Time-series and real options analysis of energy markets.
Doctoral thesis, UCL (University College London).
After the deregulation of electricity industries on the premise of increasing economic efficiency, market participants have been exposed to financial risks due to uncertain energy prices. Using time-series analysis and the real options approach, we focus on modelling energy prices and optimal decision-making in energy projects. Since energy prices are highly volatile with unexpected spikes, capturing this feature in reduced-form models leads to more informed decision-making in energy investments. In this thesis, non-linear regime-switching models and models with mean-reverting stochastic volatility are compared with ordinary linear models. Our numerical examples suggest that with the aim of valuing a gas-fired power plant, non-linear models with stochastic volatility, specifically for logarithms of electricity prices, provide better out-of-sample forecasts. Among a comprehensive scope of mitigation measures for climate change, CO2 capture and sequestration (CCS) plays a potentially significant role in industrialised countries. Taking the perspective of a coal-fired power plant owner that may decide to invest in either full CCS or partial CCS retrofits given uncertain electricity, CO2, and coal prices, we develop an analytical real options model that values the choice between the two technologies. Our numerical examples show that neither retrofit is optimal immediately, and the optimal stopping boundaries are highly sensitive to CO2 price volatility. Taking the perspective of a load-serving entity (LSE), on the other hand, we value a multiple-exercise interruptible load contract that allows the LSE to curtail electricity provision to a representative consumer multiple times for a specified duration at a defined capacity payment given uncertain wholesale electricity price. Our numerical examples suggest that interruption is desirable at relatively high electricity prices and that uncertainty favours a delay in interrupting. Moreover, we show that a deterministic approximation captures most of the value of the interruptible load contract if the volatility is low and the exercise constraints are not too severe.
|Title:||Time-series and real options analysis of energy markets|
|Open access status:||An open access version is available from UCL Discovery|
|UCL classification:||UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science|
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