The scaling properties of stock markets based on modified multiscale multifractal detrended fluctuation analysis

2015 ◽  
Vol 436 ◽  
pp. 525-537 ◽  
Author(s):  
Aijing Lin ◽  
Hui Ma ◽  
Pengjian Shang
Keyword(s):  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Detrended Fluctuation

scholarly journals Investigating Long-Range Dependence of Emerging Asian Stock Markets Using Multifractal Detrended Fluctuation Analysis

Symmetry ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1157
Author(s):  
Faheem Aslam ◽  
Saima Latif ◽  
Paulo Ferreira
Keyword(s):  
Time Series ◽  
Long Range ◽  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Financial Time Series ◽  
Long Range Dependence ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Financial Time ◽  
Detrended Fluctuation

The use of multifractal approaches has been growing because of the capacity of these tools to analyze complex properties and possible nonlinear structures such as those in financial time series. This paper analyzes the presence of long-range dependence and multifractal parameters in the stock indices of nine MSCI emerging Asian economies. Multifractal Detrended Fluctuation Analysis (MFDFA) is used, with prior application of the Seasonal and Trend Decomposition using the Loess (STL) method for more reliable results, as STL separates different components of the time series and removes seasonal oscillations. We find a varying degree of multifractality in all the markets considered, implying that they exhibit long-range correlations, which could be related to verification of the fractal market hypothesis. The evidence of multifractality reveals symmetry in the variation trends of the multifractal spectrum parameters of financial time series, which could be useful to develop portfolio management. Based on the degree of multifractality, the Chinese and South Korean markets exhibit the least long-range dependence, followed by Pakistan, Indonesia, and Thailand. On the contrary, the Indian and Malaysian stock markets are found to have the highest level of dependence. This evidence could be related to possible market inefficiencies, implying the possibility of institutional investors using active trading strategies in order to make their portfolios more profitable.

scholarly journals Evidence of Intraday Multifractality in European Stock Markets during the Recent Coronavirus (COVID-19) Outbreak

2020 ◽  
Vol 8 (2) ◽  
pp. 31 ◽  
Author(s):  
Faheem Aslam ◽  
Wahbeeah Mohti ◽  
Paulo Ferreira
Keyword(s):  
Stock Market ◽  
Market Efficiency ◽  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Policy Makers ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Index Data ◽  
European Stock Markets ◽  
Detrended Fluctuation

This study assesses how the coronavirus pandemic (COVID-19) affects the intraday multifractal properties of eight European stock markets by using five-minute index data ranging from 1 January 2020 to 23 March 2020. The Hurst exponents are calculated by applying multifractal detrended fluctuation analysis (MFDFA). Overall, the results confirm the existence of multifractality in European stock markets during the COVID-19 outbreak. Furthermore, based on multifractal properties, efficiency varies among these markets. The Spanish stock market remains most efficient while the least efficient is that of Austria. Belgium, Italy and Germany remain somewhere in the middle. This far-reaching outbreak demands a comprehensive response from policy makers to improve market efficiency during such epidemics.

Investigating efficiency of frontier stock markets using multifractal detrended fluctuation analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Faheem Aslam ◽  
Paulo Ferreira ◽  
Wahbeeah Mohti
Keyword(s):  
Stock Returns ◽  
Long Range ◽  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Long Range Dependence ◽  
Fluctuation Analysis ◽  
Content Type ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Multifractal Behavior ◽  
Detrended Fluctuation

PurposeThe investigation of the fractal nature of financial data has been growing in the literature. The purpose is to investigate the multifractal behavior of frontier markets using multifractal detrended fluctuation analysis (MFDFA).Design/methodology/approachThis study used daily closing prices of nine frontier stock markets up to 31-Aug-2020. A preliminary analysis reveals that these markets exhibit fat tails and clustering patterns. For a more robust analysis, a combination of Seasonal and Trend Decomposition using Loess (STL) and MFDFA has been employed. The former method is used to decompose daily stock returns, where later detected the long rang dependence in the series.FindingsThe results confirm varying degree of multifractality in frontier stock markets, implying that they exhibit long-range dependence. Based on these multifractality levels, Serbian and Romanian stock markets are the ones exhibiting least long-range dependence, while Slovenian and Mauritius stock markets indicating highest dependence in their series. Furthermore, the markets of Kenya, Morocco, Romania and Serbia exhibit mean reversion (anti-persistent) behavior while the remaining frontier markets show persistent behaviors.Practical implicationsThe information given by the detection of the fractal measure of data can support for investment and policymaking decisions.Originality/valueFrontier markets are of great potential from the perspective of international diversification. However, most of the research focused on other emerging and developed markets, especially in the context of multifractal analysis. This study combines the STL method and a physics-based robust technique, MFDFA to detect the multifractal behavior of frontier stock markets.

scholarly journals Multifractal Detrended Fluctuation Analysis (MF-DFA) of Stock Market Indexes. Empirical Evidence from Seven Central and Eastern European Markets

2020 ◽  
Vol 12 (2) ◽  
pp. 535 ◽  
Author(s):  
Laura Raisa Miloş ◽  
Cornel Haţiegan ◽  
Marius Cristian Miloş ◽  
Flavia Mirela Barna ◽  
Claudiu Boțoc
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Sustainable Growth ◽  
Mature Stage ◽  
Fluctuation Analysis ◽  
Eastern European ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Long Range Correlations ◽  
Detrended Fluctuation

In this paper, we present a comparative investigation of the multifractal properties of seven Central and Eastern European (CEE) stock markets using recent financial data up to August 2018 by employing seasonal and trend decompositions before applying multifractal detrended fluctuation analysis. We find that stock indices returns exhibit long-range correlations, supporting the idea that the stock markets in question are not efficient markets and have not reached a mature stage of market development. The results of the paper are of interest to investors looking for opportunities in these stock exchanges and also to policy makers in their endeavour of realizing institutional reforms in order to increase stock market efficiency and to support the sustainable growth of the financial markets.

