竞争性电力市场中的金融工程理论与实证研究
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摘要
近二十年来,世界电力工业从政府高度监管的垂直一体化模式走上打破垄断,引入竞争的电力市场化道路,已经成为潮流,电力工业从垂直一体化模式逐步转变为以电力市场为核心的竞争模式。在竞争性电力市场中,电力成为一种普通商品,其价格随区域电力市场供求关系的变化而波动,市场参与者面临着巨大的电力市场风险。随着电力市场的出现,电力衍生产品逐步成为电力交易的主要形式之一。与之相适应,竞争性电力市场中的金融工程问题得到了广泛重视。本文以国外成熟竞争性电力市场为背景,对电价模型、衍生产品定价、电力风险管理和竞争性环境下的电力项目投资分析等领域的金融工程理论进行了较深入的探索性研究。本论文主要工作和创新点如下:
(1)电价随机模型对于电力衍生产品定价、风险管理、资产定价及不确定条件下的投资决策等具有基础意义。本文中提出了基于仿射跳跃—扩散过程的,具有2个和3个跳跃分量的电价随机模型以及一种新的参数标定方法,根据主要欧洲电力市场的日前小时电价历史数据标定了模型参数并用Monte Carlo方法分析了模型的模拟效果。
(2)由于电力是典型的不能大规模储存的流商品,无套利定价原理对大多数电力衍生产品定价不再适用。本文采用Black-76公式和仿射跳跃—扩散电价模型研究了电力期货/远期、期货期权、单点期权以及摇摆期权等奇异期权的定价问题,提出了一种新的电力衍生产品风险中性概率框架,并根据德国EEX电力市场实际价格,利用解析及Monte Carlo方法给出了若干常见电力衍生产品的实际定价算例。
(3)在竞争性电力市场中,不确定的电价和电量使市场参与者面临电力市场风险。本文根据国外竞争性电力市场实际情况,对电力市场风险的来源、测度指标和管理工具进行了分析,建议采用条件在险现金流(CCFaR)作为测度电力市场风险的指标,提出了竞争性电力市场下的电力企业电力市场风险模型,通过典型电力企业实例,分析了电力市场风险的特点、电力衍生产品交易对电力市场风险管理的作用以及考虑风险约束的电力实物资产和衍生产品投资组合优化等问题,计算了不同市场条件下样本企业的电力资产组合有效前沿。
(4)在传统的电力管制体制下,电力项目投资市场是垄断的,项目经济可行性评估一般采取净现值(NPV)方法。在竞争性电力市场中,电力项目投资是开放的,投资者必须尽力在竞争者之前发现新的投资机会,对项目投资机会的价值给予充分评价,不仅要看到眼前的情况,还要考虑未来的经济环境的变化。本文将实物期权方法引入发电项目投资决策中,建立了发电项目价值估值财务模型,对影响电力项目价值的各因素建立了数学模型,在此基础上,将最小二乘Monte Carlo方法(LSM)应用于电力项目投资多维美式实物期权的定价,并给出了电力项目投资各类相关实物期权定价计算实例。
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.
(1)电价随机模型对于电力衍生产品定价、风险管理、资产定价及不确定条件下的投资决策等具有基础意义。本文中提出了基于仿射跳跃—扩散过程的,具有2个和3个跳跃分量的电价随机模型以及一种新的参数标定方法,根据主要欧洲电力市场的日前小时电价历史数据标定了模型参数并用Monte Carlo方法分析了模型的模拟效果。
(2)由于电力是典型的不能大规模储存的流商品,无套利定价原理对大多数电力衍生产品定价不再适用。本文采用Black-76公式和仿射跳跃—扩散电价模型研究了电力期货/远期、期货期权、单点期权以及摇摆期权等奇异期权的定价问题,提出了一种新的电力衍生产品风险中性概率框架,并根据德国EEX电力市场实际价格,利用解析及Monte Carlo方法给出了若干常见电力衍生产品的实际定价算例。
(3)在竞争性电力市场中,不确定的电价和电量使市场参与者面临电力市场风险。本文根据国外竞争性电力市场实际情况,对电力市场风险的来源、测度指标和管理工具进行了分析,建议采用条件在险现金流(CCFaR)作为测度电力市场风险的指标,提出了竞争性电力市场下的电力企业电力市场风险模型,通过典型电力企业实例,分析了电力市场风险的特点、电力衍生产品交易对电力市场风险管理的作用以及考虑风险约束的电力实物资产和衍生产品投资组合优化等问题,计算了不同市场条件下样本企业的电力资产组合有效前沿。
(4)在传统的电力管制体制下,电力项目投资市场是垄断的,项目经济可行性评估一般采取净现值(NPV)方法。在竞争性电力市场中,电力项目投资是开放的,投资者必须尽力在竞争者之前发现新的投资机会,对项目投资机会的价值给予充分评价,不仅要看到眼前的情况,还要考虑未来的经济环境的变化。本文将实物期权方法引入发电项目投资决策中,建立了发电项目价值估值财务模型,对影响电力项目价值的各因素建立了数学模型,在此基础上,将最小二乘Monte Carlo方法(LSM)应用于电力项目投资多维美式实物期权的定价,并给出了电力项目投资各类相关实物期权定价计算实例。
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.
引文
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