Journal of Commodity Markets最新文献_第7页

Weathering market swings: Does climate risk matter for agricultural commodity price predictability? 抵御市场波动：气候风险对农产品价格的可预测性有影响吗？

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-08-30 DOI: 10.1016/j.jcomm.2024.100423

Yong Ma, Mingtao Zhou, Shuaibing Li

The challenges posed by climate change on the agricultural market have become a pressing concern. An accurate reading of future agricultural commodity prices can be an invaluable planning instrument for diverse interested parties. Here, we explore asset pricing implications of climate risk for the agricultural commodity market from January 2005 to December 2021. Through introducing a composite climate risk index based on the four individual climate risk measures of Faccini et al. (2023), our findings provide valuable insights into the time-series predictability of aggregate climate risk on future agricultural commodity returns, both in- and out-of-sample. This powerful predictability conveys substantial economic benefits to mean–variance investors and cannot be subsumed by conventional economic predictor variables. The evidence further suggests that physical risk, especially global warming, exhibits much stronger return predictability than transition risk. Moreover, we emphasize the pivotal role of climate risk in shaping supply dynamics and capturing investor attention, thereby serving as potential drivers of return predictability. Overall, these predictive insights hold important implications for risk management, investment strategies, and policy formulation in the agricultural commodity market.

气候变化给农业市场带来的挑战已成为人们迫切关注的问题。对未来农产品价格的准确解读可以成为各利益相关方的宝贵规划工具。在此，我们探讨了 2005 年 1 月至 2021 年 12 月期间气候风险对农产品市场资产定价的影响。通过引入基于 Faccini 等人（2023 年）的四种单个气候风险度量的综合气候风险指数，我们的研究结果为总体气候风险对未来农产品收益的时间序列预测性（包括样本内和样本外）提供了宝贵的见解。这种强大的可预测性为均值方差投资者带来了巨大的经济利益，是传统经济预测变量所无法取代的。证据进一步表明，物理风险，尤其是全球变暖，比过渡风险表现出更强的收益预测性。此外，我们还强调了气候风险在影响供应动态和吸引投资者注意力方面的关键作用，从而成为收益可预测性的潜在驱动因素。总之，这些预测性见解对农产品市场的风险管理、投资策略和政策制定具有重要意义。

{"title":"Weathering market swings: Does climate risk matter for agricultural commodity price predictability?","authors":"Yong Ma, Mingtao Zhou, Shuaibing Li","doi":"10.1016/j.jcomm.2024.100423","DOIUrl":"10.1016/j.jcomm.2024.100423","url":null,"abstract":"<div><p>The challenges posed by climate change on the agricultural market have become a pressing concern. An accurate reading of future agricultural commodity prices can be an invaluable planning instrument for diverse interested parties. Here, we explore asset pricing implications of climate risk for the agricultural commodity market from January 2005 to December 2021. Through introducing a composite climate risk index based on the four individual climate risk measures of Faccini et al. (2023), our findings provide valuable insights into the time-series predictability of aggregate climate risk on future agricultural commodity returns, both in- and out-of-sample. This powerful predictability conveys substantial economic benefits to mean–variance investors and cannot be subsumed by conventional economic predictor variables. The evidence further suggests that physical risk, especially global warming, exhibits much stronger return predictability than transition risk. Moreover, we emphasize the pivotal role of climate risk in shaping supply dynamics and capturing investor attention, thereby serving as potential drivers of return predictability. Overall, these predictive insights hold important implications for risk management, investment strategies, and policy formulation in the agricultural commodity market.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100423"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142129685","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}

引用次数: 0

Expected returns on commodity ETFs and their underlying assets 商品 ETF 及其相关资产的预期回报

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-10-09 DOI: 10.1016/j.jcomm.2024.100439

Gonzalo Cortazar , Hector Ortega , Joaquin Santa Maria , Eduardo S. Schwartz

This paper proposes a new way of estimating ETFs' expected returns. Instead of using traditional CAPM-like expected return models on ETFs' market prices, it consists of implementing ETFs' investment strategy on the underlying assets and using these assets' pricing models to estimate the expected returns on the ETFs. The hypothesis is that whenever valuable knowledge is available on the underlying asset returns, this information can be helpful when estimating expected ETF returns.

