Commodity cross-sectional models based on the commodity momentum, basis, and basis-momentum factors generate superior time-series and cross-sectional commodity return forecasts compared to the historical average and time-series forecasting models that use financial, macroeconomic, and commodity-specific variables as predictors. Timing and long-short strategies based on the commodity premium forecasts from cross-sectional models achieve significant utility gains compared to strategies based on the historical average or time series predictive models’ forecasts. Our evidence is robust across many commodities and different forecasting methodologies.
{"title":"Predicting commodity returns: Time series vs. cross sectional prediction models","authors":"Timotheos Angelidis , Athanasios Sakkas , Nikolaos Tessaromatis","doi":"10.1016/j.jcomm.2025.100475","DOIUrl":"10.1016/j.jcomm.2025.100475","url":null,"abstract":"<div><div>Commodity cross-sectional models based on the commodity momentum, basis, and basis-momentum factors generate superior time-series and cross-sectional commodity return forecasts compared to the historical average and time-series forecasting models that use financial, macroeconomic, and commodity-specific variables as predictors. Timing and long-short strategies based on the commodity premium forecasts from cross-sectional models achieve significant utility gains compared to strategies based on the historical average or time series predictive models’ forecasts. Our evidence is robust across many commodities and different forecasting methodologies.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100475"},"PeriodicalIF":3.7,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868465","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 : 2025-04-03DOI: 10.1016/j.jcomm.2025.100474
Andreas Andrikopoulos , Anna Merika , Nikolaos Stoupos
We explore the effect of oil prices on shipping stocks and freight rates, delivering evidence that the effect of oil prices on stock prices is mediated by the effect of oil prices on freight rates and, thereof, the effect of freight rates on the stocks of US-listed shipping companies. Our data set runs from 2018 to 2023, and our methodological arsenal includes error correction models, MIDAS and Granger causality. In this context, we discover that after the Covid19 pandemic and during the Russo-Ukrainian war the interactions between oil prices, freight rates and stock prices have been disrupted, turning the effect of freight rates on stock prices from non-causal to causal and the effects of oil prices on freight rates from negative to positive.
{"title":"The effect of oil prices on the US shipping stock prices: The mediating role of freight rates and economic indicators","authors":"Andreas Andrikopoulos , Anna Merika , Nikolaos Stoupos","doi":"10.1016/j.jcomm.2025.100474","DOIUrl":"10.1016/j.jcomm.2025.100474","url":null,"abstract":"<div><div>We explore the effect of oil prices on shipping stocks and freight rates, delivering evidence that the effect of oil prices on stock prices is mediated by the effect of oil prices on freight rates and, thereof, the effect of freight rates on the stocks of US-listed shipping companies. Our data set runs from 2018 to 2023, and our methodological arsenal includes error correction models, MIDAS and Granger causality. In this context, we discover that after the Covid19 pandemic and during the Russo-Ukrainian war the interactions between oil prices, freight rates and stock prices have been disrupted, turning the effect of freight rates on stock prices from non-causal to causal and the effects of oil prices on freight rates from negative to positive.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100474"},"PeriodicalIF":3.7,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785411","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 : 2025-03-27DOI: 10.1016/j.jcomm.2025.100473
Joseph P. Byrne , Ryuta Sakemoto
It is widely observed that primary commodity prices comove. A parallel literature asserts that correlation risk matters for financial returns. Our novel study connects these topics and presents evidence that commodity correlation risk is both non-constant and important for returns. We reconsider therefore the relationship between primary commodities, risk and macro fundamentals, utilising methods that account for parameter uncertainty and stochastic volatility. We show that correlation risk is positively related to commodity returns and the strongest impact of risk upon return is more recent. We also demonstrate that commodity correlation risk is strongly counter-cyclical, correlation risk predicts returns, our risk measure is unrelated to other risk/uncertainty measures, and that correlation risk is linked to commodity financialization.
