Journal of Energy Markets

Kostas Andriosopoulos
Alba Graduate Business School

With 2026 drawing to a close, it is an opportune moment to reflect on a year marked by significant changes in the global energy landscape, from geopolitical developments to progressively reaching decarbonization goals. The complexity of contemporary energy markets – exemplified by continued integration of stochastic renewable energy sources, growing demand for system flexibility, evolving market structures and accelerating technological innovation – highlights the need for increasingly sophisticated analytical tools capable of modeling complex market dynamics, assessing asset value and managing risk under conditions of increasing uncertainty.

Modern energy systems are shaped by the complex interaction of multiple factors, ranging from the predictive capabilities of high-dimensional data and artificial intelligence to the physical and economic constraints of renewable energy integration and the operational complexities of real-time trading. Addressing these interrelated challenges requires quantitative approaches that integrate multisource data analytics, fundamental engineering principles and realistic representations of market microstructure. The studies featured in this issue of The Journal of Energy Markets contribute to this ongoing development by presenting novel methodological approaches to price forecasting, photovoltaic infrastructure economics and energy storage asset optimization under real-world liquidity constraints.

The issue’s first paper, “Photovoltaic cell and module efficiency as drivers of innovation in photovoltaic technology” by Vítězslav Benda and Ladislava Černá, examines the physical principles, key technological processes and economic implications associated with the efficiency of crystalline silicon solar cells and modules. In this study, different technological and design approaches are assessed, and the authors discuss the maturity of crystalline silicon photovoltaic technology and the limits of its fundamental physical efficiency. The individual design solutions presented can reduce area-dependent investment costs; however, the associated technological advancements could also increase manufacturing costs, thereby diminishing the marginal economic benefits of further efficiency improvements. Beyond direct economic implications, Benda and Černá suggest that higher-efficiency modules are an important indicator of manufacturing quality and technological competitiveness.

In our second paper, “Battery valuation on electricity intraday markets with liquidity costs”, Enzo Cognéville, Thomas Deschatre and XavierWarin develop a comprehensive modeling framework for the valuation of energy storage assets participating in intraday electricity markets. Their proposed framework combines a multifactor stochastic jump model for 24 hourly midprices with a deterministic liquidity cost model designed to capture the associated costs of executing larger transactions at different levels of the order book. Based on backtesting using 2021–3 data from the French and German electricity markets, the authors demonstrate that incorporating liquidity costs is essential for obtaining realistic estimates of battery trading performance. This becomes particularly relevant when optimizing the operation of largescale battery fleets, as liquidity constraints can materially affect trading profitability and expose strategies that disregard market depth to substantial financial losses. The findings therefore highlight the importance of explicitly accounting for market liquidity in the valuation and operational optimization of storage assets. The stochastic model for the midprice also provides better results than a deterministic framework where the midprice forecast is the spot price.

Finally, “Oil price prediction with NBEATSx using oil news embeddings and S&P 500 prices” by Sara Bourbour and MohammadAmin Mohajelin, the issue’s third paper, investigates the predictive performance of the neural basis expansion analysis with exogenous variables (NBEATSx) framework for oil prices, incorporating oil-related news outlets and Standard & Poor’s 500 index prices as the exogenous variables. By extracting information from oil-related news and integrating it with financial market indicators, the authors demonstrate that these additional sources of information significantly improve forecasting performance compared with conventional approaches. The paper provides an extensive review of existing forecasting models, classified into time series, regression, artificial neural networks, support vector machines, decision trees and hybrid decomposition-ensemble approaches. The authors’ proposed methodology achieves greater predictive accuracy than alternative models, highlighting the potential of combining textual representations of market information with equity market indicators capturing evolving economic conditions and underlying market dynamics. Finally, the study highlights the value of integrating unstructured information into quantitative forecasting frameworks for commodity markets, with implications for both financial decision-making and energy policy analysis.

Collectively, these studies illustrate the growing importance of integrating quantitative forecasting methodologies, physical and engineering constraints, and market microstructure considerations into the analysis of contemporary energy markets. By demonstrating the contribution of news-based textual embeddings to commodity price forecasting, examining the economic trade-offs associated with photovoltaic efficiency improvements, and explicitly incorporating order-book liquidity constraints into battery valuation and trading optimization, this issue advances the methodological understanding of several critical dimensions of energy market dynamics.

As we conclude another year of research and developments in the energy sector, The Journal of Energy Markets remains committed to disseminating rigorous quantitative research that advances asset valuation methodologies, risk management practices and evidence-based decision-making in increasingly complex and rapidly evolving energy markets. The editorial board and I extend our warmest wishes to our readers, contributors and collaborators for a joyful holiday season and a prosperous 2027, and we look forward to another year of insightful research and meaningful contributions to the field.