Commodity Markets Research Articles

Commodity Market Segmentation Hinders Carbon Productivity Gains in Chinese Agriculture: Moderating Effects of Economic and Informational Development

Commodity Market Segmentation Hinders Carbon Productivity Gains in Chinese Agriculture: Moderating Effects of Economic and Informational Development

Commodity Market Downturn: Systemic Risk and Spillovers during Left Tail Events

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.

INVESTMENT ANALYSIS IN SOYBEAN UBS FOR OWN USE: A CASE STUDY IN ALTO GARÇA – MT

Soybean (Glycine max) is the most widely produced legume in the world, playing an important economic, social and environmental role, in addition to influencing the commodities market in Brazil and worldwide. This has attracted many national producers to its cultivation, making it a highly competitive market with investment in research, innovation and development in all links of the chain. Therefore, the objective of this study was to evaluate the feasibility of investing in the installation of a Seed Processing Unit (UBS) for soybeans, on private property, with the purpose of producing the crop's own seed. To this end, a case study was carried out on a property in the municipality of Alto Garça - MT, using the descriptive method of exploratory nature, in which the economic impact of soybean seed production on the property was evaluated to the detriment of the reduction in production costs obtained in years following its implementation. Thus, the 2016/2017 to 2020/2021 harvests were analyzed in their cost composition and investment result from the 2017/2018 harvest. It was possible to verify the reduction in the seed cost per hectare by 38.33% in the first cycle, and by 66.87% compared to the last cycle analyzed, concluding that the investment was viable.

Heterogeneous Responses of Energy and Non-Energy Assets to Crises in Commodity Markets

In this study, we investigate the heterogeneity in energy and non-energy commodities by analyzing their four realized moments: returns, realized volatility, realized skewness and realized kurtosis. Utilizing monthly data, we examine two commodity categories over various crisis periods. This study examines a comparative approach to descriptive statistics across different crisis periods and the full sample and assesses the out-of-sample significance of heteroscedasticity using GARCH models. The findings reveal significant heterogeneity in both energy and non-energy commodities, with energy commodities exhibiting higher average returns and volatility. Crisis periods markedly influence the statistical properties of these commodities. GARCH models outperform ARMA models in forecasting realized moments, particularly for non-energy commodities. This research contributes to the literature by providing robust evidence of heterogeneity in commodity markets and highlights the importance of considering all four realized moments in such analyses.

Geopolitical Risks’ Spillovers Across Countries and on Commodity Markets: A Dynamic Analysis

We investigate the transmission of geopolitical risks between G7-BRICS countries and commodity futures prices. We find geopolitical instability after the outbreak of the Russia-Ukraine conflict. In a context where the G7 countries geopolitically influence the BRICS and vice versa, the United States, Germany, India, and Russia emerge as the predominant sources of spillovers. The commodity futures prices most influenced by geopolitical risks are those relating to energy.

Unveiling game meat: an analysis of marketing mix and consumer preferences for a forest ecosystem product

This study explores the dynamics of the game meat market, with a particular focus on venison and wild boar meat, to assess the impact of a nuanced marketing mix and strategy grounded in a comprehensive customer analysis. By conducting three pivotal research studies—namely, the Omnibus Survey (2022) and Consumer Market Analysis Polls (2021 and 2023)—and analysing their data, this research comprehensively analyses buyers’ preferences, motivations, and purchasing patterns. This paper is guided by three research questions aimed at examining the relationship between the game meat consumption and engagement in forest ecosystem services, including forest visitation, the sociodemographic characteristics of consumers and the criteria for market segmentation. The analysis focuses on identifying factors influencing the game meat consumption and examines how these factors may influence consumer behavior over time. It also explores the implications for the development of marketing strategies, based on Michael E. Porter’s approach, which is discussed in detail. Additionally, the research evaluates the role of game meat within the context of forest ecosystem services, its contribution to forest reforestation initiatives, and its relevance in the formulation of forest policy. This examination highlights the dual nature of game meat as both a market commodity and a critical element in ecosystem management and policy frameworks, seeking to harmonize the economic and ecological objectives.