We illustrate our approach by choosing the United States Oil Fund (USO), the largest oil futures-based ETF. We propose estimating ETF returns using their investment strategy in oil futures and an oil pricing model. We use a three-factor stochastic process for oil futures and forecasts calibrated using a Kalman Filter and maximum likelihood estimation procedure.

Using historical futures prices, we successfully replicate historical NAV values following their investment strategy. We then estimate ETFs' expected returns using NAVs as a proxy for ETFs' market values and implement their investment strategy priced using the oil price model. We then compare our results with the more traditional CAPM expected return estimation, obtaining a similar average but a time-varying expected ETF return that reacts to market conditions and allows us to analyze their macroeconomic determinants.

本文提出了一种估算 ETF 预期收益的新方法。它不使用传统的类似于 CAPM 的预期收益模型来估算 ETF 的市场价格，而是将 ETF 的投资策略落实到基础资产上，并使用这些资产的定价模型来估算 ETF 的预期收益。我们选择最大的基于石油期货的 ETF--美国石油基金（USO）来说明我们的方法。我们建议使用石油期货投资策略和石油定价模型来估算 ETF 收益。我们使用石油期货的三因素随机过程，并使用卡尔曼滤波器和最大似然估计程序对预测进行校准。然后，我们使用资产净值作为 ETF 市场价值的代表来估算 ETF 的预期收益，并使用石油价格模型来实施其定价投资策略。然后，我们将我们的结果与更传统的 CAPM 预期收益估算进行比较，得到一个类似的平均但随时间变化的 ETF 预期收益率，该收益率会对市场条件做出反应，并允许我们分析其宏观经济决定因素。

{"title":"Expected returns on commodity ETFs and their underlying assets","authors":"Gonzalo Cortazar , Hector Ortega , Joaquin Santa Maria , Eduardo S. Schwartz","doi":"10.1016/j.jcomm.2024.100439","DOIUrl":"10.1016/j.jcomm.2024.100439","url":null,"abstract":"<div><div>This paper proposes a new way of estimating ETFs' expected returns. Instead of using traditional CAPM-like expected return models on ETFs' market prices, it consists of implementing ETFs' investment strategy on the underlying assets and using these assets' pricing models to estimate the expected returns on the ETFs. The hypothesis is that whenever valuable knowledge is available on the underlying asset returns, this information can be helpful when estimating expected ETF returns.</div><div>We illustrate our approach by choosing the United States Oil Fund (USO), the largest oil futures-based ETF. We propose estimating ETF returns using their investment strategy in oil futures and an oil pricing model. We use a three-factor stochastic process for oil futures and forecasts calibrated using a Kalman Filter and maximum likelihood estimation procedure.</div><div>Using historical futures prices, we successfully replicate historical NAV values following their investment strategy. We then estimate ETFs' expected returns using NAVs as a proxy for ETFs' market values and implement their investment strategy priced using the oil price model. We then compare our results with the more traditional CAPM expected return estimation, obtaining a similar average but a time-varying expected ETF return that reacts to market conditions and allows us to analyze their macroeconomic determinants.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100439"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142432445","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}

引用次数: 0

Forecasting crude oil returns with oil-related industry ESG indices 利用石油相关行业 ESG 指数预测原油回报率

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-10-29 DOI: 10.1016/j.jcomm.2024.100444

Kaixin Li , Zhikai Zhang , Yudong Wang , Yaojie Zhang

We construct North American oil-related industry ESG indices based on Elastic Net and PCA/SPCA/PLS dimensionality reduction techniques. We discover that the ESG indices show significant forecasting power for crude oil returns both in- and out-of-sample, and their ability to significantly predict oil returns remains when the delayed ESG release is considered. Additionally, our analysis suggests that the predictive abilities of ESG indices remain robust and unaffected by stock returns in the oil-related industry. The ESG indices can provide information that is heterogeneous and complementary to macroeconomic variables and technical indicators. Based on the analysis over the business cycle, ESG indices show predictability in forecasting crude oil returns during economic expansions rather than recessions. Moreover, ESG indices' predictive ability is also of economic significance, as shown by the substantial economic value it generates for mean-variance investors. Finally, we explore the potential economic channels, and the result reveals that the predictive power of ESG indices arises from speculative behavior in the oil market and oil demand.

