Commodities

We analyze extreme gold price movements between 1975 and 2025 using Extreme Value Theory (EVT). Using both the Block-Maxima and Peaks-over-Threshold approaches on a daily return basis, we estimate Value-at-Risk (VaR) and Expected Shortfall (ES) for the entire distribution focusing on a long-term view. Our results demonstrate that models based on the standard normal distribution systematically underestimate extreme risks, whereas EVT provides more reliable measures. In particular, EVT captures not only rare losses, but also sudden positive rallies, highlighting gold’s dual function as a risk and opportunity asset. Asymmetries emerge in the analysis: at the 0.99 quantile, losses appear larger in absolute value than gains. At the 0.995 quantile, in some episodes, upside extremes dominate. Furthermore, we find that geopolitical and economic shocks, including the oil crises, the 2008 financial crisis, and the COVD-19 pandemic, leave distinct signatures in the extremes. By covering five decades, our study provides the most extensive EVT-based assessment of gold risks to date. Our findings contribute to debates on financial stability and provide practical guidance for investors seeking to manage tail risks while recognizing gold’s potential as both a safe haven and a speculative asset. Full article

The global push for electrification and decarbonization has sharply increased demand for critical raw materials—especially lithium and copper—heightening financial and strategic pressures on firms that lead these supply chains. Yet, the systemic financial risks arising from inter-firm interdependencies in this sector remain largely unexplored. This article presents a novel distance-based network framework to analyze systemic risk among the world’s top 15 lithium and copper producers (2020–2024). Firms are represented through standardized vectors of profitability and risk indicators (liquidity–solvency), from which we construct a two-layer similarity network using Euclidean distances. Graph-theoretic tools—including Minimum Spanning Tree, eigenvector centrality, modularity detection, and contagion simulations—reveal the structural properties and transmission pathways of financial shocks. The results show a robust-yet-fragile topology: while stable under minor perturbations, the network is highly vulnerable to failures of central firms. These findings highlight the utility of distance-based network models in uncovering hidden fragilities in critical commodity sectors, offering actionable insights for macroprudential regulators, investors, and corporate risk managers amid growing geopolitical and financial entanglement. Full article

Cryptocurrencies such as Bitcoin can be classified as commodities under the Commodity Exchange Act (CEA), giving the Commodity Futures Trading Commission (CFTC) jurisdiction over those cryptocurrencies deemed commodities, particularly in the context of futures trading. This paper presents a method for predicting both long- and short-term trends in selected cryptocurrencies based on the Fractal Market Hypothesis (FMH). The FMH applies the self-affine properties of fractal stochastic fields to model financial time series. After introducing the underlying theory and mathematical framework, a fundamental analysis of Bitcoin and Ethereum exchange rates against the U.S. dollar is conducted. The analysis focuses on changes in the polarity of the ‘Beta-to-Volatility’ and ‘Lyapunov-to-Volatility’ ratios as indicators of impending shifts in Bitcoin/Ethereum price trends. These signals are used to recommend long, short, or hold trading positions, with corresponding algorithms (implemented in Matlab R2023b) developed and back-tested. An optimisation of these algorithms identifies ideal parameter ranges that maximise both accuracy and profitability, thereby ensuring high confidence in the predictions. The resulting trading strategy provides actionable guidance for cryptocurrency investment and quantifies the likelihood of bull or bear market dominance. Under stable market conditions, machine learning (using the ‘TuringBot’ platform) is shown to produce reliable short-horizon estimates of future price movements and fluctuations. This reduces trading delays caused by data filtering and increases returns by identifying optimal positions within rapid ‘micro-trends’ that would otherwise remain undetected—yielding gains of up to approximately 10%. Empirical results confirm that Bitcoin and Ethereum exchanges behave as self-affine (fractal) stochastic fields with Lévy distributions, exhibiting a Hurst exponent of roughly 0.32, a fractal dimension of about 1.68, and a Lévy index near 1.22. These findings demonstrate that the Fractal Market Hypothesis and its associated indices provide a robust market model capable of generating investment returns that consistently outperform standard Buy-and-Hold strategies. Full article

