Commodities

The dynamic structure of electricity markets, where uncertainties abound due to, e.g., demand variations and renewable energy intermittency, poses challenges for market participants. We propose generative adversarial networks (GANs) to generate synthetic electricity price data. This approach aims to provide comprehensive data that accurately reflect the complexities of the actual electricity market by capturing its distribution. Consequently, we would like to equip market participants with a versatile tool for successfully dealing with strategy testing, risk model validation, and decision-making enhancement. Access to high-quality synthetic electricity price data is instrumental in cultivating a resilient and adaptive marketplace, ultimately contributing to a more knowledgeable and prepared electricity market community. In order to assess the performance of various types of GANs, we performed a numerical study on Turkey’s intraday electricity market weighted average price (IDM-WAP). As a key finding, we show that GANs can effectively generate realistic synthetic electricity prices. Furthermore, we reveal that the use of complex variants of GAN algorithms does not lead to a significant improvement in synthetic data quality. However, it requires a notable increase in computational costs. Full article

In this study, we investigate the ability of three higher-order risk-neutral return cumulants to predict short maturity (weekly) returns of oil futures. Our data includes weekly West Texas Crude Oil futures options that expire in 7 days (7DTE). Using a model-free approach, we estimate these risk-neutral return cumulants at the beginning of each options expiration cycle. Our results suggest that the third risk-neutral return cumulant consistently predicts the returns of various oil futures (including WTI, Brent, Dubai, Heating Oil, and RBOB Gasoline). We compare our findings with 14 other predictors and offer a theoretical explanation for the negative coefficient observed for the 7DTE third risk-neutral return cumulant. Our theory connects higher-order risk-neutral return cumulants with the risk premiums of oil futures. Furthermore, our quantitative investment strategy favors the predictability of oil futures returns. Full article

We revisit, and document new facts regarding, the financialization of U.S. energy markets in 2000–2010. We show that, after controlling for macroeconomic factors and physical energy market fundamentals, the strength of energy markets’ co-movements with the U.S. stock market is positively related to the energy paper market activity of hedge funds that trade both asset classes. This relation weakens when credit risk is elevated. We find, in contrast, no link with the aggregate positions of commodity index traders in energy futures markets. Our findings have implications for the ongoing debate regarding the financialization of commodities. Full article

The COVID-19 pandemic, with increased home cooking and decreased restaurant dining, significantly altered seafood consumption patterns. By applying an ordered logit model to identify factors affecting seafood consumption during the pandemic, this study found that the shift in seafood consumption was driven by factors such as changes in meal preparation methods, more time spent at home, and shifts in financial situations. While take-out consumption boosted overall seafood intake, popular varieties saw a rise in home consumption, while high-end seafood suffered from decreased demand as consumers focused more on home dining. This study underscores the importance of supporting suppliers, restaurants, and retailers dealing with high-end seafood, as they face economic challenges due to reduced consumption. In summary, pandemic-induced restrictions on mobility led to a notable transition from restaurant-prepared seafood to home-cooked options, highlighting the need for targeted policies to aid affected sectors. Full article

This study aims to investigate the impact of the banking sector on economic growth and commodity prices. Through panel data analysis, the research explores the relationship between the banking sector and economic growth in Spain, France, and Romania from 2000 to 2020. The findings reveal a positive correlation between the strength of the banking sector and economic growth across these nations, underscoring its pivotal role in fostering economic expansion and subsequently improving commodity prices. Additionally, this study evaluates various regulatory measures crucial ensuring the banking sector’s sustainability and preventing financial crises, including credit risk management, lending policies, liquidity constraints, and international financing and investment strategies. By analyzing the interplay between regulatory measures and banking sector performance, incorporating variables such as non-performing loans, household debt, liquid liabilities, government consumption expenditure, foreign investments, and trade openness, this research provides policymakers with valuable insights to formulate effective strategies for promoting economic stability and ensuring the sustainability and growth of the banking sector. Full article

The Seychelles blue bond is an innovative finance mechanism that has played a pivotal role in shaping the global landscape of blue bonds. Seychelles leadership in the blue economy sets a significant precedent. However, this precedent has also raised concerns among various stakeholders. This study evaluates of Seychelles’ sovereign blue bond, which was co-developed by the government of Seychelles and the World Bank. Three themes are explored, how the blue bond relates to other actors and donors in the blue economy space of Seychelles; how the blue bond contributes to advancing the national agenda and blue economy of Seychelles; and the key strengths, enablers and weaknesses of the blue bond. A series of considerations for future blue financing and blue bond mechanisms are presented, based on the findings of this study, to ensure that financing extends beyond blue washing and contributes meaningfully to the holistic transition to a sustainable blue economy. Our findings imply significant considerations for stakeholders in sustainable finance, suggesting ways to enhance the efficacy of blue bonds and emphasising the need for further research on their long-term impact and integration with other financial instruments. Full article

