Trade Risk Research Articles

The effect of COVID-19 vaccine on the international financial markets

Existing studies on the COVID-19 pandemic and vaccine development have primarily documented their effects on stock markets, with limited attention to international financial markets. This paper constructs a news-based sentiment index on COVID-19 vaccine development and examines its effects on international financial markets during the first year of the pandemic. We find positive vaccine sentiment decreases the CBOE Volatility Index (VIX) while boosting capital inflows and currency appreciation in emerging markets. It also reduces the unit price of risk in the context of carry trade risk premiums, as positive developments lower future risk and economic uncertainty.

Analyzing Common Trade Risks Faced by Tanzanian Traders in International Transactions: A Case Study of Dar es Salaam Importers and Exporters

International trade is fraught with inherent risks that can significantly impact the efficiency and success of cross-border transactions. Tanzanian importers and exporters, particularly those navigating the complexities of the Dar es Salaam port, face challenges such as shipment delays, vague contract terms, and financial disputes. This study delves into how the strategic application of International Commercial Terms (Incoterms) serves as a powerful risk management tool, offering clarity and structure to international trade agreements. Utilizing a descriptive research design, we surveyed 96 traders and conducted in-depth interviews to capture their experiences with trade risks and their understanding of Incoterms. The findings reveal a widespread gap in formal training on Incoterms, leading to frequent logistical issues and contractual ambiguities that could otherwise be mitigated. This research highlights the urgent need for targeted educational programs to enhance traders’ knowledge of Incoterms and improve the overall efficiency of Tanzania’s trade environment. By embracing these standardized terms, Tanzanian traders can transform risks into opportunities, positioning themselves as key players in the global trade ecosystem. The study concludes with actionable strategies for improving Incoterm adoption and presents a roadmap for strengthening Tanzania’s competitive edge in international commerce.

Trade risk transmission of global cobalt industrial chain based on multi-layer network

In order to study the potential systemic risk transmission in cobalt trade, this paper combined the infectious disease model with complex networks to build a multi-layer network trade risk transmission model for cobalt trade based on the transmission of export restrictions and bilateral friction in a single country, in order to simulate the degree of impact of risk transmission in cobalt industry chain, identify key countries and risk transmission paths. The results show that multi-layer network risk transmission of global cobalt trade based on two communication forms has the characteristics of “robust and fragile”. In addition, the risk transmission situation based on bilateral frictions is mainly transmitted by core countries and direct contacts. The risk transmission based on the export restriction of a single country is mainly through direct contact, indirect contact and regional transmission. We also find that the multi-layer trade network of global cobalt trade can resist the bilateral frictional transmission mode better than the transmission mode of single country export restriction. The results can support policy makers to optimize the cobalt trade structure and mitigate the negative impact of trade disruptions.

Design of an international trade target supplier evaluation system based on CART algorithm

International trade, as an important component of economic exchange between countries, is of great significance for the economic development of each country and international cooperation. In international trade, the selection and evaluation of suppliers has always been a key issue. To ensure the smooth progress of trade and the controllability of quality, it is necessary to establish a target supplier evaluation system. This article used the CART (Classification and Regression Tree) algorithm to help identify and analyze the impact of key factors on supplier evaluation and classify and evaluate suppliers. The international trade target supplier evaluation system based on the CART algorithm was also constructed, and its performance was tested in the experimental section and compared with the international trade target supplier evaluation system based on traditional algorithms. According to the experimental results, it can be concluded that both the traditional algorithm and the CART algorithm performed well in terms of application effectiveness and system user satisfaction. In terms of application effectiveness, the average score of traditional algorithms was 4.3, with a rating range of 3.8 to 4.9, while the average score of the CART algorithm was 4.6, with a rating range of 4.2 to 5.0. The satisfaction rating of system users on the CART algorithm was slightly higher than that of traditional algorithms, indicating that the CART algorithm has better application effectiveness and user satisfaction in the design of international trade target supplier evaluation systems. The design of an international trade target supplier evaluation system based on the CART algorithm can also help enterprises reduce trade risks and improve the stability and reliability of the supply chain. It has important practical significance and application value for further promoting the development of international trade.

