Impact of US-China Trade War on the Volatility of China’s Soybean Futures—Based on GARCH Models
- DOI
- 10.2991/icmete-19.2019.139How to use a DOI?
- Keywords
- US-China trade war; Soybean futures; Market volatility; GARCH models
- Abstract
The US-China trade war has lasted for more than a year, while due to the hysteresis in macro data, the impact on the economies of the two countries, especially the passive part—China, has not fully manifested. This paper explores the impact of trade war on China’s economy from the perspective of the soybean futures market which is sensitive to tariff changes. In the course of research, it is found that the yield series of futures contracts have obvious conditional heteroscedasticity. In order to further explore the symmetry of the yield of the futures market, the GARCH and EGARCH model are applied to model the data for a comparative analysis. Meanwhile, considering the characteristics of the leptokurtosis and fat-tail of the yield data, the T distribution and GED distribution are added to the model to compare the fitting effect of residuals with the traditional normal distribution. Among the 6 GARCH and EGARCH models based on different residual distributions, the AIC criterion is used to select the best fitting model. Then, a dummy variable is added to the variance equation of the selected model to estimate the impact of trade war on the volatilities of China’s soybean futures market.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Zhe Lin PY - 2019/05 DA - 2019/05 TI - Impact of US-China Trade War on the Volatility of China’s Soybean Futures—Based on GARCH Models BT - Proceedings of the 2019 International Conference on Management, Education Technology and Economics (ICMETE 2019) PB - Atlantis Press SP - 583 EP - 589 SN - 2352-5428 UR - https://doi.org/10.2991/icmete-19.2019.139 DO - 10.2991/icmete-19.2019.139 ID - Lin2019/05 ER -