scholarly journals Multi-fractal Behaviors of long term daily relative humidity and temperature observed over Benin synoptic stations (West Africa)

2019 ◽  
Vol 23 (4) ◽  
pp. 365-370
Author(s):  
Medard Noukpo Agbazo ◽  
Koton'Gobi Gabin ◽  
Kounouhewa Basile ◽  
Alamou Eric ◽  
Afouda Abel ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Fluctuation Analysis ◽  
Temperature Record ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Multifractal Strength ◽  
Generalized Hurst Exponent ◽  
Study Sites ◽  
Multifractal Property ◽  
The City

The multifractal structure of daily temperature and relative humidity is investigated in this study. Multifractal Detrended Fluctuation Analysis (MFDFA) method has been applied on data observed from 1967 to 2012 at the six synoptic stations of Benin (Cotonou, Bohicon, Parakou, Save, Natitingou and Kandi). We estimate the generalized Hurst exponent, the Renyi exponent, and the singularity spectrum from the data to quantify the multi-fractal behaviors. The results show that multi-fractality exists in both daily humidity and temperature record at Benin synoptic stations. It shows multi-fractality with the curves of h (q), τ (q) and D (q), depending on the values of q. The comparison of the multifractal properties shows that, at all the synoptic stations, the multifractal strength of the temperature is significantly different from the feature the humidity.For the temperature, among the six study sites, the multifractal strength at Natitingou is largest (∆α = 0.6917). This means that Natitingou is the city in which the multifractal property is strongly observed for temperature. At Parakou the multifractal strength is smallest (∆α = 0.5252), meaning that Parakou is the city in which the multifractal property is weakly observed. At all synoptic stations the multifractal strength are superior to 0.5 (Δα> 0.5) indicating the degree of multifractal in temperature time series.For the relative humidity, multifractal strength is smallest Kandi (∆α = 0.3031). This means that Kandi is the city in which the multifractal property is weakly observed. Furthermore, the multifractal strength of Parakou is largest (∆α = 0.7691) meaning that for the relative humidity, Parakou is the city in which the multifractal property is strongly observed. The geographic distribution of the multifractal strength reflects the role of climate dynamic processes on the multi-fractal behavior of humidity and the distinctiveness of physical processes in Benin.

A multifractal detrended fluctuation analysis of housing market: a role of financial crises in developed economies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Ali Raza ◽  
Nida Shah ◽  
Muhammad Tahir Suleman ◽  
Md Al Mamun
Keyword(s):  
Financial Crisis ◽  
Housing Market ◽  
Market Efficiency ◽  
House Price ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Run ◽  
Before And After

Purpose This study aims to examine the house price fluctuations in G7 countries by using the multifractal detrended fluctuation analysis (MF-DFA) for the years 1970–2019. The study examined the market efficiency between the short-term and long-term in the full sample period, before and after the global financial crisis period. Design/methodology/approach This study uses the MF-DFA to analyze house price fluctuations. Findings The findings confirmed that the housing market series are multifractal. Furthermore, all the markets showed long-term persistence in both the short and long-term. The USA is identified as the most persistent house market in the short run and Japan in the long run. Moreover, in terms of efficiency, Canada is identified as the most efficient house market in the long run and the UK in the short run. Finally, the result of before and after the financial crisis period is consistent with the full sample result. Originality/value The contribution of this study in the literature is fourfold. This is the first study that has examined the house prices efficiency by using the MF-DFA technique given by Kantelhardt et al. (2002). Previously, the house market prices and efficiency has been investigated using generalized Hurst exponent (Liu et al., 2019), Quantile Regression Approach (Chae and Bera, 2019; Tiwari et al., 2019) but no study to the best of the knowledge has been done that has used the MF-DFA technique on the housing market. Second, this is the first study that has focused on the house markets of G7 countries. Third, this study explores the house market efficiency by dividing the market into two periods i.e. before and after the financial crisis. The study strives to investigate if the financial crisis determines the change in the degree of market efficiency or not. Finally, the study gives valuable insights to the investors that will help them in their investment decisions.