The objective of this research is to understand the relationship between the tone of information released in government harvest reports, in extreme market conditions (rising and falling), and the behavior of agricultural commodity prices. In the period between January/2017 and February/2023, an autoregressive model of moving averages was used with a generalized autoregressive conditional heteroscedasticity approach. The evidence allows us to infer that investors can, on some occasions, use this information to direct their portfolios in order to balance risk and return. However, the full impact of the tone is not reflected immediately, possibly requiring time to be absorbed. Depending on the informational weight, the commodity, and the market context, there may or may not be an impact. This divergent empirical evidence indicates that there is a complex relationship between tone reading and asset pricing. Full article

We study Portugal’s household electricity retail market after legal liberalisation, quantifying market concentration (Herfindahl–Hirschman Index (HHI) and the four-firm concentration ratio (CR4)), consumer switching, and asymmetric wholesale-to-retail price pass-through. Using monthly data for January 2014–December 2019 (primary sample) and robustness checks for 2008–2022, we compute concentration indices from ERSE supplier shares, analyse switching dynamics, and estimate nonlinear autoregressive distributed lag (NARDL) models that decompose wholesale price changes into positive and negative components. The retail market remains highly concentrated during the primary window (HHI ≈ 6300–6800 using shares expressed as percentages on a 10,000 scale); switching rose after deregulation but stabilised at moderate monthly rates; and long-run pass-through is estimated at β⁺ ≈ 0.55–0.61 for wholesale increases and β⁻ ≈ 0.49 for decreases (Wald tests reject symmetry at conventional levels). Results are robust to alternative concentration metrics, exclusion of 2022, and varied lag orders. Policy implications emphasise tariff simplification, active consumer-activation measures, and regular monitoring of concentration and pass-through metrics. Full article

This study investigates the impact of the COVID-19 pandemic on the Tokyo mango market by combining transaction data from the Ota Fruit Market with Google Mobility indices. In Japan, mangoes are regarded as a luxury fruit, largely dependent on imports and associated with high domestic production costs, which positions them as premium commodities. To assess the influence of price dynamics and human mobility on mango trading volumes during the pandemic, this study employs an autoregressive distributed lag (ARDL) model. The long-run results indicate that mango demand was positively associated with increased residential activity: a 1% rise in time spent at home during the COVID era corresponded to an increase of 786 kg in trade volume. Similarly, a 1% increase in time spent in retail and recreation areas was associated with a 364 kg rise in trade volume. In contrast, time spent in grocery and pharmacy locations showed no statistically significant effect. In the short run, fluctuations in mobility patterns and price levels contributed to variations in demand, with sales volumes adjusting toward their long-run equilibrium. The mobility indices exhibited mixed short-term effects on trade volumes. Notably, the analysis revealed that mango trading volumes rebounded in 2022, coinciding with the easing of pandemic-related disruptions. Full article

As global economies accelerate their energy transitions, the photovoltaic sector faces critical challenges linked to material supply, security, and sustainability. Solar-grade silicon, enabling over 90 percent of photovoltaic technologies, has become a strategic commodity underpinning the expansion of renewable energy infrastructures. This short communication examines the evolving role of solar-grade silicon within the global energy transition, moving beyond its traditional classification as a technical material to frame it as a commodity of geopolitical and economic significance. We analyze recent price trends, regional production asymmetries, and trade dependencies, identifying key vulnerabilities in current supply chains. Although alternative photovoltaic materials such as perovskites and organics attract research interest, their commercial immaturity reinforces the centrality of silicon. The novelty of this contribution lies in treating solar-grade silicon through a commodity lens, integrating techno-economic metrics with policy and investment considerations. We highlight opportunities for reinforcing supply resilience through domestic production, circular economy strategies such as silicon recovery and reuse, and diversification of technological pathways. Our findings advocate for the inclusion of solar-grade silicon in strategic resource planning and industrial policy frameworks. Recognizing its unique position at the intersection of energy, technology, and trade is essential to achieving secure, scalable, and sustainable photovoltaic deployment worldwide. Full article

