中国农业气象 ›› 2026, Vol. 47 ›› Issue (5): 797-808.doi: 10.3969/j.issn.1000-6362.2026.05.013

• 农业气象保险栏目 • 上一篇    下一篇

温度衍生品在黑龙江省大豆产业天气风险管理中的应用

晏明思,钱永兰,齐丹,何亮,郑赜瑜,赵瑞,刘维,吴垂祯,张蕾   

  1. 1. 大连商品交易所,大连 116023;2. 国家气象中心,北京 100081
  • 收稿日期:2025-05-06 出版日期:2026-05-20 发布日期:2026-05-18
  • 作者简介:晏明思,E-mail:yanms@dce.com.cn
  • 基金资助:
    中国气象局创新发展专项重点项目(CXFZ2025J054);中国气象局创新发展专项项目(CXFZ2024J051);2024年度中国气象局气象软科学研究重点课题(2024ZDIANXM07);国家气象中心气象高质量发展专项项目(QXGZL202522)

Application of Temperature Derivatives in Weather Risk Management of Soybean Industry in Heilongjiang Province

YAN Ming-si, QIAN Yong-lan, QI Dan, HE Liang, Zheng Ze-yu, ZHAO Rui, LIU Wei, Wu Chui-zhen, ZHANG Lei   

  1. 1. Dalian Commodity Exchange, Dalian 116023, China; 2. National Meteorological Centre, Beijing 100081
  • Received:2025-05-06 Online:2026-05-20 Published:2026-05-18

摘要:

温度衍生品主要是用于降低或规避不利天气对农业等相关产业的潜在风险,本研究基于19802020年黑龙江省逐日气温观测资料和65个县的大豆单产数据,计算温度衍生品标的温度指数和气象产量收益,构建65个样本的场内温度衍生品最优套保策略,并采用在险价值和期望短缺两个金融风险指标进行策略评估,研究温度衍生品在黑龙江大豆产业天气风险管理中的潜在效果。结果表明:使用温度衍生品后,65个样本大豆种植的在险价值改善幅度为17.63%~63.78%,平均改善幅度为38.91%;期望短缺改善12.66%43.64%,平均改善幅度为29.24%;最优套保策略合约月份集中于7月和9月,且期望短缺的最优套保月份集中在9月。该结果说明使用温度衍生品可明显转移黑龙江大豆种植的天气风险,且主要风险时段为7月和9月,严重低温风险在9月,这与黑龙江省大豆7月易发低温冷害、9月易发早霜冻害且早霜冻害往往导致严重减产的生产实际相符。

关键词: 温度衍生品, 套期保值, 大豆, 金融气象

Abstract:

Temperature derivatives is mainly utilized to reduce or avoid the potential risks to agriculture and related industries from severe weather. The study calculated the temperature index, as the underlying of temperature derivatives, and soybean meteorological yield income respectively based on 65 countylevel daily temperatures and soybean yield data from 1980 to 2020 in Heilongjiang province. Then the optimal hedging strategies for exchangetraded temperature derivatives were constructed for the 65 samples, which were evaluated using two financial risk indicators of value at risk (VaR) and expected shortfall (ES) to assess the potential effects of temperature derivatives in managing weather risk in Heilongjiang's soybean industry. The results showed that after the use of temperature derivatives, VaR improved by 17.63% to 63.78% and ES improved by 12.66% to 43.64% for the 65 samples, for an average improvement of 38.91% and 29.24%, respectively. The contract months for optimal hedging strategy were concentrated in July and September, especially concentrated in September for the optimal of expected shortfall. The results indicated that the use of temperature derivatives could significantly transfer the weather risk of soybean cultivation in Heilongjiang, with the risk months being mainly July and September, and the severe lowtemperature risk in September, which was in line with the fact that soybean in Heilongjiang is vulnerable to cold damage in July and frost damage in September, the latter of which usually leads to severe loss of yield.

Key words: Weather derivatives, Hedge strategy, Soybean, Financial meteorology