scholarly journals Comparative Multifractal Detrended Fluctuation Analysis of Heavy Ion Interactions at a Few GeV to a Few Hundred GeV

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Gopa Bhoumik ◽  
Argha Deb ◽  
Swarnapratim Bhattacharyya ◽  
Dipak Ghosh
Keyword(s):  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Heavy Ion ◽  
Projectile Energy ◽  
Fluctuation Analysis ◽  
Data Set ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Range Correlation ◽  
Multifractal Property ◽  
Detrended Fluctuation

We have studied the multifractality of pion emission process in16O-AgBr interactions at 2.1 AGeV  and  60 AGeV,12C-AgBr  and  24Mg-AgBr interactions at 4.5 AGeV, and32S-AgBr interactions at 200 AGeV using Multifractal Detrended Fluctuation Analysis (MFDFA) method which is capable of extracting the actual multifractal property filtering out the average trend of fluctuation. The analysis reveals that the pseudorapidity distribution of the shower particles is multifractal in nature for all the interactions; that is, pion production mechanism has inbuilt multiscale self-similarity property. We have employed MFDFA method for randomly generated events for32S-AgBr interactions at 200 AGeV. Comparison of expt. results with those obtained from randomly generated data set reveals that the source of multifractality in our data is the presence of long range correlation. Comparing the results obtained from different interactions, it may be concluded that strength of multifractality decreases with projectile mass for the same projectile energy and for a particular projectile it increases with energy. The values of ordinary Hurst exponent suggest that there is long range correlation present in our data for all the interactions.

scholarly journals Price Appreciation and Roughness Duality in Bitcoin: A Multifractal Analysis

Mathematics ◽  
2021 ◽  
Vol 9 (17) ◽  
pp. 2088
Author(s):  
Cristiana Vaz ◽  
Rui Pascoal ◽  
Helder Sebastião
Keyword(s):  
Fluctuation Analysis ◽  
Informational Efficiency ◽  
Comprehensive Overview ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Range Correlations ◽  
The Public ◽  
Long Run ◽  
Short Run ◽  
The Relationship

Since its launch in 2009, bitcoin has thrived, attracting the attention of investors, regulators, academia, and the public in general. Its price dynamics, characterized by extreme volatility, severe jumps, and impressive long-term appreciation, suggest that bitcoin is a new digital asset. This study presents a comprehensive overview of the fractality of bitcoin in a high-frequency framework, namely by applying Multifractal Detrended Fluctuation Analysis (MF-DFA) and a Multifractal Regime Detecting Method (MRDM) to Bitstamp 1 min bitcoin returns from January 2013 to July 2020. The results suggest that bitcoin is multifractal, with smaller and larger fluctuations being persistent and anti-persistent, respectively. Multifractality comes from significant long-range correlations, which cast some doubts on the informational efficiency at this frequency, but mainly comes from fat-tails, which highlights the significant risks undertaken by investors in this market. Our most important result is that the degree and richness of multifractality is time-varying and increased after 2017, when volumes and prices experienced an explosive behaviour. This complexity puts into perspective the duality of bitcoin: while it is characterized by long-run attractiveness and increasing valuation, it also has a high short-run instability. Hence, this study provides some empirical evidence supporting the relationship between these two observable features.

scholarly journals COVID-19, bitcoin market efficiency, herd behaviour

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emna Mnif ◽  
Anis Jarboui
Keyword(s):  
Efficiency Index ◽  
Fluctuation Analysis ◽  
Hausdorff Topology ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Nonlinear Dynamical ◽  
Generalized Hurst Exponent ◽  
Herd Behaviour ◽  
Detrended Fluctuation ◽  
Practical Implications