{"title":"Commodity correlation risk","authors":"Joseph P. Byrne , Ryuta Sakemoto","doi":"10.1016/j.jcomm.2025.100473","DOIUrl":"10.1016/j.jcomm.2025.100473","url":null,"abstract":"<div><div>It is widely observed that primary commodity prices comove. A parallel literature asserts that correlation risk matters for financial returns. Our novel study connects these topics and presents evidence that commodity correlation risk is both non-constant and important for returns. We reconsider therefore the relationship between primary commodities, risk and macro fundamentals, utilising methods that account for parameter uncertainty and stochastic volatility. We show that correlation risk is positively related to commodity returns and the strongest impact of risk upon return is more recent. We also demonstrate that commodity correlation risk is strongly counter-cyclical, correlation risk predicts returns, our risk measure is unrelated to other risk/uncertainty measures, and that correlation risk is linked to commodity financialization.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100473"},"PeriodicalIF":3.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748274","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 : 2025-03-17DOI: 10.1016/j.jcomm.2025.100472
Ahmed H. Elsayed , Giray Gozgor , Rabeh Khalfaoui , Salma Tarchella
This paper investigates the impact of the global supply chain pressure and geopolitical tensions on prominent energy and metals markets using data from January 1998 to April 2023. To this end, the study adopts Wavelet-based Quantile-on-Quantile estimations to scrutinise the time-varying nature of the relationships over the sample period and under different market conditions. The results reveal that the global supply chain pressure predicts commodity returns across various time horizons and quantiles, particularly during extreme supply chain pressures. Conversely, the impacts of geopolitical risks are more pronounced in the short- and mid-term, suggesting investors adjust energy and metal investments accordingly. The paper also indicates that commodities can play a dual role as investment and diversification assets, offering a hedge against global supply chain disruptions and geopolitical events. These findings contribute valuable insights into risk management, investment strategies, and policymakers' decision-making processes.
{"title":"Impact of supply chain pressure on traditional energy and metal markets: A Wavelet-based Quantile-on-Quantile perspective","authors":"Ahmed H. Elsayed , Giray Gozgor , Rabeh Khalfaoui , Salma Tarchella","doi":"10.1016/j.jcomm.2025.100472","DOIUrl":"10.1016/j.jcomm.2025.100472","url":null,"abstract":"<div><div>This paper investigates the impact of the global supply chain pressure and geopolitical tensions on prominent energy and metals markets using data from January 1998 to April 2023. To this end, the study adopts Wavelet-based Quantile-on-Quantile estimations to scrutinise the time-varying nature of the relationships over the sample period and under different market conditions. The results reveal that the global supply chain pressure predicts commodity returns across various time horizons and quantiles, particularly during extreme supply chain pressures. Conversely, the impacts of geopolitical risks are more pronounced in the short- and mid-term, suggesting investors adjust energy and metal investments accordingly. The paper also indicates that commodities can play a dual role as investment and diversification assets, offering a hedge against global supply chain disruptions and geopolitical events. These findings contribute valuable insights into risk management, investment strategies, and policymakers' decision-making processes.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100472"},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-15DOI: 10.1016/j.jcomm.2025.100461
Mohammad Isleimeyyeh
This article presents a model for investigating the linkages between commodity markets arising from the operation of financial investors. The model thus examines the interactions of the physical and futures markets of one commodity with those of another commodity. The framework allows the various prices (current spot, future spot, futures prices), quantities (inventory and committed demand by processors), and futures risk premiums for two commodities to be computed, thereby enabling the price relations for any two commodities to be analyzed. Through comparative statics, I identify (i) the impact of supply and demand shocks and (ii) financialization on commodity markets. Furthermore, the model demonstrates the role of cross-commodity correlation in determining the integration between commodity markets.