Marketing Harm to Children: Children’s exposure to unhealthy commodity marketing using body cameras

Abstract Background Sophisticated, persuasive and extensive product marketing is a key driver of unhealthy commodity (UHC) consumption. This study aims to identify the nature and extent of children’s exposure to UHC marketing. Methods The study is a secondary analysis of Kids’Cam, a cross-sectional study in which 168 New Zealand 12-year-old children wore body cameras that automatically captured images of their environment every 7 seconds over four days. Images were analysed for exposure to UHC, Healthy and ‘Other’ marketing. Results Children were exposed to UHC marketing on average 76.2 times/day, nearly 2.5 times their daily exposure to ‘Healthy’ marketing. Exposure included: unhealthy food marketing (68.4/day), alcohol (5.7/day), gambling (2.1/day) and tobacco marketing (0.1/day). These exposure rates align with the level of statutory regulation each UHC faces in NZ. Food outlets were the most common setting for UHC marketing exposures, while product packaging was the most common medium. Coca-Cola (6.3/day) was the most common UHC exposure, followed by Cadbury, Tip Top, Bluebird and Powerade. Over half of children’s unhealthy food (54.9%) and alcohol (51.9%) marketing exposures were attributed to multinational corporations. In contrast, statutory bodies are responsible for almost all (97.4%) of children’s gambling marketing exposure. Conclusions Children currently grow up in an environment in which they are constantly persuaded to consume products that directly harm their health - an environment in which the profits of corporations are favoured over public health. Statutory regulation of UHC marketing is urgently needed to protect children from harm. Key messages • Children were exposed to unhealthy commodity marketing on average 76.2 times/day, nearly 2.5 times their daily exposure to ‘healthy’ marketing. • Statutory regulation of unhealthy commodity marketing is urgently needed to protect children from harm.

Stock market volatility and commodity prices

Stock market volatility and commodity prices

On the Use of SMAP Soil Moisture for Forecasting NDVI Over CONUS Cropland Regions

AbstractVegetation health forecasting (NDVI as a proxy) informs decision‐makers about the end of season crop yield productivity but is not well‐documented. This study tests improvements in vegetation health forecasting by developing a data‐driven Dynamic Agricultural Productivity Indicator (DAPI), which simultaneously incorporates satellite‐based root zone soil moisture (RZSM) and satellite‐based NDVI data. RZSM is estimated via data assimilation of satellite based SMAP SM dataset. We employ the proposed DAPI forecast across four cropland types in the CONUS, including corn, cotton, soybeans, and wheat. Results demonstrate superior performance of the DAPI forecasts compared to climatology‐based NDVI forecasts, with the largest improvements in water‐limited regions. DAPI shows particularly good performance during hydrologic disturbances such as floods and droughts. To this end, the DAPI approach is useful in estimating future vegetation health for identifying potential food‐insecure areas, predicting crop price changes, and projecting expected commodities market trends.

Decoding Market Efficiency: A Multifractal Approach to Financial Market Dynamics

Financial markets were traditionally analyzed using the Efficient Market Hypothesis (EMH), which argued that asset prices fully reflected all available information. This led to the belief that price movements were random, making it impossible to consistently outperform the market. However, emerging research had highlighted that markets could exhibit multifractality, where inefficiencies existed across different time scales, challenging the traditional EMH framework. Our study built on these insights by investigating the market efficiency of several asset classes, including stock market indices, cryptocurrencies (Bitcoin, Ethereum, USDT, and Binance), commodities (gold and crude oil), fixed income (U.S. 10-Year & 30-Year Treasury Bonds), and foreign exchange (EUR/USD & GBP/USD). Utilizing the Multifractal Detrended Fluctuation Analysis (MFDFA) method, we analyzed the multifractal properties and efficiency of each asset class. The results revealed that traditional assets exhibited monofractality, adhering more closely to the EMH. In contrast, cryptocurrencies displayed significant inefficiencies, likely due to their volatility, market structure, and susceptibility to external shocks. The findings provided valuable insights into portfolio diversification and risk management, suggesting that inefficiencies in certain asset classes might present both opportunities and risks for investors.

Intersecting Peptidomics and Bioactive Peptides in Drug Therapeutics

Abstract: Peptidomics is the study of total peptides that describe the functions, structures, and interactions of peptides within living organisms. It comprises bioactive peptides derived naturally or synthetically designed that exhibit various therapeutic properties against microbial infections, cancer progression, inflammation, etc. With the current state of the art, Bioinformatics tools and techniques help analyse large peptidomics data and predict peptide structure and functions. It also aids in designing peptides with enhanced stability and efficacy. Peptidomics studies are gaining importance in therapeutics as they offer increased target specificity with the least side effects. The molecular size and flexibility of peptides make them a potential drug candidate for designing protein-protein interaction inhibitors. These features increased their drug potency with the considerable increase in the number of peptide drugs available in the market for various health commodities. The present review extensively analyses the peptidomics field, focusing on different bioactive peptides and therapeutics, such as anticancer peptide drugs. Further, the review provides comprehensive information on in silico tools available for peptide research. The importance of personalised peptide medicines in disease therapy is discussed along with the case study. Further, the major limitations of peptide drugs and the different strategies to overcome those limitations are reviewed.

