Pricing Quanto Options in Renewable Energy Markets

IF 0.5 Q3 MATHEMATICS Malaysian Journal of Mathematical Sciences Pub Date : 2023-12-14 DOI:10.47836/mjms.17.4.02
N. A. A. Arsat,, N. A. Ibrahim, C. M. I. C. Taib
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Abstract

High level of greenhouse gases emission in fossil fuels has induced a significant transition from conventional energy sources to renewable energy. However, using renewable energy in electricity grids has limitations, such as intermittency and lack of efficient energy storage. This paper focuses on constructing the quanto options contract to help renewable energy producers hedge the risk against low photovoltaic (PV) production and electricity prices. To achieve our objective, we first model the interday PV power production with a combination of a deterministic and stochastic model. We analyse empirical data for daily solar production in three operators in Germany ranging from 1 January 2016 to 31 December 2020. We discovered that all estimated parameters of the deterministic process are highly significant. Meanwhile, we use an autoregressive (AR) process to describe the random behavior in the production. The results demonstrated that AR(2) is suitable enough to explain its stochastic factor. For the error terms analysis, we observed a clear sign of seasonal heteroskedasticity supported by the left skewed density. In addition, we observed a clear seasonal pattern in the squared error terms, where we suggest using seasonal variance and skewed normal distribution to describe its dynamic. As for an application, we embed the PV model in the power price modeling. We found that AR(3) process is sufficient to explain the price behavior and that normal distribution best fits the error terms. Using the suggested PV and power price model, we construct the quanto options contract for renewable energy producers using Monte Carlo simulations. We discovered that the electricity price payoffs are consistent throughout the year, whereas PV and quanto options payoffs vary greatly depending on the season. The quanto options price result shows that the prices vary during four seasons, with the highest variation in July.
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可再生能源市场中广义期权的定价
化石燃料排放的大量温室气体促使人们从传统能源大力转向可再生能源。然而,在电网中使用可再生能源有其局限性,如间歇性和缺乏有效的能源储存。本文的重点是构建量子期权合约,帮助可再生能源生产商规避光伏(PV)产量和电价过低的风险。为实现这一目标,我们首先结合确定性模型和随机模型对日间光伏发电量进行建模。我们分析了德国三家运营商 2016 年 1 月 1 日至 2020 年 12 月 31 日期间每日太阳能产量的经验数据。我们发现,确定性过程的所有估计参数都非常显著。同时,我们使用自回归(AR)过程来描述生产中的随机行为。结果表明,AR(2)足以解释其随机因素。在误差项分析中,我们观察到明显的季节性异方差迹象,并得到左偏密度的支持。此外,我们还在平方误差项中观察到明显的季节性模式,建议使用季节性方差和倾斜正态分布来描述其动态。在应用方面,我们将光伏模型嵌入到电价建模中。我们发现 AR(3) 过程足以解释价格行为,而正态分布最适合误差项。利用建议的光伏和电力价格模型,我们通过蒙特卡罗模拟为可再生能源生产商构建了量子期权合约。我们发现,电价回报全年一致,而光伏和量子期权回报则因季节不同而有很大差异。量子期权价格结果显示,价格在四个季节都有变化,其中七月的变化最大。
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来源期刊
CiteScore
1.10
自引率
20.00%
发文量
0
期刊介绍: The Research Bulletin of Institute for Mathematical Research (MathDigest) publishes light expository articles on mathematical sciences and research abstracts. It is published twice yearly by the Institute for Mathematical Research, Universiti Putra Malaysia. MathDigest is targeted at mathematically informed general readers on research of interest to the Institute. Articles are sought by invitation to the members, visitors and friends of the Institute. MathDigest also includes abstracts of thesis by postgraduate students of the Institute.
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