Pub Date : 2025-12-01Epub Date: 2025-09-03DOI: 10.1016/j.jcomm.2025.100511
Susana Álvarez-Diez , J. Samuel Baixauli-Soler , Gabriel Lozano-Reina , Diego Rodríguez-Linares Rey
This study analyzes volatility transmission between the EU-ETS –used here as a proxy for carbon price dynamics– and the stock returns of European firms with varying emission levels during the third and fourth phases of the EU-ETS (from January 01, 2013 to April 30, 2025), applying a connectedness framework that integrates time-frequency decomposition and block-level analysis. The empirical evidence confirms that carbon market volatility significantly affects corporate financial dynamics, especially in the short term and particularly for high-emission firms. These results validate the three hypotheses posed: (i) there is statistically significant volatility connectedness between carbon and stock markets; (ii) short-term spillovers dominate; and (iii) high-emission firms are more exposed to volatility transmission than their low-emission counterparts. These findings are robust across two different classification criteria and highlight the relevance of carbon pricing not only as an environmental policy tool but also as a financial market signal.
{"title":"Block connectedness between the EU-ETS and corporate returns: Evidence from high- and low-emission firms","authors":"Susana Álvarez-Diez , J. Samuel Baixauli-Soler , Gabriel Lozano-Reina , Diego Rodríguez-Linares Rey","doi":"10.1016/j.jcomm.2025.100511","DOIUrl":"10.1016/j.jcomm.2025.100511","url":null,"abstract":"<div><div>This study analyzes volatility transmission between the EU-ETS –used here as a proxy for carbon price dynamics– and the stock returns of European firms with varying emission levels during the third and fourth phases of the EU-ETS (from January 01, 2013 to April 30, 2025), applying a connectedness framework that integrates time-frequency decomposition and block-level analysis. The empirical evidence confirms that carbon market volatility significantly affects corporate financial dynamics, especially in the short term and particularly for high-emission firms. These results validate the three hypotheses posed: (i) there is statistically significant volatility connectedness between carbon and stock markets; (ii) short-term spillovers dominate; and (iii) high-emission firms are more exposed to volatility transmission than their low-emission counterparts. These findings are robust across two different classification criteria and highlight the relevance of carbon pricing not only as an environmental policy tool but also as a financial market signal.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100511"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105968","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 : 2025-12-01Epub Date: 2025-10-28DOI: 10.1016/j.jcomm.2025.100522
Shuaibing Li, Yong Ma
Global economic shocks and geopolitical crises have transformed gold’s volatility patterns, demanding new forecasting tools. This study develops an aligned equity market uncertainty (EMV) index using supervised machine learning to predict gold market volatility. We find that the aligned EMV index is a powerful predictor of gold market volatility both in- and out-of-sample, with particularly stronger short-term forecasting ability during recessions and more pronounced long-term effectiveness during expansions. The aligned EMV index identifies three drivers of gold volatility: (1) hedging demand during equity market stress, (2) investor sentiment spillovers, and (3) shared macroeconomic risks like inflation. Moreover, the aligned EMV index provides valuable complementary predictive information beyond general EMV indices, widely recognized economic variables, and uncertainty indicators. By incorporating this aligned EMV index into trading strategies, investors can achieve economic gains. These results underscore the interconnectedness of financial markets and the role of gold as a safe-haven asset.
