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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01f1881p338
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dc.contributor.advisorSircar, Ronnie-
dc.contributor.authorBrown, Isaiah-
dc.date.accessioned2016-06-24T13:32:01Z-
dc.date.available2016-06-24T13:32:01Z-
dc.date.created2016-04-12-
dc.date.issued2016-06-24-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp01f1881p338-
dc.description.abstractIn this thesis, we examine dynamic Cournot models of energy production, incorporating stochastic demand. We study the causes of oil price volatility and spikes in volatility, and examine the relative importance of the supply and demand sides of the market. We also investigate the implications of our models for the transition to renewable energy and government policy. In our models, we find that changes in production and consumption are not enough to generate the observed levels of price volatility or spikes in volatility. We are, however, able to match observed levels of oil price volatility by fitting the random demand factors in our models to proxies for speculation. The demand side of the market in our models generates greater volatility than the supply side. Further, we find that blockading during times of low prices is a possible cause of oil price spikes, along with speculation due to changes in expectations about future demand and supply, and the transmission of illiquidity across financial markets. Both taxing oil and subsidizing renewables are effective ways to decrease the production of oil and increase the production of renewables, but taxes lead to higher prices and lower price volatility, while subsidies lead to lower prices and higher price volatility.en_US
dc.format.extent174 pagesen_US
dc.language.isoen_USen_US
dc.titleDynamic Cournot Models for the Production of Energy under Stochastic Demanden_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2016en_US
pu.departmentOperations Research and Financial Engineeringen_US
pu.pdf.coverpageSeniorThesisCoverPage-
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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