{"title":"Financial investors and cross-commodity markets integration","authors":"Mohammad Isleimeyyeh","doi":"10.1016/j.jcomm.2025.100461","DOIUrl":"10.1016/j.jcomm.2025.100461","url":null,"abstract":"<div><div>This article presents a model for investigating the linkages between commodity markets arising from the operation of financial investors. The model thus examines the interactions of the physical and futures markets of one commodity with those of another commodity. The framework allows the various prices (current spot, future spot, futures prices), quantities (inventory and committed demand by processors), and futures risk premiums for two commodities to be computed, thereby enabling the price relations for any two commodities to be analyzed. Through comparative statics, I identify (i) the impact of supply and demand shocks and (ii) financialization on commodity markets. Furthermore, the model demonstrates the role of cross-commodity correlation in determining the integration between commodity markets.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100461"},"PeriodicalIF":3.7,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684303","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 : 2025-03-06DOI: 10.1016/j.jcomm.2025.100471
Lanyong Yang , Yongguang Zhu , Junhui Li , Shiquan Dou , Gang Liu , Deyi Xu
The global energy transition has significantly increased the demand for lithium resources, raising market concerns about the stability of the global lithium supply chain. Understanding the relationships among different commodities within this supply chain is crucial for managing associated risks. In this study, we apply a time-varying parameter vector autoregression model to investigate the spillover effects and dynamic dependency of price volatility across the lithium supply chain. Our results reveal a high degree of systemic risk among lithium supply chains. Specifically, the risk spillover from the midstream segment to the upstream segment is the strongest and increasing, while the risk spillover to the downstream segment is the weakest and showing a downward trend. Additionally, the midstream serves as the primary net transmitter of price shocks, whereas the upstream and downstream segments more often act as net receivers. We identify two main pathways for the spillover of price shocks: one from the midstream to the upstream and then to the downstream, and another directly from the midstream to the downstream. These findings are important for mitigating the accumulation of risks within the lithium supply chain.
{"title":"The midstream amplifier: Risk spillovers in China's lithium supply chain from mining to batteries","authors":"Lanyong Yang , Yongguang Zhu , Junhui Li , Shiquan Dou , Gang Liu , Deyi Xu","doi":"10.1016/j.jcomm.2025.100471","DOIUrl":"10.1016/j.jcomm.2025.100471","url":null,"abstract":"<div><div>The global energy transition has significantly increased the demand for lithium resources, raising market concerns about the stability of the global lithium supply chain. Understanding the relationships among different commodities within this supply chain is crucial for managing associated risks. In this study, we apply a time-varying parameter vector autoregression model to investigate the spillover effects and dynamic dependency of price volatility across the lithium supply chain. Our results reveal a high degree of systemic risk among lithium supply chains. Specifically, the risk spillover from the midstream segment to the upstream segment is the strongest and increasing, while the risk spillover to the downstream segment is the weakest and showing a downward trend. Additionally, the midstream serves as the primary net transmitter of price shocks, whereas the upstream and downstream segments more often act as net receivers. We identify two main pathways for the spillover of price shocks: one from the midstream to the upstream and then to the downstream, and another directly from the midstream to the downstream. These findings are important for mitigating the accumulation of risks within the lithium supply chain.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100471"},"PeriodicalIF":3.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684302","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 : 2025-03-06DOI: 10.1016/j.jcomm.2025.100470
Jinxin Cui , Aktham Maghyereh
The complex risks of global climate change and the transition to a sustainable economy have increasingly become central to research and policy debates. Climate risk perceptions influence fossil fuel, renewable energy, and carbon markets through both investment behavior and regulatory policy channels. Understanding the spillovers between climate risk perceptions and commodity markets has profound implications for sustainable investments and risk management strategies. This paper extends the existing literature by examining higher-order moment risk spillovers among perceptions of climate physical risks (CPR) and transition risks (CTR), fossil fuel, renewable energy, and carbon markets across different quantiles. Furthermore, this paper also proposes an analytical framework that integrates ex-post moment measures with an innovative QVAR extended joint connectedness approach. Our empirical analysis reveals that the connectedness outcomes are contingent upon moment orders and specific quantile levels. Notably, total spillovers are markedly higher at the extreme quantiles (especially at the 0.95 quantile) compared to the median quantile. Importantly, CPRI and CTRI serve as net transmitters of spillovers at the 0.05 and 0.95 quantiles but shift to being net recipients under normal market conditions. The directional net spillovers transmitted from climate risk perceptions to energy and carbon markets are more pronounced and consistent at the extreme higher and lower quantiles. Finally, we find that dynamic total spillovers of skewness and kurtosis at extreme quantiles are more volatile than at the median, with significant sensitivity to major events such as the COVID-19 pandemic, the Russia-Ukraine war, the Israel-Hamas war, extreme climate disasters, and the United Nations Climate Change Conferences.
