Journal of Energy Markets

All four papers in this issue of The Journal of Energy Markets reveal the extra insights that careful and advanced modeling can bring to our knowledge of price formation in energy markets. We show how new analyses can challenge conventional thinking about forward premiums, and discuss the impact of wind generation forecast errors on intraday prices. We also demonstrate the value of detailed fundamental modeling for medium- and longer-term price formation as well as the impact of estimating structural changes on stock and energy market correlations and volatility. In addition, a wide range of international markets is covered, including the Nordics, Alberta, Texas and Qatar.

In the first paper, "The Nordic futures market for power: finally mature and efficient?" by Erik Smith-Meyer and Ole Gjolberg, the authors analyze whether this market can now be considered mature and efficient. By comparing futures with their actual spot prices, many studies have documented a bias, which is often characterized as a persistent risk premium in a market dominated by long hedgers. However, in several studies this bias has alternatively been regarded as evidence of the market being immature and inefficient. Using data from 2003 to 2015, the authors test for shifts in the risk premium. They also model simulated investments in which traders persistently short nearby futures and maintain this position through expiration. They observe that, after 2008, Nordic short-term power futures became unbiased and may have matured to be at least weak-form efficient. In addition, Smith-Meyer and Gjolberg speculate that the physical integration of the Nordic and Dutch markets through the opening of the NorNed cable in 2008 may have been a contributory factor.

"Zonal merit-order effects of wind generation development on day-ahead and realtime electricity market prices in Texas" by Jay Zarnikau, Chi-Keung Woo and Shuangshuang Zhu, the second paper in this issue, uses a regression-based approach to explore the impact of wind generation development on wholesale electricity prices in the Electric Reliability Council of Texas (ERCOT) market. The authors find that wind generation development has a greater effect on real-time market (RTM) prices than day-ahead market (DAM) prices. Higher wind generation forecast errors tend to reduce RTM prices, chiefly because unanticipated increases in wind generation reduce the real-time net loads to be served by fossil fuel power plants. Improving ERCOT's load and wind generation forecast accuracy helps the convergence, and hence the trading efficiency, of DAM and RTM prices.

Our third paper looks at the Alberta electricity market, with a focus on the medium and longer term. In "Modeling Alberta power prices through fundamentals", Elham Negahdary and Antony Frank Ware identify the primary price drivers in this market and characterize their dynamics in an engineering-based, bottom-up model subject to operational constraints. Exogenous variables such as fuel prices, outages and load are represented as stochastic processes. The simulated interactions of different factors produce a distribution of prices, which can potentially be used for various trading, risk management, operational and investment decisions.

In contrast to the research focus of the previous three papers, Tarek Chebbi and Abdelkader Derbali provide a technical report: "On the role of structural breaks in identifying the dynamic conditional linkages between stock and commodity markets". While several researchers have looked at Islamic financial market indexes and energy commodities, the influence of shocks may be a crucial factor that has been overlooked until now. This paper tests the dynamic conditional correlation (DCC) between the Qatar Exchange Al Rayan Islamic Index and two energy commodities (crude oil and natural gas). The authors achieve this by including structural breaks in the DCC-generalized autoregressive conditional heteroscedasticity (GARCH) model over the period 2011-14. They find that the volatility of commodity returns is strongly correlated to that of the Al Rayan Islamic Index. They also discover that estimates of the volatility persistence decrease after incorporating structural breaks. Interesting implications emerge from this paper for both policy makers and portfolio risk managers.

Derek W. Bunn
London Business School

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