我们基于弹性网和 PCA/SPCA/PLS 降维技术构建了北美石油相关行业 ESG 指数。我们发现，ESG 指数在样本内和样本外都对原油收益率显示出显著的预测能力，而且在考虑 ESG 延迟发布的情况下，ESG 指数仍能显著预测石油收益率。此外，我们的分析表明，ESG 指数的预测能力保持稳健，不受石油相关行业股票回报率的影响。环境、社会和公司治理指数可以提供与宏观经济变量和技术指标互补的异质性信息。根据对商业周期的分析，ESG 指数在预测经济扩张期而非衰退期的原油回报率方面表现出可预测性。此外，ESG 指数的预测能力还具有重要的经济意义，它为均值方差投资者带来了巨大的经济价值。最后，我们探讨了潜在的经济渠道，结果显示 ESG 指数的预测能力来自石油市场的投机行为和石油需求。

{"title":"Forecasting crude oil returns with oil-related industry ESG indices","authors":"Kaixin Li , Zhikai Zhang , Yudong Wang , Yaojie Zhang","doi":"10.1016/j.jcomm.2024.100444","DOIUrl":"10.1016/j.jcomm.2024.100444","url":null,"abstract":"<div><div>We construct North American oil-related industry ESG indices based on Elastic Net and PCA/SPCA/PLS dimensionality reduction techniques. We discover that the ESG indices show significant forecasting power for crude oil returns both in- and out-of-sample, and their ability to significantly predict oil returns remains when the delayed ESG release is considered. Additionally, our analysis suggests that the predictive abilities of ESG indices remain robust and unaffected by stock returns in the oil-related industry. The ESG indices can provide information that is heterogeneous and complementary to macroeconomic variables and technical indicators. Based on the analysis over the business cycle, ESG indices show predictability in forecasting crude oil returns during economic expansions rather than recessions. Moreover, ESG indices' predictive ability is also of economic significance, as shown by the substantial economic value it generates for mean-variance investors. Finally, we explore the potential economic channels, and the result reveals that the predictive power of ESG indices arises from speculative behavior in the oil market and oil demand.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100444"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577461","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}

引用次数: 0

Asymmetric multi-scale systemic risk spillovers across international commodity futures markets: The role of infectious disease uncertainty 国际商品期货市场的不对称多尺度系统性风险溢出效应：传染病不确定性的作用

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-10-26 DOI: 10.1016/j.jcomm.2024.100443

Yanli Zhu , Xian Yang , Chuanhai Zhang , Sihan Liu , Jiayi Li

This paper investigates the role of infectious disease uncertainty on multi-scale risk spillovers and portfolio implications across 12 international commodity futures markets from January 2006 to August 2022. We use wavelet packet decomposition and a novel risk spillover network topology approach based on a smooth transition vector autoregression model. The main findings are summarized as follows. First, there is an obvious asymmetry in spillover effects, i.e., the intensity of risk spillovers increases significantly during periods of high infectious disease uncertainty, and clear evidence of time-varying total spillovers across various regimes and frequencies. Second, cross-category risk spillovers are more pronounced in high-uncertainty regimes, while risk networks tend to cluster within the same category during low-uncertainty regimes. Third, the role of commodity futures in the risk spillover networks varies across different time scales and regimes, with gold consistently acting as a stable net risk transmitter. We also develop optimal portfolio strategies across commodity futures markets at different time scales and regimes based on the risk spillover analysis.