Artisanal fishing is a central pillar of the Angolan economy, particularly in the southern province of Namibe, where it serves as the primary economic activity for numerous coastal communities. However, these communities face significant challenges, including competition from expanding industrial fisheries and inadequate infrastructure at fishing centers, which hampers the storage, preservation, and transportation of catches. These limitations contribute to post-harvest losses and the reduced market value of products, despite the region’s rich diversity of pelagic and demersal resources. This study evaluated the economic viability of artisanal fishing in Namibe under three production scenarios, varying in catch levels and the inclusion of fish processing activities such as dried fish and fishmeal production. Scenario A (pessimistic) assumed a 10% reduction in production compared to the best estimates; Scenario B (intermediate) was based on average reported catches; and Scenario C (optimistic) considered a 10% increase in catches, accounting for seasonal and environmental variability. Results indicated that artisanal fishing was economically viable under all scenarios, with the Internal Rate of Return (IRR) consistently exceeding the Minimum Attractive Rate of Return (MARR) of 7.5%. IRR values ranged from 34.30% (Scenario A, without by-product commercialization) to 106.28% (Scenario C, with dried fish and fishmeal production and sales), representing a more than threefold increase in profitability. This substantial gain underscores the transformative potential of processing by-products into higher-value commodities, enabling integration into larger-scale and more liquid markets. Such value addition supports the concept of a proximity economy by promoting short production cycles, reducing intermediaries, and strengthening local value chains. Beyond financial returns, the findings suggest broader socioeconomic benefits, including local economic growth, job creation, and the preservation of traditional production knowledge. The payback period was less than four years in all cases, decreasing to 1.94 years in the most favorable scenario. By-products such as dried fish and fishmeal exhibit commodity-like characteristics due to their higher commercial value, increasing demand, and potential integration into regional and animal feed markets. In conclusion, diversifying marketing strategies and maximizing the use of fish resources can significantly enhance the economic sustainability of artisanal fishing, foster socioeconomic inclusion, and support the development of artisanal fishing communities in Namibe. Full article

Gum arabic production is a key source of income for communities in several African countries. Despite this, producing nations capture only a small share of the market value due to weak domestic markets, low price incentives, and limited value-added. Meanwhile, global demand is expected to grow from USD 1.1 billion in 2025 to USD 2.2 billion by 2035, driven by rising consumption in food, pharmaceuticals, cosmetics, and textiles. Importing countries, such as France and the US, benefit from significantly higher export prices—French export prices rose from USD 1.58/kg to USD 4.63/kg—highlighting the value added from outside producer regions. This study uses a qualitative analytical approach to examine trends and challenges in enhancing value capture within producer countries. Key strategies include local value-added, collective action, compliance with international standards, market transparency, and direct trade linkages. Findings suggest that implementing these measures could raise farmgate prices by 30–50%, retain more value within African economies, and improve access to premium export markets. In conclusion, targeted interventions are crucial for strengthening the gum arabic supply chain and promoting sustainable and equitable collection practices in producer countries. Full article

Futures and forward contracts together offer farmers of all sizes important tools for shifting and managing production risk. This risk shifting is particularly apparent in the U.S. grain complex, where the United States also has a significant export position. Because of this international reach, we argue that the futures and forward markets play a critical role in reducing world food insecurity and thus contribute to satisfying Sustainable Development Goal #2: Zero Hunger. We further argue that the presence of investors willing to take the opposite side of the farmers’ natural short hedge helps futures markets perform their key functions of price discovery and risk management. In addition to these roles, futures markets also enable farmers to finance their crops more efficiently over the production cycle, supporting operational stability. Finally, we highlight that agricultural markets in the United States are supported by significant regulation at the county, state, and federal levels. These farming regulations, coupled with federal oversight of agricultural futures markets, provide sufficient confidence that the goal of Zero Hunger is being pursued in an appropriate and effective manner, reinforcing the case for agricultural futures as a meaningful component of a broader sustainable investment strategy. Full article

The enforcement of the European Union Deforestation Regulation (EUDR) may reduce the supply of natural rubber to the European Union (EU), potentially leading to price increases due to the inelastic nature of rubber demand. This study assesses the potential financial implications for smallholder producers in Ghana, considering both the opportunities and risks associated with the evolving regulatory environment under EUDR and local market access conditions. A cost–benefit analysis (CBA) was conducted to evaluate the impact of different EUDR-related export decline scenarios on the net present value (NPV) of a standard 4-hectare plantation. The results suggest that even a minor 2.5% decline in global exports to the EU could increase the NPV by 17% for an independent compliant producer. However, a simulated COVID-19-like crisis in the fifth year of production leads to a 20% decline in NPV, reflecting vulnerability to external shocks. Based on these findings, the study identifies two priorities. This first is improving the coordination and harmonization of compliance efforts across the value chain to enable more producers to benefit from potential EUDR-related price increases. The recent creation of the Association of Natural Rubber Actors of Ghana (ANRAG) presents an opportunity to support such collective mechanisms. Second, minimizing losses during demand shocks requires the Tree Crops Development Authority (TCDA) to establish clear rules and transparent reporting for authorizing unprocessed rubber exports when factories reduce purchases due to low international prices—thus preserving market access for vulnerable producers. Together, these approaches would ensure that the potential benefits of the EUDR are realized inclusively, remain stable despite market downturns, and do not undermine value addition in domestic processing factories. Full article

