What drives risk in China's soybean futures market? Evidence from a flexible GARCH-MIDAS model - Xinyu Wang; Lele Zhang; Qiuying Cheng; Song Shi; Huawei Niu (Journal of Applied Economics, 2022)
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.
Keywords: 330; GARCH-MIDAS; futures market; skewed t distribution; value at risk; volatility