Pub Date : 2025-08-22DOI: 10.1016/j.jcomm.2025.100502
Stefano Grassi , Francesco Ravazzolo , Joaquin Vespignani , Giorgio Vocalelli
This paper shows that the impact of the global money supply is disproportionally higher for energy than for non-energy commodities prices. An increase in the global money supply for energy commodity prices results mainly in demand-pull inflation, while, for non-energy commodity prices, an increase in global money supply leads to demand-pull and cost-push inflation, as energy is a key input for non-energy commodities. To quantify this effect, we use a Markov switching model with time-varying transition probabilities. This model considers periods of slow, moderate, and fast global money supply growth. We find that the response to global money supply shocks is almost double for energy than for non-energy commodity prices. We also find heterogeneous responses for energy and non-energy commodities under different regimes.
{"title":"Global money supply and energy and non-energy commodity prices: A MS-TV-VAR approach","authors":"Stefano Grassi , Francesco Ravazzolo , Joaquin Vespignani , Giorgio Vocalelli","doi":"10.1016/j.jcomm.2025.100502","DOIUrl":"10.1016/j.jcomm.2025.100502","url":null,"abstract":"<div><div>This paper shows that the impact of the global money supply is disproportionally higher for energy than for non-energy commodities prices. An increase in the global money supply for energy commodity prices results mainly in demand-pull inflation, while, for non-energy commodity prices, an increase in global money supply leads to demand-pull and cost-push inflation, as energy is a key input for non-energy commodities. To quantify this effect, we use a Markov switching model with time-varying transition probabilities. This model considers periods of slow, moderate, and fast global money supply growth. We find that the response to global money supply shocks is almost double for energy than for non-energy commodity prices. We also find heterogeneous responses for energy and non-energy commodities under different regimes.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100502"},"PeriodicalIF":4.5,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-14DOI: 10.1016/j.jcomm.2025.100501
Bartosz Uniejewski
Accurate short-term price forecasting is essential for daily operations in electricity markets. This article introduces a new method, called Smoothing Quantile Regression (SQR) Averaging, that improves upon well-performing probabilistic forecasting schemes. To demonstrate its utility, a comprehensive study is conducted on two electricity markets, including recent data covering the COVID-19 pandemic and the Russian invasion of Ukraine. The performance of SQR Averaging is evaluated both in terms of reliability and sharpness measures, and economic benefits from a trading strategy. The latter utilizes battery storage and sets limit orders using selected quantiles of the predictive distribution. SQR Averaging leads to profit increases compared to the benchmark strategy based solely on point forecasts. This is strong evidence for the practical value of using probabilistic forecasts in day-ahead power trading, even in the face of the COVID-19 pandemic and geopolitical disruptions.
{"title":"Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices","authors":"Bartosz Uniejewski","doi":"10.1016/j.jcomm.2025.100501","DOIUrl":"10.1016/j.jcomm.2025.100501","url":null,"abstract":"<div><div>Accurate short-term price forecasting is essential for daily operations in electricity markets. This article introduces a new method, called Smoothing Quantile Regression (SQR) Averaging, that improves upon well-performing probabilistic forecasting schemes. To demonstrate its utility, a comprehensive study is conducted on two electricity markets, including recent data covering the COVID-19 pandemic and the Russian invasion of Ukraine. The performance of SQR Averaging is evaluated both in terms of reliability and sharpness measures, and economic benefits from a trading strategy. The latter utilizes battery storage and sets limit orders using selected quantiles of the predictive distribution. SQR Averaging leads to profit increases compared to the benchmark strategy based solely on point forecasts. This is strong evidence for the practical value of using probabilistic forecasts in day-ahead power trading, even in the face of the COVID-19 pandemic and geopolitical disruptions.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100501"},"PeriodicalIF":4.5,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144866734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-09DOI: 10.1016/j.jcomm.2025.100503
Marie Steen, Sjur Westgaard, Ole Gjolberg
This paper evaluates the effectiveness of seven hedging strategies for reducing price risk in the U.S. grain market. The strategies are ranging from a naïve “one-for-one” hedge to advanced econometric models such as Error Correction Models and GARCH, allowing for time-varying volatility. Using monthly data for corn, wheat, and soybeans 1982–2024 for conducting out-of-sample evaluations 1997–2024, we assess whether complex models provide meaningful advantages over simpler approaches. We find that while all strategies substantially reduce risk, simpler models perform comparably to more sophisticated ones in terms of standard deviation, Value-at-Risk, and Expected Shortfall. The results remain robust to different sub-samples and estimation windows.
