2013
DOI: 10.1016/j.physa.2013.07.045
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On the multifractal effects generated by monofractal signals

Abstract: 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 of finite length of used data series and is additionally amplified by the long-term memory the data eventually may contain. We provide the detailed quantitative description of such apparent multifractal background signal as a threshold in spread of generalized Hurst exponent… Show more

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Cited by 45 publications
(43 citation statements)
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References 68 publications
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“…According to refs. [50,51] the spurious multifractal spread ∆h F SE due to presence of FSE is limited then to ∆h F SE 0.02 for q ≈ 15 and ∆h F SE 10 −3 for q ≈ 2. Examples of the fluctuation function (F q (s)), the multifractal spectrum (f (α)) and the generalized Hurst exponent (h(q)) (both for…”
Section: Influence Of Symmetric and Asymmetric Broad Distributions Ofmentioning
confidence: 99%
“…According to refs. [50,51] the spurious multifractal spread ∆h F SE due to presence of FSE is limited then to ∆h F SE 0.02 for q ≈ 15 and ∆h F SE 10 −3 for q ≈ 2. Examples of the fluctuation function (F q (s)), the multifractal spectrum (f (α)) and the generalized Hurst exponent (h(q)) (both for…”
Section: Influence Of Symmetric and Asymmetric Broad Distributions Ofmentioning
confidence: 99%
“…The scaling behavior of two point autocovariance function C s = ∆x t ∆x t+s can then be checked qualitatively and quantitatively as in Ref. [22].…”
mentioning
confidence: 89%
“…This relatively new form of entropy is emerging over an immense area of applications in social science, including economics. One of the fields of interest is modelling and predicting markets of financial returns (Drożdż & Kwapień, 2012), (Grech & Pamula, 2013). Nevertheless, due to the high frequency nature of Big Data in Official Statistics (e.g., Braaksma & Zeelenberg, 2015), the PL-based non-extensive entropy econometrics should be seen as a potential and natural estimation device in this new statistical area.…”
Section: Definition and Shannon-tsallis Entropy Relationshipsmentioning
confidence: 99%
“…However, it seems logical to imagine systems visiting the allowed micro-states in a much more complex way than defined by ergodicity. The financial market is a well-known example of such complex systems, as characterized by multifractal dimensions (Drożdż & Kwapień, 2012), (Grech & Pamula, 2013). Other examples include income distribution inside a given region, evolution of a given disease inside a region, size of cities, or cellular structure.…”
Section: Definition and Shannon-tsallis Entropy Relationshipsmentioning
confidence: 99%