Derek W. Bunn
London Business School
The three papers in this issue demonstrate the important business implications of advanced analysis and modeling. They cover the topics of asset returns from energy funds, the impact of carbon emission pricing, and the valuation of power purchase agreements (PPAs) for renewable asset offtakes.
In the issue’s first paper, “Evaluating the performance of energy exchange-traded funds”, D. K. Malhotra and Michael Marino find that the average monthly returns of energy exchange-traded funds (EETFs) have relatively high correlation with global equities and US equities. Absolute performance, as assessed by average monthly returns, showed that EETFs outperformed both US equities and global markets between 2000 and 2022. In terms of risk-adjusted performance, EETFs slightly outperformed the S&P Energy index, US equities and global equities. These funds can provide positive returns for investors during times of economic turmoil, as evidenced by the positive net alphas seen during the 2007–9 global financial crisis. The lockdowns induced by the Covid-19 pandemic had a significant impact on the energy sector, leading to poor performance for both EETFs and the S&P Energy index, but these markets have since rebounded and are now outperforming traditional stock markets.
The second paper in the issue, “Throwing green into the mix: how the EU Emissions Trading System impacted the energy mix of French manufacturing firms from 2000 to 2016” by Rayan Chebbi-Giovanetti, reveals that public policies that aim to reduce carbon emissions have acted as a constraint on production decisions. Although most empirical analyses have shown that environmental policies reduce carbon emissions, the sources of these reductions have been less transparent. This paper uses a difference-in-differences model to show how the implementation of the first three phases of the European carbon market (that is, the European Union Emissions Trading System (EU ETS)) influenced the probability of firms using less carbon-intensive energy inputs. It uses French microdata on manufacturing firms, particularly information on energy usage, carbon emissions and assignment to treatment. The results show that when considering the energy mix, firms that were subject to the European carbon market tended to use more carbon-neutral energy inputs, with specific magnitudes, during the first three EU ETS phases.
In “A two-stage nonlinear approach for modeling hourly spot power prices with an application to spot market risk valuation of the power yield of a solar array in Germany”, the final paper in this issue, Peter Kosater extends an existing Markov regime-switching model approach for power spot prices by combining it with a seasonal autoregressive moving average model that allows for intraday and weekly seasonalities. This approach also combines top-down models for wind power, solar power and power load with a bottom-up model for the hourly power yield of a solar panel, simulating hourly price and solar panel power yield paths in order to estimate the spot market risk of a small hypothetical solar array in the context of a PPA. Spot market risk arises because neither the volume nor the exact power spot prices are known when PPAs are contracted. PPAs allow the risk transfer from renewable plant operators to market participants, who are more skilled in trading and risk management.
The authors investigate the performance of energy exchange-traded funds between January 2000 and August 2022, finding a relatively high degree of correlation with the performance of US and global equities.
Throwing green into the mix: how the EU Emissions Trading System impacted the energy mix of French manufacturing firms (2000–16)
This paper investigates links between environmental policy and production decisions, with a focus on firms' energy mixes.
A two-stage nonlinear approach for modeling hourly spot power prices with an application to spot market risk valuation of the power yield of a solar array in Germany
This paper combines a seasonal autoregressive moving average model with a Markov regime-switching model approach for power spot prices, allowing intraday and weekly seasonalities to be incorporated.