A study on the pricing of weather derivatives considering risky market prices

被引：0
|
作者：
Bei H. [1 ,2 ]
Zhu L. [1 ]
Wang W. [1 ]
Sun Y. [3 ]
机构：
[1] School of Maritime Economics and Management, Dalian Maritime University, Dalian
[2] School of Management, Shanghai University, Shanghai
[3] Business School, Liaoning University, Shenyang
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2022年 / 42卷 / 12期
基金：
中国国家自然科学基金;
关键词：
ARMA model; O-U model; the market price of risk; weather derivatives;
D O I：
10.12011/SETP2022-2081
中图分类号：
学科分类号：
摘要：
As an emerging financial tool, weather derivatives have essential application prospects in agriculture, tourism, and other industries. However, there have been problems such as neglect of market risks and inaccurate pricing. Based on the traditional O-U model, the present paper combines the rate of time-varying mean reversion, the time-varying temperature volatility, and the market price of risk to construct a temperature prediction model. We employ the temperature data of the past ten years to conduct pricing research on the weather derivatives of crops. The offered model is also combined with rice, corn, and other crops with a critical impact on life. A comparison was conducted about the pricing results between the proposed model, the traditional time-varying O-U, and ARMA time series models. The numerical results show that the market price of risk can play a corrective role in pricing. Considering the market price of risk performs better in most scenarios for our O-U model. The conclusions provide theoretical guidance and practical reference for pricing agricultural weather derivatives and forming risk hedging mechanisms. © 2022 Systems Engineering Society of China. All rights reserved.
引用
收藏
页码：3265 / 3278
页数：13
相关论文
共 40 条
  • [1] Liang R, Chen B Z., Damage assessment of extreme weather events under climate change[J], Systems Engineering-Theory & Practice, 39, 3, pp. 557-568, (2019)
  • [2] Dornier F, Querel M., Caution to the wind[J], Energy and Power Risk Management, 13, 8, pp. 30-32, (2000)
  • [3] Alaton P, Djehiche B, Stillberger D., On modelling and pricing weather derivatives[J], Applied Mathematical Finance, 9, 1, pp. 1-20, (2002)
  • [4] Caballero R, Jewson S, Brix A., Long memory in surface air temperature:Detection, modeling, and application to weather derivative valuation[J], Climate Research, 21, 2, pp. 127-140, (2002)
  • [5] Ahcan A., Statistical analysis of model risk concerning temperature residuals and its impact on pricing weather derivatives[J], Insurance Mathematics & Economics, 50, 1, pp. 131-138, (2012)
  • [6] Fujita H, Mori H., A hybrid intelligent system for designing a contract model for weather derivatives[J], Procedia Computer Science, 12, pp. 361-366, (2012)
  • [7] Yamada Y., Valuation and hedging of weather derivatives on monthly average temperature[J], Journal of Risk, 10, 1, pp. 101-125, (2007)
  • [8] Vasicek O., An equilibrium characterization of the term structure[J], Journal of Financial Economics, 5, 4, pp. 627-627, (1977)
  • [9] John H, Alan W., Pricing interest-rate-derivative securities[J], Review of Financial Studies, 3, 4, pp. 573-592, (1990)
  • [10] Benth F E, Benth J S., The volatility of temperature and pricing of weather derivatives[J], Quantitative Finance, 7, 5, pp. 553-561, (2007)
1234