Local multifractal detrended fluctuation analysis for tea breeds identification

2014 ◽  
Vol 07 (05) ◽  
pp. 1450048 ◽  
Author(s):  
Fang Wang ◽  
Rui-Biao Zou ◽  
Gui-Ping Liao ◽  
Jin-Wei Li ◽  
Zi-Qiang Liu
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Estimation Method ◽  
Fluctuation Analysis ◽  
Characteristic Parameters ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Local Scaling ◽  
Comparison Results ◽  
Capacity Measure ◽  
Detrended Fluctuation

In recent years, the popular multifractal detrended fluctuation analysis (MF-DFA) is extended to two-dimensional (2D) version, which has been applied in some field of image processing. In this paper, based on the 2D MF-DFA, a novel multifractal estimation method for images, which we called the local multifractal detrended fluctuation analysis (LMF-DFA), is proposed to recognize and distinguish 20 types of tea breeds. A set of new multifractal descriptors, namely the local multifractal fluctuation exponents is defined to portray the local scaling properties of a surface. After collecting 10 tea leaves for each breed and photographing them to standard images, the LMF-DFA method is used to extract characteristic parameters for the images. Our analysis finds that there are significant differences among the different tea breeds' characteristic parameters by analysis of variance. Both the proposed LMF-DFA exponents and another classic parameter, namely the exponent based on capacity measure method have been used as features to distinguish the 20 tea breeds. The comparison results illustrate that the LMF-DFA estimation can differentiate the tea breeds more effectively and provide more satisfactory accuracy.

Multifractal detrended fluctuation analysis of pseudorapidity and azimuthal distribution of pions emitted in high energy nuclear collisions

2014 ◽  
Vol 29 (18) ◽  
pp. 1450084 ◽  
Author(s):  
Srimonti Dutta ◽  
Dipak Ghosh ◽  
Sucharita Chatterjee
Keyword(s):  
Detrended Fluctuation Analysis ◽  
High Energy ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Nuclear Collisions ◽  
200 Gev ◽  
Fluctuation Pattern ◽  
Multifractal Scaling ◽  
Detrended Fluctuation

In this paper multifractal analysis of fluctuation pattern of pions emitted in 32 S-AgBr and 16 O-AgBr interactions at 200 GeV and 60 GeV, respectively, is performed in the framework of multifractal detrended fluctuation analysis (MFDFA). The pseudorapidity and azimuthal distributions exhibit multifractal scaling properties at both energies. The variation of multifractal width with energy is also studied. The study reveals a dependence of multifractal width on energy in pseudorapidity space while no such dependence is observed in azimuthal space.

scholarly journals Multifractal detrended fluctuation analysis in examining scaling properties of the spatial patterns of soil water storage

2012 ◽  
Vol 19 (2) ◽  
pp. 227-238 ◽  
Author(s):  
A. Biswas ◽  
T. B. Zeleke ◽  
B. C. Si
Keyword(s):  
Soil Water ◽  
Detrended Fluctuation Analysis ◽  
Water Storage ◽  
Soil Water Storage ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Scaling Properties ◽  
Scaling Property ◽  
Detrended Fluctuation ◽  
Properties Of Soil

Abstract. Knowledge about the scaling properties of soil water storage is crucial in transferring locally measured fluctuations to larger scales and vice-versa. Studies based on remotely sensed data have shown that the variability in surface soil water has clear scaling properties (i.e., statistically self similar) over a wider range of spatial scales. However, the scaling property of soil water storage to a certain depth at a field scale is not well understood. The major challenges in scaling analysis for soil water are the presence of localized trends and nonstationarities in the spatial series. The objective of this study was to characterize scaling properties of soil water storage variability through multifractal detrended fluctuation analysis (MFDFA). A field experiment was conducted in a sub-humid climate at Alvena, Saskatchewan, Canada. A north-south transect of 624-m long was established on a rolling landscape. Soil water storage was monitored weekly between 2002 and 2005 at 104 locations along the transect. The spatial scaling property of the surface 0 to 40 cm depth was characterized using the MFDFA technique for six of the soil water content series (all gravimetrically determined) representing soil water storage after snowmelt, rainfall, and evapotranspiration. For the studied transect, scaling properties of soil water storage are different between drier periods and wet periods. It also appears that local controls such as site topography and texture (that dominantly control the pattern during wet states) results in multiscaling property. The nonlocal controls such as evapotranspiration results in the reduction of the degree of multiscaling and improvement in the simple scaling. Therefore, the scaling property of soil water storage is a function of both soil moisture status and the spatial extent considered.

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