Trade Risk Research Articles

Sensitivity analysis of shock distributions in the world economy.

With the ever increasing interconnectedness among countries and industries, globalization has empowered economies and promoted international trade, capital flow and labor mobility, leading to improved products and services. However, the growing interdependence has also propelled an inherent reliance on joint cooperation which has considerably influenced the complexity of global value chains (GVCs). This plays a significant role in policy decisions, raising questions about trade risks that originate from such interdependence. In this paper, we study the impact of network linkage disturbances on the output supply and input demand of countries. We model the network interconnectedness of countries according to the latest 2016 release of the World Input-Output Database (WIOD) that includes data tables for the period 2000-2014 covering 43 countries as well as a model for the Rest of the World (ROW). We assess the shock distributions across the world economy by quantifying the changes in the network linkages using sensitivity analysis. Our contribution is in the definition of a shock tensor with the purpose of evaluating the impact of link sensitivity. The shock tensor is a straightforward yet comprehensive tool that allows us to obtain ample results at various levels of granularity when combining it with aggregation operators. Our study introduces a novel methodology that enables us to acquire input and output link sensitivities for all country pairings when an economic shock initiates or concludes within a country of interest. This innovative approach also facilitates the analysis of evolving trends in these link sensitivities, providing a comprehensive understanding of the dynamics of shock propagation across the global network. Taking advantage of the time-series nature of the WIOD, our results reveal illustrative visualizations and quantative measures that characterize patterns of shock distribution and relationships among countries throughout the period from 2000 to 2014. Our methodology and results not only uncover valuable trends but also establish a structured approach to better understand the aggregate effects of shock distributions. Thus, this study could be helpful for policy makers to assess trade relationships between countries and obtain quantitative insights for making informed decisions as well as explore the overall state of the globalization as a whole.

Identifying target areas for risk-based surveillance and control of transboundary animal diseases: a seasonal analysis of slaughter and live-trade cattle movements in Uganda

Animal movements are a major driver for the spread of Transboundary Animal Diseases (TADs). These movements link populations that would otherwise be isolated and hence create opportunities for susceptible and infected individuals to meet. We used social network analysis to describe the seasonal network structure of cattle movements in Uganda and unravel critical network features that identify districts or sub-regions for targeted risk-based surveillance and intervention. We constructed weighted, directed networks based on 2019 between-district cattle movements using official livestock mobility data; the purpose of the movement (‘slaughter’ vs. ‘live trade’) was used to subset the network and capture the risks more reliably. Our results show that cattle trade can result in local and long-distance disease spread in Uganda. Seasonal variability appears to impact the structure of the network, with high heterogeneity of node and edge activity identified throughout the seasons. These observations mean that the structure of the live trade network can be exploited to target influential district hubs within the cattle corridor and peripheral areas in the south and west, which would result in rapid network fragmentation, reducing the contact structure-related trade risks. Similar exploitable features were observed for the slaughter network, where cattle traffic serves mainly slaughter hubs close to urban centres along the cattle corridor. Critically, analyses that target the complex livestock supply value chain offer a unique framework for understanding and quantifying risks for TADs such as Foot-and-Mouth disease in a land-locked country like Uganda. These findings can be used to inform the development of risk-based surveillance strategies and decision making on resource allocation. For instance, vaccine deployment, biosecurity enforcement and capacity building for stakeholders at the local community and across animal health services with the potential to limit the socio-economic impact of outbreaks, or indeed reduce their frequency.

Opportunities for regional collaboration and prevention: Assessing the risk of the live bait trade as a pathway of invasive species

Anthropogenic introductions of invasive species via various trade and transport pathways have resulted in significant threats to native biodiversity, ecological services, and conservation programs. The live bait trade represents one anthropogenic pathway in which varying preventative actions may deter the introduction of aquatic invasive species. In this study, we collected 259 environmental DNA (eDNA) samples from 112 unique live bait retailers across the central United States to detect two high-priority invasive species in the ecologically and economically important Great Plains region. Additionally, we collected information on risk factors that may influence positive eDNA detections (presence of non-advertised fish species, presence of educational signage, and distance from established, high-priority, invasive populations) to evaluate current risk and preventative actions surrounding the live bait trade pathway. Out of the 100 initially assessed bait shops, 10 % tested positive for at least one invasive target species, 12 % had non-advertised species present within purchased baitfish, and 13 % displayed educational signage regarding invasive species. From a subset of repeated and new bait retailers, 11 % and 17 % tested positive, respectfully, and none had educational signage. We also found that bait retailers closer to recorded invasive species observations had a higher probability of having a positive eDNA detection, indicating that education and outreach should target invasion fronts. Our work highlights the opportunity and need for broad-scale approaches for regulations, education and outreach, and surveillance programs. Such collaborations are needed to evaluate inconsistencies in preventative actions among regions, successfully manage pathways of invasive species introductions, and better conserve natural resources.

