Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7382071 | Physica A: Statistical Mechanics and its Applications | 2014 | 10 Pages |
Abstract
In this paper, we investigate cross-correlations between crude oil and agricultural commodity markets. Based on a popular statistical test proposed by Podobnik et al. (2009), we find that the linear return cross-correlations are significant at larger lag lengths and the volatility cross-correlations are highly significant at all of the lag lengths under consideration. Using a detrended cross-correlation analysis (DCCA), we find that the return cross-correlations are persistent for corn and soybean and anti-persistent for oat and soybean. The volatility cross-correlations are strongly persistent. Using a nonlinear cross-correlation measure, our results show that cross-correlations are relatively weak but they are significant for smaller time scales. For larger time scales, the cross-correlations are not significant. The reason may be that information transmission from crude oil market to agriculture markets can complete within a certain period of time. Finally, based on multifractal extension of DCCA, we find that the cross-correlations are multifractal and high oil prices partly contribute to food crisis during the period of 2006-mid-2008.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Li Liu,