Pricing Futures and Options in Electricity Markets

Vos

2013

Adv. Appl. Probab.

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

Section: Simulation Of Matrix-valued Subordinatorsmentioning

confidence: 95%

Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

Vos

2013

Adv. Appl. Probab.

“…We will make the simplifying assumption of P = Q, arguing that a change of measure would not alter the overall conclusions regarding the impacts of heavy tails and choice of copula on option prices. For further discussions regarding measure change in the context of electricity markets we refer to Burger et al (2004), Benth and Meyer-Brandis (2009), and Benth and Schmeck (2014).…”

Section: Financial Transmission Rightsmentioning

confidence: 99%

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

Pircalabu

2017

Energy Economics

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)).

“…From an empirical point of view, the limit of the autocovariance functions as t → ∞ are particularly interesting. From (10) and (11), we have…”

Section: Lemma 5 Suppose That L J (1) Is Integrable Formentioning

confidence: 99%

Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

Advances in Applied Probability

Vos

2013