A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets

Abstract

The recent price coupling of many European electricity markets has triggered a fundamental change in the interaction of day-ahead prices, challenging additionally the modeling of the joint behavior of prices in interconnected markets. In this paper we propose a regime-switching AR-GARCH copula to model pairs of day-ahead electricity prices in coupled European markets. While capturing key stylized facts empirically substantiated in the literature, this model easily allows us to 1) deviate from the assumption of normal margins and 2) include a more detailed description of the dependence between prices. We base our empirical study on four pairs of prices, -Western Denmark. We find that the marginal dynamics are better described by the flexible skew t distribution than the benchmark normal distribution. Also, we find significant evidence of tail dependence in all pairs of interconnected areas we consider. As a first application of the proposed empirical model, we consider the pricing of financial transmission rights, and highlight how the choice of marginal distributions and copula impacts prices. As a second application we consider the forecasting of tail quantiles, and evaluate the out-of-sample performance of competing models. to thank Jesper Jung, Esben Høg and Thomas Aalund Fredholm for providing valuable comments and suggestions. Two anonymous referees are also thanked for their constructive criticism and suggestions, which improved the presentation of this paper. † We mention in passing that univariate time series models of the ARMA-GARCH type have been successfully applied to model day-ahead electricity prices previously (see e.g. Keles et al. (2012) and Paraschiv (2013)).

Is oil price risk systemic to sectoral equity markets of an oil importing country? Evidence from a dependence-switching copula delta CoVaR approach

“…Many studies have used copula models to understand movements across markets (e.g. Ning, 2010;Meng and Liang, 2013;Reboredo & Ugolini, 2015;Kleinow & Moreira, 2016;Lourme & Maurer, 2017;Pircalabu & Benth, 2017;Ji et al, 2018). A copula is a multivariate cumulative distribution function with uniform marginal distributions on the interval (0, 1).…”

Modelling the joint behaviour of electricity prices in interconnected markets

“…Mahringer et al (2015) use a structural approach, where they model the supply and demand in a two-market setup that incorporates market coupling and allows for closed-form solutions for transmission rights. Pircalabu & Benth (2017) propose a reduced-form model in a two-market setup defined in discrete time that includes the market coupling mechanism using a regime-switching model, but no closed-form solutions for derivative prices are given.…”

“…As Pircalabu & Benth (2017) we propose a reduced-form model for day-ahead prices in a two-market setup that takes market coupling into account. Compared to Pircalabu & Benth (2017), we differentiate us by formulating the model in continuous time.…”

“…As Pircalabu & Benth (2017) we propose a reduced-form model for day-ahead prices in a two-market setup that takes market coupling into account. Compared to Pircalabu & Benth (2017), we differentiate us by formulating the model in continuous time. Instead of an ARMA-GARCH copula formulation combined with a discrete Markov chain, we assume that day-ahead prices can be described by a suitable combination and transformation of Gaussian Ornstein-Uhlenbeck processes.…”

A risk analysis of step-down equity-linked securities based on regime-switching copula

“…The authors concluded that the model efficiently reflect the asymmetric and heavy tail dependence of financial markets among countries that were considered. Pircalabu and Benth (2017) used a regime-switching copula to model the interdependence of electricity market prices among European countries. The authors identified the existence of the tail dependence of the prices.…”