Establishing the robustness of chip trade networks by dynamically considering topology and risk cascading propagation

Risk cascading propagation research mostly focuses on complex theoretical networks. Recently, the vulnerability of international chip supply has increased notably, and it is strategically important to explore how shortage risk affects the emergence dynamics of the real chip trade systems. This study abstracts the global chip trade relationship data for 2009–2021 into multiple asymmetrically weighted networks. Using macro-network and micro-node indicators, we explore the topological traits of international chip trade networks and their evolutionary laws. Accordingly, we propose risk cascading propagation models driven by node failure and edge restraint and further innovate to open up the research paradigm of focused-edge networks. Furthermore, a community infection-driven risk cascading propagation mechanism that incorporates community risk absorption capacity is introduced, considering both the propagation attenuation effects and the trade dependency degree. A multi-dimensional dynamic perspective reveals the hidden systemic risks in international chip trade. The main results are as follows: first, international chip trade networks are highly connected and cohesive, consistent with small-world characteristics. Second, the proportion of economies that collapse because of supply shortage risk shocks increases with the impact coefficient α/β\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha /\\beta$$\\end{document}. The dominant power in chip crisis propagation has shifted from Europe and America to Asia, and mainland China’s risk penetration capacity has enhanced significantly. Third, focused-edge networks conform to a multi-hub radiation pattern. Before the COVID-19 pandemic, the degree of control and spillover effects of chip supply shortages in hub economies on the international trade was increasing progressively. Fourth, an increase in absorption capacity λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document} or attenuation factor γ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\gamma$$\\end{document} consistently leads to a decline in avalanche scale, with λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document} exhibiting critical thresholds. These findings will help policymakers pursue efficient management strategies for chip trade, thereby improving supply stability and security.

A unified theory of decentralized insurance

Decentralized insurance can be used to describe risk sharing mechanisms under which participants trade risks among each other as opposed to passing risks mostly to an insurer in traditional centralized insurance. There are a wide range of decentralized practices in all kinds of forms developed around the world, including online mutual aid in East Asia, takaful in the Middle East, peer-to-peer insurance in the West, international catastrophe risk pooling by African, Caribbean and Central America countries, etc. There is also a rich literature of risk sharing in academia that offers theoretical bases of other decentralized mechanisms. This work presents a unified mathematical framework to describe the commonalities and the relationships of all these seemingly different business in practice and theoretical models in academia. Such a framework provides a fertile ground for the comparison of existing practices and the design and engineering of hybrid and innovative models.

The Application of Financial Technology in Carbon Finance

With the rapid development of the economy, the pollution of the environment in various countries is also increasing, and the concept of carbon finance is gradually emerging. Fintech has gradually entered people's vision, and how to use Fintech to help the realization of carbon finance has become a research issue for some scholars. Existing research mainly focuses on a specific application and lacks a literature review. By summarising the literature on fintech and carbon finance, this paper outlines several currently common applications. It mainly covers the application of blockchain in carbon finance, such as using the tamper-proof nature of blockchain to make the carbon credit trading process more transparent, and using the contract layer of blockchain-smart contracts to prevent the accumulation of carbon credits by adding smart contracts into the trading process of carbon credits, etc. This paper concludes the application of big data and cloud computing in carbon finance, such as using big Data and cloud computing technology to analyze massive data, as a way to reduce the risk of carbon trading, etc. The research puts forward a certain degree of recommendations on the application of financial technology in carbon finance.