{"title":"News-based equity market uncertainty aligned: An informative predictor for gold market volatility","authors":"Shuaibing Li, Yong Ma","doi":"10.1016/j.jcomm.2025.100522","DOIUrl":"10.1016/j.jcomm.2025.100522","url":null,"abstract":"<div><div>Global economic shocks and geopolitical crises have transformed gold’s volatility patterns, demanding new forecasting tools. This study develops an aligned equity market uncertainty (EMV) index using supervised machine learning to predict gold market volatility. We find that the aligned EMV index is a powerful predictor of gold market volatility both in- and out-of-sample, with particularly stronger short-term forecasting ability during recessions and more pronounced long-term effectiveness during expansions. The aligned EMV index identifies three drivers of gold volatility: (1) hedging demand during equity market stress, (2) investor sentiment spillovers, and (3) shared macroeconomic risks like inflation. Moreover, the aligned EMV index provides valuable complementary predictive information beyond general EMV indices, widely recognized economic variables, and uncertainty indicators. By incorporating this aligned EMV index into trading strategies, investors can achieve economic gains. These results underscore the interconnectedness of financial markets and the role of gold as a safe-haven asset.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100522"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416086","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 : 2025-12-01Epub 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":"2025-12-01","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 : 2025-12-01Epub Date: 2025-10-20DOI: 10.1016/j.jcomm.2025.100521
Nobuhiro Fuke , Kazuhiko Ohashi
This study employs quantile regression to examine the impact of solar photovoltaic (PV) power generation on both the level and variability of wholesale electricity prices. The analysis is based on data from April 2016 to March 2020 for the Kyushu region of Japan, which is particularly suitable for this study given its high solar PV penetration, limited interconnection capacity with other regions, and distinct seasonal variations. Results confirm the merit-order effect and demonstrate a novel finding of seasonal variation in the impact of solar PV power generation on electricity price variability: increased solar PV power generation is associated with reduced price variability in spring and summer, but not in autumn and winter. This seasonal divergence is attributable to changes in the relationship between electricity demand and solar PV output, driven by temperature-dependent demand and positive correlations between temperature, solar radiation, and PV generation. The findings have broader implications for electricity markets with high solar PV penetration and subject to seasonal changes. For policymakers and electricity market participants aiming to mitigate price fluctuations, managing PV-induced variability is more critical during low-temperature (than high-temperature) seasons. Moreover, the valuation of real options for solar PV-based storage facilities may differ between low- and high-temperature periods. A nuanced understanding of seasonal supply–demand dynamics is essential for accurately assessing price risks, evaluating the value of solar PV investments, and formulating effective policies for renewable energy integration.
{"title":"Seasonal variation in the impact of solar power generation on electricity price level and variability","authors":"Nobuhiro Fuke , Kazuhiko Ohashi","doi":"10.1016/j.jcomm.2025.100521","DOIUrl":"10.1016/j.jcomm.2025.100521","url":null,"abstract":"<div><div>This study employs quantile regression to examine the impact of solar photovoltaic (PV) power generation on both the level and variability of wholesale electricity prices. The analysis is based on data from April 2016 to March 2020 for the Kyushu region of Japan, which is particularly suitable for this study given its high solar PV penetration, limited interconnection capacity with other regions, and distinct seasonal variations. Results confirm the merit-order effect and demonstrate a novel finding of seasonal variation in the impact of solar PV power generation on electricity price variability: increased solar PV power generation is associated with reduced price variability in spring and summer, but not in autumn and winter. This seasonal divergence is attributable to changes in the relationship between electricity demand and solar PV output, driven by temperature-dependent demand and positive correlations between temperature, solar radiation, and PV generation. The findings have broader implications for electricity markets with high solar PV penetration and subject to seasonal changes. For policymakers and electricity market participants aiming to mitigate price fluctuations, managing PV-induced variability is more critical during low-temperature (than high-temperature) seasons. Moreover, the valuation of real options for solar PV-based storage facilities may differ between low- and high-temperature periods. A nuanced understanding of seasonal supply–demand dynamics is essential for accurately assessing price risks, evaluating the value of solar PV investments, and formulating effective policies for renewable energy integration.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100521"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145416085","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 : 2025-12-01Epub Date: 2025-10-16DOI: 10.1016/j.jcomm.2025.100518
Thomas Leirvik
This study employs a quantile moments approach to examine how economic policy uncertainty (EPU), geopolitical risk (GPR), and climate risks affect commodity return volatility. By incorporating interaction effects, we show that models ignoring these interactions underestimate volatility by up to 35% during stress periods. The analysis reveals varied effects across different volatility regimes, with transition climate risk intensifying market volatility particularly during turbulent times, whereas physical climate risk exhibits a mitigating effect. These findings offer valuable implications for risk management and policy coordination in commodity markets, highlighting the importance of considering interaction effects both normal and volatile market conditions.
