Stochastic modeling of electricity prices and option pricing

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dc.contributor.authorOmungoh, Philgonah Awuor
dc.date.accessioned2022-06-13T09:45:23Z
dc.date.available2022-06-13T09:45:23Z
dc.date.issued2021
dc.descriptionResearch thesis submitted to Strathmore University in fulfillment of the requirements for the Master of Science in Mathematical Financeen_US
dc.description.abstractVolatility and abrupt price changes is a problem that has marred the electricity market for decades. This problem is especially observed in deregulated markets whose prices are influenced by supply and demand factors. Another consideration is the fact that electricity is non-storable which means that its prices are quite difficult to control. In an effort to address these problems, the current study was developed to price electricity and options used to hedge against volatility and unexpected price jumps. The mean reverting jump diffusion was applied by taking into account day ahead spot prices derived from the Nordic electricity market or the Nord Pool. To price spread options, I applied the Monte Carlo simulation model. The analysis of the data was undertaken through R programming undertaken within the Anaconda software. The need to price electricity options was to furnish market participants with instruments to manage the financial risks that come with price volatility due power failure and demand factors. The analysis shows the complex nature of electricity pricing, hence there is no closed form solution for pricing these derivatives. While the study findings were not directly applicable to the Kenyan and East African context, it provided a robust context for future research especially as the need for a deregulated market grows in the country.en_US
dc.identifier.urihttp://hdl.handle.net/11071/12823
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectElectricity pricesen_US
dc.subjectMean-revertingen_US
dc.subjectDiffusionen_US
dc.subjectMonte-Carlo simulationen_US
dc.subjectSpread optionen_US
dc.titleStochastic modeling of electricity prices and option pricingen_US
dc.typeThesisen_US
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MSc.MF Theses and Dissertations (2021)