On the Effects of Physical Climate Risks on the Chinese Energy Sector

We examine the impact of physical climate risks on energy markets in China, distinguishing between traditional energy and new energy stock markets, and the energy commodity market, utilizing a time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR). Specifically, we investigate the dynamic effects of five specific subtypes of physical climate risks, namely waterlogging by rain, drought, typhoon, cryogenic freezing, and high temperature, on WTI oil prices and coal prices. The findings reveal that these physical climate risks exhibit time-varying similar effects on the returns of traditional energy and new energy stocks, but heterogeneous effects on the returns of WTI oil prices and coal prices. Finally, we categorize and examine the impact of both acute and chronic physical risks on the energy commodity market.

FROM CALENDAR TIME TO BUSINESS TIME: THE CASE OF COMMODITY MARKETS

We address the problem of modeling commodity forward curves, while preserving empirical features observed in commodity markets. By letting a commodity market to “ live” in the tempo of a business rather than calendar clock, we create a model with a rich but realistic set of features, such as stochastic volatility, stochastic rate of mean reversion and various shapes of forward curves such as backwardation and contango. The model, when applied to extensive historical datasets of crude oil and natural gas forward curves, shows a remarkably good fit to the observed futures prices, also in periods of high volatility and negative prices. The model is developed in such a way that it can be used for a wide variety of applications, ranging from exotic derivatives pricing to risk management of commodity portfolios.

Features of foreign investment in business companies that occupy a dominant position in the commodity market

The object of the study is certain issues of the procedure for foreign investments in strategic sectors of the economy. The subject of the study is devoted to the procedure for making foreign investments in business entities that occupy a dominant position in the commodity market. The dominant economic entity has market power, which provides an opportunity to shape the economic environment by determining the number of market participants, the behavior of suppliers of goods (works, services) and their consumers. The author examines the issues of necessary regulatory approvals of transactions of foreign investors for the acquisition of assets of dominant entities, as well as general antitrust and special rules for determining the existence of a dominant position in business entities operating in various sectors of the economy. The methodological basis of the study was based on systematic and formal legal methods, as well as the method of technical and legal analysis. The conclusions of the study are based on the constitutionally significant goals of ensuring national defense and state security, Russian legislation provides for the need to obtain additional regulatory approvals for foreign participation in business entities that occupy a dominant position on the market. At the same time, the book value of assets and the amount of revenue of a foreign investor does not matter, a group of persons to which he belongs, as well as a business entity whose assets are planned to be acquired by a foreign investor (a group of persons to which a foreign investor belongs), unlike transactions subject to approval within the framework of antimonopoly control. In some cases, the control of foreign investments applies special rules for determining the fact of market dominance for some business entities, which differ from the rules of antimonopoly legislation.

Local multi-modal energy market for thermal-electric energy systems with consideration of temperature flexibility in heating subnetworks

District heating systems are critical in this transition towards climate-neutral energy systems as they enable a close coupling of thermal and electric energy systems. However, the operation of these multi-modal energy systems and adequate representation of conversion dependencies, such as from heat pumps, remain challenging.To address this challenge, a novel method is presented that incorporates the temperature of subnetworks of district heating systems into the market matching of a local energy market for thermal-electric energy systems. This market-based coordination approach includes a linear formulation of market orders tailored to the needs of consumers, producers, and prosumers in local multi-modal energy systems. Emphasis is put on the temperature flexibility of heat pumps that concurrently participate in both heat and electricity markets. Complementary market commodities are introduced to account for temperature constraints set by the market participants. The physical models of the district heating network and electric distribution grid are formulated linearly and incorporated into the market-matching.The proposed method is applied in a case study representing a German district heating system. We conclude that the temperature flexibility of heating subnetworks, and dependencies involved in energy conversion can be incorporated within a linear market-matching problem.

Multi-model transfer function approach tuned by PSO for predicting stock market implied volatility explained by uncertainty indexes

