Pub Date : 2025-06-01Epub 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":"2025-06-01","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 : 2025-06-01Epub 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":"2025-06-01","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 : 2025-06-01Epub 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":"2025-06-01","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 : 2025-06-01Epub 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":"2025-06-01","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}
Pub Date : 2025-03-01Epub 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":"2025-03-01","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}
Pub Date : 2025-03-01Epub Date: 2025-02-06DOI: 10.1016/j.jcomm.2025.100459
Iris Li , Erdinc Akyildirim , Thomas Conlon , Shaen Corbet
This research examines investor response to negative Environmental, Social, and Governance (ESG) reputational events across international commodity-related corporations. By distinguishing between G7 and non-G7 nations, we highlight a negative equity market response to such ESG-related reputational events, emphasising the influence of regional, governance and environmental factors alongside corporate reporting practices. The research further assesses the potential of corporate ESG preparedness in mitigating negative market outcomes. It also identifies commodities such as wheat, rice, and cocoa to be notably susceptible to reputational dynamics, whereas commodity markets such as oil and gold present evidence of marked resilience. The findings emphasise the importance of sector-specific regulatory approaches to ensure rigorous governance standards, especially in essential food production sectors.
{"title":"Corporate reputational dynamics and their impact on global commodity markets","authors":"Iris Li , Erdinc Akyildirim , Thomas Conlon , Shaen Corbet","doi":"10.1016/j.jcomm.2025.100459","DOIUrl":"10.1016/j.jcomm.2025.100459","url":null,"abstract":"<div><div>This research examines investor response to negative Environmental, Social, and Governance (ESG) reputational events across international commodity-related corporations. By distinguishing between G7 and non-G7 nations, we highlight a negative equity market response to such ESG-related reputational events, emphasising the influence of regional, governance and environmental factors alongside corporate reporting practices. The research further assesses the potential of corporate ESG preparedness in mitigating negative market outcomes. It also identifies commodities such as wheat, rice, and cocoa to be notably susceptible to reputational dynamics, whereas commodity markets such as oil and gold present evidence of marked resilience. The findings emphasise the importance of sector-specific regulatory approaches to ensure rigorous governance standards, especially in essential food production sectors.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100459"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377910","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 : 2025-03-01Epub Date: 2025-01-11DOI: 10.1016/j.jcomm.2025.100458
Augusto Seabra Santos, Alexandre Nunes Almeida
This study explores the relationship between speculators and the volatility of live cattle futures in Brazil, focusing on two distinct categories of speculation: day traders (and scalpers) and institutional investors. Analyzing the nearest and October contracts from 2006 to 2019, the research employs the ARIMA-GARCH methodology to estimate volatilities. Additional analyses are conducted to estimate the expected and unexpected effects of speculators on the previously determined volatility levels. Our findings indicate that day trader speculators heighten the volatility of contracts nearing expiration, primarily due to their unexpected actions and limited market information usage. They tend to buy high and sell low. In contrast, institutional investors, with access to more comprehensive information, have a moderate influence on volatility, capable of strategically maneuvering market distortions. The accuracy of the conclusions is strengthened by robustness and placebo tests.
{"title":"Do different speculation strategies cause distinct impacts on the volatility of the live cattle futures in Brazil?","authors":"Augusto Seabra Santos, Alexandre Nunes Almeida","doi":"10.1016/j.jcomm.2025.100458","DOIUrl":"10.1016/j.jcomm.2025.100458","url":null,"abstract":"<div><div>This study explores the relationship between speculators and the volatility of live cattle futures in Brazil, focusing on two distinct categories of speculation: day traders (and scalpers) and institutional investors. Analyzing the nearest and October contracts from 2006 to 2019, the research employs the ARIMA-GARCH methodology to estimate volatilities. Additional analyses are conducted to estimate the expected and unexpected effects of speculators on the previously determined volatility levels. Our findings indicate that day trader speculators heighten the volatility of contracts nearing expiration, primarily due to their unexpected actions and limited market information usage. They tend to buy high and sell low. In contrast, institutional investors, with access to more comprehensive information, have a moderate influence on volatility, capable of strategically maneuvering market distortions. The accuracy of the conclusions is strengthened by robustness and placebo tests.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100458"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181346","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 : 2025-03-01Epub Date: 2025-01-22DOI: 10.1016/j.jcomm.2025.100457
Takashi Kanamura
We aim to formulate sustainability risk (Srisk) quantitatively in finance for the first time and validate the formulation by conducting empirical analyses. Applying the general sustainability concept to finance supported by existing studies proposes a new financial and quantitative model of Srisk defined by the price differences between sustainable and conventional assets and characterized by mean-reversion, cyclicity, and diversification effects on market risk. Then, the parameter estimation results of the model using ESG and the corresponding stock indexes confirm these three characteristics and indicate the convergence of expected returns of ESG indexes over stock indexes, resulting in the feasibility of securing returns in the pairs trading. Finally, we discuss the model’s robustness regarding Srisk’s three characteristics and the regime-switching of Srisk’s mean-reversion due to fundamental shifts by conducting econometric analyses of sustainable asset prices.
