• Energy Research

Abstract We study the effect that shocks to oil and stock prices have over the returns of the largest oil firms listed at the New York Stock Exchange. We found evidence of asymmetric effects, conditioning on a given quantile of the oil companies’ stock return distributions. That is, both, shocks to the stock market and to crude oil prices, induce effects of opposite signs on the lower and upper quantiles of the returns of oil firms, and they tend to be non-significant on the median of the daily return distributions. We also document asymmetries among the reactions of oil companies’ prices to the two shocks, which are more pronounced and last longer in the case of the stock market, compared to crude oil. Overall we provide evidence in favor of economically and statically significant risk spillovers, from oil and stock markets to energy firms, which last typically between one a three days.

Abstract A nonlinear factor model based on fundamental weather variables, in addition to market-related variables, is proposed for modeling the price of electricity. The full conditional distribution of electricity prices using quantile regressions is modeled and the effect of weather factors on upside and downside risks in the electricity market is analyzed. Data from the Nord Pool is used to fit the proposed model to a wide and highly integrated market, as well as several individual national markets, and to search for possible asymmetries in both individual and aggregated levels of the price dynamics. By doing so, important differences across countries and quantiles in the price responses to weather variations are documented, but mostly extensive evidence in favor of the quantile-factor model based on weather variables is provided.

The environmental effects generated by the energy sector worldwide have become increasingly evident, raising the concerns of governments, industries and the research sector for addressing this problem. In the search for alternatives, hydrogen technology has drawn attention for its benefits as a new energy vector, since it is highly efficient and clean, and has multiple sources of generation. In Colombia, the possible generation of this energy vector from coal gasification has been estimated, since coal is a resource that is abundant in the territory. However, as a technology that uses a fossil resource, an analysis of the environmental effects of its implementation is necessary. The present work uses a system dynamics model to analyse the carbon dioxide (CO2) emissions that would be generated in this process in the national context. Through simulation scenarios, a comparative analysis is carried out of the effects of the current use of coal within the energy matrix versus the use of this resource for hydrogen generation in the medium and long term. The results indicate that the implementation of this technology accompanied by a minimum CO2 capture process would represent a reduction in the total emissions of the energy matrix.

