dc.rights.license | CC-BY-NC-ND | |
dc.contributor.advisor | Oosterlee, C.W. | |
dc.contributor.author | Kooi, Justus van | |
dc.date.accessioned | 2023-12-07T00:00:56Z | |
dc.date.available | 2023-12-07T00:00:56Z | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/45609 | |
dc.description.abstract | We developed a market equilibrium model based on a constrained quadratic optimisation problem
that maximizes the profit margins of liquefied natural gas (LNG) shipping companies. In 2022,
the European LNG imports and prices have increased sharply due to the reduced pipeline gas
from Russia. The market equilibrium model is calibrated to realistic trade volumes and prices for
the most influential regions in the LNG market. We calibrate the market equilibrium model by
solving a bilevel optimisation problem, to obtain ask and bid parameters, which cannot be collected
directly from market data. We present a scenario analysis, in which we show that European prices
would have increased by 5% if China had not been in lockdown during 2022. To illustrate the
usability and limitations of our model, we also investigate the effects of the Panama Canal drought
on trade flows and the impact of Australian port labour strikes on Asian imports based on the
market data from August 2023. | |
dc.description.sponsorship | Utrecht University | |
dc.language.iso | EN | |
dc.subject | We developed a market equilibrium model based on a constrained quadratic optimisation problem
that maximizes the profit margins of liquefied natural gas (LNG) shipping companies. The model is calibrated using bilevel optimisation. We perform several scenario analysis of realistic events to show the capabilities and limitations of this model. | |
dc.title | Market Equilibrium Model for LNG Shipments | |
dc.type.content | Master Thesis | |
dc.rights.accessrights | Open Access | |
dc.subject.keywords | Market equilibrium model; Constrained quadratic optimisation; Bilevel optimisation; Mathematical Modelling; Global LNG trade | |
dc.subject.courseuu | Mathematical Sciences | |
dc.thesis.id | 26356 | |