A study on the legal risk assessment of virtual currency transactions based on statistical analysis

Abstract This paper first analyzes the definition and characteristic attributes of virtual currency transactions, secondly constructs the legal risk indicator evaluation system, then pre-processes the evaluation data and assigns the indicators, and then constructs the legal risk evaluation model using TOPSIS-grey correlation. Finally, the quantitative data analysis was carried out by analyzing the indicator weights and evaluating indicators. The results show that the overall score of the trading platform is 73.86, with the evaluation scores of the first-level indicators being 24.56, 11.35, 16.23, 15.42, and 6.30, respectively. This study fully illustrates that the use of TOPSIS-grey correlation analysis can provide data support and a decision-making basis for legal risk assessment and prevention and new directions for reforming and developing the legal risks of virtual currency trading.

Reproductive tactics, birth timing and the risk-resource trade-off in an income breeder.

In variable environments, habitats that are rich in resources often carry a higher risk of predation. As a result, natural selection should favour individuals that balance allocation of time to foraging versus avoiding predation through an optimal decision-making process that maximizes fitness. The behavioural trade-off between resource acquisition and risk avoidance is expected to be particularly acute during gestation and lactation, when the energetic demands of reproduction peak. Here, we investigated how reproductive female roe deer adjust their foraging activity and habitat use during the birth period to manage this trade-off compared with non-reproductive juveniles, and how parturition date constrains individual tactics of risk-resource management. Activity of reproductive females more than doubled immediately following parturition, when energy demand is highest. Furthermore, compared with non-reproductive juveniles, they increased their exposure to risk by using open habitat more during daytime and ranging closer to roads. However, these post-partum modifications in behaviour were particularly pronounced in late-parturient females who adopted a more risk-prone tactic, presumably to compensate for the growth handicap of their late-born offspring. In income breeders, individuals that give birth late may be constrained to trade risk avoidance for foraging during peak allocation to reproduction, with probable consequences for individual fitness.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.

Fortify the investment performance of crude oil market by integrating sentiment analysis and an interval-based trading strategy

To mitigate the impact of market uncertainty on trading investments, this paper proposes a forecasting and investing framework for crude oil market by integrating interval models and machine learning models. Firstly, natural language processing technique is employed to analyze text information from social and news media, enabling the capture of market and societal sentiment. Subsequently, deep learning models are integrated to combine sentiment data with other economic variables for more accurate predictions of crude oil prices. Furthermore, this paper introduces a trading strategy with interval constraints based on interval prediction models to reduce trading risk arising from the uncertainty of point forecasts in investments. Through trading simulations, it is discovered that employing the interval constrained strategy is more effective in reducing trading risk and enhancing investment returns compared to point-based trading strategies. This interval-based strategy offers a novel approach to mitigating investment risk in the crude oil market.

ROOT MAP OF RISK, PERCEPTION AND ACTION AT RETAIL TRADERS OF HONEY WATERMELON

The front side of the coin represents business potential, while the reverse side depicts the associated business hazards, indicating that risk is an important component of enterprise. The root cause of the risk, which can be used to decide what action to take, can be difficult to identify, when the hazard is not clearly characterized, as this may result in action simply covering the risk. Similar concerns exist in the honey watermelon business. This study involved 28 fruit traders (retailers) who were selected based on the census method. This research has three objectives. First, find out the root cause (risk) of the honey water melon trade to fruit traders in Bengkulu City by using the Ishikawa diagram analysis tool (risk causal map analysis). The research results obtained are prejudiced. Second, to find out the perceptions of fruit traders on the risks of the honey watermelon trade in Bengkulu City using the Likert-scale-analysis tool, the results are 75% categorized as neutral. Third, to find out the actions of the trader group on the risk of buying and selling honey melon. iIt is mostly carried out in Bengkulu City using a qualitative descriptive analysis tool, and the research results obtained by the traders choose to do research (examine) and carry out risk identification.