L'évaluation des projets d'investissement a été réalisée principalement grâce à l'analyse des flux de trésorerie actualisés (DCF), dont les mesures de faisabilité financière ont été fondamentalement fondées sur des approches telles que la valeur actuelle nette (NPV) et le taux de rendement interne (IRR), qui sont largement discutées dans le domaine de l'évaluation des projets énergétiques. Despite this, the classical methods have a limitation when perceiving relevant characteristics for decision-making in high-risk investments, such as the uncertainty of the cash flows and the quantification of risk. An alternative to the use of these methods is the technique known as Decoupled Net Present Value (DNPV), which decouples the risk associated with the project from the value of money over time. Cette méthodologie d'évaluation a été appliquée à un projet d'auto-génération d'énergie solaire photovoltaïque en Colombie. Dans cette étude, les résultats obtenus grâce au DNPV ont été équivalents à 2.3-fold the value obtained by means of NPV. Thus, many renewable energy projects can become undervalued since traditional methods mistakenly associated a discount rate that includes a very high risk premium and that in many occasions it is more related to the sources of financing of the project instead of representing the risk component that it has. Keywords : Decoupled net present value (DNPV), Renewable energy projects, Solar energy investments JEL Classifications : Q2, Q4 DOI : https://doi.org/10.32479/ijeep.10577 The evaluation of investment projects has been carried out mainly through the analysis of Discounted Cash Flow (DCF), whose financial feasibility measures have been based fundamentally on approaches such as the Net Present Value (NPV) and the Internal Rate of Return (IRR), which are widely discussed in the field of energy project valuation. Despite this, the classical methods have a limitation when perceiving relevant characteristics for decision-making in high-risk investments, such as the uncertainty of the cash flows and the quantification of risk. An alternative to the use of these methods is the technique known as Decoupled Net Present Value (DNPV), which decouples the risk associated with the project from the value of money over time. This valuation methodology was applied to a photovoltaic solar energy self-generation project in Colombia. In this study, the results obtained through the DNPV were equivalent to 2.3-fold the value obtained by means of NPV. Thus, many renewable energy projects can become undervalued since traditional methods mistakenly associated a discount rate that includes a very high risk premium and that in many occasions it is more related to the sources of financing of the project instead of representing the risk component that it has. Keywords: Decoupled net present value (DNPV), Renewable energy projects, Solar energy investments JEL Classifications: Q2, Q4 DOI: https://doi.org/10.32479/ijeep.10577 The evaluation of investment projects has been carried out mainly through the analysis of Discounted Cash Flow (DCF), whose financial feasibility measures have been based fundamentally on approaches such as the Net Present Value (NPV) and the Internal Rate of Return (IRR), which are widely discussed in the field of energy project valuation. Despite this, the classical methods have a limitation when perceiving relevant characteristics for decision-making in high-risk investments, such as the uncertainty of the cash flows and the quantification of risk. An alternative to the use of these methods is the technique known as Decoupled Net Present Value (DNPV), which decouples the risk associated with the project from the value of money over time. This valuation methodology was applied to a photovoltaic solar energy self-generation project in Colombia. In this study, the results obtained through the DNPV was equivalent to 2.3-fold the value obtained by means of NPV. Thus, many renewable energy projects can become undervalued since traditional methods mistakenly associated a discount rate that includes a very high risk premium and that in many occasions it is more related to the sources of financing of the project instead of representing the risk component that it has. Keywords: Decoupled net present value (DNPV), Renewable energy projects, Solar energy investments JEL Classifications: Q2, Q4 DOI: https://doi.org/10.32479/ijeep.10577 The evaluation of investment projects has been carried out mainly through the analysis of Discounted Cash Flow (DCF), whose financial feasibility measures have been based fundamentally on approaches such as the Net Present Value (NPV) and the Internal Rate of Return (IRR), which are widely discussed in the field of energy project valuation. Despite this, the classical methods have a limitation when perceiving relevant characteristics for decision-making in high-risk investments, such as the uncertainty of the cash flows and the quantification of risk. An alternative to the use of these methods is the technique known as Decoupled Net Present Value (DNPV), which decouples the risk associated with the project from the value of money over time. This valuation methodology was applied to a photovoltaic solar energy self-generation project in Colombia. In this study, the results obtained through the DNPV was equivalent to 2.3-fold the value obtained by means of NPV. Thus, many renewable energy projects can become undervalued since traditional methods mistakenly associated a discount rate that includes a muy high risk premium and that in many occasions it is more related to the sources of financing of the project instead of representing the risk component that it has. Keywords: Decoupled net present value (DNPV), Renewable energy projects, Solar energy investments JEL Classifications: Q2, Q4 DOI: https://doi.org/10.32479/ijeep.10577 تم تقييم المشاريع الاستثمارية بشكل أساسي من خلال تحليل التدفقات النقدية المخصومة، والتي استندت تدابير جدواها المالية بشكل أساسي إلى مناهج مثل صافي القيمة الحالية ومعدل العائد الداخلي، والتي تمت مناقشتها على نطاق واسع في مجال تقييم مشاريع الطاقة. على الرغم من ذلك، فإن الطرق الكلاسيكية لها قيود عند إدراك الخصائص ذات الصلة لصنع القرار في الاستثمارات عالية المخاطر، مثل عدم اليقين في التدفقات النقدية وتحديد كمية المخاطر. بديل لاستخدام هذه الأساليب هو التقنية المعروفة باسم صافي القيمة الحالية المنفصلة (DNPV)، والتي تفصل المخاطر المرتبطة بالمشروع عن قيمة المال بمرور الوقت. تم تطبيق منهجية التقييم هذه على مشروع التوليد الذاتي للطاقة الشمسية الكهروضوئية في كولومبيا. في هذه الدراسة، كانت النتائج التي تم الحصول عليها من خلال صافي القيمة الحالية تعادل 2.3 ضعف القيمة التي تم الحصول عليها عن طريق صافي القيمة الحالية. وبالتالي، يمكن أن تصبح العديد من مشاريع الطاقة المتجددة مقومة بأقل من قيمتها لأن الطرق التقليدية ربطت عن طريق الخطأ معدل خصم يتضمن علاوة مخاطر عالية جدًا وأنه في كثير من الأحيان يكون أكثر ارتباطًا بمصادر تمويل المشروع بدلاً من تمثيل عنصر المخاطر الذي يحتوي عليه. الكلمات المفتاحية: صافي القيمة الحالية المنفصلة (DNPV)، مشاريع الطاقة المتجددة، استثمارات الطاقة الشمسية تصنيفات JEL: Q2، Q4 DOI: https://doi.org/10.32479/ijeep.10577

