Commodity Exchange Research Articles

Research on the Role of Risk Hedging and Arbitrage Strategies in Financial Derivatives Investment

In financial derivatives investment, risk hedging and arbitrage strategies play a key role. Risk hedging aims to reduce the uncertainty caused by asset price fluctuations and provide investors with stable returns through derivatives such as futures, options, and credit default swaps (CDS). This strategy is widely used by enterprises and financial institutions to manage commodity prices, exchange rates, and credit risks. Arbitrage strategies use market price differences, especially pricing differences in different markets or at various time points, to seek risk-free or low-risk returns. This paper reviews existing literature on financial derivatives, sorting out the role of risk hedging in financial derivatives investment. It summarizes the basic principles, application cases, advantages, and limitations of risk hedging. Additionally, the research delves into the role of arbitrage strategies in financial derivatives investment, covering its basic principles, types, application cases, advantages, and limitations. This research finds that hedging strategies, through instruments such as futures, options, and credit default swaps, provide effective risk management by stabilizing returns and reducing the impact of market volatility. Arbitrage strategies, on the other hand, exploit market inefficiencies to generate low-risk or risk-free profits, thereby enhancing market efficiency and liquidity. Despite these advantages, this paper also highlights certain limitations, such as the complexity and cost of hedging instruments, and the diminishing arbitrage opportunities as markets become more efficient.

Retail Investor Protection in the Age of Digital Trading: Regulatory Challenges and Solutions

The research analyzes the regulatory challenges posed by these platforms and to develop effective solutions. The study examines existing regulatory frameworks, such as the Dodd-Frank Act, MiFID II, and the Commodity Exchange Act, as well as market data on trading behaviors and feedback from retail investors and regulatory bodies. Key findings include the identification of significant regulatory gaps, particularly in the areas of anti- money laundering (AML) and know-your-customer (KYC) requirements, and the lack of clarity in the classification of digital assets as securities or commodities. The significance of these findings lies in their implications for enhancing investor protection and market stability. The broader implications suggest that a more integrated and technology-driven regulatory framework could enhance transparency, prevent market manipulations, and ensure a level playing field for all market participants. This research contributes to the ongoing discourse on digital asset regulation to safeguard retail investors in the digital trading era.

Global commodities in precolonial Southern Africa: local concepts and global conversations

ABSTRACT Research on Southern Africa between ca. 500 CE and ca. 1500 CE has been dominated by tracing the connection of the subcontinent to the maritime trade across the Indian Ocean. But until recently, the lack of effective tools to reconstruct precolonial movements of commodities made it appear as if Africa, despite its vast size, lacked internal long-distance exchange. We challenge this assumption by combining oral historical with archaeological and scientific data to identify long-distance internal African commodity exchange and associated variable networks of distribution. We identify long-distance exchange of commodities, such as iron hoes, copper ingots and ostrich eggshell beads that are fulfilled, as mediated by different cosmologies, quotidian and luxury desires in ancient southern and Central Africa. We conclude that precolonial Southern Africa was deeply interconnected through networks of production and exchange and that entanglements with the Indian Ocean provided optional commodities to complement the pre-existing and the locally available.

Magic money: commodities and exchange in Bronze Age Europe

ABSTRACT Bronze Age Europe has been described as the first globalized economy: long-distance trade in bronze and other materials is seen as centrally implicated in the social and political transformations of the period. Recent research pointing to the existence of standardized units of weight (given material form in ‘proto-currencies’ such as the well-known bronze ösenringe of the Early Bronze Age, as well as in the appearance of weights and balance beams during the Late Bronze Age) has reignited longstanding discussions around the relative significance of commodity and gift exchange during the period. In this paper, we revisit anthropological discussions of trade and exchange on the one hand, and of ethnomathematics on the other, to consider the social implications of Bronze Age numeracy and metrology. In this way, it is possible to avoid imagining the Bronze Age as a proto-Capitalist economy and instead consider how economics, society and cosmology were inextricably intertwined.

Transformer Based Ship Detector: An Improvement on Feature Map and Tiny Training Set

The exponential increment of commodity exchange has raised the need for maritime border security in recent years. One of the most critical tasks for naval border security is ship detection inside and outside the territorial sea. Conventionally, the task requires a substantial human workload. Fortunately, with the rapid growth of the digital camera and deep-learning technique, computer programs can handle object detection tasks well enough to replace human labor. Therefore, this paper studies how to apply recent state-of-the-art deep-learning networks to the ship detection task. We found that with a suitable number of object queries, the Deformable-DETR method will improve the performance compared to the state-of-the-art ship detector. Moreover, comprehensive experiments on different scale datasets prove that the technique can significantly improve the results when the training sample is limited. Last but not least, feature maps given by the method will focus well on key objects in the image.

