Journal of Energy Markets

Derek W. Bunn
London Business School

Oil and gas commodities, and their related products, hold fundamental and preeminent roles in the energy markets. Analysis of their price dynamics and risk has continued to attract the attention of researchers, not only because of the modeling challenges involved but also due to the practical impacts that improved methods can provide. This issue of The Journal of Energy Markets offers three contributions on this topic.

In the issue’s first paper, “Directional predictability between returns and trading volume in the futures markets of energy: insights into traders’ behavior”, Dimitrios Panagiotou investigates the directional predictability between returns and volume (and vice versa). The study employs the cross-quantilogram approach that enables estimation of the temporal association between two stationary time series at different parts of their joint distribution. This is applied to daily prices and trading volumes from five energy futures markets (West Texas Intermediate (WTI), Brent, Natural Gas, Heating Oil and Gasoline). The empirical results indicate that high levels of volume lead extreme returns. Low levels of trading activity generally have no information content about future returns. Conversely, extreme returns precede high levels of volume only in the case of WTI.

In the second paper in the issue, “Dynamics of biofuel prices on the European market: impact of the EU environmental policy on the resources market”, Francis Declerck, Jean-Pierre Indjehagopian and Frédéric Lantz seek to explain the major drivers of biodiesel market prices by examining agricultural resource prices and gasoil prices for automotive fuels in the context of the environmental policy of the European Union (EU). The EU’s policy has led to an increase in biofuel production since the early 2000s. Biodiesel prices are affected by the EU policy, as well as by rapeseed and oil prices, which have fluctuated a lot over the last decade. An econometric analysis was performed using monthly data from November 2006 to January 2016. However, with tests for structural breaks showing several changes in price behavior, this led to a regime-switching model that reveals two main regimes for the biodiesel price formation process. When oil prices are high, biodiesel, rapeseed and diesel oil prices are functionally interrelated, but in the alternative regime when oil prices are low, biodiesel prices are mostly related to rapeseed prices.

Moving on from price formation dynamics to price risk management, in “Oil value-at-risk forecasts: a filtered semiparametric approach”, our third and final paper, Wei Kuang proposes the generalized autoregressive conditional heteroscedasticity (GARCH) model combined with the Cornish–Fisher expansion in a semiparametric approach for oil price value-at-risk (VaR) forecasts. This is designed to address skewness and excess kurtosis in addition to volatility dynamics. Kuang compares the performance of the proposed approach with historical simulation (HS) and the GARCHtype models using various innovation distributions: empirical, normal, skewed Student and generalized Pareto. The analysis covers 2012–20 for Brent and WTI, each with a total of 2001 observations. Kuang finds that the HS approach significantly underestimates the risks for both long and short positions over the recent turbulent market periods. This observation reinforces the importance of the filtering process in VaR forecasts. Overall, the proposed approach provides the most accurate VaR forecasts, especially at the high confidence levels for the long positions. In conclusion, this analysis serves as a useful guide to practitioners and policy makers for oil market risk management.

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