The phenomenon of rising forward price volatility, both historical and implied, as maturity approaches is referred to as the Samuelson effect or maturity effect. Disregarding this effect leads to significant mispricing of early-exercise options, extendible options, or other path-dependent options. The primary objective of the research is to identify a practical way to incorporate the Samuelson effect into the evaluation of commodity derivatives. We choose to model the instantaneous variance employing the exponential decay parameterizations of the Samuelson effect. We develop efficient calibration techniques utilizing historical futures data and conduct an analysis of statistical errors to provide a benchmark for model performance. The study employs 15 years of data for WTI, Brent, and NG, producing excellent results, with the fitting error consistently inside the statistical error, except for the 2020 crisis period. We assess the stability of the fitted parameters via cross-validation techniques and examine the model’s out-of-sample efficacy. The approach is generalized to encompass seasonal commodities, such as natural gas and electricity. We illustrate the application of the calibrated model of instantaneous variance for the evaluation of commodity derivatives, including swaptions, as well as in the evaluation of power purchase agreements (PPAs). We demonstrate a compelling application of the Samuelson effect to a widely utilized auto-callable equity derivative known as the snowball. Full article

The COVID-19 pandemic had significant global impacts. In Japan, consumers refrained from going out, and dining out decreased significantly, which strongly affected the restaurant industry and resulted in a shift in food demand from eating out to home consumption. The seafood industry is no exception to this trend. This study surveyed 300 individuals with experience in seafood transactions across wholesalers, restaurants, and retailers to examine how the pandemic influenced supply and demand patterns from a distribution perspective. Results indicated that while the volume of luxury seafood handled by restaurants and wholesalers decreased, the volume handled by retailers increased. Conversely, the volume of inexpensive popular seafood declined across all three sectors. The findings suggest that some of the luxury seafood previously sold to restaurants was redirected to retailers as consumer demand shifted from dining out to home consumption during the pandemic. Full article

Weather derivative markets, particularly Chicago Mercantile Exchange (CME) Heating Degree Day (HDD) and Cooling Degree Day (CDD) futures, face challenges from complex temperature dynamics and spatially heterogeneous co-extremes that standard Gaussian models overlook. Using daily data from 13 major U.S. cities (2014–2024), we first construct a two-stage baseline model to extract standardized residuals isolating stochastic temperature deviations. We then estimate the Extreme Value Index (EVI) of HDD/CDD residuals, finding that the nonlinear degree-day transformation amplifies univariate tail risk, notably for warm-winter HDD events in northern cities. To assess multivariate extremes, we compute Tail Dependence Coefficient (TDC), revealing pronounced, geographically clustered tail dependence among HDD residuals and weaker dependence for CDD. Finally, we compare Gaussian, Student’s t, and Regular Vine Copula (R-Vine) copulas via joint VaR–ES backtesting. The R-Vine copula reproduces HDD portfolio tail risk, whereas elliptical copulas misestimate portfolio losses. These findings highlight the necessity of flexible dependence models, particularly R-Vine, to set margins, allocate capital, and hedge effectively in weather derivative markets. Full article

Oil inventories are essential in alleviating realized and anticipated supply shocks and represent a key market indicator. This study examines the responses of global and country oil inventories to supply shocks under tight and loose market conditions. We utilize an expanded version of the GVAR model, adding the OECD oil inventories variable, incorporating major oil-producing countries: Iran, Russia, and Venezuela, and extending the coverage period. Our simulations indicate that a negative global supply shock significantly affects oil inventories under “tight” market conditions. The model correctly predicts the trajectory of changes to oil inventories in South Korea following a supply shock to Russian production in tight markets and Iranian output in loose markets. This case also shows that commercial players, using their inventories as a buffer, can negate government attempts to maintain constant levels of reserves. Overall, the response to the oil inventory tends to vary across producing and importing countries and market conditions. Such dynamics highlight potential problems with specific policies, such as using inventories as a buffer to alleviate price fluctuations or disrupting the oil production of individual countries through sanctions, as these measures oftentimes result in unintended consequences due to complex interconnections of the global oil market. Full article

