Summer 2025

This paper investigates long-term Crude Oil (CL) price forecasting, focusing on the unobservable trend. The authors hypothesize that combining individual trend estimates improves accuracy and reduces risk. The paper compares five individual trend estimation methods (Cubic Polynomial, Symmetric MA, Hodrick-Prescott Filter, MODWT, and SS2000) and combine them using seven techniques (simple average, median, weighted average, MLR, PCA, FFNN, and the authors’ novel METS 2.0, which incorporates wavelet denoising). The authors argue that forecasting the trend itself, rather than the price, is crucial for long-term strategies. Using monthly NYMEX CL futures data (1983-2021), various statistical measures and an out-of-sample exercise computing 349, 347, 344, and 338 forecasts 1, 3, 6, and 12 months ahead, the authors find that combined trends outperform individual estimates, particularly METS 2.0 and MLR and show superior forecasting capacity in longer horizons.

This paper presents a dynamic risk measure called the Tail Climate Transition Risk Exposure (TCaRE) to evaluate industry portfolios’ exposure to climate transition risk (CTR) as firms transition to a low-carbon economy. CTR affects profitability by decreasing the value of companies engaged in polluting activities, which can lead to stranded assets. It relates to stricter climate policies, emerging technologies, and shifting consumer preferences. The authors employ carbon emission allowance prices as a key indicator of CTR to propose TCaRE based on a safety-first investment principle and utilize a tail estimator to analyze the impact of significant shifts in carbon prices in determining the links between stock and carbon returns.

This paper captures the comovement in price uncertainty of major agricultural, metals and energy commodity markets and assesses their macroeconomic effects for a set of advanced and emerging markets. Results show that an increase in the common commodity price uncertainty results in a drop in business investment and trade. Importantly, this methodology enables the disentangling of “good” and “bad” macroeconomic effects of oil price uncertainty: when an oil price uncertainty shock is common to all commodities, then the macroeconomic effect is likely to be negative, similar to a global demand shock. However, when the uncertainty shock is only specific to the oil market, the short-run effect tends to be positive.

This paper develops a set of innovative text-based indices capturing oil market sentiment and oil price uncertainty. The textual analysis includes over 6 million news items, spanning from January 1982 to June 2021. The evidence shows that sentiment indicators readily react to economic and geopolitical events impacting oil prices, thereby enabling said indicators to accurately predict the price of oil. In contrast, uncertainty measures have inherent weaknesses thus yielding unreliable oil price forecasts. This research results in a novel and robust text indicator that offers valuable insights into predicting the intricate dynamics of crude oil prices, particularly excelling in short-term forecasts and during periods of economic recessions.

In 2020, the International Maritime Organization implemented a limit to the sulphur content emitted by vessels. To comply, a vessel should either incur the capital cost to be retrofitted with a scrubber or burn fuels that emit less sulphur but are more expensive. The authors examine this dilemma by developing a Vector Error Correction Model that links freight rates, fuel prices, and the green investment decision of scrubber installation. The results, across the tanker and dry bulk sectors from 2021 to 2024, suggest that the freight premium of scrubber-fitted vessels positively depends on the spread between very low- and high-sulphur fuel oil prices and negatively on the size of the scrubber-fitted fleet. Scrubber investment, in turn, is determined by the past freight premium and the fuel spread. Being the first to investigate the interplay between green shipping investment and price uncertainty, the paper’s findings yield significant industry and policy implications.

Measures towards net-zero transition need to ensure the well-functioning of the market. This paper focuses on shipping where the existing environmental regulations lack consideration for the industry’s economic performance. The authors apply a stochastic frontier analysis to estimate the carbon, production, cost, and allocative efficiencies for 14 major shipping segments and 664 individual vessels. The paper’s findings suggest that carbon and production efficiencies have increased but cost efficiency has decreased from 2021 to 2024. There is scope for the average vessel to reduce its carbon emissions by 31%. Additionally, fuel is underused by 37% and capital is overused by 58%. Technical inefficiencies increase the total cost by 6%, with market price dynamics increasing it by 17%. The results suggest that, without further policy intervention and clear economic incentivization, there is limited potential for the industry to follow the energy transition pathway.

Lithium requirements will increase substantially in the energy transition – raising concerns about adequacy and affordability of lithium over the long term. A cumulative availability curve (CAC) helps assess these concerns. A CAC summarizes estimates of quantities, costs and locations of resources, which are key characteristics of future resource availability. With estimates of in situ resources and production costs for 150 conventional and unconventional lithium deposits, the CAC developed in this study shows that: in situ resources doubled between 2009 and 2023 to 726 million metric tonnes lithium carbonate equivalent (LCE), illustrating the dynamic nature of our knowledge of resources; cost estimates suggest an incentive price of US$12,500-$15,000 per metric tonne LCE, well below the peak price in 2023 but above the average price from 2011 to 2020; and resources are more geographically dispersed than current production. Production is not constrained by physical availability but by investment to convert resources into reserves, and further into operating mines and processing facilities, in ways that are environmentally and socially responsible.

