On the multifractal effects generated by monofractal signals
arXiv:1307.2014 · doi:10.1016/j.physa.2013.07.045
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 values or a threshold in the width of multifractal spectrum below which multifractal properties of the system are only apparent, i.e. do not exist, despite or . We find this effect quite important for shorter or persistent series and we argue it is linear with respect to autocorrelation exponent . Its strength decays according to power law with respect to the length of time series. The influence of basic linear and nonlinear transformations applied to initial data in finite time series with various level of long memory is also investigated. This provides additional set of semi-analytical results. The obtained formulas are significant in any interdisciplinary application of multifractality, including physics, financial data analysis or physiology, because they allow to separate the 'true' multifractal phenomena from the apparent (artificial) multifractal effects. They should be a helpful tool of the first choice to decide whether we do in particular case with the signal with real multiscaling properties or not.
arXiv comment36 pages, 41 figures
References in corpus (23)
- Multifractal detrended fluctuation analysis of nonstationary time series
- Multifractality in Human Heartbeat Dynamics
- Detecting Long-range Correlations with Detrended Fluctuation Analysis
- Effect of Trends on Detrended Fluctuation Analysis
- Effect of nonstationarities on detrended fluctuation analysis
- Method for Generating Long-Range Correlations for Large Systems
- Multifractal Properties of Price Fluctuations of Stocks and Commodities
- Wavelet versus Detrended Fluctuation Analysis of multifractal structures
- Nonlinearity and Multifractality of Climate Change in the Past 420,000 Years
- Quantitative features of multifractal subtleties in time series
- Multifractality in the stock market: price increments versus waiting times
- Finite-size effect and the components of multifractality in financial volatility
- Components of multifractality in high-frequency stock returns
- Generalized Hurst exponent and multifractal function of original and translated texts mapped into frequency and length time series
- Multifractal Fluctuations in Seismic Interspike Series
- Multifractal nature of stock exchange prices
- Volatility of Linear and Nonlinear Time Series
- Long range correlation in cosmic microwave background radiation
- Multiscaling behavior in the volatility return intervals of Chinese indices
- A case study of stratus cloud base height multifractal fluctuations
- Multifractal Analysis of Polyalanines Time Series
- Computational approach to multifractal music
- Effects of maximal fluctuation moment and detrending polynomial orders on the observed multifractal features within MFDFA
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