Arsat, N. A. A.N. A. A.ArsatIbrahim, N. A.N. A.IbrahimTaib, C. M. I. C.C. M. I. C.Taib2024-05-292024-05-2920232024-2-19N. A. A., A., N. A. , I., & C. M. I. C. , T. (2023). Malaysian Journal of Mathematical Sciences (MJMS). Malaysian Journal of Mathematical Sciences ; UPM. https://mjms.upm.edu.my/lihatmakalah.php?kod=2023/December/17/4/531-5561823-8343https://www.scopus.com/record/display.uri?eid=2-s2.0-85184176304&origin=resultslist&sort=plf-f&src=s&sid=47f412d7a706a0fe380d40dc39bea717&sot=b&sdt=b&s=TITLE-ABS-KEY%28Pricing+Quanto+Options+in+Renewable+Energy+Markets%29&sl=114&sessionSearchId=47f412d7a706a0fe380d40dc39bea717&relpos=0https://mjms.upm.edu.my/lihatmakalah.php?kod=2023/December/17/4/531-556https://oarep.usim.edu.my/handle/123456789/10793Vol. 17, No. 4High 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.en-USphotovoltaic productions; electricity prices; Quanto optionsArticle531556174