Journal of Commodity Markets最新文献

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U.S. climate policy uncertainty shocks and the growth in renewable energy production 美国气候政策的不确定性冲击和可再生能源生产的增长

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-07-05 DOI: 10.1016/j.jcomm.2025.100493

James E. Payne , Saban Nazlioglu , Ahmet Koncak , Bradley T. Ewing

Investment in renewable energy production has been subject to swings in the U.S. policy stance on climate change creating uncertainty. Determining how and to what extent the renewable energy sector responds to climate policy uncertainty is relevant to understanding the energy transition from fossil fuels to renewables. This study examines the relationship between the growth in renewable energy production and its sub-components and climate policy uncertainty while accounting for oil price uncertainty and the growth in oil prices, industrial production, and carbon emissions, respectively. Utilizing generalized impulse response analysis within a vector autoregressive model framework, we find that total renewable energy production responds negatively to shocks to climate policy uncertainty but exhibits only a small positive response to oil price uncertainty. Further examination of renewable energy production by its sub-components (i.e., hydropower, biomass, geothermal, wind, and solar) shows that the time path responses to uncertainty shocks differ by sub-component. The findings suggest that policies to facilitate an energy transition by treating renewables similarly may not have the desired effects and thus should be tailored to individual sub-components to achieve targeted goals for renewable energy production.

可再生能源生产的投资一直受到美国气候变化政策立场摇摆的影响，造成了不确定性。确定可再生能源部门如何以及在多大程度上应对气候政策的不确定性，与理解从化石燃料到可再生能源的能源转型有关。本研究考察了可再生能源生产及其子成分的增长与气候政策不确定性之间的关系，同时分别考虑了油价的不确定性以及油价、工业生产和碳排放的增长。利用向量自回归模型框架内的广义脉冲响应分析，我们发现可再生能源生产总量对气候政策不确定性的冲击呈负响应，但对油价不确定性仅表现出微小的正响应。对可再生能源生产的子成分（即水电、生物质能、地热、风能和太阳能）的进一步研究表明，对不确定性冲击的时间路径响应因子成分而异。研究结果表明，通过类似对待可再生能源来促进能源转型的政策可能不会产生预期的效果，因此应该针对单个子组件进行定制，以实现可再生能源生产的目标。

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引用次数: 0

Decomposed and partial connectedness between oil shocks and sovereign credit risk in emerging economies: Insights from the Russia-Ukraine war 新兴经济体中石油冲击与主权信用风险之间的分解和部分联系：来自俄乌战争的洞察

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-15 DOI: 10.1016/j.jcomm.2025.100492

Nader Naifar

This paper explores the decomposed and partial connectedness between oil shocks and sovereign credit risk, emphasizing the dynamics in emerging economies divided between oil-importing and exporting nations. Using data from June 28, 2013, to June 1, 2023, empirical findings indicate that oil demand and supply shocks have become net receivers during the Russo-Ukrainian war, absorbing spillovers from sovereign credit risks. Risk shocks emerge as the only consistent and intensifying net transmitters, indicating the growing role of geopolitical uncertainty in driving volatility. Mexico appears as a notable net transmitter. Brazil also plays a persistent role as a systemic transmitter, while Russia's diminishing influence and higher self-insulation reflect financial decoupling under sanctions. A decreased total connectedness during the conflict suggests a decoupling trend among countries. Our analysis demonstrates the predominance of external over internal connectedness, emphasizing the significant influence of global events. The results display distinct connectedness patterns between oil-importing and exporting countries, reflecting the varied effects of oil price volatility on sovereign credit risk, particularly during geopolitical instability.

