Cross-correlation between crude oil and refined product prices
Li Liu and
Guofeng Ma
Physica A: Statistical Mechanics and its Applications, 2014, vol. 413, issue C, 284-293
Abstract:
In this paper, we investigate cross-correlations between crude oil and refined product prices based on the well-known detrended cross-correlation analysis (DCCA). Our findings indicate that the cross-correlations are significant and strong. Furthermore, the multifractality in cross-correlations is also revealed. The cross-correlation coefficients are as high as 0.9 for larger time scales and are greater than those for smaller time scales. Two popular models, vector error correction model and bivariate BEKK volatility model, are found to have very limited power in capturing long-range cross-correlations, suggesting the drawbacks of these conventional models in actual applications. Long-term cross-correlations are stronger in recent ten years than those in the past decades.
Keywords: Detrended cross-correlation analysis; Crude oil; Refined product; Multifractality (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843711400572X
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:413:y:2014:i:c:p:284-293
DOI: 10.1016/j.physa.2014.07.007
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 ().