{"title":"Performance of systemic stress in agricultural commodities and its implication for volatility prediction in SSA equities","authors":"Qingying Zheng , Jintao Wu , Boqiang Lin","doi":"10.1016/j.jcomm.2025.100480","DOIUrl":"10.1016/j.jcomm.2025.100480","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100480"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144178566","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}
{"title":"Supply and Demand shocks: the short-term and long-term drivers of oil price uncertainty","authors":"Theodora Bermpei , Athanasios Triantafyllou","doi":"10.1016/j.jcomm.2025.100495","DOIUrl":"10.1016/j.jcomm.2025.100495","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100495"},"PeriodicalIF":3.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631106","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}
Martina Danielova Zaharieva, Audronė Virbickaitė, André Portela Santos
{"title":"Intraday volatility transmission in global energy markets: A Bayesian nonparametric approach","authors":"Martina Danielova Zaharieva, Audronė Virbickaitė, André Portela Santos","doi":"10.1016/j.jcomm.2025.100496","DOIUrl":"10.1016/j.jcomm.2025.100496","url":null,"abstract":"<div><div>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 <em>heat wave</em> and <em>meteor shower</em> 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.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"39 ","pages":"Article 100496"},"PeriodicalIF":4.5,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766993","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}
Ahmed H. Elsayed , Giray Gozgor , Rabeh Khalfaoui , Salma Tarchella
{"title":"Impact of supply chain pressure on traditional energy and metal markets: A Wavelet-based Quantile-on-Quantile perspective","authors":"Ahmed H. Elsayed , Giray Gozgor , Rabeh Khalfaoui , Salma Tarchella","doi":"10.1016/j.jcomm.2025.100472","DOIUrl":"10.1016/j.jcomm.2025.100472","url":null,"abstract":"<div><div>This paper investigates the impact of the global supply chain pressure and geopolitical tensions on prominent energy and metals markets using data from January 1998 to April 2023. To this end, the study adopts Wavelet-based Quantile-on-Quantile estimations to scrutinise the time-varying nature of the relationships over the sample period and under different market conditions. The results reveal that the global supply chain pressure predicts commodity returns across various time horizons and quantiles, particularly during extreme supply chain pressures. Conversely, the impacts of geopolitical risks are more pronounced in the short- and mid-term, suggesting investors adjust energy and metal investments accordingly. The paper also indicates that commodities can play a dual role as investment and diversification assets, offering a hedge against global supply chain disruptions and geopolitical events. These findings contribute valuable insights into risk management, investment strategies, and policymakers' decision-making processes.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100472"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143684301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Assessing government expenditures multipliers under oil price swings","authors":"El Mostafa Bentour","doi":"10.1016/j.jcomm.2025.100477","DOIUrl":"10.1016/j.jcomm.2025.100477","url":null,"abstract":"<div><div>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.</div><div>- 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.</div><div>- 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.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100477"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918318","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}
{"title":"The short- and long-run cyclical variation of the cross-asset nexus: Mixed-frequency evidence on financial and ‘financialised’ assets","authors":"Menelaos Karanasos , Stavroula Yfanti , Jiaying Wu","doi":"10.1016/j.jcomm.2025.100462","DOIUrl":"10.1016/j.jcomm.2025.100462","url":null,"abstract":"<div><div>We study the dynamic interdependence between stocks, a risky and financial ‘by definition’ asset class, and the ‘financialised’ assets from the real estate and commodity markets. We first introduce a new multivariate corrected Dynamic Conditional Correlations Mixed-Data Sampling (cDCC-MIDAS) model through which we analyse short- and long-run time-varying correlation dynamics among stocks, real estate, and five commodity types with direct implications for risk management and portfolio optimisation. The correlation analysis identifies short- and long-run hedging properties and interdependence types and concludes on strong countercyclical cross-asset interlinkages, highly dependent on the state of the economy in most cases (contagion effects) and weak procyclical connectedness for certain safe-haven assets (flight-to-quality). We further investigate the macro-relevance and crisis-vulnerability of the correlations’ evolution by unveiling the macro-determinants of asset co-movements. The economic environment plays a key role as a contagion or flight-to-quality transmitter, outweighing the effects of economic linkages among assets, while the uncertainty channel intensifies the macro impact on the cross-asset nexus.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100462"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andreas Andrikopoulos , Anna Merika , Nikolaos Stoupos