{"title":"Interactive effects of economic, geopolitical, and climate risks on commodity volatility","authors":"Thomas Leirvik","doi":"10.1016/j.jcomm.2025.100518","DOIUrl":"10.1016/j.jcomm.2025.100518","url":null,"abstract":"<div><div>This study employs a quantile moments approach to examine how economic policy uncertainty (EPU), geopolitical risk (GPR), and climate risks affect commodity return volatility. By incorporating interaction effects, we show that models ignoring these interactions underestimate volatility by up to 35% during stress periods. The analysis reveals varied effects across different volatility regimes, with transition climate risk intensifying market volatility particularly during turbulent times, whereas physical climate risk exhibits a mitigating effect. These findings offer valuable implications for risk management and policy coordination in commodity markets, highlighting the importance of considering interaction effects both normal and volatile market conditions.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100518"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320599","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 : 2025-12-01Epub Date: 2025-10-10DOI: 10.1016/j.jcomm.2025.100520
Abebe Hailemariam , Kris Ivanovski
Climate policy uncertainty has emerged as a key source of systemic risk in global commodity markets, particularly for energy transition metals. The volatile and uneven trajectory of climate policy shaped by shifting political priorities, macro financial shocks and regulatory reversals creates uncertainty for metals markets and long horizon investment. Using monthly data from 1988 to 2024, this study applies a Structural Vector Autoregression (SVAR) model with exogenous controls to identify the impact of climate policy uncertainty on energy transition metals while accounting for macroeconomic drivers. The findings show that uncertainty shocks trigger persistent price declines for nickel and more moderate short-lived effects for aluminium and copper. Additional analysis shows that investor sentiment operates as a transmission channel through which the effects of climate policy uncertainty transmits to changes in transition metal prices. A dynamic spillover analysis further shows that climate policy uncertainty usually acts as a net shock receiver but becomes more influential during systemic crises. Time varying Granger causality tests confirm an uni-directional influence of climate policy uncertainty on energy transition metals, especially around major policy events. These findings highlight the evolving role of climate policy uncertainty in shaping the dynamics of transition metal prices and show the need for credible and coordinated policy frameworks to support the energy transition.
{"title":"The dynamics of energy transition metals under climate policy uncertainty","authors":"Abebe Hailemariam , Kris Ivanovski","doi":"10.1016/j.jcomm.2025.100520","DOIUrl":"10.1016/j.jcomm.2025.100520","url":null,"abstract":"<div><div>Climate policy uncertainty has emerged as a key source of systemic risk in global commodity markets, particularly for energy transition metals. The volatile and uneven trajectory of climate policy shaped by shifting political priorities, macro financial shocks and regulatory reversals creates uncertainty for metals markets and long horizon investment. Using monthly data from 1988 to 2024, this study applies a Structural Vector Autoregression (SVAR) model with exogenous controls to identify the impact of climate policy uncertainty on energy transition metals while accounting for macroeconomic drivers. The findings show that uncertainty shocks trigger persistent price declines for nickel and more moderate short-lived effects for aluminium and copper. Additional analysis shows that investor sentiment operates as a transmission channel through which the effects of climate policy uncertainty transmits to changes in transition metal prices. A dynamic spillover analysis further shows that climate policy uncertainty usually acts as a net shock receiver but becomes more influential during systemic crises. Time varying Granger causality tests confirm an uni-directional influence of climate policy uncertainty on energy transition metals, especially around major policy events. These findings highlight the evolving role of climate policy uncertainty in shaping the dynamics of transition metal prices and show the need for credible and coordinated policy frameworks to support the energy transition.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100520"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320605","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 : 2025-12-01Epub Date: 2025-09-26DOI: 10.1016/j.jcomm.2025.100517
Yan Jiang , Tian Gan , Xiaokun Wei , Honghui Zou
Crude oil is considered a vital energy source that significantly shapes firms' production, operation, investment and financing activities. This paper examines the association between oil price volatility (OPV) and corporate debt choice. Using a sample of Chinese listed firms from 2008 to 2022, we find that OPV can increase (decrease) reliance on bank debt (bond financing). This finding is consistent after conducting various robustness checks. Besides, this effect is greater for energy-related industries, less competitive industries, or non-stated-owned firms. Moreover, we find that this effect stems from increased information asymmetry and escalated financial distress risks. Finally, OPV arising from positive price fluctuations has a greater impact on debt choice than negative price changes. This study enhances the understanding of OPV's economic implications, emphasizing the need for policymakers to consider the macroeconomic context when evaluating firms' debt strategies.