本文研究了 2006 年 1 月至 2022 年 8 月期间 12 个国际商品期货市场中传染病不确定性对多尺度风险溢出的作用和投资组合的影响。我们采用了小波包分解法和基于平稳过渡向量自回归模型的新型风险溢出网络拓扑方法。主要发现总结如下。首先，溢出效应存在明显的不对称性，即在传染病不确定性较高的时期，风险溢出的强度会显著增加，并且有明显证据表明不同制度和频率下的总溢出是时变的。第二，在高不确定性时期，跨类别风险溢出效应更为明显，而在低不确定性时期，风险网络往往聚集在同一类别内。第三，商品期货在风险溢出网络中的作用在不同的时间尺度和制度下各不相同，黄金一直是稳定的净风险传递者。我们还根据风险溢出分析，制定了不同时间尺度和制度下商品期货市场的最优投资组合策略。

{"title":"Asymmetric multi-scale systemic risk spillovers across international commodity futures markets: The role of infectious disease uncertainty","authors":"Yanli Zhu , Xian Yang , Chuanhai Zhang , Sihan Liu , Jiayi Li","doi":"10.1016/j.jcomm.2024.100443","DOIUrl":"10.1016/j.jcomm.2024.100443","url":null,"abstract":"<div><div>This paper investigates the role of infectious disease uncertainty on multi-scale risk spillovers and portfolio implications across 12 international commodity futures markets from January 2006 to August 2022. We use wavelet packet decomposition and a novel risk spillover network topology approach based on a smooth transition vector autoregression model. The main findings are summarized as follows. First, there is an obvious asymmetry in spillover effects, i.e., the intensity of risk spillovers increases significantly during periods of high infectious disease uncertainty, and clear evidence of time-varying total spillovers across various regimes and frequencies. Second, cross-category risk spillovers are more pronounced in high-uncertainty regimes, while risk networks tend to cluster within the same category during low-uncertainty regimes. Third, the role of commodity futures in the risk spillover networks varies across different time scales and regimes, with gold consistently acting as a stable net risk transmitter. We also develop optimal portfolio strategies across commodity futures markets at different time scales and regimes based on the risk spillover analysis.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100443"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572506","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}

引用次数: 0

A comparative study of factor models for different periods of the electricity spot price market 不同时期电力现货价格市场因素模型的比较研究

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-09-20 DOI: 10.1016/j.jcomm.2024.100435

Christian Laudagé , Florian Aichinger , Sascha Desmettre

Due to major shifts in the European energy supply, a structural change can be observed in Austrian electricity spot price data starting from the second quarter of the year 2021 onward. In this work, we study the performance of two different factor models for the electricity spot price in three different time periods. To this end, we consider three samples of EEX data for the Austrian base load electricity spot price, one from the pre-crisis from 2018 to 2021, the second from the time of the crisis from 2021 to 2023, and the whole data from 2018 to 2023. For each of these samples, we investigate the fit of a classical 3-factor model with a Gaussian base signal and one positive and one negative jump signal and compare it with a 4-factor model to assess the effect of adding a second Gaussian base signal to the model.

For the calibration of the models, we develop a tailor-made Markov Chain Monte Carlo method based on Gibbs sampling. To evaluate the model adequacy, we provide simulations of the spot price as well as a posterior predictive check for the 3- and the 4-factor model. We find that the 4-factor model outperforms the 3-factor model in times of non-crises. In times of crisis, the second Gaussian base signal does not lead to a better fit of the model. To the best of our knowledge, this is the first study regarding stochastic electricity spot price models in this new market environment. Hence, it serves as a solid base for future research.

由于欧洲能源供应的重大变化，从 2021 年第二季度开始，奥地利电力现货价格数据出现了结构性变化。在这项工作中，我们研究了两个不同因素模型在三个不同时期对电力现货价格的影响。为此，我们考虑了奥地利基本负荷电力现货价格的三个 EEX 数据样本，一个是危机前从 2018 年到 2021 年的样本，第二个是危机期间从 2021 年到 2023 年的样本，以及 2018 年到 2023 年的全部数据。对于这些样本中的每一个，我们都研究了带有高斯基本信号和一正一负跳跃信号的经典 3 因子模型的拟合度，并将其与 4 因子模型进行比较，以评估在模型中添加第二个高斯基本信号的效果。为了评估模型的充分性，我们提供了现货价格的模拟结果，并对 3 因子模型和 4 因子模型进行了后验预测。我们发现，在非危机时期，4 因子模型优于 3 因子模型。在危机时期，第二个高斯基本信号并不能使模型拟合得更好。据我们所知，这是在新市场环境下对随机电力现货价格模型的首次研究。因此，它为今后的研究奠定了坚实的基础。