{"title":"Hedging grain price risk. Keep it simple! Econometric evidence from the grain markets, 1982–2024","authors":"Marie Steen, Sjur Westgaard, Ole Gjolberg","doi":"10.1016/j.jcomm.2025.100503","DOIUrl":"10.1016/j.jcomm.2025.100503","url":null,"abstract":"<div><div>This paper evaluates the effectiveness of seven hedging strategies for reducing price risk in the U.S. grain market. The strategies are ranging from a naïve “one-for-one” hedge to advanced econometric models such as Error Correction Models and GARCH, allowing for time-varying volatility. Using monthly data for corn, wheat, and soybeans 1982–2024 for conducting out-of-sample evaluations 1997–2024, we assess whether complex models provide meaningful advantages over simpler approaches. We find that while all strategies substantially reduce risk, simpler models perform comparably to more sophisticated ones in terms of standard deviation, Value-at-Risk, and Expected Shortfall. The results remain robust to different sub-samples and estimation windows.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100503"},"PeriodicalIF":4.5,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-05DOI: 10.1016/j.jcomm.2025.100498
Merve Olmez Turan , Ben Gilbert , Tulay Flamand
We estimate the price elasticity of residential natural gas demand for 23 European Union (EU) countries using monthly data from 2011 to 2022. While neighboring countries’ weather shocks can in theory act as a supply shifter to identify demand, it is unclear which subset of neighbors in practice should be used, if any. To address this issue, we compare four traditional instrumental variables (IV) models to several post-LASSO approaches: post-LASSO Ordinary Least Squares (OLS), post-LASSO IV, and two-stage post-LASSO IV. We compare these models on a country-by-country basis and for the full panel. We find that the third traditional IV model that we examined performs best in most cases for individual countries. In addition, we find that the first traditional IV model has the most reliable results at the panel-level. Our preferred estimates suggest that country-level price elasticities range from to , with a median of , in line with estimates from the previous literature. We find that residential natural gas price elasticities vary widely across Europe, with Hungary, Germany, France, and Lithuania being the most elastic, and Estonia and Portugal the least. However, Gross Domestic Product (GDP) trends during the energy crisis do not align perfectly with elasticity patterns, highlighting the need for caution in linking demand elasticities directly to economic outcomes. Broader macroeconomic factors also play a significant role in shaping national responses to the crisis.