Crude oil price forecasting with multivariate selection, machine learning, and a nonlinear combination strategy

Crude oil price forecasting has been one of the research hotspots in the field of energy economics, which plays a crucial role in energy supply and economic development. However, numerous influencing factors bring serious challenges to crude oil price forecasting, and existing research has room for further improvement in terms of an integrated research roadmap that combines impact factor analysis with predictive modelling. This study aims to examine the impact of financial market factors on the crude oil market and to propose a nonlinear combined forecasting framework based on common variables. Four types of daily exogenous financial market variables are introduced: commodity prices, exchange rates, stock market indices, and macroeconomic indicators for ten indicators. First, various variable selection methods generate different variable subsets, providing more diversity and reliability. Next, common variables in the subset of variables are selected as key features for subsequent models. Then, four models predict crude oil prices using common features as inputs and obtain the prediction results for each model. Finally, the nonlinear mechanism of the deep learning technology is introduced to combine above single prediction results. Experimental results reveal that commodity and foreign exchange factors in financial markets are critical determinants of crude oil market volatility over the long term, as observed in experiments conducted on the West Texas Intermediate and Brent oil price datasets. The proposed model demonstrates strong performance regarding average absolute percentage error, recorded at 2.9962% and 2.4314%, respectively, indicating high forecasting accuracy and robustness. This forecasting framework offers an effective methodology for predicting crude oil prices and enhances understanding the crude oil market.

Designated market makers and agricultural futures market quality: Evidence from China's Dalian commodity exchange

AbstractMany financial markets use designated market makers (DMMs), but the impacts of DMMs on agricultural futures markets – and in particular, how to arrange DMMs among contracts expiring in different months – are largely neglected. In 2017, Chinese exchanges started recruiting DMMs for inactive contracts when they become nearby contracts to address the discontinuous trading activity of nearest‐to‐maturity contracts, which enables us to study the benefit and cost of recruiting DMMs for inactive contracts using a quasi‐experimental framework. Leveraging tick‐by‐tick data on corn and soybean meal futures, we find that DMMs improve the market quality of inactive contracts without disrupting the market quality of dominant contracts. Heterogeneity analysis in policy settings suggests that more DMMs are conducive to improving market quality for corn and soybean meal futures. We demonstrate that DMM policy is a feasible measure to facilitate continuous activeness in Chinese agricultural futures markets. Our results are important for exchanges and regulators seeking to better design and implement designated market‐making programs in agricultural futures markets.

The Necessary Illusion – Giannotti on Fetishism

The main aim of this article is to investigate the most fundamental meanings that José Arthur Giannotti attributes to the phenomenon of fetishism in Marx. His interpretation, as expounded in Certa herança marxista [Certain Marxist Heritage] and grounded in the concept of a necessary illusion in a predominantly Kantian sense, appears to challenge a fundamental aspect of the new readings that Uspian Philosophical Marxism, with Giannotti as a key figure, has advanced since the 1960s. These new readings have underscored the notion of real abstraction as the foundation of commodity fetishism in a predominantly Hegelian sense. The article aims to clarify that Giannotti's interpretation does not aim to replace one perspective with another but rather to integrate the initial insights of the critique of real abstraction with the illusory measurement practices inherent in the process of production and exchange of commodities.

ҚАЗАҚСТАНДАҒЫ КӨТЕРМЕ САУДА НАРЫҒЫНЫҢ ИНФРАҚҰРЫЛЫМЫ: ЖАҒДАЙЫ МЕН ДАМУ БАҒЫТТАРЫ

This article analyzes the key components of the infrastructure of the food wholesale trade market in Kazakhstan. The authors provide a comprehensive review of retail trade formats in a regional context and assess the level of provision of trading platforms for the population. The study examines the structure of legal entities in trade, employment in regions, service preparation centers, wholesale trade centers, retail areas of large facilities, markets in rural areas, and the technical equipment ofspecialized markets.Additionally, the operation ofcommodity exchanges and the issues of purchasing products for stabilization funds are also explored. The state continues to play a key role in the food market, and the authors note that the Government of Kazakhstan is actively working on the development of digital infrastructure in food trade. The analysis identifies several issues that require state intervention, as well as the need to improve logistics and intermediary services. The authors emphasize the importance of introducing modern technologies alongside the development of commodity exchanges and mobile trade.