本文探讨了石油冲击与主权信用风险之间的分解和部分联系，强调了石油进口国和出口国之间划分的新兴经济体的动态。利用2013年6月28日至2023年6月1日的数据，实证结果表明，在俄乌战争期间，石油需求和供应冲击已成为净接受者，吸收了主权信用风险的溢出效应。风险冲击是唯一持续且不断加剧的净传导因素，表明地缘政治不确定性在推动波动方面的作用日益增强。墨西哥是一个值得注意的净发射机。巴西也一直扮演着系统性传递者的角色，而俄罗斯影响力的减弱和更高的自我隔离反映了制裁下的金融脱钩。冲突期间总连通性的下降表明了国家间的脱钩趋势。我们的分析表明外部连通性优于内部连通性，强调了全球事件的重大影响。结果显示石油进口国和出口国之间存在明显的联系模式，反映了油价波动对主权信用风险的不同影响，特别是在地缘政治不稳定的情况下。

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引用次数: 0

Risk, uncertainty, world business cycles, and the U.S. stock-oil relationship 风险，不确定性，世界经济周期，以及美国股票和石油的关系

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-10 DOI: 10.1016/j.jcomm.2025.100491

André Varella Mollick

We examine in this paper the transmission of geopolitical risks (GPR), VIX, economic policy uncertainty (EPU), and “macro uncertainty” shocks to real WTI oil and U.S. stock returns (S&P 500). Structural vector autoregressions (SVAR) are applied to monthly data from 1990:1 to 2023:6 with identification based on long-run restrictions of impulse responses from risk/uncertainty measures to world industrial production. The main results are: First, oil prices respond positively to shocks in GPR and macro uncertainty in the short-run, but not to shocks in VIX and EPU. Second, stock returns respond negatively and for longer to both GPR and VIX shocks. Third, S&P 500 moves up with positive real WTI shocks for between 5 and 8 months, supporting favorable stock market reaction to oil fundamentals. By verifying shock contributions to real asset prices, the pair (GPR, VIX) outperforms other combinations of risk/uncertainty. Two-regime Markov-Switching VARs present satisfactory regime classification measures.

本文研究了地缘政治风险（GPR）、波动率指数（VIX）、经济政策不确定性（EPU）和“宏观不确定性”冲击对实际WTI原油和美国股票回报（标准普尔500指数）的传导。结构向量自回归（SVAR）应用于1990:1至2013:6期间的月度数据，并基于风险/不确定性措施对世界工业生产的脉冲响应的长期限制进行识别。主要结果是：首先，油价在短期内对GPR和宏观不确定性的冲击有积极的反应，但对VIX和EPU的冲击没有积极的反应。其次，股票回报对GPR和VIX冲击的反应为负，且持续时间更长。第三，标准普尔500指数在5到8个月的时间里随着西德克萨斯中质原油的积极冲击而上涨，支持股市对石油基本面的有利反应。通过验证冲击对实际资产价格的影响，该货币对（GPR， VIX）优于其他风险/不确定性组合。双状态马尔可夫开关var提供了令人满意的状态分类方法。

引用次数: 0

How financial markets respond to climate policy uncertainty: A dynamic resilience analysis 金融市场如何应对气候政策的不确定性：动态弹性分析

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-04 DOI: 10.1016/j.jcomm.2025.100490

Xiaoyang Yao, Sairidaer Maimaitijiang, Jianfeng Li, Wei Le

In the context of the global transition to a sustainable development, focusing on the impact of climate policy uncertainty (CPU) on financial markets is important to prevent green swan events. This paper analyzes the resilience of major stock and commodities markets to CPU shocks from the perspectives of absorption intensity and duration, which imply the ability to withdraw the shocks and recover from them, respectively. Based on these two aspects, we construct a resilience index and explore the impacts of macroeconomic conditions on resilience. We find that most markets exhibit negative responses to CPU shocks, except for natural gas and precious metals. Most markets’ resilience to CPU has intensified, whereas, traditional energy sectors and the agricultural commodities market still shown the most vulnerability to CPU shocks. Compared to negative causality, the macro-economic conditions show higher level of positive causality to resilience. An increase in macro-economic uncertainty can exacerbate the deterioration of market resilience.

