Multiscale Multifractal Detrended Fluctuation Analysis and Trend Identification of Liquidity in the China's Stock Markets

2021 ◽  
Author(s):  
Ruzhen Yan ◽  
Ding Yue ◽  
Xu Wu ◽  
Wei Gao
Keyword(s):  
Stock Markets ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Trend Identification ◽  
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.

Multifractal detrended fluctuation analysis of temperature in Spain (1960–2019)

2021 ◽  
pp. 126118
Author(s):  
Javier Gómez-Gómez ◽  
Rafael Carmona-Cabezas ◽  
Ana B. Ariza-Villaverde ◽  
Eduardo Gutiérrez de Ravé ◽  
Francisco José Jiménez-Hornero
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Detrended Fluctuation
Sign in / Sign up

Export Citation Format

Share Document