PurposeUnlike previous crisis where investors tend to put their assets in safe havens like gold, the recent coronavirus pandemic is characterised by an increase in the Bitcoin purchasing described as risk heaven. This paper aims to analyse the Bitcoin dynamics and the investor response by focusing on herd biases. Therefore, the main objective of this work is to study the degree of efficiency through multifractal analysis in order to detect herd behaviour leading to build the best predictions and strategies.Design/methodology/approachThis paper develops a novel methodology that detects the presence of herding biases and assesses the inefficiency of Bitcoin through an inefficiency index (MLM) by using statistical indicators defined by measures of persistence. This study, also, investigates the nonlinear dynamical properties of Bitcoin by estimating the Multifractal Detrended Fluctuation Analysis (MFDFA) leading to deduce the effect of COVID-19 on the Bitcoin performance. Besides, this work performs an event study to capture abnormal changes created by COVID-19 related events capable to analyse the Bitcoin market response.FindingsThe empirical results of the generalized Hurst exponent GHE estimation indicates that Bitcoin is multifractal before this pandemic and becomes less fractal after the outbreak. Using an efficiency index (MLM), Bitcoin is found to be more efficient after the pandemic. Based on the Hausdorff topology, the authors showed that this pandemic has reduced the herd bias.Research limitations/implicationsThe uncertainty of COVID-19 disease and the lasting of its duration make it difficult to make the best prediction.Practical implicationsThe main contribution of this study is the evaluation of the Bitcoin value after the COVID19 outbreak. This work has practical implications as it provides new insights on trading opportunities and social reactions.Originality/valueTo the authors’ knowledge, this work represents the first study that analyses the Bitcoin response to different events related to COVID-19 and detects the presence of herding behaviour in such a crisis.

Fish Sound Characterization Using Multifractal Detrended Fluctuation Analysis

2020 ◽  
Vol 19 (01) ◽  
pp. 2050009 ◽  
Author(s):  
Kranthikumar Chanda ◽  
Shubham Shet ◽  
Bishwajit Chakraborty ◽  
Arvind K. Saran ◽  
William Fernandes ◽  
...  
Keyword(s):  
Hurst Exponent ◽  
Detrended Fluctuation Analysis ◽  
Linear Method ◽  
Multifractal Spectrum ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Generalized Hurst Exponent ◽  
Estuarine Systems ◽  
Detrended Fluctuation ◽  
Sound Data

This work involves the application of a non-linear method, multifractal detrended fluctuation analysis (MFDFA), to describe fish sound data recorded from the open waters of two major estuarine systems. Applying MFDFA, the second-order Hurst exponent [Formula: see text] values are found to be [Formula: see text] and [Formula: see text] for the fish families Batrachoididae (common name: Toadfish) and Sciaenidae (common name: Croakers, drums), respectively. The generalized Hurst exponent [Formula: see text]-related width parameters [Formula: see text] are found to be [Formula: see text] and [Formula: see text], respectively, for toadfish and Sciaenidae vocalizations, implying greater heterogeneity and multifractal characteristics. The results suggest that the Sciaenidae fish calls are smoother in comparison with Batrachoididae. Clustering of multifractal spectrum-related parameters with respect to toadfish and Sciaenidae vocalization characteristics is observed in this analyses.

Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

2017 ◽  
Vol 28 (02) ◽  
pp. 1750028 ◽  
Author(s):  
Yang Yujun ◽  
Li Jianping ◽  
Yang Yimei
Keyword(s):  
Time Series ◽  
Financial Time Series ◽  
Renyi Entropy ◽  
Rényi Entropy ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Financial Time ◽  
Stock Indices ◽  
Generalized Hurst Exponent ◽  
Detrended Fluctuation

This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.