在全球向可持续发展转型的背景下，关注气候政策不确定性（CPU）对金融市场的影响对于防止绿天鹅事件至关重要。本文从吸收强度和持续时间的角度分析了主要股票和商品市场对CPU冲击的弹性，这两个角度分别意味着从冲击中撤出和恢复的能力。基于这两个方面，我们构建了弹性指数，并探讨了宏观经济条件对弹性的影响。我们发现，除了天然气和贵金属之外，大多数市场对CPU冲击表现出负面反应。大多数市场对CPU的抵御能力已经增强，而传统能源部门和农产品市场仍然最容易受到CPU冲击。宏观经济条件对弹性的正向因果关系高于负向因果关系。宏观经济不确定性的增加会加剧市场弹性的恶化。

引用次数: 0

Performance of systemic stress in agricultural commodities and its implication for volatility prediction in SSA equities 农业大宗商品的系统性压力表现及其对SSA股票波动性预测的影响

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-05-25 DOI: 10.1016/j.jcomm.2025.100480

Qingying Zheng , Jintao Wu , Boqiang Lin

Extensive research has underscored the linkage and risk exposure of Sub-Saharan Africa (SSA) equities to international agricultural commodities. However, the role of systemic agricultural commodity stress in predicting equity volatility has received less attention. We first utilize the Tail Event-driven NETwork (TENET) methodology to construct a Systemic Stress Index (SSI) for agricultural commodities to capture the extreme risks in these markets. We then develop a GARCH-MIDAS-SSI specification to examine the index's predictive capabilities and its relationship with SSA equities (Nigeria, Botswana, Uganda, Mauritius, Kenya, and Ghana). Our results show that the SSI significantly rises during global crises, and its upward trend correlates with increased volatility in SSA equities. More importantly, the SSI exhibits robust forecasting capabilities for volatility in SSA equity markets, both in-sample and out-of-sample. Given the deepening trend of commodity financialization and the frequent occurrence of global crises, these insights are pertinent for both investors and market regulators in their decision-making processes.

广泛的研究强调了撒哈拉以南非洲（SSA）股票与国际农产品的联系和风险敞口。然而，系统性农产品压力在预测股票波动方面的作用受到的关注较少。我们首先利用尾部事件驱动网络（TENET）方法构建农产品的系统压力指数（SSI），以捕捉这些市场中的极端风险。然后，我们开发了GARCH-MIDAS-SSI规范，以检查该指数的预测能力及其与SSA股票（尼日利亚、博茨瓦纳、乌干达、毛里求斯、肯尼亚和加纳）的关系。我们的研究结果表明，在全球危机期间，SSI显著上升，其上升趋势与SSA股票的波动性增加相关。更重要的是，SSI对SSA股票市场的波动性（样本内和样本外）表现出强大的预测能力。鉴于商品金融化趋势的深化和全球危机的频繁发生，这些见解对投资者和市场监管机构在决策过程中都有重要意义。

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引用次数: 0

Geopolitical risk and energy market tail risk forecasting: An explainable machine learning approach 地缘政治风险和能源市场尾部风险预测：一个可解释的机器学习方法

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-05-14 DOI: 10.1016/j.jcomm.2025.100478

Mohammad Ashraful Ferdous Chowdhury , Mohammad Abdullah , Emmanuel Joel Aikins Abakah , Aviral Kumar Tiwari

This study develops a forecasting model for energy market tail risk, with a focus on the predictive role of geopolitical risk factors. Using daily energy commodities data spanning from 2000 to 2024, this study evaluates the performance of machine learning models. Results indicate that the Light Gradient Boosting Machine (LGBM) consistently outperforms other models based on key metrics. Robustness tests across different tail risk levels affirm LGBM as the optimal choice for energy market tail risk forecasting. Furthermore, model interpretability reveals that geopolitical risk indicators contribute significantly, with a 19.15 % impact on the forecasting model. Notably, the foreign exchange market, influences predictions by 15 %, while the monetary policy, contributes 12.19 %. Our findings have significant implications for regulators, industry practitioners, and investors seeking optimal tail risk forecasting during geopolitical conflicts.