{"title":"How good are weather shocks for identifying energy elasticities? A LASSO-IV approach to European natural gas demand","authors":"Merve Olmez Turan , Ben Gilbert , Tulay Flamand","doi":"10.1016/j.jcomm.2025.100498","DOIUrl":"10.1016/j.jcomm.2025.100498","url":null,"abstract":"<div><div>We estimate the price elasticity of residential natural gas demand for 23 European Union (EU) countries using monthly data from 2011 to 2022. While neighboring countries’ weather shocks can in theory act as a supply shifter to identify demand, it is unclear which subset of neighbors in practice should be used, if any. To address this issue, we compare four traditional instrumental variables (IV) models to several post-LASSO approaches: post-LASSO Ordinary Least Squares (OLS), post-LASSO IV, and two-stage post-LASSO IV. We compare these models on a country-by-country basis and for the full panel. We find that the third traditional IV model that we examined performs best in most cases for individual countries. In addition, we find that the first traditional IV model has the most reliable results at the panel-level. Our preferred estimates suggest that country-level price elasticities range from <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>61</mn></mrow></math></span> to <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>01</mn></mrow></math></span>, with a median of <span><math><mrow><mo>−</mo><mn>0</mn><mo>.</mo><mn>13</mn></mrow></math></span>, in line with estimates from the previous literature. We find that residential natural gas price elasticities vary widely across Europe, with Hungary, Germany, France, and Lithuania being the most elastic, and Estonia and Portugal the least. However, Gross Domestic Product (GDP) trends during the energy crisis do not align perfectly with elasticity patterns, highlighting the need for caution in linking demand elasticities directly to economic outcomes. Broader macroeconomic factors also play a significant role in shaping national responses to the crisis.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100498"},"PeriodicalIF":4.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144860639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-31DOI: 10.1016/j.jcomm.2025.100496
Martina Danielova Zaharieva, Audronė Virbickaitė, André Portela Santos
We specify a volatility transmission model for international energy markets that divides a global trading day into three distinct trading zones, allowing us to investigate the heat wave and meteor shower hypotheses proposed in Engle et al. (1990). The resulting multivariate GARCH model is specified using a highly flexible semiparametric Bayesian framework with non-Gaussian innovations, designed to deal with asymmetry and heavy tails found in financial time series. The empirical results for the oil and natural gas futures markets suggest that volatility transmission is a combination of effects that are both related to volatility in the same region and volatility in the region immediately preceding it. Furthermore, accounting for the fat-tailed behavior not only dramatically improves the in-sample fit, but also helps to uncover additional cross-market (or cross-country) effects and gives us further insights into the exact channels through which energy shocks are transmitted throughout the world. Finally, accounting for both heat wave and meteor shower effects within a non-Gaussian framework leads to substantial improvements in the accuracy of Value-at-Risk estimates.
{"title":"Intraday volatility transmission in global energy markets: A Bayesian nonparametric approach","authors":"Martina Danielova Zaharieva, Audronė Virbickaitė, André Portela Santos","doi":"10.1016/j.jcomm.2025.100496","DOIUrl":"10.1016/j.jcomm.2025.100496","url":null,"abstract":"<div><div>We specify a volatility transmission model for international energy markets that divides a global trading day into three distinct trading zones, allowing us to investigate the <em>heat wave</em> and <em>meteor shower</em> hypotheses proposed in Engle et al. (1990). The resulting multivariate GARCH model is specified using a highly flexible semiparametric Bayesian framework with non-Gaussian innovations, designed to deal with asymmetry and heavy tails found in financial time series. The empirical results for the oil and natural gas futures markets suggest that volatility transmission is a combination of effects that are both related to volatility in the same region and volatility in the region immediately preceding it. Furthermore, accounting for the fat-tailed behavior not only dramatically improves the in-sample fit, but also helps to uncover additional cross-market (or cross-country) effects and gives us further insights into the exact channels through which energy shocks are transmitted throughout the world. Finally, accounting for both heat wave and meteor shower effects within a non-Gaussian framework leads to substantial improvements in the accuracy of Value-at-Risk estimates.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100496"},"PeriodicalIF":4.5,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-30DOI: 10.1016/j.jcomm.2025.100500
Mengjiao Wang , Jianxu Liu
This study examines the systemic risk spillovers from gold and crude oil to six major emerging market currencies, with particular attention to the role of U.S. dollar (USD) strength in shaping these risk transmission mechanisms. We develop a multi-to-one Conditional Value-at-Risk (MCoVaR) analysis framework, extending the traditional CoVaR methodology by using time-varying canonical vine copulas to capture the dependence structures among gold, oil, and emerging market currencies. Our findings first reveal positive pairwise dependencies between gold, crude oil, and each currency, with heterogeneous dependence structures in how individual currencies relate to the two commodities. Crucially, the MCoVaR estimates confirm that emerging market currencies experience amplified risk spillovers during joint extreme shocks in gold and oil markets. Moreover, USD strength variation plays a crucial role in shaping commodity-to-currency systemic risk transmission by not only directly influencing the valuations of gold, oil, and emerging market currencies but also indirectly affecting the time-varying dependence between these assets. These findings highlight the importance of systemically accounting for joint commodity shocks in currency risk assessment, especially during periods of sustained USD strength with volatile commodity prices.
