and DFA based on generalized Hurst exponents to compare the relative efficiency between short- and long-run horizons and small and large fluctuations of emerging and developed Islamic stock markets.
Bouoiyour, Jamal +2 more
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Multifractal detrended fluctuation analysis: Practical applications to financial time series
Mathematics and Computers in Simulation, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Thompson, James R., Wilson, James R.
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Multifractal Detrended Fluctuation Analysis of Return on Bitcoin*
International Review of Finance, 2019AbstractWe revisit the issue of market efficiency of Bitcoin, which is an important part of the new financial technology (FinTech), by analyzing the Bitcoin returns using two recently developed analytical techniques called bipower variation method and Multifractal Detrended Fluctuation Analysis (MF‐DFA). MF‐DFA allows us to analyze the return series in
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Multifractal Detrended Fluctuation Analysis of Eye-Tracking Data
2017In this contribution, we perform detrended fluctuation analysis on eye movement data obtained using an eye tracker with different experimentation subjects performing a set of distinct cognitive tasks. We define three different paradigms: spotting differences among two similar pictures, answering questions in a multiple choice questionnaire, and ...
M. L. Freije +7 more
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Physica A: Statistical Mechanics and its Applications, 2019
Abstract In this paper, we comprehensively investigate the multifractality of Bitcoin market, find the sources of multifractal features and go further to study the multifractal cross-correlations between Bitcoin prices and other financial markets (gold and USDX). We find both Bitcoin prices and volumes display multifractal features.
Xin Zhang, Liansheng Yang, Yingming Zhu
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Abstract In this paper, we comprehensively investigate the multifractality of Bitcoin market, find the sources of multifractal features and go further to study the multifractal cross-correlations between Bitcoin prices and other financial markets (gold and USDX). We find both Bitcoin prices and volumes display multifractal features.
Xin Zhang, Liansheng Yang, Yingming Zhu
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