In this study, Gaussian process (GP) regression is used to normalize observed commodity data and produce predictions at densely interpolated time intervals. The methodology is applied to an empirical oil price dataset. A Gaussian kernel with data-dependent initialization is used to calculate prediction means and confidence intervals. This approach generates synthetic data points from the denoised dataset to improve prediction accuracy. From this augmented larger dataset, a procedure is developed for estimating an upcoming crash-like behavior of the commodity price. Finally, multiple data-science-driven algorithms are used to demonstrate how data densification using GP regression improves the detection of forthcoming large fluctuations in a particular commodity dataset. Full article

The exploitation of the Amazon biome in search of net profit, specifically in the production of cocoa (Theobroma cacao) and açaí (Euterpe oleracea), has caused deforestation, degradation of natural resources, and high greenhouse gas (GHG) emissions, highlighting the urgency of improving the environmental, economic and social sustainability of these crops. These species were selected for their rapid expansion in the Amazon, driven by global demand, their local economic relevance, and their potential to either promote conservation or drive deforestation, depending on the production system. This study analyzes the pillars of environmental, social, and economic sustainability of cocoa and açaí production systems in the Amazon, comparing monoculture, agroforestry, and extractivism to support forest conservation strategies in the biome. Analysis of the environmental life cycle, social life cycle, and economic performance were used to determine the carbon footprint, the final point of workers, and the net profit of the activities. According to the results found in this study, cocoa monoculture had the largest carbon footprint (1.35 tCO₂eq/ha), followed by agroforestry (1.20 tCO₂eq/ha), açaí monoculture (0.84 tCO₂eq/ha) and extractivism (0.25 tCO₂eq/ha). In the carbon balance, only the areas outside indigenous lands presented positive carbon. Regarding the economic aspect, the net profit of açaí monoculture was USD 6783.44/ha, extractivism USD 6059.42/ha, agroforestry USD 4505.55/ha, and cocoa monoculture USD 3937.32/ha. In the social sphere, in cocoa and açaí production, the most relevant negative impacts are the subcategories of child labor and gender discrimination, and the positive impacts are related to the sub-category of forced labor. These results suggest that açaí and cocoa extractivism, under responsible management plans, offer a promising balance between profitability and environmental conservation. Furthermore, agroforestry systems have also demonstrated favorable outcomes, providing additional benefits such as biodiversity conservation and system resilience, which make them a promising sustainable alternative. Full article

Debt-for-nature instruments are financial transactions that allow countries to restructure and reduce foreign debt in exchange for investments in environmental conservation measures. Can debt-for-nature instruments attract more capital for biodiversity finance? Debt-for-nature instruments first appeared in the market in the 1980s; however, they have seen a recent surge in popularity, with transactions predominantly focused on marine conservation. These transactions have gained attention for their size, innovative nature, and conservation focus. However, they have also faced criticism surrounding sovereignty, effectiveness, and transaction costs. The descriptive qualitative analysis of a comprehensive and global sample of the eight tripartite type debt-for-nature instruments brought to market since 2015, with a detailed case study of the Belize transaction, indicates that such deals may be costly to negotiate, the use of blue bond labeling can be misleading, conservation benefits are limited, and they have limited replicability. On the positive side, these deals have introduced innovative structures to unlock additional funds for conservation. The best examples are structured with a larger financial commitment to nature and strong enforcement mechanisms. In some cases, the transaction laid the groundwork for future marine conservation funding and commitments. Debt-for-nature instruments are not a silver bullet for either environmental impact or debt refinancing; however, the benefits of recent transactions indicate a role for such innovative instruments in conservation finance. Full article

The COVID-19 pandemic and the Russia–Ukraine war have struck the world’s energy markets. This study analyzed how the recent unstable fossil fuel markets impacted the Japanese electricity contracts, classified as extra-high-, high-, and low-voltage contracts. Multiple structural break tests were conducted to endogenously determine breaks affecting electricity prices during January 2019 to November 2022. By incorporating the effects of these breaks in the autoregressive distributed lag (ARDL) model, the study analyzed the effects of natural gas, coal, and crude oil prices on the types of electricity contract prices. The results of the analyses indicated a surge in electricity prices for low- and high-voltage contracts driven by an increase in natural gas. The results imply the importance of providing proper financial support to mitigate the effects of soaring electricity prices and implementing policies to diversify the electricity generation mix in Japan. Full article