Volume 6, Number 4 (December 2013)
This issue of The Journal of Energy Markets focuses on financial engineering and energy derivatives, covering the topics of weather derivatives, electricity option pricing, spread volatility and risk premiums in power markets. With the trend toward greater renewable energy, the impact of weather conditions (which are always important for determining demand) is becoming crucial on the supply side. Accordingly, our first two papers in this issue analyze temperature derivatives. In "On the modeling of temperature dynamics for pricing weather-related products", Zografia Anastasiadou and Brenda López-Cabrera propose a model for the temporal dynamics of temperature with the aim of pricing temperature derivatives. The time series dynamics are based on novel specifications of the mean and volatility of temperatures and are estimated using data collected in four European cities.
The problem of forecasting weather using weather futures is studied in "Weather forecasting with market prices of weather futures" by Matthias Ritter. The author demonstrates that temperature futures contracts traded at the Chicago Mercantile Exchange are generally better at forecasting the underlying temperature index than meteorological forecasts.
European call and put options on electricity futures are traded at many power exchanges. In the third paper in this issue, "Pricing electricity swaptions under a stochastic volatility term structure model", Rikard Green, Karl Larsson and Marcus Nossman propose a dynamic model for power futures prices that includes the maturity effect and stochastic volatility. They show that option prices can be derived by Fourier transform methods and they calibrate their model to implied volatilities observed in the Nordic power market Nord Pool.
The modeling and analysis of commodity pairs are of great interest in energy markets. In "Spread volatility of cointegrated commodity pairs", Rainer Döttling and Pascal Heider present a study of the spread volatility in a cointegrated model for two commodities with mean reversion. In their model, the terminal spread volatility is analytically available; moreover, it is fitted to data series for coal and power taken from the German power market EEX, to gas and power data collected from the British National Balancing Point market, and finally to data about Brent and gas oil.
The risk premium in power markets is a delicate issue and it is challenging to model. Based on a new and sophisticated class of models for power spot price dynamics called Lévy semistationary processes, Almut E. D. Veraart and Luitgard A. M. Veraart undertake an empirical investigation into the risk premium in the German EEX market in our issue's final paper: "Risk premiums in energy markets". They find that the spot price has some predictive power but that there is still a large degree of unexplained variability. They show that fitting a model of the forward directly gives a very good fit in the case where the forward dynamics are specified via the Lévy semistationary class.
The five papers in this issue were selected, after peer reviewing, from a specially focused workshop co-organized by René Aïd, Fred Espen Benth, Valery Kholodnyi, Peter Laurence and Almut Veraart at the Wolfgang Pauli Institute in Vienna. The workshop was part of a special topic year on "Financial Engineering for Energy and Commodity Risk Management and Hedging of Commodity Derivatives" hosted by the institute, and all five papers here benefited from discussions and feedback from over 100 participants. We thank Norbert Mauser, the director of the Wolfgang Pauli Institute, for his support and help, as well as the Centre of Mathematics for Applications (CMA), the EDF and Verbund Trading for additional financial support.
Fred Espen Benth
University of Oslo
University of Rome, "La Sapienza"
Imperial College London
Papers in this issue
On the modeling of temperature dynamics for pricing weather-related products
Spread volatility of cointegrated commodity pairs
Pricing electricity swaptions under a stochastic volatility term structure model
Weather forecasting with market prices of weather futures
Risk premiums in energy markets