报告题目：The effects of climate on the price of agricultural financial derivatives: a case study of the corn price in the US market

报  告 人： 孙勋 研究员

邀  请 人： 刘德地 教授

时      间： 2022年7月18日（星期一）上午10:00-12:00

地      点： 水电科技大楼A区202会议室

腾讯视频会议（ID: 247 740 198）

报告人简介：

孙勋博士，华东师范大学研究员，博士生导师，国际水文科学协会（IAHS）会刊Hydrological Sciences Journal副主编。曾在美国哥伦比亚大学、法国索邦大学（原皮埃尔玛丽居里大学）、法国格勒诺布尔大学、新加坡国立大学、澳大利亚阿德莱德大学学习和工作。研究方向为水文与气候风险，主要研究领域包括：洪水、暴雨的概率分析与预测；农业金融衍生品与气象保险；极端灾害及其社会经济影响；极端事件与极值理论；统计建模、人工智能(AI)与大数据分析。

报告简介：

Corn is the 1st economic field crop in the world, whose price stability guarantees sustainable and equitable food security. Most previous farm commodity price prediction model only focus on detecting the autoregression of historical transaction, while ignoring other factors. For agricultural commodities, different climate condition leads to different harvest situation, thus bringing volatility to prices. Therefore, it is reasonable to propose a method based on climate indices to measure the degree of their influence on price fluctuation.

A multiple regression model is developed for predicting corn price movements at the nation level. The June-September season is selected to target the essential growing stages of corn which are especially sensitive to drought, high temperature stress and water stress. In order to describe the movements of price, the price difference between June and September is chosen as the dependent variable. Daily climate data are obtained from PRISM which integrates both satellite and meteorological station observation data, and monthly price data are sourced from USDA. 39-year trend from 1981-2019 is explored to construct a predictive model. The results show that the accuracy of predicting up and down of price is 85%. Specifically, temperature in July has an identifiable effect on price movements which explains 36.99% price variation. These results imply that during the key growing period, climate indices occupy an important position on improving crop price forecast ability.

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