Modeling the Electricity Spot Price with Switching Regime Semi-Nonparametric Distributions

Alfredo Trespalacios, Lina M. Cortés, Javier Perote
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Abstract

Spot prices of electricity in liberalized markets feature seasonality, mean reversion, random short-term jumps, skewness and highly kurtosis, as a result from the interaction between the supply and demand and the physical restrictions for transportation and storage. To account for such stylized facts, we propose a stochastic process with a component of mean reversion and switching regime to represent the dynamics of the spot price of electricity and its logarithm. The short-term movements are represented by semi-nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. The application is done for the Colombian electricity market, where El Niño phenomenon represents an additional source of risk that should be considered to guarantee long-term supply, sustainability of investments and efficiency of prices. We show that the switching regime model with SNP distributions for the random components outperforms traditional models leading to accurate estimates and simulations, and thus being a useful tool for risk management and policy making.
基于开关状态半非参数分布的电力现货价格建模
自由化市场的电力现货价格具有季节性、均值回归、短期随机跳变、偏态和高度峰度的特点,这是供需相互作用以及运输和储存的物理限制的结果。为了解释这种程式化的事实,我们提出了一个随机过程,其中包含均值回归和切换机制的成分,以表示电力现货价格及其对数的动态。短期运动由半非参数(SNP)分布表示,与以往的研究传统上假设高斯过程相反。该应用是针对哥伦比亚电力市场的,在那里,El Niño现象代表了一个额外的风险来源,应该考虑确保长期供应,投资的可持续性和价格的效率。我们表明,具有随机成分SNP分布的切换状态模型优于传统模型,导致准确的估计和模拟,从而成为风险管理和政策制定的有用工具。
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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