What drives risk in China’s soybean futures market? Evidence from a flexible GARCH-MIDAS model

Xinyu Wang, Lele Zhang, Qiuying Cheng, Song Shi and Huawei Niu

Journal of Applied Economics, 2022, vol. 25, issue 1, 454-475

Abstract: Modeling futures market risk simultaneously influenced by macro low-frequency information and daily risk factors is a valuable challenge. We propose a new general framework for it based on the flexible GARCH-MIDAS model. It uses a skewed t distribution to describe the asymmetry of long and short trading positions, allows for a different number of trading days per month, and can identify the optimal combination of risky factors. We also derive its impact response function on how low-frequency factors directly influence the high-frequency futures market risk. Through an exhaustive empirical analysis of the Chinese soybean futures market, we not only find its excellent out-of-sample market risk forecasting performance but also offer systematic recommendations for improving risk management.

Date: 2022
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DOI: 10.1080/15140326.2022.2046989

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