本研究建立能源市场尾部风险的预测模型，重点研究地缘政治风险因素的预测作用。使用2000年至2024年的每日能源商品数据，本研究评估了机器学习模型的性能。结果表明，基于关键指标的光梯度增强机（LGBM）始终优于其他模型。不同尾部风险水平的鲁棒性检验证实LGBM是能源市场尾部风险预测的最优选择。此外，模型的可解释性表明，地缘政治风险指标对预测模型的影响显著，为19.15%。值得注意的是，外汇市场对预测的影响为15%，而货币政策的影响为12.19%。我们的研究结果对在地缘政治冲突中寻求最佳尾部风险预测的监管机构、行业从业者和投资者具有重要意义。

引用次数: 0

Trading-hour and nontrading-hour volatility in crude oil and U.S. dollar markets and its implications for portfolio optimization 原油和美元市场的交易时段和非交易时段波动性及其对投资组合优化的影响

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-05-10 DOI: 10.1016/j.jcomm.2025.100479

Yu-Sheng Lai

The covariance between crude oil prices and U.S. dollar exchange rates is crucial for energy investors, and stock prices differ between trading and nontrading hours. Thus, the present study uses a two-component generalized autoregressive conditional heteroskedasticity (GARCH) model to analyze whole-day returns. Our analysis of data from 2007 to 2021 reveals that trading-hour and nontrading-hour returns contain crucial information for modeling whole-day covariance. Additionally, out-of-sample portfolio comparisons indicate that a two-component model is more effective than simpler models for portfolio optimization, resulting in substantial basis point fees when switching from the static to the two-component model. Crucially, the economic value generated by the two-component model is not offset by reasonable transaction costs; more risk-averse investors can generate higher benefits.

原油价格和美元汇率之间的协方差对能源投资者来说至关重要，而股票价格在交易时间和非交易时间之间存在差异。因此，本研究采用双组分广义自回归条件异方差（GARCH）模型来分析全天收益。我们对2007年至2021年的数据进行了分析，发现交易时段和非交易时段的收益包含了全天协方差建模的关键信息。此外，样本外的投资组合比较表明，对于投资组合优化，双组分模型比简单模型更有效，当从静态模型切换到双组分模型时，会产生大量基点费用。关键是，双组分模型产生的经济价值没有被合理的交易成本所抵消；规避风险的投资者越多，收益越高。

引用次数: 0

Assessing government expenditures multipliers under oil price swings 评估油价波动下的政府支出乘数

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-05-05 DOI: 10.1016/j.jcomm.2025.100477

El Mostafa Bentour

This paper evaluates the impact of government expenditure on output under oil price swings using an SVAR model on a sample of 18 MENA countries. We found that, under an oil price decrease, expenditure multipliers are higher than under an oil price increase and could attain more than one in the short run while going beyond the value of two in the long run. Moreover, on average, spending multiples in oil-exporting countries are higher than those in oil-importing countries at times of decreasing oil prices, while the opposite is noticed at times of increasing oil prices. These results are in line with the recent literature on fiscal multipliers, being large in times of recessions while being weak in times of expansions. Accordingly, some policy recommendations arise from this study as follows.

- The study endorses the adoption of a countercyclical fiscal policy in oil-exporting countries where in times of decreasing oil prices, a surge in government expenditure is more beneficial to the economy, compared to times of high oil prices.

- Oil exporting countries should continue their ongoing effort of diversification away from hydrocarbon sectors to disentangle from implied exogenous shocks and the effects of oil price swings on the fiscal policy stance.

