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dc.contributor.authorChiweshe, Dyson
dc.date.accessioned2020-03-04T06:50:04Z
dc.date.available2020-03-04T06:50:04Z
dc.date.issued2017
dc.identifier.citationCiweshe, D. (2017). On the analysis of risk premiums in power markets using the Barndorff-Nielsen and Shephard model with leverage. (Unpublished thesis). University of Zimbabwe.en_US
dc.identifier.urihttp://hdl.handle.net/10646/3875
dc.description.abstractThis thesis is devoted to the study of risk premiums in power markets using the Ornstein- Uhlenbeck process with Barndorff-Nielsen and Shephard stochastic volatility with leverage. Forwards were priced using a class of measures that simultaneously allow for change of level and speed in the mean reversion popularized by Benth and Ortiz-Latorre. The change of measure enables the study of the behaviour of the risk premium under specific conditions. The forward prices and risk premiums were computed for the arithmetic and geometric price models. An analysis of the risk premium for the arithmetic model was conducted yielding shapes which are typically observed on energy markets. For the geometric spot price model the risk premium contained an expectation which does not allow for thorough analysis of the risk premium. An affine transform was performed yielding a system of Riccati Ordinary Differential Equations.en_US
dc.language.isoen_ZWen_US
dc.subjectOrnstein- Uhlenbeck processen_US
dc.subjectBarndorff-Nielsenen_US
dc.subjectShephard stochastic volatilityen_US
dc.subjectrisk premiumen_US
dc.subjectgeometric spot price modelen_US
dc.subjectaffine transformen_US
dc.subjectRiccati Ordinary Differential Equations.en_US
dc.titleOn the analysis of risk premiums in power markets using the Barndorff-Nielsen and Shephard model with leverageen_US
thesis.degree.advisorOrtiz-Latorre, Salvador, Prof
thesis.degree.countryZimbabween_US
thesis.degree.disciplineMathematicsen_US
thesis.degree.facultyFaculty of Scienceen_US
thesis.degree.grantorUniversity of Zimbabween_US
thesis.degree.grantoremailspecialcol@uzlib.uz.ac.zw
thesis.degree.levelMScen_US
thesis.degree.nameMaster of Science in Mathematicsen_US
thesis.degree.thesistypeThesisen_US
dc.date.defense2017


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