City Research Online

Abstract

Reconstruction and deregulation in the international power markets has let prices to be determined by the fundamental rules of Supply and Demand, which brought a substitution from Supply Risk pre-regulation, to Price risk, thus increasing the necessity of hedging using derivatives such as futures and options and therefore brought the issue of pricing these derivatives into focus. However the traditional approaches for the pricing of derivatives are not applicable to electricity due to the unique features of the power market such as the fact that electricity is not storable. Under these circumstances, arbitrage across time and space is limited in the electricity market. As a consequence there is a need for a good model that is able to capture the dynamics of the electricity spot prices for the purposes of Derivatives pricing and Risk Management. In this thesis we propose three different spot models for the Scandinavia electricity market; First, we propose a seasonal affine jump diffusion spike model, which can distinguish the behaviour of electricity spot prices between normal periods and periods when spikes occur. Second, we propose a seasonal affine jump diffusion regime-switching spike, which is an extension of the spike model but contains two separate regimes to distinguish between periods of high and low water levels in the reservoirs, reflecting the availability of hydropower in the market. Third, we propose a seasonal affine jump diffusion three-factor spike model which again extends the spike model but allows the equilibrium level to be stochastic in order to capture the long-run dynamics of the market that are uncovered from the shape of the forward term structure. The performance of our models is compared to that of other models proposed in the literature in terms of fitting the observed term structure, as well as by generating simulated price paths which have the same statistical properties as the actual prices observed in the market. In particular, our models perform well in terms of capturing the spikes and explaining their fast mean reversion as well as in terms of reflecting the seasonal volatility observed in the market. Then we use these models and provide semi-closed form solutions for European option prices and investigate whether the shape of the model implied volatility smile is consistent to the one that is anticipated to be observed in the market. Furthermore, we also perform a sensitivity analysis for Asian option prices which are widely used in the market. Finally, we apply a modified Least Squares Monte Carlo algorithm for the pricing of swing options, and investigate the sensitivity of the incremental swing premium to changes of different parameters used to capture the stochastic behaviour of the power spot prices

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HG Finance
Departments:	Bayes Business School > Finance Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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