This study presents a comprehensive bibliometric analysis conducted in R Studio of the scientific landscape regarding commodity markets, trading strategies, sustainable production, integration of technologies such as machine learning, and their economic impacts, covering publications from 1974 to 2023. Employing a sophisticated query in Scopus, we meticulously compiled and analyzed data, revealing an annual growth rate of 10.46% in related scientific publications, with an average citation rate of 6.60 per document. The results indicate sustained interest in commodity research over time, with a significant increase observed in scientific production, particularly since the early 2008s. International collaboration is prominent, reflecting the global nature of research in commodity markets. Key themes such as “futures markets”, “commodity prices”, and “energy commodities” emerge from the analysis of keywords and bigrams, highlighting areas of interest within the field. Additionally, thematic mapping highlights emerging and niche themes in commodity research, providing insight into evolving trends and areas of specialization. Factorial analysis of keywords reveals the underlying structures of association between key concepts, shedding light on the intricate dynamics of research in the field of commodities. This research delineates the complex interplay between commodity markets and global economic dynamics, offering invaluable insights for academics, policymakers, and market participants aiming to navigate the intricate world of commodities in the digital age. Full article

Gold prices have been of major interest for a lot of investors, analysts, and economists. Accordingly, a number of different modeling approaches have been used to forecast gold prices. In this manuscript, the geometric Brownian motion approach, used in the pricing of numerous types of assets, is used to forecast the prices of gold at yearly, monthly, and quarterly frequencies. This approach allows for simulating one-period-ahead prices and the associated probabilities. The expected prices obtained from the simulated prices and probabilities are found to provide reliable forecasts when compared with the observed yearly, monthly, and quarterly prices. Full article

Real assets in the energy market are subject to ecological uncertainty due to the penetration of renewables. We illustrate this point by analyzing electrolyzers, a class of assets that recently became the subject of large interest, as they lead to the production of the desirable green hydrogen and green ammonia. The latter has the advantage of being easily stored and has huge potential in decarbonizing both the fertilizer and shipping industries. We consider the optimization of green ammonia production with different types of electricity procurement in the context of stochastic power and ammonia markets, a necessary assumption to translate the features of renewable, hence intermittent, electricity. We emphasize the importance of using stochastic prices to model the volatile nature of the price dynamics effectively, illustrating the project risks that hedging activities can mitigate. This study shows the pivotal role of flexibility when dealing with fluctuating renewable production and volatile electricity prices to maximize profits and better manage risks. Full article

We analyze the role of hedge fund, swap dealer, and arbitrageur activity in the crude oil market. The contribution of our work is to examine the role of institutional traders in switching between high-volatility and low-volatility regimes. Using confidential position data on institutional investors, we first analyze the linkages between trader positions and fundamentals. We find that these institutional position changes reflect fundamental economic factors. Subsequently, we adopt a Markov regime-switching model with time-varying probabilities and find that institutional position changes contribute incrementally to the probability of regime changes. Full article

The paper conducts extensive research on how Alaska’s oil production is affected by shocks in oil supply, aggregate demand, and oil-specific demand under both symmetric and asymmetric scenarios. We demonstrate that employing an empirical model with the inclusion of an asymmetric assumption provides a more suitable approach for comprehensively understanding the short and long-term impacts of various oil shocks on Alaska’s oil production. We also find that Alaska’s oil production is significantly affected by oil supply and aggregate demand shocks over both short and long periods, whereas oil-specific demand shocks have a minimal impact. Finally, our research identifies asymmetric effects in the long term, particularly concerning the influence of aggregate demand and oil-specific demand shocks on Alaska’s oil production. However, no asymmetric effects are observed for the three oil shocks in the short term. Full article

This paper examines the relationship between commodity index returns and the Office of Financial Research Financial Stress Index (OFR FSI). Utilizing the S&P GSCI and its five sub-indices (agriculture, livestock, energy, industrial metals, and precious metals), we find that the causal relationship between financial market stress and commodity index returns is conditional on the sample period examined and the methodology employed. We also note that stress in financial markets has a negative relationship with commodity index returns during low commodity return states; however, during high commodity return states, financial market stress exhibits a positive relationship with commodity index returns. Our findings highlight the importance of considering a time-varying framework for analyzing commodity return dynamics. Full article

