Hedging temperature risk with CDD and HDD temperature futures

IF 1.3 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Applied Stochastic Models in Business and Industry Pub Date : 2023-09-06 DOI:10.1002/asmb.2815
Fred Espen Benth, Jukka Lempa
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Abstract

Abstract This paper is concerned with managing risk exposure to temperature using weather derivatives. We consider hedging temperature risk using so‐called HDD‐ and CDD‐index futures, which are instruments written on temperatures in specific locations over specific time periods. The temperatures are modelled as continuous‐time autoregressive (CARMA) processes and pricing of the hedging instrument is done under an equivalent pricing measure. We develop hedging strategies for locations, cutoff temperatures, and time periods different to the ones in the traded contracts, allowing for more flexibility in the hedging application. The dynamic hedging strategies are expressed explicitly by the term structure of the volatility. We also provide numerical case studies with temperatures following a CAR(3)‐process to illustrate the temporal behaviour of the hedge under different scenarios.
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用CDD和HDD温度期货对冲温度风险
本文关注的是利用天气衍生品来管理温度风险暴露。我们考虑使用所谓的HDD和CDD指数期货来对冲温度风险,这是一种基于特定时间段特定地点温度的工具。温度建模为连续时间自回归(CARMA)过程,套期保值工具的定价是在等效定价措施下完成的。我们针对不同于交易合约的地点、截止温度和时间段制定对冲策略,从而在对冲应用中具有更大的灵活性。动态套期保值策略通过波动性的期限结构来明确表达。我们还提供了CAR(3)过程后温度的数值案例研究,以说明不同情景下对冲的时间行为。
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来源期刊
CiteScore
2.70
自引率
0.00%
发文量
67
审稿时长
>12 weeks
期刊介绍: ASMBI - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis) was first published in 1985, publishing contributions in the interface between stochastic modelling, data analysis and their applications in business, finance, insurance, management and production. In 2007 ASMBI became the official journal of the International Society for Business and Industrial Statistics (www.isbis.org). The main objective is to publish papers, both technical and practical, presenting new results which solve real-life problems or have great potential in doing so. Mathematical rigour, innovative stochastic modelling and sound applications are the key ingredients of papers to be published, after a very selective review process. The journal is very open to new ideas, like Data Science and Big Data stemming from problems in business and industry or uncertainty quantification in engineering, as well as more traditional ones, like reliability, quality control, design of experiments, managerial processes, supply chains and inventories, insurance, econometrics, financial modelling (provided the papers are related to real problems). The journal is interested also in papers addressing the effects of business and industrial decisions on the environment, healthcare, social life. State-of-the art computational methods are very welcome as well, when combined with sound applications and innovative models.
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