Predicting daily precision improvement of Jakarta Islamic Index in Indonesia’s Islamic stock market using big data mining

PurposeThis paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.Design/methodology/approachThis research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.FindingsThe experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.Practical implicationsThis research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.Originality/valueThis research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

Political risks, excess and carry trade returns in global markets

We re-examine the relationship between exchange rates and sovereign risk and provide evidence that sovereign risk affects advanced economies and emerging markets differently. Also, double-sorting 34 currencies from developed and emerging economies into different portfolios based on the level of macro risk and political risk, we provide evidence that local determinants of sovereign risk are priced in the FX markets. Local political risk in particular seems to have become an important carry trade risk factor in the post-2007 financial crisis era. High macro risk portfolios in the presence of high political risk lead to higher excess returns. Our results are robust across country categories and currency regimes, with stronger results for emerging economies. This is one of the few papers to examine how the local components of sovereign risk, rather than the systematic risk component, drive currency carry trade returns. We contribute a fresh perspective that supports the risk-based view on the UIP puzzle.

UCDM: A User-Centric Data Model in Power Blockchain

Background: As innovative information technology, blockchain has combined the advantages of decentralization, immutability, data provenance, and contract operation automatically, which can be used to solve the issues of single point failure, high trading cost, low effectiveness, and data potential risk in power trading. However, in the traditional power blockchain, the design of functional components in blockchain, such as the data structure of the block, does not take the actual features of power into account, thus leading to a performance bottleneck in practical application. Motivated by business characteristics of power trading, a user-centric data model UCDM in consortium blockchain is proposed to achieve efficient data storage and quick data retrieval. Methods: The proposed UCDM is designed by considering the requirements of transaction retrieval and analysis, thus supporting the requirements of concurrent data requests and mass data storage. The ID of each user will independently form its own chain over the blockchain. Results: Compared with the traditional data model, the extensive experimental results demonstrate that the proposed UCDM has shorter processing delay, higher throughput, and shorter response latency, thus having practical value. Conclusion: UCDM is an effective solution to the transaction retrieval and analysis in power blockchain. Furthermore, the participant of the blockchain network has a unique identity over the world, which ensures high security during trading.

The Future Role of International Trade Risk Elimination and Investment Promotion in the Development of Economic Relations Between Azerbaijan and Latvia

Abstract After regaining its state independence, Azerbaijan got a favorable opportunity to enter the world market. The income from the country’s rich oil and gas resources served to rapidly increase the gross domestic product. Today, the government of Azerbaijan is preparing an action plan for the development of the non-oil sector in order to reduce the country’s dependence on oil and gas exports. In particular, there are some economic spheres that have a great need to be revived and have the main share in budget revenues. Although Azerbaijan has left behind most of its competitors in the viticulture and winemaking sector for many years, in the current conditions this sector relies on foreign investments for its development. Although tourism opportunities in Azerbaijan are very wide, the level of service in hotels and recreation centers is very low. Expensive prices in return for the level of service provided have a negative impact on the growth of Azerbaijan’s tourism revenues. Unfortunately, there are also serious problems in the development of the forestry and machine-building industries and wheat production in the country. Latvia has already specialized and has some experience in exporting in the listed economic sectors in Eastern Europe. The entry of Latvian investment into Azerbaijan will serve to strengthen economic relations between the two countries and maximize mutual income. In the research work, these issues will be considered and analyzed separately by economic spheres.

China-Australia Trade Relations and China’s Barley Imports

The high concentration of China’s barley import sources determines that China’s barley import trade is vulnerable to the impact of tariff policy adjustment. In particular, in 2020, China implemented anti-dumping and anti-subsidy policies against Australia, the largest source of barley imports. Therefore, whether China’s barley import trade will face import risks due to the adjustment of tariff policy has become a question worth discussing. Based on the above background, this study uses the partial equilibrium model to explore the impact of China’s adjustment of tariff policy on imported barley from Australia on China’s barley industry under the changing trade relations between China and Australia. Through analyzing the feasibility of developing domestic barley industry and expanding barley import sources, further explore strategies to deal with barley import trade risks. The results show that: Under the three import tariff adjustment simulations, the total import volume of China’s barley shows a downward trend, and the import price increases to varying degrees. However, the relatively small increase in domestic production suggests that the domestic barley market is less able to cope with the risk of a sharp drop in imports. At the same time, affected by the adjustment of tariff policy, some Chinese consumer demand is difficult to satisfy. China can deal with trade risks by implementing an import diversification strategy.

