Power Forward Curve Model with Mitigated Swell Based on Constrained Least Square Error Approach

Takuji Matsumoto, Misao Endo
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Abstract

To construct a power forward curve (PFC), which is indispensable for decision-making such as pricing of electricity transactions, we propose a modeling method with relatively small error while satisfying the reasonable PFC requirements summarized in the previous study. In particular, we focus on the problem that the PFC obtained by the existing method, which simultaneously satisfies the smoothness and arbitrage-free conditions, tends to "swell" significantly when the price of electricity futures rises, and the fit deteriorates significantly, and propose a method to mitigate this problem. Specifically, using B-spline basis functions, we solve a constrained least-square-error-based optimization problem instead of minimizing the integral of squared curvature, which has been used in previous studies. The empirical study examines the errors between the realized spot prices and the PFCs using multiple futures products for different observation points, and finds that our method effectively mitigates the "swell" problem and is more accurate overall than the previous method. Furthermore, it is shown that the fit of the forward curve can be improved by, for example, incorporating the seasonal trend of the holiday effect to calculate the structural pattern of the PFC, providing useful suggestions for modeling practitioners.
基于约束最小二乘误差法的减胀功率正向曲线模型
为了构建电力交易定价等决策中不可缺少的功率前向曲线(power forward curve, PFC),我们提出了一种误差较小的建模方法,同时满足前人研究中总结的合理的功率前向曲线要求。特别针对现有方法得到的同时满足平滑和无套利条件的PFC在电力期货价格上涨时出现明显“膨胀”、拟合明显恶化的问题,提出了一种缓解该问题的方法。具体而言,我们利用b样条基函数解决了一个基于约束最小二乘误差的优化问题,而不是像以往的研究那样最小化曲率平方积分。实证研究使用多个期货产品对不同观测点检验了现货实现价格与PFCs之间的误差,发现我们的方法有效地缓解了“膨胀”问题,总体上比以前的方法更准确。此外,研究还表明,考虑假日效应的季节性趋势来计算PFC的结构模式,可以改善远期曲线的拟合,为建模从业者提供有用的建议。
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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