Multifractal analysis on international crude oil markets based on the multifractal detrended fluctuation analysis

2010 ◽  
Vol 389 (14) ◽  
pp. 2805-2815 ◽  
Author(s):  
Rongbao Gu ◽  
Hongtao Chen ◽  
Yudong Wang
Keyword(s):  
Crude Oil ◽  
Detrended Fluctuation Analysis ◽  
Multifractal Analysis ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Oil Markets ◽  
Detrended Fluctuation

A modified Multifractal Detrended Fluctuation Analysis (MFDFA) approach for multifractal analysis of precipitation

2021 ◽  
Vol 565 ◽  
pp. 125611
Author(s):  
Jorge Luis Morales Martínez ◽  
Ignacio Segovia-Domínguez ◽  
Israel Quiros Rodríguez ◽  
Francisco Antonio Horta-Rangel ◽  
Guillermo Sosa-Gómez
Keyword(s):  
Detrended Fluctuation Analysis ◽  
Multifractal Analysis ◽  
Fluctuation Analysis ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Detrended Fluctuation

scholarly journals Multifractal analysis of solar flare indices and their horizontal visibility graphs

2012 ◽  
Vol 19 (6) ◽  
pp. 657-665 ◽  
Author(s):  
Z. G. Yu ◽  
V. Anh ◽  
R. Eastes ◽  
D.-L. Wang
Keyword(s):  
Time Series ◽  
Solar Cycle ◽  
Detrended Fluctuation Analysis ◽  
Multifractal Analysis ◽  
Fluctuation Analysis ◽  
Horizontal Visibility ◽  
Multifractal Detrended Fluctuation Analysis ◽  
X Ray ◽  
Visibility Graphs ◽  
Detrended Fluctuation

Abstract. The multifractal properties of the daily solar X-ray brightness, Xl and Xs, during the period from 1 January 1986 to 31 December 2007 which includes two solar cycles are examined using the universal multifractal approach and multifractal detrended fluctuation analysis. Then we convert these time series into networks using the horizontal visibility graph technique. Multifractal analysis of the resulting networks is performed using an algorithm proposed by us. The results from the multifractal analysis show that multifractality exists in both raw daily time series of X-ray brightness and their horizontal visibility graphs. It is also found that the empirical K(q) curves of raw time series can be fitted by the universal multifractal model. The numerical results on the raw data show that the Solar Cycle 23 is weaker than the Solar Cycle 22 in multifractality. The values of h(2) from multifractal detrended fluctuation analysis for these time series indicate that they are stationary and persistent, and the correlations in the time series of Solar Cycle 23 are stronger than those for Solar Cycle 22. Furthermore, the multifractal scaling for the networks of the time series can reflect some properties which cannot be picked up by using the same analysis on the original time series. This suggests a potentially useful method to explore geophysical data.

THE EFFICIENCY OF SIN STOCKS: A MULTIFRACTAL ANALYSIS OF DRUG INDICES

2021 ◽  
pp. 1-22
Author(s):  
Faheem Aslam ◽  
Paulo Ferreira ◽  
Fahd Amjad ◽  
Haider Ali
Keyword(s):  
Time Series ◽  
Market Efficiency ◽  
Detrended Fluctuation Analysis ◽  
Multifractal Analysis ◽  
Fluctuation Analysis ◽  
Self Similarity ◽  
Multifractal Detrended Fluctuation Analysis ◽  
The North ◽  
Daily Data ◽  
Detrended Fluctuation

This study provides the first evidence of market efficiency of drug indices, especially cannabis and tobacco, which are known in finance as sin markets. The multifractal detrended fluctuation analysis (MFDFA) is employed on the daily data of six cannabis and one tobacco indices in order to measure efficiency by quantifying the intensity of self-similarity. The findings confirm multifractality in all sample series. Interestingly, Dow Jones Tobacco (DJUSTB) Index shows the highest multifractality, demonstrating the lowest efficiency, whereas S&P/TSX Cannabis (SPTXCAN) Index is the most efficient of all the time series under analysis, with the lowest multifractality levels. Only the North American Marijuana (NAMMAR), Cannabis World Index Gross Total Return (CANWLDGR) and DJUSTB show persistent behavior. These findings could be of interest to policymakers and regulators to establish new reforms to improve the efficiency of these markets, as well as for actual and potential investors.

Measuring efficiency of international crude oil markets: A multifractality approach

2015 ◽  
Vol 36 ◽  
pp. 1560013
Author(s):  
H. M. Niere
Keyword(s):  
Time Series ◽  
Crude Oil ◽  
Long Range ◽  
Detrended Fluctuation Analysis ◽  
Strong Dependence ◽  
Fluctuation Analysis ◽  
Long Range Correlations ◽  
Oil Markets ◽  
Detrended Fluctuation ◽  
Hurst Exponents

The three major international crude oil markets are treated as complex systems and their multifractal properties are explored. The study covers daily prices of Brent crude, OPEC reference basket and West Texas Intermediate (WTI) crude from January 2, 2003 to January 2, 2014. A multifractal detrended fluctuation analysis (MFDFA) is employed to extract the generalized Hurst exponents in each of the time series. The generalized Hurst exponent is used to measure the degree of multifractality which in turn is used to quantify the efficiency of the three international crude oil markets. To identify whether the source of multifractality is long-range correlations or broad fat-tail distributions, shuffled data and surrogated data corresponding to each of the time series are generated. Shuffled data are obtained by randomizing the order of the price returns data. This will destroy any long-range correlation of the time series. Surrogated data is produced using the Fourier-Detrended Fluctuation Analysis (F-DFA). This is done by randomizing the phases of the price returns data in Fourier space. This will normalize the distribution of the time series. The study found that for the three crude oil markets, there is a strong dependence of the generalized Hurst exponents with respect to the order of fluctuations. This shows that the daily price time series of the markets under study have signs of multifractality. Using the degree of multifractality as a measure of efficiency, the results show that WTI is the most efficient while OPEC is the least efficient market. This implies that OPEC has the highest likelihood to be manipulated among the three markets. This reflects the fact that Brent and WTI is a very competitive market hence, it has a higher level of complexity compared against OPEC, which has a large monopoly power. Comparing with shuffled data and surrogated data, the findings suggest that for all the three crude oil markets, the multifractality is mainly due to long-range correlations.

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
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