{"title":"Oil price volatility and corporate debt choice: Evidence from China","authors":"Yan Jiang , Tian Gan , Xiaokun Wei , Honghui Zou","doi":"10.1016/j.jcomm.2025.100517","DOIUrl":"10.1016/j.jcomm.2025.100517","url":null,"abstract":"<div><div>Crude oil is considered a vital energy source that significantly shapes firms' production, operation, investment and financing activities. This paper examines the association between oil price volatility (OPV) and corporate debt choice. Using a sample of Chinese listed firms from 2008 to 2022, we find that OPV can increase (decrease) reliance on bank debt (bond financing). This finding is consistent after conducting various robustness checks. Besides, this effect is greater for energy-related industries, less competitive industries, or non-stated-owned firms. Moreover, we find that this effect stems from increased information asymmetry and escalated financial distress risks. Finally, OPV arising from positive price fluctuations has a greater impact on debt choice than negative price changes. This study enhances the understanding of OPV's economic implications, emphasizing the need for policymakers to consider the macroeconomic context when evaluating firms' debt strategies.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100517"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220837","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 : 2025-12-01Epub Date: 2025-11-07DOI: 10.1016/j.jcomm.2025.100525
Kyriaki Tselika , Maria Tselika , Elias Demetriades
In the evolving European energy landscape, it is essential to deepen our understanding of the interplay between electricity markets, volatility, and policy uncertainty. This paper investigates volatility spillovers across 11 European electricity markets and examines how three distinct policy uncertainty indices – economic, energy, and environmental – affect these spillovers. We employ three advanced econometric approaches to assess how the interconnected European market receives and transmits volatility. Furthermore, we analyze the influence of policy uncertainty on volatility transmission across markets using both linear and quantile regression models, allowing us to capture dynamics across different time horizons and market conditions. Our findings reveal significant fluctuations in volatility spillovers, both in the short-term and long-term market. An increase in all three policy uncertainty indices reduce short-term spillovers while energy policy uncertainty increases long-term volatility. This effect highlights the complex relationship between policy uncertainty and electricity market dynamics in Europe. The study provides crucial insights for policymakers and market participants, highlighting the need for strategic risk management and coordinated policy frameworks to mitigate the impacts of volatility and enhance market stability. Lastly, this research contributes to a deeper understanding of how policy uncertainty shapes the evolving European electricity markets.
{"title":"Policy uncertainty and volatility spillovers in European electricity markets: Implications for market dynamics and innovation","authors":"Kyriaki Tselika , Maria Tselika , Elias Demetriades","doi":"10.1016/j.jcomm.2025.100525","DOIUrl":"10.1016/j.jcomm.2025.100525","url":null,"abstract":"<div><div>In the evolving European energy landscape, it is essential to deepen our understanding of the interplay between electricity markets, volatility, and policy uncertainty. This paper investigates volatility spillovers across 11 European electricity markets and examines how three distinct policy uncertainty indices – economic, energy, and environmental – affect these spillovers. We employ three advanced econometric approaches to assess how the interconnected European market receives and transmits volatility. Furthermore, we analyze the influence of policy uncertainty on volatility transmission across markets using both linear and quantile regression models, allowing us to capture dynamics across different time horizons and market conditions. Our findings reveal significant fluctuations in volatility spillovers, both in the short-term and long-term market. An increase in all three policy uncertainty indices reduce short-term spillovers while energy policy uncertainty increases long-term volatility. This effect highlights the complex relationship between policy uncertainty and electricity market dynamics in Europe. The study provides crucial insights for policymakers and market participants, highlighting the need for strategic risk management and coordinated policy frameworks to mitigate the impacts of volatility and enhance market stability. Lastly, this research contributes to a deeper understanding of how policy uncertainty shapes the evolving European electricity markets.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"40 ","pages":"Article 100525"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145525859","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 : 2025-09-01Epub 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":"2025-09-01","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 : 2025-09-01Epub 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":"2025-09-01","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}
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