Modeling Energy Spreads with a Generalized Novel Mean-Reverting Stochastic Process

Mir Hashem Avonleghi, M. Davison
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引用次数: 0

Abstract

The spread between two related energy prices is a very important quantity throughout energy finance. Of particular interest are spreads between different energy types, different delivery points (location spreads) and different delivery times (calendar spreads). Each underlying price process may be modeled directly. At times, however, it is a useful simplification to consider the spread as a distinct process, which may itself be directly modeled. For this purpose, we investigate the continuous limit of a mean-reverting random walk and its extensions. Analytical results about the solution of this process, including its stationary distribution, are obtained. This new mean-reverting process is compared with the Vasicek process, and its advantages are discussed. We show that this new model for spread dynamics is capable of capturing kurtosis. It can also capture the possible skewness in the transition density of the price spread process. Since the analytical transition density is unknown for this nonlinear stochastic process, the local linearization method is deployed to estimate the model parameters. We apply this method to empirical data for modeling the spread between West Texas Intermediate (WTI) crude oil and West Texas Sour (WTS) crude oil.
用一种广义新颖均值回归随机过程建模能量扩散
在整个能源金融中,两种相关能源价格之间的价差是一个非常重要的量。特别令人感兴趣的是不同能源类型、不同交付点(地点点)和不同交付时间(日历点)之间的价差。每个基础价格过程都可以直接建模。然而,有时将扩散视为一个可以直接建模的独特过程是一种有用的简化方法。为此,我们研究了均值回归随机漫步的连续极限及其扩展。得到了该过程解的解析结果,包括其平稳分布。并与Vasicek法进行了比较,讨论了其优点。我们证明了这种新的传播动力学模型能够捕捉峰度。它还可以捕获价格价差过程过渡密度中可能存在的偏度。由于该非线性随机过程的解析过渡密度未知,采用局部线性化方法估计模型参数。我们将此方法应用于西德克萨斯中质原油(WTI)和西德克萨斯酸原油(WTS)之间价差的实证数据建模。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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