Journal of Commodity Markets最新文献

英文中文

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 : 2025-09-01 Epub 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

Supply and Demand shocks: the short-term and long-term drivers of oil price uncertainty 供给和需求冲击：油价不确定性的短期和长期驱动因素

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-09-01 Epub Date: 2025-07-11 DOI: 10.1016/j.jcomm.2025.100495

Theodora Bermpei , Athanasios Triantafyllou

We empirically show the role of supply and demand shocks as drivers of short and long-run price uncertainty in the crude oil market. We first define oil price uncertainty as the purely unforecastable component of oil price fluctuations and show that uncertainty of the short-run oil price fluctuations is driven by oil supply shocks, while the uncertainty for medium and long-run forecast horizons is mainly caused by aggregate demand. While our findings on the impact of oil supply disruptions on oil price uncertainty are in line with the implications of the theory of storage, we do not find similar results for the medium and the long, whereby the global demand shocks are found to be the main driver for the increasing oil price uncertainty. Interestingly, we show that the recessionary effect of short and medium-horizon uncertainty shocks, we find that long-run oil price uncertainty shocks lead to expansions in global economic activity.

我们的经验表明，供应和需求冲击的作用，作为驱动因素的短期和长期的价格不确定性在原油市场。我们首先将油价不确定性定义为油价波动的纯不可预测成分，并表明短期油价波动的不确定性是由石油供应冲击驱动的，而中长期预测视野的不确定性主要是由总需求引起的。虽然我们关于石油供应中断对油价不确定性影响的研究结果与储存理论的含义一致，但我们没有发现中期和长期的类似结果，即发现全球需求冲击是油价不确定性增加的主要驱动因素。有趣的是，我们展示了短期和中期不确定性冲击的衰退效应，我们发现长期油价不确定性冲击导致全球经济活动的扩张。

引用次数: 0

Intraday volatility transmission in global energy markets: A Bayesian nonparametric approach 全球能源市场的日内波动传导：贝叶斯非参数方法

IF 4.5 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-09-01 Epub Date: 2025-07-31 DOI: 10.1016/j.jcomm.2025.100496

Martina Danielova Zaharieva, Audronė Virbickaitė, André Portela Santos

We specify a volatility transmission model for international energy markets that divides a global trading day into three distinct trading zones, allowing us to investigate the heat wave and meteor shower hypotheses proposed in Engle et al. (1990). The resulting multivariate GARCH model is specified using a highly flexible semiparametric Bayesian framework with non-Gaussian innovations, designed to deal with asymmetry and heavy tails found in financial time series. The empirical results for the oil and natural gas futures markets suggest that volatility transmission is a combination of effects that are both related to volatility in the same region and volatility in the region immediately preceding it. Furthermore, accounting for the fat-tailed behavior not only dramatically improves the in-sample fit, but also helps to uncover additional cross-market (or cross-country) effects and gives us further insights into the exact channels through which energy shocks are transmitted throughout the world. Finally, accounting for both heat wave and meteor shower effects within a non-Gaussian framework leads to substantial improvements in the accuracy of Value-at-Risk estimates.

我们为国际能源市场指定了一个波动传导模型，该模型将全球交易日划分为三个不同的交易区，使我们能够研究Engle等人（1990）提出的热浪和流星雨假说。由此产生的多元GARCH模型使用具有非高斯创新的高度灵活的半参数贝叶斯框架来指定，旨在处理金融时间序列中的不对称性和重尾。石油和天然气期货市场的实证结果表明，波动率传导是与同一地区的波动率和前一地区的波动率相关的效应的组合。此外，考虑肥尾行为不仅可以显著提高样本内拟合，还有助于揭示额外的跨市场（或跨国）效应，并使我们进一步了解能源冲击在全球传播的确切渠道。最后，在非高斯框架内考虑热浪和流星雨的影响，可以大大提高风险价值估计的准确性。

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引用次数: 0

Impact of supply chain pressure on traditional energy and metal markets: A Wavelet-based Quantile-on-Quantile perspective 供应链压力对传统能源和金属市场的影响：基于小波的分位数对分位数视角

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-01 Epub Date: 2025-03-17 DOI: 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.