Knowledge, attitudes, and practices towards the risk of zoonotic diseases, wildlife trade and wildlife consumption in Latin America

Knowledge, attitudes, and practices towards the risk of zoonotic diseases, wildlife trade and wildlife consumption in Latin America

Financial Hedging of Operational Risk Constraints: A General Framework

We consider the operation of a non-financial corporation and present a novel risk-management framework that supports the joint optimization of the firm’s operational and financial decisions. Specifically, we study the problem of maximizing the firm’s operating profits when these profits depend on movements in the financial markets, and where the decision maker—the firm’s manager—is risk averse. Critically, our framework (i) imposes risk aversion through a generic class of risk constraints, and (ii) considers explicitly the differences that can exist between the shareholders’ and manager’s beliefs about future market risks. Together, these aspects allow us to remove speculation so that financial instruments can only be used for hedging purposes. We analyze our problem in an incomplete financial market setting and consider different informational assumptions. Within this framework, we characterize the optimal financial hedging strategy so that the problem reduces to a constrained maximization over operational policies. Our results show how financial hedging can be effectively used to expand the set of admissible operating policies, and identify conditions under which the risk constraint can be completely ignored when solving for an optimal operating policy. We illustrate our methodology in the context of an exporter firm which faces exchange rate risk in trading.

Research on Trade Risk and Preventive Measures of Domestic Anti-wear Hydraulic Oil Products

With the acceleration of global economic integration, the international trade activities of domestic anti-wear hydraulic oil products continue to increase, and the trade risks of chemical products such as anti-wear hydraulic oil products brought by export are also highlighted. In order to prevent the trade risk of domestic anti-wear hydraulic oil products, this paper puts forward some strategies, such as strengthening market research, implementing diversified market strategy, strengthening communication with international partners and establishing trade risk early warning mechanism, to solve the problems of unstable market demand, price fluctuation, trade barriers and policy risk faced by the trade of domestic anti-wear hydraulic oil products. In order to provide a useful reference for ensuring the stability and sustainable development of China's anti-wear hydraulic oil industry and further enhancing national economic security.

The nexus between economic growth and conditional exchange rate volatility: evidence from emerging economies

PurposeThe purpose of this paper was to examine the nexus between conditional exchange rate volatility and economic growth in BRICS countries. Further, the dynamic causation between economic growth and exchange rate volatility is also examined.Design/methodology/approachWe employed three techniques, namely, dynamic panel models, static panel models and Dumitrescu and Hurlin (DH) panel causality test to examine the economic growth–conditional exchange rate volatility nexus in BRICS countries.FindingsThe overall results showed that conditional exchange rate volatility has a negative and significant effect on economic growth. Interestingly, the results showed that whenever the exchange rate volatility exceeds the 0–1.54 range, the economic growth of BRICS is reduced, on average, by 5%. Further, the results of the causality test reconciled with that of ARDL wherein unidirectional causality from exchange rate volatility, exports, labour force and gross capital formation to economic growth was found.Research limitations/implicationsThe urgent recommendation is to develop and align fiscal, monetary, trade and exchange rate policies, either through creating a common currency region or through coordinated measures to offset volatility and trade risks in the long run. Further, to offset the impact of excessive exchange rate changes, BRICS economies can set up currency hedging systems, implement temporary capital controls during periods of extreme volatility or create currency swap agreements with other nations or regions. Last, but not least, investment and labour policies that are coherent and well-coordinated can support market stabilisation, promote investment and increase worker productivity and job prospects.Originality/valueResearchers hold contrasting views regarding the effect of exchange rate volatility on economic growth. Some researchers claim that exchange rate volatility reduces growth, and several shreds of empirical evidence claim that lower exchange rate volatility is linked with an increase in economic growth, at least in the short run. However, the challenge lies in establishing the optimal range beyond which exchange rate volatility becomes detrimental to economic growth. The present study contributes to this aspect by seeking to identify the optimal spectrum beyond which excessive shifts in exchange rate volatility negatively affect economic growth, or endeavors to define the acceptable spectrum within which these fluctuations actually boost growth. To the best of our knowledge, this study is the first to analyse the given research area. The present study used a dummy variable technique to capture the impact of permissible exchange rate band on the economic growth.