Using quarterly data for the 2002–2022 period, we estimate the output and inflation effects of several commodity prices (agricultural raw materials, crude oil, and metals) for 8 Eastern European countries with different exchange rate regimes. The Kalman filter is used for estimating the time-varying parameters. Our main findings can be summarized in the following way: (i) higher crude oil prices are inflationary in most of the countries (except Slovakia), with a stronger price effect since 2020; (ii) crude oil prices are neutral with respect to output growth in 4 out of 8 countries, with an expansionary effect in Croatia, Slovenia, and Romania, as well as a contractionary effect in Slovakia, but the crude oil shock of 2021–2022 seems to be expansionary in almost all countries (except Slovakia), regardless of the exchange rate regime practiced; (iii) inflation and output effects of metals prices are quite heterogeneous across countries; (iv) agricultural raw material prices play a role in both inflation and output growth only in Bulgaria and Poland. Since 2021, a growing inflationary impact of crude oil prices suggests a stronger monetary policy reaction to the oil shock, especially in the presence of its favorable output effect. Full article

The effect of trade-related government expenditure on backward and forward participation in global value chains (GVCs) is at the heart of the present analysis. The latter builds on an unbalanced panel dataset of 74 developing countries over the annual period from 2005 to 2018. It has used several estimators, the primary one being the Quantile via Moments approach. The outcomes suggest that trade-related government expenditure exerts no significant effect on countries’ forward participation in GVCs. At the same time, countries located in the 20th to 90th quantiles experience a positive and significant effect of trade-related government expenditure on backward participation in GVCs, with the magnitude of this positive effect being larger for countries in the upper quantiles than for countries in the lower quantiles. The least integrated countries into the backward participation in GVCs (i.e., those in the 10th quantile) experience no significant effect of trade-related government expenditure on backward participation in GVCs. Interestingly, expenditure in favour of developing economic infrastructure, and expenditure for enhancing productive capacities reinforce each other in positively affecting backward GVC participation by countries located in the upper quantiles (i.e., the 50th to 90th quantiles). However, the interaction between these two types of trade-related government expenditure does not influence countries’ forward participation in GVCs. These findings shed light on the importance of trade-related expenditure for enhancing developing countries’ participation in backward GVCs. Full article

Innovation and technology are important tools for delivering efficiency and productivity improvement in the minerals sector. The uptake of technologies has proven to be an important lever for increasing the productivity of the mining sector. This paper provides a comprehensive analysis of mine-level productivity using global data of copper, gold, and platinum from 1991 to 2020. Various drivers of productivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in terms of technical efficiency and productivity across mines and regions. The further decomposition of total factor productivity (TFP) into its different components suggests that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities sectors. Our findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in the productivity of different commodities sectors (e.g., South Africa vs. Zimbabwe) give policymakers insights into how to support production scale and productivity through appropriate input mixes. Full article

This study analyses a series of live cattle spot and futures prices from the Boi Gordo Index (BGI) in Brazil. The objective is to develop a model that best portrays this commodity’s behaviour to estimate futures prices more accurately. The database created contains 2010 daily entries in which trade in futures contracts occurs, as well as BGI spot sales in the market, from 1 December 2006 to 30 April 2015. One of the most important reasons why this type of risk needs to be measured is to set loss limits. To identify patterns in price behaviour in order to improve future transaction results, investors must analyse fluctuations in asset values for longer periods. Bibliographic research reveals that no other study has conducted a comprehensive analysis of this commodity using this approach. Cattle ranching is big business in Brazil given that in 2021, this sector moved BRL 913.14 billion (USD 169.29 billion). In that year, agribusiness contributed 26.6% of Brazil’s total gross domestic product. Using the proposed risk modelling technique, economic agents can make the best decision about which options within these investors’ reach produce more effective risk management. The methodology is based on Holt–Winters exponential smoothing algorithm, autoregressive integrated moving-average (ARIMA), ARIMA with exogenous inputs, generalised autoregressive conditionally heteroskedastic and generalised autoregressive moving-average (GARMA) models. More specifically, five different methods are applied that allow a comparison of 12 different models as ways to portray and predict the BGI commodity behaviours. The results show that GARMA with order c(2,1) and without intercept is the best model. Investors equipped with such precise modelling insights stand at an advantageous position in the market, promoting informed investment decisions and optimising returns. Full article

This paper conducts an empirical analysis of risk premiums in the Brazilian electricity market, a critical but understudied field. Employing two distinct methodologies—Average Forward Prices and Last Observed Forward Prices—the study calculates risk premiums between spot and forward electricity prices. Our analysis consistently identifies negative risk premiums, which serve as indicators that the market may be underestimating certain types of risk. These underestimations are potentially influenced by inherent market uncertainties, including volatile demand, unpredictable supply, and frequent regulatory shifts. Additionally, we observe a high volatility in risk premiums, signifying a dynamic and ever-changing market where expectations are continuously recalibrated. Such conditions present possible arbitrage opportunities for market actors and underline the need for policymakers to introduce measures mitigating market unpredictability. By focusing on these nuances, this paper enriches the broader discourse on risk premiums in electricity markets and underscores the necessity for further research aimed at devising effective risk management strategies. Full article