ENSO-Driven Correlation Dynamics in Agricultural and Energy Markets: A DCC-MIDAS Approach

Abstract

This paper embeds the Oceanic Niño Index (ONI) into a two-stage DCC-MIDAS model to examine how ENSO drives long-run correlation between soybean futures and WTI crude oil over September 2000 to June 2026 (N = 6,465 daily observations). The estimated long-run ENSO slope is negative and significant (θρ = −0.145, p<0.05), indicating that El Niño episodes reduce soybean-oil correlation while La Niña episodes raise it. An asymmetric decomposition confirms this pattern is driven entirely by La Niña (θ− = +0.284, p<0.05), with El Niño having no significant effect (θ+ = −0.031); a Wald test rejects symmetry at the 1% level (χ²(1) = 7.459, p = 0.006). The mechanism operates through opposing variance channels: ENSO lowers soybean long-run variance (θsoybean = −0.541) but raises oil long-run variance (θoil = +0.421), mechanically decoupling the two markets under El Niño. Estimated MIDAS effective lags reveal that correlation integrates climate information (2.8 months) far more rapidly than individual market volatilities (11.2 months for soybean, 15.2 months for oil). These findings have direct implications for commodity portfolio diversification and dynamic hedging strategies conditioned on ENSO forecasts.

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