{"title":"Twin commodity shocks: A multi-to-one CoVaR analysis of systemic risk spillovers from gold and crude oil to emerging market currencies","authors":"Mengjiao Wang , Jianxu Liu","doi":"10.1016/j.jcomm.2025.100500","DOIUrl":"10.1016/j.jcomm.2025.100500","url":null,"abstract":"<div><div>This study examines the systemic risk spillovers from gold and crude oil to six major emerging market currencies, with particular attention to the role of U.S. dollar (USD) strength in shaping these risk transmission mechanisms. We develop a multi-to-one Conditional Value-at-Risk (MCoVaR) analysis framework, extending the traditional CoVaR methodology by using time-varying canonical vine copulas to capture the dependence structures among gold, oil, and emerging market currencies. Our findings first reveal positive pairwise dependencies between gold, crude oil, and each currency, with heterogeneous dependence structures in how individual currencies relate to the two commodities. Crucially, the MCoVaR estimates confirm that emerging market currencies experience amplified risk spillovers during joint extreme shocks in gold and oil markets. Moreover, USD strength variation plays a crucial role in shaping commodity-to-currency systemic risk transmission by not only directly influencing the valuations of gold, oil, and emerging market currencies but also indirectly affecting the time-varying dependence between these assets. These findings highlight the importance of systemically accounting for joint commodity shocks in currency risk assessment, especially during periods of sustained USD strength with volatile commodity prices.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100500"},"PeriodicalIF":4.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-19DOI: 10.1016/j.jcomm.2025.100497
Verena Hagspiel , Ådne Jonsbråten , Maxime Lesage , Filip Fremo Minge , Farida Mustafina
This study analyzes the impact of two principally different tax systems on potential investment decision-making in marine minerals projects, using the Norwegian Continental Shelf as a case study. The exploration phase of a project is modeled as a multistage decision process through which a company acquires information to reduce geological uncertainties about potential deposits. At different decision gates, the company decides whether it is optimal to continue exploration or abandon the deposits based on their expected economic viability. A dynamic valuation framework is used to evaluate the impact of potential tax systems on corporate decision-making concerning both the exploration of deposits and the project value resulting from the extraction of deposits. Specifically, a standard corporate tax system and variations of the Norwegian petroleum tax system are compared.
The findings suggest that a tax system similar to the Norwegian petroleum tax system, but with lower tax and refund rates, offers advantages for both companies and the states. Specifically, the petroleum tax system with a 30% total tax rate and a 25% refund rate yields the highest expected net present value for the company and reduces its exploration risks compared to the standard corporate tax system. While shifting parts of the exploration risks from the company to the state, the petroleum tax system with a 60% total tax rate and a 55% refund rate generates the highest net tax balance for the state. A trade-off tax system could be designed to share the risks inherent in mineral exploration and extraction, maintaining a balance between corporate and regulatory decision-makers by encouraging investment in the sector and ensuring sustainable economic benefits to the state.