Cotton market contagion: analyzing volatility spillovers across borders

PurposeThe paper analyzes the volatility transmission within the cotton markets by utilizing commodity futures prices from the USA, China and India, encompassing important global events that have significantly influenced the global cotton markets, like the China-USA trade dispute, the COVID-19 outbreak and the Russia–Ukraine conflict.Design/methodology/approachThe authors employ a volatility spillover measure developed by Diebold and Yilmaz (2009, 2012, 2014). Additionally, the methodology proposed by Baruník and Křehlík (2018), which divides the overall volatility spillover into short, medium and long-term segments has been used. To investigate the volatility connectedness, weekly (close-to-close) returns of the cotton futures contracts that are traded on the Chicago Board of Trade Dalian Commodity Exchange National Commodity Exchange of India (NCDEX), and Multi Commodity Exchange (MCX) are considered.FindingsThe paper identifies the presence of long-term volatility transmission among the three cotton futures markets. It demonstrates that a global shock like the Russia–Ukraine conflict has a greater impact on volatility in other markets than USA–China trade disputes. It also highlights the weakening role of the US cotton futures markets as a price leader for Indian and Chinese markets.Research limitations/implicationsSince only three major markets have been studied, the future studies can explore the interconnectedness by including other important markets including Brazil, Turkey, Bangladesh, etc. Further, the moderating role of relationship between other important variables such as cotton production, harvest, inventory, exchange rate, oil price, trade policies, etc. can be examined. Furthermore, the interconnectedness with the regional spot markets in India can also be examined to study how the volatility from the futures market can affect the volatility in the spot markets and vice-versa.Practical implicationsThe understanding of domestic food price volatility and its transmission from international to domestic markets is crucial for designing effective policies to address excessive volatility and protect vulnerable groups like producers, consumers, etc.Social implicationsThe findings emphasize on the substantial market dependence with the US and the Chinese markets which have a significant impact on the Indian markets with considerable implications for hedgers, producers and exporters, particularly during periods of higher volatility.Originality/valueThis study assesses the interdependencies among three major cotton-producing countries and the influence of factors like the USA–China trade tensions in 2018, the COVID-19 crisis and the Russia–Ukraine conflict in order to gauge the degree of volatility interconnection among these key players in the cotton market.

Electricity trade at exchanges of the world: Contextual analysis of Indian electricity exchanges

This study probes the relationship between price and traded volume in electricity exchanges worldwide. Deploying the generalised method of moments estimation on panel data from the day-ahead market of exchanges in 20 countries for the period 2015–2020, this study finds that an increase in the share of exchange-traded electricity in a country's total electricity consumption significantly reduces price. A critical analysis of the Indian electricity exchanges in this study reveals that even after 13 years of operations, consumers do not derive surplus as is expected from commodity exchanges.

Planning’s ecologies: Democratic planning in the age of planetary crises

The idea of planning has reappeared as an object of interest for critical research on post-capitalist organizational futures. This article offers a critical review of the emerging scholarship on planning, with reference to historical and contemporary precursors to democratic planning. Building on this review, the article develops a critical political ecology of planning that situates planning thought and practice within the matrix of the oikos. This encompasses not only the sphere of production and commodity exchange, but also the household of reproductive labor and the planetary household of the natural world. In this way, it is argued that democratic planning is indispensable for generating the forms of collective intelligibility and power needed to heal the metabolic relations of society and nature. By reimagining and reframing planning, the article aims to expand “the archive” of social imaginaries, as part of broader efforts to envision and develop more desirable organizational futures.

Risk spillovers and optimal hedging in commodity ETFs: A TVP-VAR Approach

Despite the growing popularity of commodity exchange traded funds (ETFs), research on their risk transmission dynamics is lacking. The study employs a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model to analyze volatility transmission among commodity ETFs during significant events like the COVID-19 pandemic and geopolitical conflicts. It aims to minimize interconnectedness among ETFs to reduce associated risk using the Mean Co-skewness optimal portfolio (MCoP) technique. The findings emphasize the importance of adaptability in portfolio management and provide actionable information for investors seeking to optimize allocation and manage risk exposure effectively in dynamic market environments.

ДЕЯТЕЛЬНОСТЬ ПРОДОТРЯДОВ И ПРОДАРМИИ В САРАТОВСКОЙ ГУБЕРНИИ В 1918 ГОДУ

The purpose of the article is to investigate the causes, the legal basis of the activities of Food Detachments and Food armies, as well as the tasks assigned to them to seize surplus grain in villages. The scientific novelty of the study is the insufficient knowledge of the activities of Food Detachments and Food armies in the Saratov province. The study uses the main methods of scientific and historical cognition, such as: descriptive, comparative historical, logical, analysis of archival materials. As a result of the study, it was revealed that in 1918, the cities under the control of the Soviet government were threatened with famine, despite the fact that there was bread in the agricultural provinces. But the peasants did not willingly hand it over, due to the unsettled system of commodity exchange between the village and the city. Based on this circumstance, the Soviet government decided to forcibly withdraw bread from the villages. The solution of this issue was entrusted to the workers of the Food Detachments and the Red Army soldiers of the Food Army, however, despite the common tasks, their activities were distinguished by the fact that the Food detachments took part of the harvested bread for themselves, and the Soldiers handed over everything to the state.