Impact of the Taiwan-China War on Indonesian Trade

Risks of China versus Taiwan War Indonesia needs to be aware of the tension between China and Taiwan, which has heated up again after being triggered by Nancy Pelosi's trip to Taiwan as chairman of the US House of Representatives (DPR), the conflict between the two could have an impact on trade performance, tensions between China and Taiwan are also now isattracting the attention of the world. This geopolitical conflict needs to be watched out for by Indonesia, considering that China-Taiwan has been Indonesia's important trading partner in the last two decades because it will have an impact on Indonesia's trade and good relations with the two countries; Indonesia needs to minimize trade risks due to the conflict between the two countries by looking for export destinations. as well as sources of imports from other countries. China is Indonesia's leading trading partner, with an international trading contribution of more than 20% in 2021. This contribution places China as Indonesia's number 1 export destination with an export value of USD 53.8 billion. In the same year, China was also the most significant import destination country, with an import value of USD 56.3 billion. Indonesia's trade with Taiwan also continues to grow every year. In 2021, Indonesia's exports to Taiwan were worth USD 7.0 billion, placing Taiwan as the ninth largest export destination for Indonesia.

A multi-criteria decision-making framework for distributed generation projects investment considering the risk of electricity market trading

Under the background of distributed generation (DG) participating in market trade, the scale of DG has developed rapidly. The investment decision of DG is actually a multi-criteria decision-making (MCDM) problem, nevertheless the current framework rarely considers the risk of market trading. Thus a framework containing scheme attributes and market risks needs to be established. Firstly, an index system including economic benefit, environmental and social benefit and market risk is established. Secondly, subjective and objective weight are combined by using game theory in weighting process. Among them, the subjective weight of each index is determined based on the plus-minus decision-making trial and evaluation laboratory model (plus-minus DEMATEL); the objective weight is determined by the combination of triangular intuitionistic fuzzy number (TIFN) and integrated determination of objective criteria weights (IDOCRIW) model. Finally, the TODIM model is used to rank the alternatives. Taking Shanghai as a case study, the robustness of the proposed framework is verified by sensitivity analysis and comparative analysis. The results show that the weights of index C34 is 0.12, indicating that market participants have a greater influence on market risk. The research will provide an effective tool for investment decision of DG in market trading.

Mengembangkan Penjualan UMKM Alby Key dengan Web E-Commerce

During the pandemic, people are exposed to the risks of in-person trading and tend to switch to digital trading. The purpose of this study is to examine the development of micro, small and medium enterprises (MSMEs) using the waterfall method. The data shows that online sales and purchases have increased significantly, prompting businesses to adopt digital distribution systems. The research highlights the need for community creativity, especially to reduce direct transactions and increase revenues through Internet platforms. In business settings, e-commerce acts as an intermediary for online transactions. Develop online sales and provide features that help buyers improve customer satisfaction and overall sales. The study provides a systematic and sequential overview of how MSMEs are evolving in meeting the challenges of the pandemic, highlighting the importance of adaptation and innovation in digitally enabled trading to business success.

From Large to Powerful: International Comparison, Challenges and Strategic Choices for China’s Livestock Industry

Accelerating the construction of a strong livestock industry is of great significance to better guarantee the supply of livestock products and improve the quality, efficiency and competitiveness of the industry. This study constructed an evaluation index system including supply security, scientific and technological support, industrial resilience and international trade to evaluate the strength of China’s livestock industry, and then conducted an in-depth analysis of the issues and challenges of the construction of a livestock powerhouse. The research results showed that China’s livestock industry ranked 5th in the world, such that China was transitioning from being a large-producing livestock country to being a livestock powerhouse, although improvement was still needed to reach the goal. There were significant differences across species. China’s layer industry was a world leader; the pig, sheep and goat, and broiler industries were strong; and the beef cattle and dairy industries were weaker. There are still many challenges, such as the fact that the domestic supply security capacity needs to be strengthened, the level of scientific and technological support needs to be improved, the modern operation system needs to be sound, the industry and supply chain are not highly resilient, the international trade risks are increasing, and the policy support system needs to be improved. It is recommended to improve the institutional mechanism for the construction of the livestock industry, promote a high level of self-reliance and self-improvement in science and technology, build a modern livestock operation system, enhance the resilience and security level of the industry and supply chain, and consolidate and expand international trade and cooperation.

