Work

Exploring dynamic extreme dependence of oil and agricultural markets

Year: 2025

Type: article

Abstract: This study examines the dynamic extreme dependence between oil markets and a set of non-exploited agricultural assets (Barley, coffee, maize, rice, sorghum, sugar, wheat) prices using 1990-2023 monthly prices data. Our time-varying copula models allow us to investigate nonlinear and asymmetric dependence between pairwise assets. We find evidence of positive exceedance correlation at small and medium quantiles/thresholds and negative exceedance correlation for quantiles higher than 0.6 for five out of seven food assets. Findings also indicate a tent-shaped quantile dependence for all food assets and demonstrate a time variation in the association path between oil and food asset returns. Important policy implications are derived from empirical findings. • Time-varying copulas are proposed for oil-agriculture markets dynamic dependence. • Daily data on WTI, Barley, Coffee, Maize, Rice, Sorghum, Sugar, Wheat over the period 1990M01-2023M01 are used • Positive (negative) exceedance correlation at small and medium (high) quantiles/thresholds for five out of seven food assets. • Tent-shaped quantile dependence for all food assets • Time variation in the association path between oil and food asset returns

Source: International Review of Economics & Finance

DOI: 10.1016/j.iref.2025.104032

Authors: Khalid M. Kisswani, Amine Lahiani, Mahelet G. Fikru

Institution: Gulf University for Science & Technology

Language: English

Topic: Market Dynamics and Volatility

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $1,930