FLUCTUATION OF GOLD PRICE IN INDIA VERSUS GLOBAL CONSUMER PRICE INDEX

Fractals ◽  
2014 ◽  
Vol 22 (01n02) ◽  
pp. 1450004 ◽  
Author(s):  
P. MALI
Keyword(s):  
Time Series ◽  
Price Index ◽  
Consumer Price Index ◽  
Temporal Correlation ◽  
Gold Price ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Gold Market ◽  
Generalized Hurst Exponent ◽  
Two Parameters

The time series of gold price in the Indian market and the global consumer price index for the period of January 1985 to June 2013 are analyzed in terms of the multifractal detrended fluctuation analysis (MF-DFA). Multifractal variables, such as the generalized Hurst exponent, the multifractal mass exponent, the singularity spectrum, are extracted for both the series. Special emphasis is given on the possible source(s) of correlations in these series. The multifractal results are fitted to the generalized binomial multifractal model consists of only two parameters. Our analysis show that the multifractal nature of the Indian gold market time series and the global consumer price index series is due to both the long-range temporal correlation and the fat-tailed probability density function of the values. Surprisingly, the series are well described by the two-parameter binomial multifractal model used.

scholarly journals Technical note: Long-term persistence loss of urban streams as a metric for catchment classification

2018 ◽  
Vol 22 (6) ◽  
pp. 3551-3559 ◽  
Author(s):  
Dusan Jovanovic ◽  
Tijana Jovanovic ◽  
Alfonso Mejía ◽  
Jon Hathaway ◽  
Edoardo Daly
Keyword(s):  
Negative Relationship ◽  
Technical Note ◽  
Annual Rainfall ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Climatic Regions ◽  
Catchment Size ◽  
The Usa ◽  
The Impact

Abstract. Urbanisation has been associated with a reduction in the long-term correlation within a streamflow series, quantified by the Hurst exponent (H). This presents an opportunity to use the H exponent as an index for the classification of catchments on a scale from natural to urbanised conditions. However, before using the H exponent as a general index, the relationship between this exponent and level of urbanisation needs to be further examined and verified on catchments with different levels of imperviousness and from different climatic regions. In this study, the H exponent is estimated for 38 (deseasonalised) mean daily runoff time series, 22 from the USA and 16 from Australia, using the traditional rescaled-range statistic (R∕S) and the more advanced multifractal detrended fluctuation analysis (MF-DFA). Relationships between H and catchment imperviousness, catchment size, annual rainfall and specific mean discharge were investigated. No clear relationship with catchment area was found, and a weak negative relationship with annual rainfall and specific mean streamflow was found only when the R∕S method was used. Conversely, both methods showed decreasing values of H as catchment imperviousness increased. The H exponent decreased from around 1.0 for catchments in natural conditions to around 0.6 for highly urbanised catchments. Three significantly different ranges of H exponents were identified, allowing catchments to be parsed into groups with imperviousness lower than 5 % (natural), catchments with imperviousness between 5 and 15 % (peri-urban) and catchments with imperviousness larger than 15 % (urban). The H exponent thus represents a useful metric to quantitatively assess the impact of catchment imperviousness on streamflow regime.

WAVELET MULTIFRACTAL DETRENDED FLUCTUATION ANALYSIS OF ENCRYPTION AND DECRYPTION MATRICES

2013 ◽  
Vol 24 (09) ◽  
pp. 1350069 ◽  
Author(s):  
J. S. MURGUÍA ◽  
M. MEJÍA CARLOS ◽  
C. VARGAS-OLMOS ◽  
M. T. RAMÍREZ-TORRES ◽  
H. C. ROSU
Keyword(s):  
Hurst Exponent ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Scaling Method ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Encryption And Decryption ◽  
Singularity Exponent ◽  
Generalized Hurst Exponent ◽  
Different Dimensions ◽  
Detrended Fluctuation

In this paper, we study in detail the multifractal features of the main matrices of an encryption system based on a rule-90 cellular automaton. For this purpose, we consider the scaling method known as the wavelet transform multifractal detrended fluctuation analysis (WT-MFDFA). In addition, we analyze the multifractal structure of the matrices of different dimensions, and find that there are minimal differences in all the examined multifractal quantities such as the multifractal support, the most frequent singularity exponent, and the generalized Hurst exponent.

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