Thermal coal futures trading volume predictions through the neural network

Purpose Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020. Design/methodology/approach The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases. Findings A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume. Originality/value The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

Multi-view attributed graph clustering based on graph diffusion convolution with adaptive fusion

Graph clustering is one of the popular techniques in data mining, which is widely used in social network analysis, recommendation system and anomaly detection. The existing methods based on multi-view attributed graph ignore the difference of different views and the consistency between views. To this end, this paper proposes a novel method for multi-view attributed graph clustering based on graph diffusion convolution with adaptive fusion. Specifically, a graph diffusion convolution is firstly employed to propagate features of the adjacency and attribute matrices on each view. A linear encoder–decoder is then used to learn the graph embedding representation of each view. Meanwhile, the consistency learning module is applied to capture the geometric relationship consistency of different views for finding a consistent embedding space during the embedding representation learning. To measure the importance of different views, the attention mechanism is subsequently utilized to adaptively learn the weights of different views to fuse multiple views of data for the final clustering. Finally, the graph representation learning and clustering tasks are jointly optimized to obtain a clustering friendly graph representation. Experiments conducted on two public datasets and three real futures datasets from the Zhengzhou Commodity Exchange demonstrate the effectiveness of the proposed method in the task of graph clustering.

Price spillovers and interdependences in China's agricultural commodity futures market: Evidence from the US-China trade dispute

We examine the effects of the US-China trade dispute on price spillovers and interdependencies among the ten most liquid agricultural futures contracts traded on China's commodity exchanges by employing the time-varying connectedness framework modified by Antonakakis, Chatziantoniou, and Gabauer (2020). We find that the overall market frictions increase modestly due to the clustering of mixed informational disturbances caused by the trade dispute. This lowers the gross spillovers in the entire asset system by reducing the efficiency of general price signal transmission. Notably, subsidiary products of rapeseed and soybean contribute the most to the total and net directional spillovers in the whole market, acting as shock transmitters before the trade dispute. The RBD palm market gains a dominant role as a shock transmitter during the trade dispute and its role strengthens further after the trade agreement was reached. Additionally, the average intensity of pairwise spillovers declines considerably during the trade dispute, suggesting weakening asset interconnectedness. The responsiveness of shock transmission channels to the trade dispute impacts is found to vary across industrial chains and the presence of delayed economic effects is detected in the structural changes of market interdependences.

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.

Peluang pertumbuhan ekonomi di Kabupaten Majene Provinsi Sulawesi Barat

Background: The high production of capture fisheries in Majene Regency is not balanced by a marketing system and infrastructure in the form of adequate fishing ports and fish processing units. Findings: It is recorded that currently Majene Regency only has 2 (two) fishing port units, namely PPI Palipi and PPP Banggae with a total of 30,887 fishermen, the largest in West Sulawesi out of a total of 57,318 people. With these conditions, the catch of Majene Regency fishermen is mostly sold in the middle of the sea. Methods: This paper uses a literature review method sourced from literature, such as scientific articles, books, journals, and online media. Conclusion: The number of fishing port infrastructure in Majene Regency is still relatively low when viewed from the amount of production in other regencies/cities in West Sulawesi Province. So a government policy step is needed as a form of support for economic growth that is in accordance with the potential in Majene Regency, one of which is fisheries. Thus, it is hoped that fishery products which are superior commodities can be distributed to areas that do not have the potential for capture fisheries resources or the exchange of commodities through a buying and selling system.

BARTER TRANSACTIONS IN THE FOREIGN ECONOMIC ACTIVITY OF RUSSIAN COMPANIES UNDER SANCTIONS

The article examines the reasons for the return to barter transactions in the context of the application of economic sanctions to business operations in modern Russia, concerning difficulties with settlements in national currencies, difficulties with logistics and others. The results of the analysis of publications on the topic of barter transactions in difficult economic conditions are presented, which showed the ambiguity of scientists' opinions regarding barter transactions: some believe that this situation is associated with a shortage of funds and high inflation, others with non-payments in credit chains and the lack of the possibility of selling counter goods. The authors believe that in any case, it is advisable to take into account the specifics of barter transactions. The article provides an assessment of the dynamics of foreign trade, the trends of which in terms of exports and imports are characteristic, including for barter transactions. The advantages of barter transactions in terms of circumventing difficulties in international settlements and the lack of barter transactions related to determining the equivalent value of exchanged goods are investigated. The advantages of barter transactions are revealed, consisting in demonstrating the flexibility of conducting foreign trade in difficult economic conditions. The risks in barter transactions and the possibilities of their insurance have been identified. The results of the study can be used in the process of developing and conducting various types of barter transactions that contribute to strengthening international relations to maintain commodity exchange in difficult conditions of economic sanctions against Russia.