{"title":"A comparative study of factor models for different periods of the electricity spot price market","authors":"Christian Laudagé , Florian Aichinger , Sascha Desmettre","doi":"10.1016/j.jcomm.2024.100435","DOIUrl":"10.1016/j.jcomm.2024.100435","url":null,"abstract":"<div><p>Due to major shifts in the European energy supply, a structural change can be observed in Austrian electricity spot price data starting from the second quarter of the year 2021 onward. In this work, we study the performance of two different factor models for the electricity spot price in three different time periods. To this end, we consider three samples of EEX data for the Austrian base load electricity spot price, one from the pre-crisis from 2018 to 2021, the second from the time of the crisis from 2021 to 2023, and the whole data from 2018 to 2023. For each of these samples, we investigate the fit of a classical 3-factor model with a Gaussian base signal and one positive and one negative jump signal and compare it with a 4-factor model to assess the effect of adding a second Gaussian base signal to the model.</p><p>For the calibration of the models, we develop a tailor-made Markov Chain Monte Carlo method based on Gibbs sampling. To evaluate the model adequacy, we provide simulations of the spot price as well as a posterior predictive check for the 3- and the 4-factor model. We find that the 4-factor model outperforms the 3-factor model in times of non-crises. In times of crisis, the second Gaussian base signal does not lead to a better fit of the model. To the best of our knowledge, this is the first study regarding stochastic electricity spot price models in this new market environment. Hence, it serves as a solid base for future research.</p></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100435"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405851324000540/pdfft?md5=263715891f55b2845be32b1642e61920&pid=1-s2.0-S2405851324000540-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142271999","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}

引用次数: 0

Have the causal effects between equities, oil prices, and monetary policy changed over time? 股票、油价和货币政策之间的因果效应是否随着时间的推移而改变？

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-11-13 DOI: 10.1016/j.jcomm.2024.100446

Alexander Kurov , Eric Olson , Marketa Halova Wolfe

We reexamine the contemporaneous causal effects between the U.S. stock prices, crude oil prices, and monetary policy from 2005 to 2022. Our study offers two main contributions. First, we generalize a novel identification approach based on exogenous intraday shifts in the volatility in futures markets from two markets to multiple markets. Second, we examine contemporaneous causal effects between the U.S. stock prices, crude oil prices, and monetary policy. We show that the coefficients measuring contemporaneous causality have substantially changed over time. Specifically, we find that since 2008 stock returns affect crude oil returns. This time variation is also evident in the effect of monetary policy on the crude oil returns. We show that this time variation is consistent with two explanations: the zero lower bound (ZLB) and increased synchronization of crude oil prices with the business cycle.

我们重新研究了 2005 年至 2022 年美国股票价格、原油价格和货币政策之间的同期因果效应。我们的研究有两大贡献。首先，我们将基于期货市场波动性日内外生变化的新型识别方法从两个市场推广到多个市场。其次，我们研究了美国股票价格、原油价格和货币政策之间的同期因果效应。我们发现，衡量同期因果关系的系数随着时间的推移发生了很大变化。具体而言，我们发现自 2008 年以来，股票收益率会影响原油收益率。这种时间变化在货币政策对原油收益率的影响中也很明显。我们表明，这种时间变化符合两种解释：零下限（ZLB）和原油价格与商业周期的同步性增强。

引用次数: 0

Food-fuel nexus beyond mean-variance: New evidence from a quantile approach 超越均值方差的粮食-燃料关系：来自量化方法的新证据

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-10-20 DOI: 10.1016/j.jcomm.2024.100441

