施瓦茨-史密斯双因素模型的相关测量误差

IF 0.6 Q4 STATISTICS & PROBABILITY Dependence Modeling Pub Date : 2022-01-01 DOI:10.1515/demo-2022-0106
J. Han, N. Kordzakhia, P. Shevchenko, S. Trück
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引用次数: 0

摘要

摘要Schwartz–Smith双因素模型通常用于大宗商品市场中衍生品的定价。为了估计和预测期货价格的期限结构,商品现货价格的对数表示为作为不可观测状态变量的短期和长期因素的总和。作为现货价格函数导出的期货价格导致了一组同时的测量方程,该方程用于通过过滤程序联合估计不可观测的状态变量和模型参数。我们提出了一个修正模型,其中假设测量方程中的误差项是串行相关的。此外,为了进行比较分析,还考虑了期货价格对数收益率的建模。使用2017年1月至2021年4月的欧洲单位津贴(EUA)期货价格说明了两个拟议模型的样本外预测性能。从历史上看,这一时期对应于欧盟排放交易体系(EU-ETS)第三阶段的后半部分和第四阶段的开始。
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On correlated measurement errors in the Schwartz–Smith two-factor model
Abstract The Schwartz–Smith two-factor model is commonly used for pricing of derivatives in commodity markets. For estimating and forecasting the term structures of futures prices, the logarithm of commodity spot price is represented as the sum of short- and long-term factors being the unobservable state variables. The futures prices derived as functions of the spot price lead to the simultaneous set of measurement equations, which is used for joint estimation of unobservable state variables and the model parameters through a filtering procedure. We propose a modified model where the error terms in the measurement equations are assumed to be serially correlated. In addition, for comparative analysis, the modelling of the logarithmic returns of futures prices is also considered. Out-of-sample prediction performances of two proposed models were illustrated using European Unit Allowances (EUA) futures prices from January 2017 to April 2021. Historically, this period corresponds to the second half of Phase III, and the beginning of Phase IV of the European Union Emission Trading System (EU-ETS).
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
期刊最新文献
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