Trading with Frenemies: How Economic Diplomacy Affects Exports

Abstracts Trade is inherently risky, involving a commitment problem for both importers and exporters. The former must deal with ex ante uncertainty about whether exporters will deliver the goods or services as promised, while the latter has to identify an importer willing to trade a product. How, then, do firms establish trading relationships, especially in new markets? While both classical and newer trade theories tend to downplay the role of government in trade, we argue that government institutions play a crucial role in resolving this uncertainty. Specifically, export promotion agencies and embassies in foreign countries vet potential trade contacts and head off potential disputes before they get too serious, thus insuring against the basic risks of trade. We expect that this institutional backing will have stronger export-promoting effects on great powers’ trade with economically developing and politically dissimilar countries. Using a large collection of U.S. State Department cables from the 1970s that concern export promotion, we find strong evidence that promotion efforts had the largest effect when economic trade barriers were high and in countries that were politically dissimilar to the U.S. Rather than passively participating in trade, government bureaucrats play a large role in helping firms establish trading relationships.

Carbon financial trading risk based on multidimensional analysis of data flow from the perspective of low-carbon economy

Carbon financial trading risk based on multidimensional analysis of data flow from the perspective of low-carbon economy

The Effects of the Development Zone Upgrading on the Diversification of Firm’s Product Exports: Evidence from Chinese Exporters

Against the backdrop of frequent international trade frictions, reducing external risks in export trade through industrial policies has become crucial for China’s high-quality and steady foreign trade development. This paper examines the impact of development zone upgrading policies on the diversification of firm product exports by using a time-varying difference-in-differences model. We find that after the upgrading of development zones, the diversification of firm product exports increases by 2.13%, and concentration decreases by 1.33%. Moreover, this policy has a stronger impact on the diversification level of product exports for firms upgraded to customs special supervision areas, located inland, and engaged in general trade. These conclusions remain robust even after conducting additional robustness tests using alternative measures of the dependent variable, different identification methods for development zone upgrading, and controlling for other industrial policy effects. Furthermore, the upgrading of development zones improves export diversification through three main channels: enhancing firm innovation capabilities, optimizing management efficiency, and providing financial support to firms.

A Study on Combating Illegal Trade in Green Sea Turtles based on a Multi-Model Strategy

This study addresses the long-standing and increasingly complex issue of global illegal wildlife trade, proposing a system solution aimed at monitoring and combating this trade, with a special emphasis on the protection of green sea turtles. The ARIMA Predict Model was utilized to demonstrate that increased enforcement efforts and higher operational expenses are significantly associated with reduced volumes of illegal wildlife trade. An illegal trade risk model was developed, employing SLSQP to enhance accuracy, constrained by budget allocation, maximum RFID reader capacity, and device failure rates. Furthermore, the Sea Turtle Movement Model was crafted by examining seasonal behaviors, agent-based movement patterns, temperature preferences, stochastic elements, and simulation time steps, enabling the delineation of migratory paths of sea turtles across different seasons. Ant Colony Optimization (ACO) was applied to optimize patrol routes. The findings underscored the necessity for additional governmental support, encompassing legal authorization, environmental access, international collaboration, and financial backing. The project’s effectiveness was assessed using the Risk Reduction Coefficient Model and Monte Carlo simulations, which significantly reduced illegal trade by 34.43%, with projections indicating continued declines over the subsequent five years.

From isolation to revival: trade recovery amid global health crises

BackgroundThe COVID-19 pandemic has highlighted the importance of designing effective trade recovery measures in response to global health events (GHEs). This study combines international trade risk management theory and multi-case comparative analysis of past GHEs to present a theoretical framework for designing national trade recovery measures for future events.ResultsThe research finds that during GHEs, trade risks shift to fundamental uncertainty, requiring spatial–temporal-subject dimension recovery measures. The study suggests changing the focus of trade recovery policy design from emergency-oriented and single-dimension measures to reserve-oriented and enduring-effect measures of comprehensive dimensions at micro- and macroeconomic levels.ConclusionThe study contributes to the debate on managing trade risks in times of crisis, where there is a need to develop effective trade recovery measures that account for the complexities of global trade and the unique challenges of GHEs. The findings provide practical guidance for trade officials and policymakers to design measures in response to GHEs to improve a country’s overall trade recovery.

