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Abstract

This thesis addresses the topics of spot price modelling, risk management, and investment applications in the energy markets. Eight of the most important energy markets that trade futures contracts on NYMEX, and one Spot Energy Index (SEI) proposed for the first time in this thesis, are investigated. A new modelling approach is proposed for optimally capturing the behaviour of the energy spot prices, combining a mean-reverting and a spike model that incorporate two different speeds of mean reversion, and time-varying volatility modelled as a GARCH and an EGARCH process. The aforementioned modelling approach is also evaluated in terms of its ability to quantify energy spot price risk by accurately calculating Value-at-Risk (VaR) and Expected Shortfall (ES) measures. A number of commonly used VaR methodologies are evaluated along with various Monte Carlo (MC) simulations based models and a Hybrid Monte Carlo with Historical Simulation (MC-HS) approach, introduced in this thesis for the first time. This thesis also delves into index investment applications for the energy markets that have recently attracted a lot of attention. To that end, the index tracking problem is addressed by applying equity algorithmic trading using two innovative Evolutionary Algorithms (EAs), aiming to replicate the performance of a direct energy commodity investment which is proxied by the constructed spot energy index. The empirical evidence in this thesis shows that the proposed modelling approach can effectively capture the behaviour of the energy spot prices examined, and that it is the most reasonable, efficient, and consistent approach for calculating the VaR of spot energy prices and the SEI, for both long and short positions. Hence, it can be successfully applied for forecasting, risk management, derivatives pricing, and policy development and monitoring purposes. Finally, it is shown that energy commodities, proxied by the SEI, can have equity-like returns as they can be effectively tracked with stock portfolios selected by the investment methodology proposed in this thesis. The latter investment approach can be used by fund managers to set-up energy Exchange Traded Funds that would track the performance of the SEI, giving them the full flexibility of any investment style, long or short, that equities can provide.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HB Economic Theory
Departments:	Bayes Business School Doctoral Theses Bayes Business School > Bayes Business School Doctoral Theses

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