With a simple decomposition method, the authors estimate the monthly shifts in global oil demand and non-OPEC+ supply that have occurred since 2010. The authors find evidence that during the Jan 2017 – Sep 2024 period, OPEC+ attempted to stabilize the price of crude oil much below the values assessed by market observers. Using a structural model of OPEC+’s behavior, the paper finds that judgmental errors regarding the size of market shocks that OPEC+ attempted to offset significantly increased after the start of the Pandemic due to the unprecedented nature and size of those shocks. Despite this, without OPEC+’s actions the price volatility would have been much higher than actual, nearly doubled during the Pre-Pandemic period (Jan 2017 – Feb 2020), and higher by 86 percent during the Pandemic (May 2020 – Jan 2022) and by 50 percent during the Ukraine War (Feb 2022 – Sept 2024). The paper’s results provide evidence that actions taken by consuming countries during the Ukraine War, such as coordinated releases from national stockpiles of crude oil, contributed to reduce price volatility by at least 20 percent (2.4 percentage points), a factor that OPEC+ appears to have factored into its production plans.

Mechanisms to incentivize divestment strategies, such as divestment schedules, are an important component of carbon reduction strategies. The authors use dynamic asset allocation methodologies to assess this impact over time on index portfolios (S&P 500 and FTSE 100), and global exchange-traded funds (ETFs). Although return profiles are not affected, the risk profile of S&P 500 divestment portfolios is impacted by rapid divestment strategies as divestment concentration increases. Instantaneous divestment may benefit management structure, while slower divestment provides greater stability in portfolios’ tracking errors and benefits carbon reduction, especially from reinvested capital. Divesting from energy and utilities sectors reduces the carbon footprint of up to 7%, while ETFs’ divesting from highly carbon concentrated ETFs offers further carbon footprint reductions. Investing in funds with a low carbon footprint results in lower dividend returns and management fees. Although ETFs’ returns are insensitive to divestment strategies and schedules, their risk profiles are affected, proportionally to their carbon intensity, especially for rapid divestment and at the expense of higher tracking errors. Divestment strategies based on ESG rating screening of FTSE 100 portfolios improve diversification and impact risk/return performance. The paper’s study underscores the importance of considering such factors as dividends, management structure, and carbon reduction targets.

The analysis of the impact of a tariff war on commodities is more complex than one might anticipate. Changes in tariff policy by one country always set off retaliation by other countries, and responses are not limited to counter tariffs but can also involve regulations, export controls, and sanctions. In the land of an eye-for-an-eye, one can easily be blindsided by unanticipated consequences as behavioral feedback effects bounce through a complex global economic system. There are three pillars to the paper’s framework for tariff analysis. (1) Every policy shift is interconnected, and one should not analyze a specific policy shift on its own. (2) One should divide the analysis into a transition period and the longer-run equilibrium to appropriately consider the short-term serious implications of shocking the global economic system. And (3) focus on the two primary competing narratives. That is, there are often two competing narratives of what may occur given policy shocks and markets will tend to price the probability-weighted average of the two different and competing scenarios until it becomes clear which narrative is more correct. The bottom line is that when there are multiple major policy shifts underway simultaneously, the analysis quickly gets exponentially more complex, and a simple bilateral trade analysis will always be misleading and potentially far off the mark.

Nearly every investor in the mining sector recognizes the adage, “Good management can turn a mediocre project into a success, while poor management can ruin a good one.” Interviews with sophisticated investors affirm that management critically impacts investment success or failure. Despite the belief that the people aspects may outweigh technical, ESG, and other considerations, many investors lack robust tools and methodologies for an impartial management due diligence process. Current due diligence focuses on more tangible “below ground risks,” such as ore reserves, mine plans, and costs, and “on the ground risks,” including environmental and social factors. An overview of current management due diligence practices and recommendations for best practices for mining investors to ensure a more rigorous process are presented.

The Commodity Insights Digest is delighted to have the opportunity to interview Menelaos Vakalopoulos. In this interview, he discusses how his professional journey evolved where he learned that “it is crucial to take risks and seize opportunities,” particularly early in one’s career. He notes that it is becoming essential for professionals in the energy sector to get comfortable with Python or similar programming languages: the “volume of data … is expanding quickly, and a lot of the traditional software used in the industry just cannot keep up,” he explained. Vakalopoulos also provided his view that the “future is not about fossil fuels disappearing overnight — it is about a gradual transformation toward a cleaner and more flexible energy system.”  Finally, he discusses his view that networking is one of the biggest accelerators for career growth.