n Annual Proceedings of the South African Statistical Association Conference - Analysis of interdependence between agricultural and energy commodity price dynamics with Bayesian multivariate DCC GARCH approach

Volume 2018 Number Congress 1
  • ISSN :


This article investigates the interdependence (measured by conditional correlation) between the price returns of 5 major agricultural and 3 major energy commodities in South Africa and studies their dynamics over time using the daily data between the 2nd of January, 2007 and the 31st of October, 2016. The conditional correlations were studied using a Bayesian multivariate dynamic conditional correlation GARCH (DCC-MGARCH) approach with skewness and heavy tails. A computationally intensive Markov Chain Monte Carlo (MCMC) algorithm was adopted and implemented for both parameter estimation and model comparison. Based on the information criteria, the Bayesian DCC-MGARCH model with the error skewed-multivariate Student’s t (mvt) distribution performed better than other competitive methods. The results reveal that the estimatedDCCbetween the price returns of agricultural and energy commodities is significant, suggesting interdependence between the price returns of the agricultural and energy commodities. In addition, the findings have significant implications in the domain of agricultural and energy commodities market sector.

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