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

Author

Listed:
  • Xinyu Wang
  • Lele Zhang
  • Qiuying Cheng
  • Song Shi
  • Huawei Niu

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.

Suggested Citation

  • Xinyu Wang & Lele Zhang & Qiuying Cheng & Song Shi & Huawei Niu, 2022. "What drives risk in China’s soybean futures market? Evidence from a flexible GARCH-MIDAS model," Journal of Applied Economics, Taylor & Francis Journals, vol. 25(1), pages 454-475, December.
    • Handle: RePEc:taf:recsxx:v:25:y:2022:i:1:p:454-475
    DOI: 10.1080/15140326.2022.2046989
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