{"title":"Assessing the impact of tax systems on investment incentives in future marine minerals projects on the Norwegian Continental Shelf","authors":"Verena Hagspiel , Ådne Jonsbråten , Maxime Lesage , Filip Fremo Minge , Farida Mustafina","doi":"10.1016/j.jcomm.2025.100497","DOIUrl":"10.1016/j.jcomm.2025.100497","url":null,"abstract":"<div><div>This study analyzes the impact of two principally different tax systems on potential investment decision-making in marine minerals projects, using the Norwegian Continental Shelf as a case study. The exploration phase of a project is modeled as a multistage decision process through which a company acquires information to reduce geological uncertainties about potential deposits. At different decision gates, the company decides whether it is optimal to continue exploration or abandon the deposits based on their expected economic viability. A dynamic valuation framework is used to evaluate the impact of potential tax systems on corporate decision-making concerning both the exploration of deposits and the project value resulting from the extraction of deposits. Specifically, a standard corporate tax system and variations of the Norwegian petroleum tax system are compared.</div><div>The findings suggest that a tax system similar to the Norwegian petroleum tax system, but with lower tax and refund rates, offers advantages for both companies and the states. Specifically, the petroleum tax system with a 30% total tax rate and a 25% refund rate yields the highest expected net present value for the company and reduces its exploration risks compared to the standard corporate tax system. While shifting parts of the exploration risks from the company to the state, the petroleum tax system with a 60% total tax rate and a 55% refund rate generates the highest net tax balance for the state. A trade-off tax system could be designed to share the risks inherent in mineral exploration and extraction, maintaining a balance between corporate and regulatory decision-makers by encouraging investment in the sector and ensuring sustainable economic benefits to the state.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100497"},"PeriodicalIF":4.5,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-11DOI: 10.1016/j.jcomm.2025.100495
Theodora Bermpei , Athanasios Triantafyllou
We empirically show the role of supply and demand shocks as drivers of short and long-run price uncertainty in the crude oil market. We first define oil price uncertainty as the purely unforecastable component of oil price fluctuations and show that uncertainty of the short-run oil price fluctuations is driven by oil supply shocks, while the uncertainty for medium and long-run forecast horizons is mainly caused by aggregate demand. While our findings on the impact of oil supply disruptions on oil price uncertainty are in line with the implications of the theory of storage, we do not find similar results for the medium and the long, whereby the global demand shocks are found to be the main driver for the increasing oil price uncertainty. Interestingly, we show that the recessionary effect of short and medium-horizon uncertainty shocks, we find that long-run oil price uncertainty shocks lead to expansions in global economic activity.
{"title":"Supply and Demand shocks: the short-term and long-term drivers of oil price uncertainty","authors":"Theodora Bermpei , Athanasios Triantafyllou","doi":"10.1016/j.jcomm.2025.100495","DOIUrl":"10.1016/j.jcomm.2025.100495","url":null,"abstract":"<div><div>We empirically show the role of supply and demand shocks as drivers of short and long-run price uncertainty in the crude oil market. We first define oil price uncertainty as the purely unforecastable component of oil price fluctuations and show that uncertainty of the short-run oil price fluctuations is driven by oil supply shocks, while the uncertainty for medium and long-run forecast horizons is mainly caused by aggregate demand. While our findings on the impact of oil supply disruptions on oil price uncertainty are in line with the implications of the theory of storage, we do not find similar results for the medium and the long, whereby the global demand shocks are found to be the main driver for the increasing oil price uncertainty. Interestingly, we show that the recessionary effect of short and medium-horizon uncertainty shocks, we find that long-run oil price uncertainty shocks lead to expansions in global economic activity.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100495"},"PeriodicalIF":3.7,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-07DOI: 10.1016/j.jcomm.2025.100494
Yulian Zhang , Shigeyuki Hamori
We employ a quantile time-frequency connectedness model to investigate the interdependencies among four asset groups: cryptocurrencies (Bitcoin, Ethereum, and BNB), stocks (S&P 500, Euro Stoxx 50, FTSE 100, and Nikkei 225), safe-haven assets (gold, the US dollar, and treasury bills), and energy markets (oil, gas, coal, and electricity), using daily data from November 2017 to November 2024 (1625 observations). Our results reveal that, under normal market conditions, markets are more affected by their own shocks than by cross-market spillovers. This indicates that investors should pay closer attention to endogenous risks during stable periods. Moreover, we find that diversification across different asset classes is more effective under normal conditions, while investing within the same group may be more appropriate during bullish or bearish market phases. Market uncertainty also tends to rise as conditions become more extreme. This study is the first to confirm quantile-based connectedness both within and across asset classes in the time-frequency domain. Our findings contribute to a deeper understanding of market interactions and offer practical insights for investment decisions, portfolio management, and regulatory policy in an increasingly interconnected global financial environment.
