Detrended Moving Average Analysis Research Articles

Detection of oriented fractal scaling components in anisotropic two-dimensional trajectories

We propose a novel class of mixed fluctuations with different orientations and fractal scaling features as a model for anisotropic two-dimensional (2D) trajectories hypothesized to appear in complex systems. Furthermore, we develop the oriented fractal scaling component analysis (OFSCA) to decompose such mixed fluctuations into the original orientation components. In the OFSCA, the original orientations are detected based on the principle that the original angles are orthogonal to the angles with the minimum and maximum scaling exponents of the mixed fluctuations. In our approach, the angle-dependent scaling properties are estimated using the Savitzky–Golay-filter-based detrended moving-average analysis (DMA), which has a higher detrending order than the conventional moving-average-filter-based DMA. To illustrate the OFSCA, we demonstrate that the numerically generated time-series of mixed fractional Gaussian noise (fGn) processes with non-orthogonal orientations and different scaling exponents is successfully decomposed into the original fGn components. We demonstrate the existence of oriented components in the 2D trajectories by applying OFSCA to real-world time-series, such as human postural fluctuations during standing and seismic ground acceleration during the great 2011 Tohoku-oki earthquake.

A Novel Approach to Study the Variability of NGC 5548

Abstract Understanding the properties of the continuum radiation and broad emission lines of active galactic nuclei provides significant information not only to model the radiation mechanism and constrain the geometry and kinematics of the broad-line region (BLR) but also to probe the central engine of the sources. Here we investigate the multifractal behavior of the Hβ emission line and the 5100 Å continuum flux light curves of NGC 5548. The aim is to search for multiscaling signatures in the light curves and check if there is a possible nonlinear relationship between them. To this end, we use a multifractality analysis technique called the Multifractal Detrended Moving Average analysis. We detect multifractal (nonlinear) signatures in the full monitoring and densely sampled period of the Hβ line and 5100 Å continuum light curves of NGC 5548, possibly indicating the presence of complex and nonlinear interaction in the 5100 Å continuum and Hβ emission line regions. Moreover, the degree of multifractality of the Hβ line is found to be about twice that of the 5100 Å continuum. The nonlinearity of both emissions could be generated when the BLR reprocesses the radiation from the central compact source. Finally, we found that antipersistent long-range temporal correlation is the main source of the multifractality detected in both light curves.

Long-range temporal correlation in Auditory Brainstem Responses to Spoken Syllable/da/

The speech auditory brainstem response (sABR) is an objective clinical tool to diagnose particular impairments along the auditory brainstem pathways. We explore the scaling behavior of the brainstem in response to synthetic /da/ stimuli using a proposed pipeline including Multifractal Detrended Moving Average Analysis (MFDMA) modified by Singular Value Decomposition. The scaling exponent confirms that all normal sABR are classified into the non-stationary process. The average Hurst exponent is H = 0:77 ± 0:12 at 68% confidence interval indicating long-range correlation which shows the first universality behavior of sABR. Our findings exhibit that fluctuations in the sABR series are dictated by a mechanism associated with long-term memory of the dynamic of the auditory system in the brainstem level. The q-dependency of h(q) demonstrates that underlying data sets have multifractal nature revealing the second universality behavior of the normal sABR samples. Comparing Hurst exponent of original sABR with the results of the corresponding shuffled and surrogate series, we conclude that its multifractality is almost due to the long-range temporal correlations which are devoted to the third universality. Finally, the presence of long-range correlation which is related to the slow timescales in the subcortical level and integration of information in the brainstem network is confirmed.

Identification of defective two dimensional semiconductors by multifractal analysis: The single-layer [formula omitted] case study

Two dimensional semiconductor such as single-layer transition metal dichalcogenides (SL-TMD) have attracted most attentions as an atomically thin layer semiconductor materials. Typically, lattice point defects (sulfur vacancy) created by physical/chemical method during growth stages, have disadvantages on electronic properties. However, photoluminescence (PL) spectroscopy is conventionally used to characterize single-layer films but until now it has not been used to show the presence of defects or estimate their population due to overall similarity of general feature PL spectra. To find a feasible and robust method to determine the presence of point defects on single layer MoS2 without changing the experimental setup, Multifractal Detrended Fluctuation Analysis (MF-DFA) and Multifractal Detrended Moving Average Analysis (MF-DMA) are applied on the PL spectrum of single layer MoS2. We compare the scaling behavior of PL spectrum of pristine and defective single layer MoS2 determined by MF-DFA and MF-DMA. Our results reveal that PL spectrum has multifractal nature and different various population of point defects (sulfur vacancy) on single layer MoS2 change dramatically multifractality characteristics (Hurst, Hölder exponents) of photoluminescence spectrum. It is exhibited creating more lattice point leads to smaller fluctuations in luminescent light that it can help to design special defect structure for light emitted devices. The relative populations of point defects are almost elucidated without utilizing expensive characterization instruments such as scanning tunneling microscopy (STM) and high resolution transmission electron microscopy (HR-TEM).

Impact of Scaling Range on the Effectiveness of Detrending Methods

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 properties of scaling ranges for these techniques are reviewed. The efficiency and exactness of all three methods towards proper determination of scaling Hurst exponent H is discussed, particularly for short series of uncorrelated and persistent data.