Linjie Wang , Xiaoli Etienne , Jian Li

This paper investigates the dynamic relationship between crude oil, ethanol, and corn markets across various quantiles of return distributions, as well as at higher statistical moments. Using a quantile vector autoregression model and data from 2007 to 2022, we find that the cross-market linkages are quantile dependent, with the strongest connections observed in the tails of the distribution. A shock to the oil market significantly impacts ethanol and corn returns under extreme bearish and bullish conditions. Positive shocks to the corn market reduce ethanol returns when the ethanol market is highly bullish, but this effect becomes positive in the left tail of the distribution. We also identify significant co-movement in higher statistical moments between these markets. Extreme excess kurtosis in the food-fuel nexus is more likely to occur with high financial market uncertainty, a bullish stock market, contracting industrial production, and a strong US dollar. In addition to these variables, credit spreads, futures market liquidity, futures term structure, and hedging pressure also influence kurtosis in individual markets within the nexus.

本文研究了原油、乙醇和玉米市场在收益率分布的不同量级以及更高的统计时刻之间的动态关系。利用量级向量自回归模型和 2007 年至 2022 年的数据，我们发现跨市场的联系取决于量级，在分布的尾部观察到最强的联系。在极端看跌和看涨的情况下，石油市场的冲击会对乙醇和玉米的收益产生重大影响。当乙醇市场高度看涨时，玉米市场的正向冲击会降低乙醇收益率，但这种影响在分布的左尾部变为正向。我们还发现这些市场之间在较高统计矩上存在明显的共同波动。在金融市场不确定性高、股市看涨、工业生产萎缩和美元走强的情况下，粮食与燃料之间的关系更容易出现极度过度峰度。除这些变量外，信用利差、期货市场流动性、期货期限结构和套期保值压力也会影响关联中各个市场的峰度。

{"title":"Food-fuel nexus beyond mean-variance: New evidence from a quantile approach","authors":"Linjie Wang , Xiaoli Etienne , Jian Li","doi":"10.1016/j.jcomm.2024.100441","DOIUrl":"10.1016/j.jcomm.2024.100441","url":null,"abstract":"<div><div>This paper investigates the dynamic relationship between crude oil, ethanol, and corn markets across various quantiles of return distributions, as well as at higher statistical moments. Using a quantile vector autoregression model and data from 2007 to 2022, we find that the cross-market linkages are quantile dependent, with the strongest connections observed in the tails of the distribution. A shock to the oil market significantly impacts ethanol and corn returns under extreme bearish and bullish conditions. Positive shocks to the corn market reduce ethanol returns when the ethanol market is highly bullish, but this effect becomes positive in the left tail of the distribution. We also identify significant co-movement in higher statistical moments between these markets. Extreme excess kurtosis in the food-fuel nexus is more likely to occur with high financial market uncertainty, a bullish stock market, contracting industrial production, and a strong US dollar. In addition to these variables, credit spreads, futures market liquidity, futures term structure, and hedging pressure also influence kurtosis in individual markets within the nexus.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100441"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142536028","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}

引用次数: 0

Do oil market shocks affect financial distress? Evidence from firm-level global data 石油市场冲击会影响财务困境吗？来自公司层面全球数据的证据

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-09-29 DOI: 10.1016/j.jcomm.2024.100436

Mohammad Mahdi Mousavi , Giray Gozgor , Albert Acheampong

This study investigates the impact of three oil price shocks on financial distress of global firms using a dataset of 8130 firms across 48 countries from 2002 to 2022. It also analyses the role of energy diversification in the relationship between oil shocks and firm distress. The findings reveal that aggregate demand and specific demand shocks increase firm distress risk, while supply shocks reduce it. Furthermore, the results suggest that energy diversification mitigates the impact of specific demand shocks on firm distress. The study also implements several robustness checks, and the results remain consistent. Potential policy implications are also discussed.