Untangling the web: dynamics of Australia's online terrestrial invertebrate trade

AbstractThe trade and keeping of exotic pets has serious implications for both biosecurity and biodiversity conservation. In Australia, the online trade of live invertebrates is an understudied and unregulated issue, with almost non‐existent monitoring. It is uncertain what species are being traded, whether they are being identified correctly, and how they are being sourced (i.e., captive bred or wild harvested, native, or alien). Consequently, potential invasion risks and conservation concerns remain unknown. Here, we explored the online trade of terrestrial invertebrates in Australia across a range of publicly available e‐commerce platforms. We detected 264 species of invertebrate traded, from 71 families and 168 genera over 12 months. The native Extatosoma tiaratum (giant prickly stick insect) was the most traded species, while the most popular families were Phasmatidae (stick insects), Formicidae (ants) and Theraphosidae (tarantulas). Three species are known to be invasive in Australia, while 87% of species traded were native. The conservation status of almost of the species (92%) listed in the invertebrate trade has not been evaluated. Exploring socio‐demographic relationships, we found that human population density was positively correlated with the location of invertebrate sellers. Further, we found the classifieds website had lower prices in contrast to traditional online pet‐stores (median of c. A$7 less). Finally, we did not observe a saturation in the number of species traded in our one‐year study, exemplifying the need for large scale monitoring and risk assessments for Australia's online terrestrial invertebrate trade. We recommend continued surveillance of live invertebrate trade on e‐commerce sites. Substantial changes to legislation and monitoring methods are required at a national level to control the vast number of invertebrates traded across the country, and to minimise the future risks of the invertebrate trade.

Insider Trading in the Clinical Trial Setting

The Securities and Exchange Commission’s enforcement agenda regularly includes charges of trading based on material nonpublic information about a clinical drug trial conducted to obtain FDA approval to market a new drug. Almost half of the recent cases have been accompanied by a criminal indictment. In an academic setting, researchers and those who advise them, unlike employees of public companies, are not generally given training about the risks of securities trading. Recent developments in the law might be applied in connection with clinical trial information in ways that would not have been foreseen until recently. It is time for a comprehensive analysis of how the law of insider trading may be applied to the important endeavor of clinical drug trials. Clinical trials should not be sullied by conflicts created by unlawful trading. This Article begins with the basic principles of insider trading, followed by a summary of how clinical trials are conducted and regulated. It then turns to the ways in which nonpublic information material to the stock price of the sponsor of the trial might be used to trade or tip. The analysis that follows identifies a number of situations where use or disclosure of material nonpublic information about a trial could be unlawful. Employees of sponsors of the trial, clinical investigators, and even the subjectsparticipating in a trial could run afoul of the prohibition on insider trading, such as when information has been used in breach of a confidentiality agreement or exchanged between an investigator and a trial participant, exchanged among trial participants, gleaned from attending medical conferences, and obtained in other settings specific to this industry. Presenting the full potential reach of the law facilitates taking steps to avoid violating the law. The analysis demonstrates that anyone involved in a clinical drug trial must be attuned to the risks of misusing material nonpublic information, including in scenarios not yet pursued by the SEC. By understanding the potential reach of the law, those involved in or who learn information about a specific trial can take steps to avoid or minimize the risk of liability. The Article concludes with recommendations to achieve this end. The Article thus presents a complete case study of an industry-specific application of insider trading law, with recommendations that can be applied to other industries.

Modeling the systemic trade risk of crude oil from a network perspective, combined with a sentiment proxy

Introduction: Trade networks of crude oil are susceptible to cascade of initial shocks that increase systemic trade risks and threaten energy security. This study introduces a novel method of modelling systemic trade risk of crude oil which is combined with a sentiment proxy from a network perspective.Method: We construct sentiment instability to evaluate the uncertainty of crude oil trade in a country and use the PageRank algorithm to measure supplier diversity from a network perspective instead of direct trade partners.Result: At the global level, we show that the distribution of systemic oil trade risk has an obvious heterogeneity and a significant negative correlation between systemic trade risk of crude oil and trade volume volatility. At the regional level, we compare the systemic trade risk of crude oil between China and America and systemic trade risks show strongly significant correlations with the price volatility in both China and America. Furthermore, the structure of trade network can effectively reduce the systemic risk in America while it increases the systemic trade risk in China.Discussion: Our results can give a reason for an irrational practice of Chinese crude oil imports which are “buying when the price is rising and not buying when the price is declining”.