Derek W. Bunn
London Business School
The analysis of risk in energy markets is the underlying theme of most of the papers published in this journal. The development of models for prices and volatility, analysis of demand and supply, trading and hedging, as well as considerations of strategic behavior and government interventions all ultimately impact on the business risks of market participants. Risk mitigation and management is, furthermore, of increasing concern in monitoring organizational performance. This issue of The Journal of Energy Markets continues to reflect this important perspective very well.
In a paper titled “The multiple-mean-reversion jump-diffusion model for Nordic electricity spot prices” by Matylda Jabło´nska, Hasifa Nampala and Tuomo Kauranne, we have another contribution to the heavily researched (but still far from overresearched) theme of spot electricity price behavior. A wide variety of models have been developed to capture the complexities of these time series, and regime switching has become established as a promising technique. This paper expands substantially upon existing formulations, with an innovative mean-reversion process and multiple regimes.
Oil remains a focal point with regard to commodity risk, having macroeconomic as well as energy commodity interactions. In “Oil demand and energy security in Asian countries”, by Chin-Ho Cho, Yun-Peng Chu and Hao-Yen Yang, we see a timely analysis of the relationships among crude oil consumption, income and oil prices for Asian countries over the period 1971–2005. The authors observe that, in terms of price elasticity, a rise in the oil price due to the depletion of oil in the future will not smoothly reduce oil consumption and may only result in extreme inflation, while the advance of renewable energy may do little to reduce oil consumption in Asian countries. Thiswould clearly have wide implications, if it turned out to be the case, not least for attempts to mitigate greenhouse gas emissions in the transportation sector. With a more explicit risk-management orientation, the paper by Paolo Zagaglia, “Parametric approaches to risk management for natural gas prices: an out-of-sample evaluation”, looks at a range of generalized autoregressive conditional heteroskedasticity (GARCH) models for specifying the predictive distribution of NewYork Mercantile Exchange daily spot gas prices, concluding that the GARCH model with a generalized exponential distribution appears to outperform the competing models in terms of risk-management loss functions.
Finally, with the topic of volatility modeling being crucial for option pricing and risk in general, the paper by Mikhail V. Deryabin, “Implied volatility surface reconstruction for energy markets: spot price modeling versus surface parameterization”, provides a methodological comparison for calculating implied volatilities. One method involves fitting an exponential mean-reverting jump-diffusion model to the data, while an alternative uses a particular parameterization of the volatility surface that ensures no-arbitrage conditions. The second offers some advantages and these are discussed in the paper.
Overall, the methodological quality and practical implications of these papers continue to reflect the extensive research agenda in modeling energy markets and the importance of trying to link new approaches with practical relevance. The Journal of Energy Markets continues to receive a strong flow of submissions at this key interface of research and practice.
Implied volatility surface reconstruction for energy markets: spot price modeling versus surface parametrization