{"title":"The effect of oil prices on the US shipping stock prices: The mediating role of freight rates and economic indicators","authors":"Andreas Andrikopoulos , Anna Merika , Nikolaos Stoupos","doi":"10.1016/j.jcomm.2025.100474","DOIUrl":"10.1016/j.jcomm.2025.100474","url":null,"abstract":"<div><div>We explore the effect of oil prices on shipping stocks and freight rates, delivering evidence that the effect of oil prices on stock prices is mediated by the effect of oil prices on freight rates and, thereof, the effect of freight rates on the stocks of US-listed shipping companies. Our data set runs from 2018 to 2023, and our methodological arsenal includes error correction models, MIDAS and Granger causality. In this context, we discover that after the Covid19 pandemic and during the Russo-Ukrainian war the interactions between oil prices, freight rates and stock prices have been disrupted, turning the effect of freight rates on stock prices from non-causal to causal and the effects of oil prices on freight rates from negative to positive.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100474"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xingyu Dai , Imran Yousaf , Jiqian Wang , Qunwei Wang , Chi Keung Marco Lau
{"title":"The pass-through of macro variable to volatility co-movement among U.S. currency and commodity futures markets system","authors":"Xingyu Dai , Imran Yousaf , Jiqian Wang , Qunwei Wang , Chi Keung Marco Lau","doi":"10.1016/j.jcomm.2025.100463","DOIUrl":"10.1016/j.jcomm.2025.100463","url":null,"abstract":"<div><div>This paper explores how the U.S. macro variable influences volatility co-movement in currency and commodity futures markets system. It does this by using the Dynamic Equicorrelation-Mixed Data Sampling-X model, and then calculating the daily realized volatility (RV), good volatility (GV), and bad volatility (BV) of 22 futures using 5-min high-frequency data. The Hodrick-Prescott filter method is applied to compute the raw, cycle, and trend components of the news for 17 macro variables and 4 principal components of these macro variables. There are three key study findings. First, the raw component of monetary policy uncertainty is the best fit for RV co-movement, while the raw component of trade policy uncertainty is the best fit for GV and BV co-movement. Second, almost all macro variables show that the trend component news do not affect volatility co-movement. Finally, the duration of the impact of macro variables exceeds 4 months, while the influence of raw news on BV co-movement is generally shorter. The macro variable information also helps currency and commodity futures investors to make global minimum variance portfolio optimization.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100463"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trading-hour and nontrading-hour volatility in crude oil and U.S. dollar markets and its implications for portfolio optimization","authors":"Yu-Sheng Lai","doi":"10.1016/j.jcomm.2025.100479","DOIUrl":"10.1016/j.jcomm.2025.100479","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100479"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143947296","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}
{"title":"Predicting commodity returns: Time series vs. cross sectional prediction models","authors":"Timotheos Angelidis , Athanasios Sakkas , Nikolaos Tessaromatis","doi":"10.1016/j.jcomm.2025.100475","DOIUrl":"10.1016/j.jcomm.2025.100475","url":null,"abstract":"<div><div>Commodity cross-sectional models based on the commodity momentum, basis, and basis-momentum factors generate superior time-series and cross-sectional commodity return forecasts compared to the historical average and time-series forecasting models that use financial, macroeconomic, and commodity-specific variables as predictors. Timing and long-short strategies based on the commodity premium forecasts from cross-sectional models achieve significant utility gains compared to strategies based on the historical average or time series predictive models’ forecasts. Our evidence is robust across many commodities and different forecasting methodologies.</div></div>","PeriodicalId":45111,"journal":{"name":"Journal of Commodity Markets","volume":"38 ","pages":"Article 100475"},"PeriodicalIF":3.7,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}