{"title":"Risk valuation of quanto derivatives on temperature and electricity","authors":"Aurélien Alfonsi, Nerea Vadillo","doi":"arxiv-2310.07692","DOIUrl":null,"url":null,"abstract":"This paper develops a coupled model for day-ahead electricity prices and\naverage daily temperature which allows to model quanto weather and energy\nderivatives. These products have gained on popularity as they enable to hedge\nagainst both volumetric and price risks. Electricity day-ahead prices and\naverage daily temperatures are modelled through non homogeneous\nOrnstein-Uhlenbeck processes driven by a Brownian motion and a Normal Inverse\nGaussian L\\'evy process, which allows to include dependence between them. A\nConditional Least Square method is developed to estimate the different\nparameters of the model and used on real data. Then, explicit and semi-explicit\nformulas are obtained for derivatives including quanto options and compared\nwith Monte Carlo simulations. Last, we develop explicit formulas to hedge\nstatically single and double sided quanto options by a portfolio of electricity\noptions and temperature options (CDD or HDD).","PeriodicalId":501355,"journal":{"name":"arXiv - QuantFin - Pricing of Securities","volume":"48 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - Pricing of Securities","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2310.07692","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper develops a coupled model for day-ahead electricity prices and
average daily temperature which allows to model quanto weather and energy
derivatives. These products have gained on popularity as they enable to hedge
against both volumetric and price risks. Electricity day-ahead prices and
average daily temperatures are modelled through non homogeneous
Ornstein-Uhlenbeck processes driven by a Brownian motion and a Normal Inverse
Gaussian L\'evy process, which allows to include dependence between them. A
Conditional Least Square method is developed to estimate the different
parameters of the model and used on real data. Then, explicit and semi-explicit
formulas are obtained for derivatives including quanto options and compared
with Monte Carlo simulations. Last, we develop explicit formulas to hedge
statically single and double sided quanto options by a portfolio of electricity
options and temperature options (CDD or HDD).