Rating of crop price insurance in China with evidence from corn

Minghua Ye, Kang Chen, Tongjiang Wang, Junsheng Zhu

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: Crop price insurance can reduce losses from price volatility for crop producers, but pricing is one paramount important issue. The objective of this research is to provide a tentative method for pricing of crop price insurance with data from the futures market. Design/methodology/approach: With weekly settlement price of January corn futures from the second week of January 2009 to the fourth week of April 2020 in China, we assume that corn futures price follows fractional Brownian motion, and apply an improved Black model. Findings: Our results reveal that the proposed model can be used to yield a fair premium and crop price insurance with varying insured prices and gradient coverage ratios can be used to meet the divergent needs of farmers at an affordable cost for price risk management purposes. Research limitations/implications: Results can be fine-tuned by extending research to crops such as wheat and rice, and by modeling price volatility with data from options market. Originality/value: This study offers one plausible way to rate crop price insurance using data from the futures market, and thus adds to this thread of literature by incorporating fractional Brownian motion into an improved Black model.

Keywords

  • China
  • Corn
  • Crop price insurance
  • Improved black model
  • Insurance premium rating

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