{"title":"Examining perceived spillovers among climate risk, fossil fuel, renewable energy, and carbon markets: A higher-order moment and quantile analysis","authors":"Jinxin Cui , Aktham Maghyereh","doi":"10.1016/j.jcomm.2025.100470","DOIUrl":"10.1016/j.jcomm.2025.100470","url":null,"abstract":"<div><div>The complex risks of global climate change and the transition to a sustainable economy have increasingly become central to research and policy debates. Climate risk perceptions influence fossil fuel, renewable energy, and carbon markets through both investment behavior and regulatory policy channels. Understanding the spillovers between climate risk perceptions and commodity markets has profound implications for sustainable investments and risk management strategies. This paper extends the existing literature by examining higher-order moment risk spillovers among perceptions of climate physical risks (CPR) and transition risks (CTR), fossil fuel, renewable energy, and carbon markets across different quantiles. Furthermore, this paper also proposes an analytical framework that integrates ex-post moment measures with an innovative QVAR extended joint connectedness approach. Our empirical analysis reveals that the connectedness outcomes are contingent upon moment orders and specific quantile levels. Notably, total spillovers are markedly higher at the extreme quantiles (especially at the 0.95 quantile) compared to the median quantile. Importantly, CPRI and CTRI serve as net transmitters of spillovers at the 0.05 and 0.95 quantiles but shift to being net recipients under normal market conditions. The directional net spillovers transmitted from climate risk perceptions to energy and carbon markets are more pronounced and consistent at the extreme higher and lower quantiles. Finally, we find that dynamic total spillovers of skewness and kurtosis at extreme quantiles are more volatile than at the median, with significant sensitivity to major events such as the COVID-19 pandemic, the Russia-Ukraine war, the Israel-Hamas war, extreme climate disasters, and the United Nations Climate Change Conferences.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100470"},"PeriodicalIF":3.7,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143637289","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}
We study the dynamic interdependence between stocks, a risky and financial ‘by definition’ asset class, and the ‘financialised’ assets from the real estate and commodity markets. We first introduce a new multivariate corrected Dynamic Conditional Correlations Mixed-Data Sampling (cDCC-MIDAS) model through which we analyse short- and long-run time-varying correlation dynamics among stocks, real estate, and five commodity types with direct implications for risk management and portfolio optimisation. The correlation analysis identifies short- and long-run hedging properties and interdependence types and concludes on strong countercyclical cross-asset interlinkages, highly dependent on the state of the economy in most cases (contagion effects) and weak procyclical connectedness for certain safe-haven assets (flight-to-quality). We further investigate the macro-relevance and crisis-vulnerability of the correlations’ evolution by unveiling the macro-determinants of asset co-movements. The economic environment plays a key role as a contagion or flight-to-quality transmitter, outweighing the effects of economic linkages among assets, while the uncertainty channel intensifies the macro impact on the cross-asset nexus.
{"title":"The short- and long-run cyclical variation of the cross-asset nexus: Mixed-frequency evidence on financial and ‘financialised’ assets","authors":"Menelaos Karanasos , Stavroula Yfanti , Jiaying Wu","doi":"10.1016/j.jcomm.2025.100462","DOIUrl":"10.1016/j.jcomm.2025.100462","url":null,"abstract":"<div><div>We study the dynamic interdependence between stocks, a risky and financial ‘by definition’ asset class, and the ‘financialised’ assets from the real estate and commodity markets. We first introduce a new multivariate corrected Dynamic Conditional Correlations Mixed-Data Sampling (cDCC-MIDAS) model through which we analyse short- and long-run time-varying correlation dynamics among stocks, real estate, and five commodity types with direct implications for risk management and portfolio optimisation. The correlation analysis identifies short- and long-run hedging properties and interdependence types and concludes on strong countercyclical cross-asset interlinkages, highly dependent on the state of the economy in most cases (contagion effects) and weak procyclical connectedness for certain safe-haven assets (flight-to-quality). We further investigate the macro-relevance and crisis-vulnerability of the correlations’ evolution by unveiling the macro-determinants of asset co-movements. The economic environment plays a key role as a contagion or flight-to-quality transmitter, outweighing the effects of economic linkages among assets, while the uncertainty channel intensifies the macro impact on the cross-asset nexus.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100462"},"PeriodicalIF":3.7,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-24DOI: 10.1016/j.jcomm.2025.100463
Xingyu Dai , Imran Yousaf , Jiqian Wang , Qunwei Wang , Chi Keung Marco Lau
This paper explores how the U.S. macro variable influences volatility co-movement in currency and commodity futures markets system. It does this by using the Dynamic Equicorrelation-Mixed Data Sampling-X model, and then calculating the daily realized volatility (RV), good volatility (GV), and bad volatility (BV) of 22 futures using 5-min high-frequency data. The Hodrick-Prescott filter method is applied to compute the raw, cycle, and trend components of the news for 17 macro variables and 4 principal components of these macro variables. There are three key study findings. First, the raw component of monetary policy uncertainty is the best fit for RV co-movement, while the raw component of trade policy uncertainty is the best fit for GV and BV co-movement. Second, almost all macro variables show that the trend component news do not affect volatility co-movement. Finally, the duration of the impact of macro variables exceeds 4 months, while the influence of raw news on BV co-movement is generally shorter. The macro variable information also helps currency and commodity futures investors to make global minimum variance portfolio optimization.