本研究使用 2002 年至 2022 年 48 个国家 8130 家公司的数据集，研究了三次石油价格冲击对全球公司财务困境的影响。研究还分析了能源多样化在石油冲击与企业困境之间关系中的作用。研究结果表明，总需求和特定需求冲击会增加企业困境风险，而供应冲击则会降低风险。此外，研究结果表明，能源多样化减轻了特定需求冲击对企业困境的影响。研究还进行了若干稳健性检验，结果保持一致。研究还讨论了潜在的政策影响。

引用次数: 0

Commodity market downturn: Systemic risk and spillovers during left tail events 商品市场下滑：左尾事件中的系统风险和溢出效应

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-11-03 DOI: 10.1016/j.jcomm.2024.100445

Samet Gunay , Destan Kirimhan , Emrah Ismail Cevik

We investigate systemic risk and spillovers in the commodity network during left-tail events using state-of-the-art methodologies: the Component Exponent Shortfall (CES), Quantile-Vector Autoregression (QVAR) and Causality-in-Risk. Our analysis focuses on five commodity groups: Energy (Crude Oil, Heating Oil, Natural Gas, Coal), Base Metals (Aluminum, Copper, Nickel, Zinc), Ferrous Metals (Iron, Steel), Precious Metals (Gold, Palladium, Platinum, Silver), and Others (Rubber). Across the models utilized, we consistently find that energy commodities and precious metals, along with copper as a standalone commodity, represent the most systemically risky group. Thus, portfolios incorporating these commodities are advised to implement more careful diversification to mitigate risks stemming from systemic factors. This may require additional attention to precious metals, as they are often considered safe-haven assets. Expediting the implementation of regulations that promote the replacement of fossil energy sources with green alternatives could be instrumental in managing systemic risk in the commodity market while also facilitating global sustainability. Finally, the results show that the impact of the Israeli-Palestinian conflict on both systemic risk and spillovers has been limited compared to the effects of COVID-19 and the Russia-Ukraine war.

我们采用最先进的方法：成分指数短缺（CES）、量子矢量自回归（QVAR）和风险中的因果关系，研究左尾事件期间商品网络的系统性风险和溢出效应。我们的分析侧重于五类商品：能源（原油、取暖油、天然气、煤炭）、基本金属（铝、铜、镍、锌）、黑色金属（铁、钢）、贵金属（金、钯、铂、银）和其他（橡胶）。在所有使用的模型中，我们始终发现能源商品和贵金属，以及作为独立商品的铜，是系统风险最大的一组。因此，建议包含这些商品的投资组合更加谨慎地进行分散投资，以降低系统性因素带来的风险。这可能需要额外关注贵金属，因为它们通常被视为避险资产。加快实施促进以绿色替代品取代化石能源的法规，有助于管理商品市场的系统性风险，同时也有利于全球的可持续发展。最后，研究结果表明，与 COVID-19 和俄乌战争的影响相比，以巴冲突对系统风险和溢出效应的影响有限。

{"title":"Commodity market downturn: Systemic risk and spillovers during left tail events","authors":"Samet Gunay , Destan Kirimhan , Emrah Ismail Cevik","doi":"10.1016/j.jcomm.2024.100445","DOIUrl":"10.1016/j.jcomm.2024.100445","url":null,"abstract":"<div><div>We investigate systemic risk and spillovers in the commodity network during left-tail events using state-of-the-art methodologies: the Component Exponent Shortfall (CES), Quantile-Vector Autoregression (QVAR) and Causality-in-Risk. Our analysis focuses on five commodity groups: Energy (Crude Oil, Heating Oil, Natural Gas, Coal), Base Metals (Aluminum, Copper, Nickel, Zinc), Ferrous Metals (Iron, Steel), Precious Metals (Gold, Palladium, Platinum, Silver), and Others (Rubber). Across the models utilized, we consistently find that energy commodities and precious metals, along with copper as a standalone commodity, represent the most systemically risky group. Thus, portfolios incorporating these commodities are advised to implement more careful diversification to mitigate risks stemming from systemic factors. This may require additional attention to precious metals, as they are often considered safe-haven assets. Expediting the implementation of regulations that promote the replacement of fossil energy sources with green alternatives could be instrumental in managing systemic risk in the commodity market while also facilitating global sustainability. Finally, the results show that the impact of the Israeli-Palestinian conflict on both systemic risk and spillovers has been limited compared to the effects of COVID-19 and the Russia-Ukraine war.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100445"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142651524","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}