{"title":"Portfolio implications based on quantile connectedness among cryptocurrency, stock, energy, and safe-haven assets","authors":"Yulian Zhang , Shigeyuki Hamori","doi":"10.1016/j.jcomm.2025.100494","DOIUrl":"10.1016/j.jcomm.2025.100494","url":null,"abstract":"<div><div>We employ a quantile time-frequency connectedness model to investigate the interdependencies among four asset groups: cryptocurrencies (Bitcoin, Ethereum, and BNB), stocks (S&P 500, Euro Stoxx 50, FTSE 100, and Nikkei 225), safe-haven assets (gold, the US dollar, and treasury bills), and energy markets (oil, gas, coal, and electricity), using daily data from November 2017 to November 2024 (1625 observations). Our results reveal that, under normal market conditions, markets are more affected by their own shocks than by cross-market spillovers. This indicates that investors should pay closer attention to endogenous risks during stable periods. Moreover, we find that diversification across different asset classes is more effective under normal conditions, while investing within the same group may be more appropriate during bullish or bearish market phases. Market uncertainty also tends to rise as conditions become more extreme. This study is the first to confirm quantile-based connectedness both within and across asset classes in the time-frequency domain. Our findings contribute to a deeper understanding of market interactions and offer practical insights for investment decisions, portfolio management, and regulatory policy in an increasingly interconnected global financial environment.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100494"},"PeriodicalIF":3.7,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144595509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-05DOI: 10.1016/j.jcomm.2025.100493
James E. Payne , Saban Nazlioglu , Ahmet Koncak , Bradley T. Ewing
Investment in renewable energy production has been subject to swings in the U.S. policy stance on climate change creating uncertainty. Determining how and to what extent the renewable energy sector responds to climate policy uncertainty is relevant to understanding the energy transition from fossil fuels to renewables. This study examines the relationship between the growth in renewable energy production and its sub-components and climate policy uncertainty while accounting for oil price uncertainty and the growth in oil prices, industrial production, and carbon emissions, respectively. Utilizing generalized impulse response analysis within a vector autoregressive model framework, we find that total renewable energy production responds negatively to shocks to climate policy uncertainty but exhibits only a small positive response to oil price uncertainty. Further examination of renewable energy production by its sub-components (i.e., hydropower, biomass, geothermal, wind, and solar) shows that the time path responses to uncertainty shocks differ by sub-component. The findings suggest that policies to facilitate an energy transition by treating renewables similarly may not have the desired effects and thus should be tailored to individual sub-components to achieve targeted goals for renewable energy production.
{"title":"U.S. climate policy uncertainty shocks and the growth in renewable energy production","authors":"James E. Payne , Saban Nazlioglu , Ahmet Koncak , Bradley T. Ewing","doi":"10.1016/j.jcomm.2025.100493","DOIUrl":"10.1016/j.jcomm.2025.100493","url":null,"abstract":"<div><div>Investment in renewable energy production has been subject to swings in the U.S. policy stance on climate change creating uncertainty. Determining how and to what extent the renewable energy sector responds to climate policy uncertainty is relevant to understanding the energy transition from fossil fuels to renewables. This study examines the relationship between the growth in renewable energy production and its sub-components and climate policy uncertainty while accounting for oil price uncertainty and the growth in oil prices, industrial production, and carbon emissions, respectively. Utilizing generalized impulse response analysis within a vector autoregressive model framework, we find that total renewable energy production responds negatively to shocks to climate policy uncertainty but exhibits only a small positive response to oil price uncertainty. Further examination of renewable energy production by its sub-components (i.e., hydropower, biomass, geothermal, wind, and solar) shows that the time path responses to uncertainty shocks differ by sub-component. The findings suggest that policies to facilitate an energy transition by treating renewables similarly may not have the desired effects and thus should be tailored to individual sub-components to achieve targeted goals for renewable energy production.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100493"},"PeriodicalIF":3.7,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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