This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical threats to the CBOE Volatility Index (VIX). In this study, the relationship between the various uncertainty metrics throughout the period 2012—2022, using a multi-model transfer function technique optimized by particle swarm optimization (PSO) is estimated. Furthermore, we utilize PSO for parameter optimization within the multi-model framework, improving model performance and convergence speed. According to empirical findings, the CBOE Volatility Index reacts nonlinearly to the uncertainty indices. Specifically, the conclusions of the performance metrics show that the OVX index (MAPE: 4.1559%; RMSE: 1.0476% and W: 96.74%) outperforms the geopolitical risk index, the Bloomberg energy index, and the economic policy uncertainty index in predicting the volatility of the US equities market. Although individual models have generated respectful performance, results from the aggregate simulation show that when all predictors are combined, they simultaneously provide better performance indicators (MAVE: 2.7511 %; RMSE: 0.7361%; R2: 98.93%) than when they are estimated separately. In addition, results provide evidence that, when considering non-linear patterns in the data, the multi-model transfer function technique calibrated using PSO demonstrates its outperformance over autoregressive baseline models, traditional econometric models, and deep learning techniques. The effectiveness and accuracy of the multi-model transfer function method tuned by PSO as a forecasting tool are confirmed by the convergence analysis of the cost function. Our methodology innovates by employing a multi-model transfer function technique, which captures the complex and nonlinear relationships between uncertainty indicators and the VIX more comprehensively than traditional single-model approaches. These results are important for traders in terms of hedging as well as portfolio diversification by investing in defensive equities and for policymakers in terms of reliability and preciseness of volatility forecasts.

A Study of the Mediating Effect and Path of Customer Fit in Repeat Purchase Behavior in the Residential Market Driven by Digital Marketing Technology

Improving the repeat purchase intention of customers of real estate enterprises from marketing strategies is increasingly important for real estate enterprises to achieve the goal of stable and increasing long-term profits. This paper, driven by digital marketing technology, takes customer repeat purchase behavior in residential commodity market as the research object. The variables of brand community value, customer fit and repeat purchase behavior are first defined and selected. Then the relationship model of brand community value, customer fit and repeat purchase behavior was established, questionnaire research was conducted on mature real estate community members, and data analysis and structural equation model fitting were carried out using SPSS and AMOS software in order to test the mediating effect of customer fit in repeat purchase behavior in the residential market as well as the path. The study concluded that the standardized coefficient of customer fit on customers’ repeat purchase intention is 0.36, which has a significant positive effect. Meanwhile, customer fit has a mediating effect between the five dimensions of brand community value and repeat purchase behavior, and all five dimensions have a partial mediating effect in the process of influencing repeat purchase intention.

International Currency and Commodity Market

International Currency and Commodity Market

Does speculation impair informational efficiency? New evidence from the Indian agricultural commodity market

Purpose This study explores the association between market efficiency and speculation. The government of India temporarily banned the futures trading of various commodities several times citing the presence of speculation. Many controversies exist about this topic; thus, this study clarifies the association between market efficiency and speculation and investigates whether market reforms altered this association.Design/methodology/approach The data for nine commodities is collected from the National Commodity and Derivative Exchange (NCDEX) for 2005–2022. Regression analysis and Automatic Variance Ratio (AVR) were adopted to inspect the informational efficiency and influence of speculation in the commodity market. Furthermore, this study uses different sub-samples to understand the changes in the market microstructure and its effects on market quality.Findings The results confirm an inverse and significant relationship between information efficiency and speculation and a deviation from the random walk process observed. Therefore, return predictability exists in the market. This study confirms that market reforms do not reduce the influence of speculation on market efficiency. The study concludes that the market is not weak-form efficient.Research limitations/implications This study has certain limitations, since this study is empirical in nature, it may possess the limitations of empirical research.Originality/value This paper has dual novelty. First, this study investigates the effects of market reforms. Second, this study captures the influence of speculation in the Indian agricultural commodity market by considering the market microstructure aspects.

Effects of banditry on food security in Zamfara State

Banditry is a great security issue in the Northeastern part of Nigeria for years. It affected the human life and security of properties. Food security to be precise is one major aspect that is affected where livestock, market and other food related commodities are badly affected in terms of production, consumption and commerce. This paper aims to look in to the effects of banditry on food security in Zamfara State. Selected areas for the study are where data from focus group discussion were derived for the study, it includes among others; Shinkafi, Bakura Maradun and Anka. The study employed Frustration Aggression Theory as the theoretical pedestal to analyze the drive causing food security in the study areas. Among the findings of the study is that, banditry has a great effect on the security of food in the study area, it reduces production, retards other farming activities, destroys livestock, halts commercial activities, causes famine and destroys the environment. Other findings angles on the human security in Zamfara State, lives are not secured, farmlands are abandoned, cattle are rustled which cripples the political economy of Zamfara State. The paper thus recommends a holistic and strategic approach curtail banditry especially in the areas riddled with its effect, farmlands, market places and grazing lands should be adequately protected to secure food and safe peoples’ life. Intelligence on the hideouts of the bandits and their plots should be acquired using traditional or people at the grass root, to detect abnormal activities like huge procurement of food from the markets, drugs from pharmacies, supply of fuel and presence of unknown people in the areas.