本文利用1998年1月至2023年4月的数据，研究了全球供应链压力和地缘政治紧张局势对主要能源和金属市场的影响。为此，本研究采用基于小波的分位数对分位数估计来考察样本期间和不同市场条件下关系的时变性质。结果表明，全球供应链压力预测了不同时间范围和分位数的商品回报，特别是在极端供应链压力下。相反，地缘政治风险的影响在中短期更为明显，这意味着投资者将相应地调整能源和金属投资。该论文还指出，大宗商品可以扮演投资和多元化资产的双重角色，为全球供应链中断和地缘政治事件提供对冲。这些发现为风险管理、投资策略和决策者的决策过程提供了有价值的见解。

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 : 2025-06-01 Epub 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

The short- and long-run cyclical variation of the cross-asset nexus: Mixed-frequency evidence on financial and ‘financialised’ assets 跨资产关系的短期和长期周期性变化：金融和“金融化”资产的混合频率证据

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-01 Epub Date: 2025-02-28 DOI: 10.1016/j.jcomm.2025.100462

Menelaos Karanasos , Stavroula Yfanti , Jiaying Wu

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.

我们研究了股票这一 "顾名思义 "的高风险金融资产类别与房地产和商品市场的 "金融化 "资产之间的动态相互依存关系。我们首先引入了一个新的多元校正动态条件相关混合数据采样（cDCC-MIDAS）模型，通过该模型，我们分析了股票、房地产和五种商品之间的短期和长期时变相关动态，这对风险管理和投资组合优化具有直接影响。相关性分析确定了短期和长期的对冲属性和相互依存类型，并得出结论：在大多数情况下（传染效应），强反周期性跨资产相互联系高度依赖于经济状况，而某些避险资产的弱顺周期性联系（逃向质量）。通过揭示资产共同运动的宏观决定因素，我们进一步研究了相关性演变的宏观相关性和危机脆弱性。经济环境作为传染或 "逃离质量 "的传播者发挥着关键作用，其影响超过了资产间经济联系的影响，而不确定性渠道则加剧了宏观对跨资产关系的影响。

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引用次数: 0

The effect of oil prices on the US shipping stock prices: The mediating role of freight rates and economic indicators 油价对美国航运股票价格的影响：运价和经济指标的中介作用

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-01 Epub Date: 2025-04-03 DOI: 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.

我们探讨了石油价格对航运股票和运价的影响，提供证据表明石油价格对股票价格的影响是由石油价格对运价的影响介导的，因此，运价对美国上市航运公司股票的影响。我们的数据集从2018年到2023年，我们的方法库包括误差修正模型、MIDAS和格兰杰因果关系。在此背景下，我们发现，在新冠肺炎大流行和俄乌战争期间，油价、运费和股价之间的相互作用被打乱，运费对股价的影响由非因果变为因果，油价对运费的影响由负向正。

引用次数: 0

The pass-through of macro variable to volatility co-movement among U.S. currency and commodity futures markets system 宏观变量对美国货币和商品期货市场系统波动的传递

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2025-06-01 Epub Date: 2025-02-24 DOI: 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.

本文探讨了美国宏观变量如何影响货币和商品期货市场系统的波动联动性。通过使用动态等相关混合数据采样- x模型，然后使用5分钟高频数据计算22个期货的日实现波动率（RV），良好波动率（GV）和不良波动率（BV）。采用Hodrick-Prescott滤波方法对17个宏观变量和4个宏观变量的主成分计算新闻的原始成分、周期成分和趋势成分。有三个关键的研究发现。首先，货币政策不确定性的原始成分最适合RV的联合运动，而贸易政策不确定性的原始成分最适合GV和BV的联合运动。其次，几乎所有的宏观变量都表明趋势分量的消息不会影响波动的共同运动。最后，宏观变量的影响持续时间超过4个月，而原始新闻对BV联动性的影响一般较短。宏观变量信息也有助于货币和商品期货投资者进行全局最小方差投资组合优化。

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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 : 2025-06-01 Epub 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

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 : 2025-06-01 Epub 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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