Financial uncertainty in American livestock markets does not spread evenly. A new analysis of ten years of daily futures prices finds that feeder cattle and live cattle are locked in a tight, two-way exchange of volatility, while lean hogs largely keep their risk to themselves. The study, published in Agricultural and Food Economics, examined 2,506 daily observations from March 9, 2016, to March 4, 2026, covering feeder cattle, live cattle, and lean hog futures alongside Brent crude oil, the U.S. Dollar Index, and the CBOE Volatility Index (VIX).
The research team, led by Faruk Urak with colleagues including Gürkan Bozma, Mehmet Selim Yıldız, Tayyar Arı, and Abdulbaki Bilgic, applied a vector error correction model combined with an asymmetric multivariate BEKK-GARCH(t) framework. This class of models jointly estimates long-run price relationships, short-run adjustment, time-varying variances, and cross-market transmission, while allowing negative and positive shocks to affect volatility differently. The three livestock futures represent distinct segments of the U.S. meat market: feeder cattle reflect the value of animals entering feedlots, live cattle represent finished cattle ready for slaughter, and lean hogs refer to market-ready hogs with a different biological production cycle and pricing dynamics.
A central structural finding is that the three livestock price series share a single long-run equilibrium, identified by Johansen cointegration testing. The estimated cointegrating relationship links the three markets in a way the authors interpret as consistent with cost pass-through along the cattle production chain: a one percent increase in live cattle prices is associated with a 1.330 percent increase in feeder cattle prices. The negative coefficient on lean hog prices in that relationship, estimated at minus 0.330, points to a long-run substitution effect between beef and pork, in which rising pork prices relative to beef shift consumer demand and production resources toward cattle.
Short-run behavior diverges sharply from this integrated long-run picture. When the VIX rises, returns in feeder cattle and live cattle fall significantly, with the effect statistically significant at the one percent level for feeder cattle and the five percent level for live cattle. Lean hog returns, by contrast, show no significant response to the uncertainty index. The authors describe this as a selective rather than uniform effect of financial uncertainty on the livestock sector. Notably, neither Brent crude oil nor the U.S. Dollar Index achieved statistical significance in any of the three mean equations once the VIX was accounted for, suggesting that their influence, if any, operates through volatility rather than through price levels.
The variance equations reveal the study’s most detailed findings. Feeder cattle display short-run shock sensitivity, volatility persistence, and a pronounced asymmetric response: the own-market ARCH coefficient is 0.186, the GARCH coefficient is 0.728, and the own-asymmetry coefficient is 0.341, all significant at the one percent level. In practical terms, a new shock immediately raises feeder cattle volatility, that elevated volatility carries forward into subsequent periods, and negative shocks generate a statistically distinct volatility response compared with positive shocks of similar size.
Lean hogs show a different internal profile. Their own-market ARCH coefficient of 0.123 is significant, but the standout feature is an exceptionally high GARCH coefficient of 0.987, indicating that once hog volatility rises, a large share of that uncertainty persists into later periods. The authors find no statistically significant own-market asymmetry for lean hogs, meaning the persistence of hog-market uncertainty is not accompanied by detectable sign-dependent amplification. Live cattle fall in between, with significant own-market ARCH and GARCH coefficients of 0.385 and 0.748 and a weaker, marginally significant asymmetry coefficient of 0.193 at the ten percent level.
Cross-market transmission is concentrated in the cattle complex. The feeder cattle and live cattle pair shows significant bidirectional persistence in volatility transmission, with GARCH cross-coefficients of 0.205 and 0.238, meaning volatility originating in one cattle market contributes to the lasting uncertainty of the other. Short-run transmission between the two cattle markets is directionally asymmetric: a significant coefficient running from live cattle shocks to feeder cattle volatility coexists with an insignificant reverse ARCH coefficient. Between feeder cattle and lean hogs, significant ARCH coefficients in both directions indicate immediate cross-market shock transmission, with the larger coefficient indicating that hog volatility responds more strongly to feeder cattle shocks than the reverse. The average conditional correlation between feeder and live cattle is 0.627, far above the 0.089 and 0.081 averages for the feeder-hog and hog-cattle pairs.
Specification tests reinforce the model’s structure. A likelihood-ratio test rejects the restriction that all off-diagonal elements of the ARCH, GARCH, and asymmetry matrices are zero, confirming that cross-market spillovers are statistically significant and that a diagonal specification would be misspecified. A separate test rejects the joint absence of asymmetry, validating the asymmetric extension. Interestingly, tests of whether the DXY, oil, or the VIX influence cross-market volatility transmission all fail to reject the null hypothesis, leading the authors to conclude that observed spillovers are driven primarily by the markets’ own shock, persistence, and asymmetry dynamics rather than by macro-financial variables acting as contagion channels.
A robustness exercise reintroducing discrete crisis indicators for the COVID-19 pandemic, the Russia-Ukraine war, and the Iran conflict alongside the VIX shows the two risk representations are complementary. The crisis dummies retain significant explanatory power beyond the VIX, concentrated in the variance equations, while the VIX’s joint contribution beyond the dummies is comparatively modest. The horse-race specification reveals heterogeneous crisis responses: pandemic indicators raise conditional variance for feeder cattle and lean hogs while lowering it for live cattle, the Russia-Ukraine war altered variance throughout the system with pronounced effects involving the cattle markets, and Iran-related indicators concentrated their variance effects in the cattle markets, a pattern the authors link to the Strait of Hormuz energy channel, through which roughly one-fifth of global oil trade flows.
The authors caution that the analysis has limits. It relies on a single fixed-parameter BEKK specification, covers only three livestock commodities, and uses a VIX that cannot decompose the distinct contributions of health, financial, and geopolitical uncertainty. They also note that longer-term multivariate dependencies at the twenty-lag horizon remained partially unmodeled. For risk managers, the practical message is that combining feeder and live cattle offers limited diversification under typical conditions given their high average correlation, while the near-zero cross-species correlations suggest greater scope for diversification between cattle and hog markets, though periods of systemic stress can temporarily raise co-movement and erode that protection.
Subject of Research: Volatility spillovers among US feeder cattle, live cattle, and lean hog futures markets under macroeconomic uncertainty
Article Title: Geopolitical risk, energy shocks, and the dynamics of volatility spillovers in livestock markets
Article References: Urak, F., Bozma, G., Yıldız, M. S., Arı, T., & Bilgic, A. (2026). Geopolitical risk, energy shocks, and the dynamics of volatility spillovers in livestock markets. Agricultural and Food Economics, 14(1), Article 75. https://doi.org/10.1186/s40100-026-00521-7
Image Credits: AI Generated
DOI: 10.1186/s40100-026-00521-7
Keywords: livestock futures, volatility spillovers, feeder cattle, live cattle, lean hogs, VIX, GARCH, cointegration, geopolitical risk, commodity markets, risk management, beef supply chain
News Source: William Thompson. (October 28, 2026). Cattle Markets Share Risk While Hogs Go Their Own Way, Decade of Futures Data Shows. Scienmag.
