Multifractal analysis of the WTI crude oil market, US stock market and EPU
Can-Zhong Yao,
Cheng Liu and
Wei-Jia Ju
Physica A: Statistical Mechanics and its Applications, 2020, vol. 550, issue C
Abstract:
This paper adopts multifractal methods to analyze the nonlinear correlations among economic policy uncertainty (EPU), the crude oil market and the stock market. First, using multifractal detrended fluctuation analysis (MF-DFA), we find that each of the three series shows multifractality, and the sources of multifractality are all from long-range correlations and fat-tailed distributions. However, for the stock and oil price series, the long-range correlation has a greater impact, while the fat-tailed distribution contributes more to EPU multifractality. Furthermore, we apply multifractal detrended cross-correlation analysis (MF-DCCA) to analyze the cross-correlation multifractal features among the three series. The generalized Hurst exponents of any two series are significantly greater than 0.5, and the stock and oil price series have the strongest cross-correlation values. Coupling detrended fluctuation (CDFA) analysis of the three series shows that the coupling correlation among the three sequences is also multifractal. The chi-squared statistic reveals that the contribution of the stock market to the multifractality of the coupling correlation is greater than that of other series, and EPU has the smallest influence on the coupling correlation. Finally, we employ multiscale multifractal analysis (MMA) to visualize the dynamic behaviors of the correlations among the series. The results show that the cross-correlation of stock with the oil price has some symmetry at small- and large-scale fluctuations. Additionally, the influence of EPU on the overall coupling features is mainly reflected under small-scale fluctuations, and at large scales, the coupling correlation of the three series remains similar to the Hurst surface of stock with the oil price. These results are useful for building predictive models.
Keywords: EPU; Correlation; Multifractal analysis; Contribution (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119322629
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:550:y:2020:i:c:s0378437119322629
DOI: 10.1016/j.physa.2019.124096
Access Statistics for this article
Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis
More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().