Theoretical And Empirical Studies On The Financial Engineering In The Competitive Electricity Market

In the past two decades, electricity industry worldwide has been gradually transformed from the regulated vertical integrated model to a competitive model. Under the competitive model, electricity becomes a common commodity and the electricity price fluctuated with its supply and consumption in the regional market. In the competitive electricity market, market participants are facing huge risk and electricity derivatives have become one of the major forms of electricity trading. Therefore, the financial engineering methods are more and more widely used. Under the background of mature competitive electricity market abroad, this thesis deeply probed into the financial engineering theory in the fields of electricity price model, electricity derivative pricing, electricity market risk management and the electricity project investment, etc. The main work and innovations would be described as follows:Firstly, the stochastic electricity price model is crucial for the pricing of the electricity derivatives, the electricity market risk management, the appraisal of asset and the investment decision under uncertainty. This thesis proposed stochastic electricity price models based on the Affine Jump Diffusion process with two or three jump components and a novel approximative parameter calibration method. The calibration results for major European electricity markets using historical hourly spot electricity prices are presented and Monte Carlo simulations are performed to test the effectiveness of the models.Secondly, because electricity is a typical non-storable flow commodity, the non-arbitrage principle is no longer valid for the pricing of electricity derivatives. This paper studied the pricing of the electricity future, future option, single point option and some typical swing options using the Black-76 formula or the Affine Jump-Diffusion electricity price model and proposed a new risk neutral framework for the pricing of electricity derivatives. Pricing examples for some typical electricity derivatives are given based on the EEX market historical prices using analytical and Monte Carlo method.Thirdly, in the competitive electricity market, the fluctuating electricity price and trading volume forced the electricity market participants to face huge electricity market risk. This article analyzed the sources, measure and management tools of electricity market risk under the background of mature competitive electricity markets abroad and proposed Conditional Cash Flow at Risk (CCFaR) as the proper electricity market risk measure. A corporate electricity market risk model under the competitive electricity market is also presented and through the sample of a typical electricity utility, the characteristics of electricity market risk and the role of the electricity derivatives trading in the electricity market risk management are analyzed. The real asset and electricity derivatives investment portfolio combined optimization problem under risk constraint is also studied and the efficient frontiers of the sample company under different market circumstances are calculated.Fourthly, in the traditional regulated electricity industry, the project investment market is monopolized by large vertical integrated utilities. The project economic feasibility study is usually based on the Net Present Value (NPV) method. In the competitive electricity market, the project invest market is open for competition and the investors have to try their best to find new investment opportunities prior to their competitors. Therefore, proper estimation on the project value not only taken into consideration of the current economic situation, but also future evolution of economic environment is crucial for the project investment decision in the competitive electricity market. This thesis established the electricity generation project value appraisal model and models for the key factors affecting the project value. On this basis, the Least Square Monte Carlo Method is used for the pricing of the multi-dimensional American real options embedded in the project investment. Examples of pricing for the various real options are given in this thesis.