本文以18个中东和北非国家为样本，使用SVAR模型评估了油价波动下政府支出对产出的影响。我们发现，在油价下跌的情况下，支出乘数高于油价上涨的情况，并且在短期内可以达到1以上，而在长期内可以超过2。此外，平均而言，石油出口国的支出倍数在油价下跌时高于石油进口国，而在油价上涨时则相反。这些结果与最近有关财政乘数的文献一致，即在衰退时期乘数较大，而在扩张时期乘数较弱。因此，本研究提出的一些政策建议如下。-该研究支持石油出口国采取反周期财政政策，因为在油价下跌时期，与高油价时期相比，政府支出的激增对经济更有利。-石油出口国应继续其正在进行的努力，摆脱碳氢化合物部门的多样化，以摆脱潜在的外部冲击和石油价格波动对财政政策立场的影响。

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引用次数: 0

Extremal dependence in Australian electricity markets 对澳大利亚电力市场的极度依赖

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-05-02 DOI: 10.1016/j.jcomm.2025.100476

Lin Han , Ivor Cribben , Stefan Trück

Electricity markets are significantly more volatile than other comparable financial or commodity markets. Extreme price outcomes and their transmission between regions pose significant risks for market participants. We examine the dependence between extreme spot price outcomes in the Australian National Electricity Market (NEM). We investigate extremal dependence both in a univariate and multivariate setting, applying the extremogram developed by Davis and Mikosch (2009) and Davis et al., 2011, Davis et al., 2012. We measure the persistence of extreme prices within individual regional markets and the transmission of extreme prices across different regions. With both 5-minute and 30-minute price data, we find that extreme prices are more persistent in the market with a higher share of intermittent renewable energy. We also find that the persistence of extreme prices is more prevalent in more concentrated markets. We also show significant extremal price dependence between different regions, which is typically stronger between physically interconnected markets. The dependence structure of extreme prices shows asymmetric and time-dependent patterns. Applying the extremograms, we further show the effectiveness of the Australian Energy Market Commission’s 2016 rebidding rule with respect to reducing the share of isolated price spikes that are often considered as an indication of strategic bidding. Our results provide important information for the hedging decisions of market participants and for policymakers who aim to reduce market volatility and extreme price outcomes through effective regulations that guide the trading behaviour of market participants as well as improved network interconnections.

电力市场的波动性明显高于其他可比较的金融或商品市场。极端的价格结果及其在地区间的传导给市场参与者带来了重大风险。我们研究了澳大利亚国家电力市场（NEM）的极端现货价格结果之间的依赖关系。我们使用Davis和Mikosch（2009）以及Davis等人（2011）和Davis等人（2012）开发的极值图研究了单变量和多变量设置中的极值依赖性。我们衡量了个别区域市场中极端价格的持久性，以及极端价格在不同地区之间的传导。通过5分钟和30分钟的价格数据，我们发现，在间歇性可再生能源占比较高的市场中，极端价格更为持久。我们还发现，极端价格的持续存在在更集中的市场中更为普遍。我们还显示，不同地区之间存在显著的极端价格依赖性，在物理上相互关联的市场之间，这种依赖性通常更强。极端价格的依赖结构呈现不对称和时间依赖的模式。应用极值图，我们进一步展示了澳大利亚能源市场委员会2016年重新竞标规则在减少孤立价格飙升份额方面的有效性，这些价格飙升通常被认为是战略竞标的指示。我们的研究结果为市场参与者的对冲决策和决策者提供了重要的信息，他们旨在通过有效的监管来指导市场参与者的交易行为以及改善网络互联来减少市场波动和极端价格结果。

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引用次数: 0

Predicting commodity returns: Time series vs. cross sectional prediction models 预测商品收益：时间序列与横断面预测模型

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-04-07 DOI: 10.1016/j.jcomm.2025.100475

Timotheos Angelidis , Athanasios Sakkas , Nikolaos Tessaromatis

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.

与使用金融、宏观经济和特定商品变量作为预测因子的历史平均值和时间序列预测模型相比，基于商品动量、基础和基础动量因素的商品横截面模型产生了更好的时间序列和横截面商品回报预测。与基于历史平均或时间序列预测模型预测的策略相比，基于横断面模型的商品溢价预测的时机和多空策略获得了显著的效用收益。我们的证据在许多商品和不同的预测方法中都是强有力的。

引用次数: 0

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