Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/314171 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Applied Economics [ISSN:] 1667-6726 [Volume:] 25 [Issue:] 1 [Year:] 2022 [Pages:] 454-475
Publisher: 
Taylor & Francis, Abingdon
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.
Subjects: 
GARCH-MIDAS
futures market
skewed t distribution
value at risk
volatility
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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