Abstract
Accurate risk measurement is critical to improve the level of market risk quantitative management. At present the indicator of VaR has been widely applied in the measurement of agricultural market extreme risk. However, the basic application research of VaR estimation techniques is not in-depth enough to efficiently estimate the increasingly complicated market risks. This study analyzed summary statistics for the soybean futures market price return, measured its price risk with the VaR method based on GARCH model, and discussed the impacts of residual probability distribution’s assumptions of normal distribution, Student-t distribution and generalized error distribution on the accuracy of VaR estimation. The results showed that VaR based on GARCH model could better depict the distribution and volatility of soybean futures market return, and to some extent the accuracy of VaR could be improved considering residual’s skewness.
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Acknowledgements
The authors gratefully acknowledge the financial support from the Project of National Key Technology R&D Program of China (grant No. 2012BAH20B04) and the National Natural Science Foundation of China (grant No.71203221).
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Li, G., Xu, S., Wang, S., Yu, H. (2014). Study on Extreme Risk Measurement of Chinese Soybean Futures Market—VaR Based on GARCH Model. In: Xu, S. (eds) Proceedings of 2013 World Agricultural Outlook Conference. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54389-0_14
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DOI: https://doi.org/10.1007/978-3-642-54389-0_14
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