{"title":"The pass-through of macro variable to volatility co-movement among U.S. currency and commodity futures markets system","authors":"Xingyu Dai , Imran Yousaf , Jiqian Wang , Qunwei Wang , Chi Keung Marco Lau","doi":"10.1016/j.jcomm.2025.100463","DOIUrl":"10.1016/j.jcomm.2025.100463","url":null,"abstract":"<div><div>This paper explores how the U.S. macro variable influences volatility co-movement in currency and commodity futures markets system. It does this by using the Dynamic Equicorrelation-Mixed Data Sampling-X model, and then calculating the daily realized volatility (RV), good volatility (GV), and bad volatility (BV) of 22 futures using 5-min high-frequency data. The Hodrick-Prescott filter method is applied to compute the raw, cycle, and trend components of the news for 17 macro variables and 4 principal components of these macro variables. There are three key study findings. First, the raw component of monetary policy uncertainty is the best fit for RV co-movement, while the raw component of trade policy uncertainty is the best fit for GV and BV co-movement. Second, almost all macro variables show that the trend component news do not affect volatility co-movement. Finally, the duration of the impact of macro variables exceeds 4 months, while the influence of raw news on BV co-movement is generally shorter. The macro variable information also helps currency and commodity futures investors to make global minimum variance portfolio optimization.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100463"},"PeriodicalIF":3.7,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529765","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 : 2025-02-07DOI: 10.1016/j.jcomm.2025.100460
Yeguang Chi, Lina El-Jahel, Thanh Vu
This study investigates the impact of media emotion intensity on commodities futures returns. Emotion intensity measures the proportion of emotional content relative to factual content in media news. The media emotion intensity factor generates an annual premium of 13% after transaction cost. This premium is more pronounced for commodities with low media coverage, high momentum, high basis-momentum, high hedging pressure, and backwardation. Emotion intensity significantly predicts the trading tendencies of both commercial and non-commercial traders and the cross-section of commodity futures returns at both portfolio and individual levels. We also find that media emotion intensity predicts future commodities’ sentiment. Further, other commonly considered risk sources cannot subsume the predictability of the media emotion intensity factor.
{"title":"Media emotion intensity and commodity futures pricing","authors":"Yeguang Chi, Lina El-Jahel, Thanh Vu","doi":"10.1016/j.jcomm.2025.100460","DOIUrl":"10.1016/j.jcomm.2025.100460","url":null,"abstract":"<div><div>This study investigates the impact of media emotion intensity on commodities futures returns. Emotion intensity measures the proportion of emotional content relative to factual content in media news. The media emotion intensity factor generates an annual premium of 13% after transaction cost. This premium is more pronounced for commodities with low media coverage, high momentum, high basis-momentum, high hedging pressure, and backwardation. Emotion intensity significantly predicts the trading tendencies of both commercial and non-commercial traders and the cross-section of commodity futures returns at both portfolio and individual levels. We also find that media emotion intensity predicts future commodities’ sentiment. Further, other commonly considered risk sources cannot subsume the predictability of the media emotion intensity factor.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100460"},"PeriodicalIF":3.7,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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