Analysis shows that geopolitical risk significantly influences volatility in wheat futures, highlighting the roles of control variables and distribution dynamics.
This study looks at the impact of geopolitical risk on the volatility of wheat futures returns over the period 2012–2023, while controlling for inventories, shipping rates, and speculative activity. Using the volatility of CBOT first nearby futures returns, we apply a quantile regression approach to assess the impact of the variables on different parts of the volatility distribution. More specifically, we adopt the Quantile Autoregressive Distributed Lag (QARDL) model, which allows for examining the dynamic short- and long-run effects. We find that geopolitical risk has a non-linear, large positive effect on the top quartile of the distribution of wheat futures returns. We also show that the response of the volatility of wheat futures to shocks in the control variables is mostly non-linear across the conditional quantiles, significant in the tails and not around the median.
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Amagbo et al. (2025) studied this question.
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