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dc.contributor.authorMaina, Francis Karanja
dc.date.accessioned2019-05-02T17:16:55Z
dc.date.available2019-05-02T17:16:55Z
dc.date.issued2018
dc.identifier.urihttp://hdl.handle.net/11071/6458
dc.descriptionSubmitted in partial fulfillment of the requirements for the Degree of Bachelor of Business Science in Finance at Strathmore Universityen_US
dc.description.abstractThe following research project will propose a mean-reverting stochastic process for modelling the daily average temperature in the Kenyan context. The proposed modelling framework will then be used to price a weather derivatives instrument. First, a general description of weather derivatives is provided along with their applicability in the market. Different models postulated in modeling the dynamics of temperature are then outlined. The Alaton model is then highlighted; a model that prescribes an Ornstein – Uhlenbeck process for the modeling of temperature. The methodology is then outlined as well as a description of the calibration of the model. Thereafter, the aforementioned model dynamics are used in pricing a CDD call option.en_US
dc.language.isoen_USen_US
dc.publisherStrathmore Universityen_US
dc.subjectFinanceen_US
dc.subjectFinancial modelingen_US
dc.subjectTemperature dynamicsen_US
dc.subjectDerivativesen_US
dc.titleModeling temperature dynamics and pricing temperature derivatives: an investigative Kenyan exampleen_US
dc.typeUndergraduate projecten_US


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