Scaling range of power laws that originate from fluctuation analysis

We extend our previous study of scaling range properties performed for detrended fluctuation analysis (DFA) [Physica A 392, 2384 (2013)] to other techniques of fluctuation analysis (FA). The new technique, called modified detrended moving average analysis (MDMA), is introduced, and its scaling range properties are examined and compared with those of detrended moving average analysis (DMA) and DFA. It is shown that contrary to DFA, DMA and MDMA techniques exhibit power law dependence of the scaling range with respect to the length of the searched signal and with respect to the accuracy R^{2} of the fit to the considered scaling law imposed by DMA or MDMA methods. This power law dependence is satisfied for both uncorrelated and autocorrelated data. We find also a simple generalization of this power law relation for series with a different level of autocorrelations measured in terms of the Hurst exponent. Basic relations between scaling ranges for different techniques are also discussed. Our findings should be particularly useful for local FA in, e.g., econophysics, finances, or physiology, where the huge number of short time series has to be examined at once and wherever the preliminary check of the scaling range regime for each of the series separately is neither effective nor possible.

Efficiency of Crude Oil Futures Markets: New Evidence from Multifractal Detrending Moving Average Analysis

In this paper, we examine the weak-form efficient market hypothesis of crude oil futures markets by testing for the random walk behavior of prices. Using a method borrowed from statistical physics, we find that crude oil price display weak persistent behavior for time scales smaller than a year. For time scales larger than a year, strong mean-reversion behaviors can be found. That is, crude oil futures markets are not efficient in the short-term or in the long-term. By quantifying the market inefficiency using a "multifractality degree", we find that the futures markets are more inefficient in the long-term than in the short-term. Furthermore, we investigate the "stylized fact" of volatility dynamics on market efficiency. The simulating and empirical results indicate that volatility clustering, volatility memory and extreme volatility have adverse effects on market efficiency, especially in the long-term.

An investigation on the relationship between solar irradiance signal from ERBS and 8B solar neutrino flux signals from SNO

In the present work an attempt has been made to investigate statistical association between solar neutrino flux data (both D2O and Salt data) collected from Sudbury Neutrino Observatory and solar irradiance data detected by Earth Radiation Budget Satellite. To serve the present purpose we have used the Multifractal Detrended Cross Correlation Analysis (MF-DCCA) based on Detrended Fluctuation Analysis (MF-X-DFA) method and the Detrending Moving Average Analysis (MF-X-DMA) which explores the long term power-law cross correlations between above two pairs of data sets. Investigation also has been made to find the frequency and time dependent local phase relationship in each pair of data sets using continuous wavelet transform (CWT) based Semblance Analysis. The Semblance Analysis reveals that there exists positive phase correlation as well as negative phase correlation between solar irradiance and D2O data at different time sub-intervals. This type of mixed phase correlation is also experienced between solar irradiance and Salt data at different time sub-intervals. The causal relationship between the D2O and the solar irradiance time series and that between Salt and solar irradiance time series have been revealed using Singular Spectral Analysis (SSA). Calculations indicate that possibly the present solar neutrino flux data (both D2O and Salt data) is supportive to predict the solar irradiance data but may not the vice versa which in turn suggests that the variability of nuclear energy generation process inside the Sun may influence the solar activity.

Statistical properties of the yuan exchange rate index

We choice the yuan exchange rate index based on a basket of currencies as the effective exchange rate of the yuan and investigate the statistical properties of the yuan exchange rate index after China’s exchange rate system reform on the 21st July 2005. After dividing the time series into two parts according to the change in the yuan exchange rate regime in July 2008, we compare the statistical properties of the yuan exchange rate index during these two periods. We find that the distribution of the two return series has the exponential form. We also perform the detrending moving average analysis (DMA) and the multifractal detrending moving average analysis (MFDMA). The two periods possess different degrees of long-range correlations, and the multifractal nature is also unveiled in these two time series. Significant difference is found in the scaling exponents τ(q) and singularity spectra f(α) of the two periods obtained from the MFDMA analysis. Besides, in order to detect the sources of multifractality, shuffling and phase randomization procedures are applied to destroy the long-range temporal correlation and fat-tailed distribution of the yuan exchange rate index respectively. We find that the fat-tailedness plays a critical role in the sources of multifractality in the first period, while the long memory is the major cause in the second period. The results suggest that the change in China’s exchange rate regime in July 2008 gives rise to the different multifractal properties of the yuan exchange rate index in these two periods, and thus has an effect on the effective exchange rate of the yuan after the exchange rate reform on the 21st July 2005.

Long-term correlations and multifractal nature in the intertrade durations of a liquid Chinese stock and its warrant

The intertrade duration of equities is an important financial measure, characterizing trading activities; it is defined as the waiting time between successive trades of an equity. Using the ultrahigh-frequency data of a liquid Chinese stock and its associated warrant, we perform a comparative investigation of the statistical properties of their intertrade duration time series. The distributions of the two equities can be better described by the shifted power-law form than the Weibull form, and their scaled distributions do not collapse onto a single curve. Although the intertrade durations of the two equities have very different magnitude, their intraday patterns exhibit very similar shapes. Both detrended fluctuation analysis (DFA) and detrending moving average analysis (DMA) show that the 1 min intertrade duration time series of the two equities are strongly correlated. In addition, both multifractal detrended fluctuation analysis (MFDFA) and multifractal detrending moving average analysis (MFDMA) unveil that the 1 min intertrade durations possess multifractal nature. However, the difference between the two singularity spectra of the two equities obtained from the MFDMA is much smaller than that from the MFDFA.