Supply chain risk in grain trading: Inventories as real options for shipping grain

AbstractIntegrating trading and logistics is an important challenge in commodity trading. Trading and logistics are strategic decisions and are integral to most commodities including grain shipping by rail, in addition to other modes (barges, ocean shipping). There are substantial risks, such as the ordering and placement of rail cars. The other risk is having sufficient grain stocks to load rail cars. Alternatives for managing these risks include holding grain inventories and the strategic use of shipping options. The purpose of this study is to develop a model for determining an optimal grain inventory strategy for shippers. The real option methodology is used to value uncertainty in rail car velocity and determine optimal purchases and inventories. The results show the importance of integrating trading and logistics decisions and illustrate that inventories can be interpreted and valued as real options that are affected by uncertainties. Taken together, the real options indicate how much extra inventory shippers should maintain to mitigate risks and maximize profits.

Research on Innovative Strategies and Practices for Optimizing Guangzhou's Foreign Trade Dependence

The article explores the optimization strategies for Guangzhou's foreign trade dependence, focusing on three major strategies: diversified market layout, innovation-driven development strategy, and coordinated development of service trade and goods trade. It is pointed out that Guangzhou needs to reduce its dependence on a single market by diversifying its market layout, enhance its core competitiveness in foreign trade through implementing an innovation-driven development strategy, and promote the coordinated development of service trade and goods trade to optimize its foreign trade structure and achieve high-quality foreign trade development. The implementation of these strategies will help Guangzhou reduce its foreign trade risks, enhance its international competitiveness, and provide strong support for the sustainable and healthy development of the economy and society.

Risk expectation from trade protectionism and firm innovation strategies: Theory and evidence from China

In this study, we construct a new measurement of a firm's trade risk expectation. We investigate how exporters’ innovation strategies respond to trade protection and their risk expectation by studying the global anti-dumping investigations against China. Specifically, using information on targeted products, we identify the trade risk level of each firm. We then develop a theoretical model to analyze how a multi-product firm adjusts its innovation strategies by its trade risk expectation when affected by anti-dumping measures, and the spillover effects of trade risk expectation on the firm's innovation strategies. This model predicts that first, affected firms will increase their R&D investment and innovation output in response to the increase of trade risk. Second, firms are more likely to choose high-quality innovation when their trade risk expectations increase. Third, for unaffected firms, an increase in trade risk expectation will lead to a growth in their innovation outputs. These predictions are aligned with the Chinese data, which are matched with an anti-dumping dataset from the Global Anti-dumping Database and several firm-level datasets. After changing the definition of trade risk expectation, excluding the cases also affected by countervailing measures and those with a zero anti-dumping tax rate, our results remain constant. This gives us further confidence that exporters with higher trade risks are more responsive to trade protection.

The asset-backing risk of stablecoin trading: the case of Tether

This article aims to analyse the asset-backing risk of stablecoins, focusing on international accounting standards, classification criteria, and auditing standards and using Tether as a case study. It examines Tether’s issuance, backing, controls, ratios, and regulations to assess risk transmission and mitigation. The results suggest a need for unified and strengthened accounting and auditing standards to enhance user confidence. Liquidity, solvency, and debt ratios were applied to Tether's balance sheets; while Tether has made efforts to increase its transparency, and although it possesses highly liquid assets, challenges remain regarding its liquidity, solvency, and debt. An independent auditors' valuation is crucial for investor confidence, demonstrating that more specific regulations are required for stablecoins. Future research should explore other stablecoins to comprehensively understand the accounting and auditing challenges in the field.