Analyzing extreme comovements in agricultural and energy commodity markets using a regular vine copula method

2018, Econjournals. All rights reserved. Using a regular vine copula approach, this paper analyzes the dependence structure and tail dependence patterns among daily prices of three agricultural commodities (corn, soybean, and wheat) and two energy commodities (ethanol and crude oil) from June 2006 to June 2016. Our findings suggest that the prices of corn and crude oil are linked through the ethanol market, which are consistent with the results from previous studies. We also find that crude oil and agricultural commodity prices are statistically dependent during the extreme market downturns but independent during the extreme market upturns. In addition, the results from our sub-sample analysis show that both the upper and lower tail dependence between crude oil and other commodity markets become weaker in the recent years when the ethanol market became more mature.

Analyzing extreme comovements in agricultural and energy commodity markets using a regular vine copula method Academic Article