{"title":"A quantitative model of sustainability risk in finance","authors":"Takashi Kanamura","doi":"10.1016/j.jcomm.2025.100457","DOIUrl":"10.1016/j.jcomm.2025.100457","url":null,"abstract":"<div><div>We aim to formulate sustainability risk (Srisk) quantitatively in finance for the first time and validate the formulation by conducting empirical analyses. Applying the general sustainability concept to finance supported by existing studies proposes a new financial and quantitative model of Srisk defined by the price differences between sustainable and conventional assets and characterized by mean-reversion, cyclicity, and diversification effects on market risk. Then, the parameter estimation results of the model using ESG and the corresponding stock indexes confirm these three characteristics and indicate the convergence of expected returns of ESG indexes over stock indexes, resulting in the feasibility of securing returns in the pairs trading. Finally, we discuss the model’s robustness regarding Srisk’s three characteristics and the regime-switching of Srisk’s mean-reversion due to fundamental shifts by conducting econometric analyses of sustainable asset prices.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100457"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181347","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 : 2025-03-01Epub Date: 2024-11-16DOI: 10.1016/j.jcomm.2024.100448
Håkan Jankensgård , Nicoletta Marinelli , Rafael Schiozer
Hedging maturity, i.e., how far out in time hedging activities stretch, is an important yet under-investigated aspect of corporate risk management. In this article, we analyse firms’ hedging maturity decision and carry out a comprehensive empirical analysis. We develop three hypotheses to explain hedging maturity. The collateral hypothesis states that longer maturities are predicated on the availability of internal resources that serve as collateral in a hedging transaction. The matching hypothesis argues that firms match their hedging maturity with the maturity of their debt and investment portfolios. The flexibility hypothesis holds that the ability to change operations or investment strategies at low cost is conducive to shorter maturities. Using hand-collected data on derivative positions in the oil and gas industry, we find evidence consistent with all three hypotheses.
{"title":"Time to get mature: Collateral, flexibility and the hedging horizon decision","authors":"Håkan Jankensgård , Nicoletta Marinelli , Rafael Schiozer","doi":"10.1016/j.jcomm.2024.100448","DOIUrl":"10.1016/j.jcomm.2024.100448","url":null,"abstract":"<div><div>Hedging maturity, <em>i.e.</em>, how far out in time hedging activities stretch, is an important yet under-investigated aspect of corporate risk management. In this article, we analyse firms’ hedging maturity decision and carry out a comprehensive empirical analysis. We develop three hypotheses to explain hedging maturity. The collateral hypothesis states that longer maturities are predicated on the availability of internal resources that serve as collateral in a hedging transaction. The matching hypothesis argues that firms match their hedging maturity with the maturity of their debt and investment portfolios. The flexibility hypothesis holds that the ability to change operations or investment strategies at low cost is conducive to shorter maturities. Using hand-collected data on derivative positions in the oil and gas industry, we find evidence consistent with all three hypotheses.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100448"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181345","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 : 2025-03-01Epub Date: 2024-11-29DOI: 10.1016/j.jcomm.2024.100449
Katarzyna Chȩć, Bartosz Uniejewski, Rafał Weron
Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then combining their forecasts can bring significant accuracy gains in day-ahead electricity price forecasting. However, not much attention has been paid to predicting the LTSC, and the last 24 hourly values of the estimated pattern are typically copied for the target day. To address this gap, we introduce a novel approach which extracts the trend-seasonal pattern from a price series extrapolated using price forecasts for the next 24 h. We assess it using two 5-year long test periods from the German and Spanish power markets, covering the Covid-19 pandemic, the 2021/2022 energy crisis, and the war in Ukraine. Considering parsimonious autoregressive and LASSO-estimated models, we find that improvements in predictive accuracy range from 3% to 15% in terms of the root mean squared error and exceed 1% in terms of profits from a realistic trading strategy involving day-ahead bidding and battery storage.
{"title":"Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market","authors":"Katarzyna Chȩć, Bartosz Uniejewski, Rafał Weron","doi":"10.1016/j.jcomm.2024.100449","DOIUrl":"10.1016/j.jcomm.2024.100449","url":null,"abstract":"<div><div>Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then combining their forecasts can bring significant accuracy gains in day-ahead electricity price forecasting. However, not much attention has been paid to predicting the LTSC, and the last 24 hourly values of the estimated pattern are typically copied for the target day. To address this gap, we introduce a novel approach which extracts the trend-seasonal pattern from a price series extrapolated using price forecasts for the next 24 h. We assess it using two 5-year long test periods from the German and Spanish power markets, covering the Covid-19 pandemic, the 2021/2022 energy crisis, and the war in Ukraine. Considering parsimonious autoregressive and LASSO-estimated models, we find that improvements in predictive accuracy range from 3% to 15% in terms of the root mean squared error and exceed 1% in terms of profits from a realistic trading strategy involving day-ahead bidding and battery storage.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"37 ","pages":"Article 100449"},"PeriodicalIF":3.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181344","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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