Purpose This study aims to assess volatility spillovers and directional connectedness between electricity (EPs) and natural gas prices (GPs) in the Canadian electricity market, based on a hydrothermal power generation market strongly dependent on exogenous variables such as fossil fuel prices and climatology factors. Design/methodology/approach The methodology is divided into two stages. First, a quantile vector autoregression model is used to evaluate the direction and magnitude of the influence between natural gas and electricity prices through different quantiles of their distributions. Second, a cross-quantilogram is estimated to measure the directional predictability between these prices. The data set consists of daily electricity and natural gas prices between January 2015 and December 2023. Findings The main finding shows that electricity prices are pure shock receivers of volatility from natural gas prices for the different quantiles. In this way, natural gas price fluctuations explain 0.20%, 0.98% and 22.72% of electricity price volatility for the 10th, 50th and 90th quantiles, respectively. On the other hand, a significant and positive correlation is observed in the high quantiles of the electricity prices for any natural gas price value. Originality/value The study described the risk to the electricity market caused by nonrenewable source price fluctuations and provided evidence for designing regulatory policies to reduce its exposure in Alberta, Canada. It also allows us to understand the importance of natural gas in the energy transition process and define it as the fundamental determinant of the electricity market dynamic.

The extent to which external factors explain profitability in the energy sector and their commonalities is largely unknown from the previous literature. We identify three latent factors underlying the profitability of 1,347 global energy firms, from 2000 Q1 to 2021 Q2. We rely on a novel Dynamic Factor Model estimated by Functional Principal Components. Profitability factors are strongly associated with global financial and macroeconomic factors, including energy commodity prices, interest rates, exchange rates, economic activity and financial uncertainty. We compare our empirical results for various energy subsectors and show that profitability of oil and gas companies is highly sensitive to changes in interest rates and fuel prices, while renewable energy and uranium firms are more sensitive to exchange rates. We also provide a ranking of firms based on their association with the common factors of profitability, which can be used to monitor the resilience of the energy sector. JEL Classification: Q43, O16, G32

Abstract Accurate decisions regarding exposure to and hedging against market risk, both of which are crucial for electricity producers and consumers, depend on a correct assessment of electricity price dynamics. This paper proposes a comprehensive empirical methodology to model price variations in electricity markets based on hydrothermal power generation. This proposal combines advances in time-series econometrics related to regime modeling, conditional heteroskedasticity, and extreme events. The study considers stylized facts of the series describing electricity prices, which are especially relevant for accurate risk pricing. More importantly, the proposed methodology enables the description and characterization of asymmetries at almost every level: intraday patterns, seasonal components, spikes, volatility regimes and extreme values; and the estimation of the effects of such asymmetries on traditional risk measures, such as VaR and CVaR. Different tail behaviors of positive and negative electricity returns are documented, which are relevant for assessing the risks of selling and buying strategies. In addition, asymmetries in risk that are conditional on the time at which the transaction occurs are found.

COVID-19 disease shocked global economic activity and affected the electricity markets due to lockdown and work-from-home policies. Therefore, this study proposes an empirical analysis to identify the electricity spot price response during the preventive and mandatory insulation in Colombia, where the economic contraction caused the largest decrease in the electricity demand, especially in the industrial sector. The methodology applied was quantile regression to quantify the non-linear effect on the spot price returns, and two sample periods were selected to contrast the results: 2018 and 2019. The main findings showed that regulated demand variation caused the highest variability on the spot price dynamic during the strict quarantine. However, the price could not fully capture the effects of the demand change due to the short duration of the shock and, also, the price variability in 2019 was higher than 2020 by an El Niño shock.

Abstract Background Research on portfolio optimization for energy generation often does so from a financial perspective. This study addressed a unique challenge: determining which companies, amidst a globalized electricity market, should be retained for climate risk preservation during specialization. Utilizing weather and generation data from 106 power plants across Argentina, we adapted integer-portfolio-optimization tools. Originally designed for financial index funds, these tools helped us construct a portfolio of power plants for a resilient energy mix. Results Our findings revealed optimal companies for retention by analyzing different portfolio configurations, where the number of plants was adjusted iteratively. In each iteration of the model, we selected a set of representative plants that minimize climate risk, which sometimes resulted in a plant being included in one portfolio but not another. This approach identified the specific companies and technologies essential for a diversified and climate-resilient energy portfolio while ensuring a strategic transition toward specialization and stabilizing generation risk in the face of variable weather conditions. Conclusions This paper presents a groundbreaking solution for specialization in a globalized energy market. Through portfolio optimization, we identified pivotal companies for each stage of the transition in Argentina. Firms like Parque Eólico La Genoveva and Complejo Hidroeléctrico Centrales Cacheuta Alvarez Condarco, showcased the balance needed for wind and hydroelectric sources. These insights should be used to guide policymakers to ensure a controlled and effective transition while maintaining stable generation risk.