Stochastic modeling of electricity prices and option pricing - Omungoh, Philgonah Awuor (Strathmore University, 2021)
Volatility 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.
Research thesis submitted to Strathmore University in fulfillment of the requirements for the Master of Science in Mathematical Finance
Keywords: Electricity prices; Mean-reverting; Diffusion; Monte-Carlo simulation; Spread option