引用次数: 0

Importance of geopolitical risk in volatility structure: New evidence from biofuels, crude oil, and grains commodity markets 地缘政治风险在波动结构中的重要性：来自生物燃料、原油和谷物商品市场的新证据

IF 3.7 4区经济学 Q1 BUSINESS, FINANCE

Journal of Commodity Markets

Pub Date : 2024-12-01 Epub Date: 2024-10-16 DOI: 10.1016/j.jcomm.2024.100440

Renata Karkowska, Szczepan Urjasz

This paper aims to explore the complex linkages and evolving structure of price volatility in the global oil, biofuels, and grain commodity markets during periods of global turbulence. With the growing urgency for energy stability amid climate change, biofuels are gaining traction as a viable alternative energy source. However, their production can significantly impact essential commodities like grains and vegetable oils, increasing food prices and heightened market volatility. We introduced a TVP-VAR frequency connectedness method to address this, analyzing data from January 1, 2013, to September 29, 2023. Our approach offers a fresh perspective on market dynamics and geopolitical risks.

The study underscores the growing influence of agricultural shocks on energy markets, particularly within the ethanol sector. It confirms that the Russia-Ukraine war, a significant geopolitical event, has had a profound and enduring impact on the interconnectedness of these markets across various timeframes and frequencies. We offer concrete, actionable policy recommendations to mitigate the transmission of market shocks within the energy and food sectors, thereby bolstering investor and policymaker confidence and facilitating informed decision-making.

本文旨在探讨全球动荡时期全球石油、生物燃料和谷物商品市场价格波动的复杂联系和演变结构。随着气候变化对能源稳定性的要求日益迫切，生物燃料作为一种可行的替代能源正受到越来越多的关注。然而，生物燃料的生产会对谷物和植物油等基本商品产生重大影响，导致粮食价格上涨，加剧市场波动。为此，我们引入了 TVP-VAR 频率连通性方法，分析了 2013 年 1 月 1 日至 2023 年 9 月 29 日的数据。我们的方法为市场动态和地缘政治风险提供了一个全新的视角。研究强调了农业冲击对能源市场日益增长的影响，尤其是在乙醇行业。研究证实，俄乌战争这一重大地缘政治事件对这些市场在不同时间框架和频率下的相互关联性产生了深远而持久的影响。我们提出了具体可行的政策建议，以减轻市场冲击在能源和食品行业的传播，从而增强投资者和决策者的信心，促进知情决策。

{"title":"Importance of geopolitical risk in volatility structure: New evidence from biofuels, crude oil, and grains commodity markets","authors":"Renata Karkowska, Szczepan Urjasz","doi":"10.1016/j.jcomm.2024.100440","DOIUrl":"10.1016/j.jcomm.2024.100440","url":null,"abstract":"<div><div>This paper aims to explore the complex linkages and evolving structure of price volatility in the global oil, biofuels, and grain commodity markets during periods of global turbulence. With the growing urgency for energy stability amid climate change, biofuels are gaining traction as a viable alternative energy source. However, their production can significantly impact essential commodities like grains and vegetable oils, increasing food prices and heightened market volatility. We introduced a TVP-VAR frequency connectedness method to address this, analyzing data from January 1, 2013, to September 29, 2023. Our approach offers a fresh perspective on market dynamics and geopolitical risks.</div><div>The study underscores the growing influence of agricultural shocks on energy markets, particularly within the ethanol sector. It confirms that the Russia-Ukraine war, a significant geopolitical event, has had a profound and enduring impact on the interconnectedness of these markets across various timeframes and frequencies. We offer concrete, actionable policy recommendations to mitigate the transmission of market shocks within the energy and food sectors, thereby bolstering investor and policymaker confidence and facilitating informed decision-making.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"36 ","pages":"Article 100440"},"PeriodicalIF":3.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142445380","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}

引用次数: 0