Trade Research Articles

Unveiling the Economic Impact of Technology Trade in Leading Global Economies

Abstract In today's rapidly evolving technological era, high-tech trade is not just a part of international commerce but a key factor that shapes the economic landscapes of nations. The objective of this paper is to analyze how technological innovation, as represented by high-tech exports, contributes to economic growth and to identify the disparities in economic progress among countries with different levels of integration into the global high-tech market. This paper focuses on the importance of high-technology trade in economic development. Specifically, it aims to establish a connection between technology-intensive exports and Gross Domestic Product in three major global economies: China, the United States, and the European Union. The study's empirical evidence strongly supports a notable association between high-technology exports and the growth of gross domestic product, thereby reaffirming the crucial role of technological trade in enhancing economic development. Furthermore, the analysis provides additional insight by highlighting those economies with extensive involvement in the global high-technology market experience superior economic growth. This underscores the vital significance of technological innovation and trade integration in attaining a competitive advantage in the global economic landscape. This study adds to the existing literature by providing empirical evidence of the economic consequences of technology trade, highlighting the need for policy frameworks that encourage innovation and integration into the global high-technology market.

PROBLEMS AND PROSPECTS OF FINANCIAL DERIVATIVES MARKET DEVELOPMENT

The article studies the problems and prospects of the financial derivatives market development. Globalizing the economic space contributes to transforming the stock market into the principal source of capital allocation. Still, the current conditions of the derivatives market in Ukraine do not correspond to the needs of the national economy, which requires strengthening the regulation of their activities to ensure the hedging of risks of market participants. The article analyses the dynamics of derivatives trading in the global exchange market, assesses the dynamics of world exchange trading in financial derivatives, and analyses the turnover of OTC derivatives in the EU. It also studies the dynamic changes in the amounts paid under the terms of contracts for derivative securities in the world by maturity, region and industry sector; the dynamics of options and futures trading in the global exchange market. In this analysis, we examine the trading volumes of derivatives within the financial market of Ukraine. We estimate the volume of trading within both exchange and over-the-counter markets, and present the dynamics of exchange contracts as well as the share of financial instrument trading in the securities market. The factors hindering the development of the derivatives market in Ukraine are identified. These factors include legislative shortcomings, the current level of derivatives market infrastructure, and the current state of development of the underlying asset markets. The article also analyses the derivatives market and provides prospects for its development. To ensure the future development of the financial derivatives market in Ukraine, it is essential to take certain measures. These include comprehensive regulation of the derivatives market, ensuring the operation of regulated markets and building their infrastructure, and introducing appropriate instruments to protect participants and hedge risks.

The Predictive Ability of U.S. Stock Market Skewness on Indonesian Stock Market Returns

The three-moment capital asset pricing model (three-moment CAPM) suggests that the expected excess return on stocks should include compensation for skewness risk. This study aims to investigate the ability of U.S. stock market skewness to predict Indonesian stock market returns. The data used in this research includes the S&P500 Index, JCI, JII, and LQ45 from January 2001 to December 2022. The results of this study indicate that U.S. stock market skewness can predict future excess returns of the Indonesian stock market. Additionally, when the estimation model incorporates alternative variables from both the U.S. and Indonesian stock markets, the predictive ability of U.S. stock market skewness remains significant and outperforms these alternative variables. The findings of this research can be used as a strategy for investors when trading in the Indonesian stock market. When the skewness of the U.S. stock market increases, the return of the Indonesian stock market is expected to decrease in the following month.

Freeport as a Hub in the Art Market: Shanghai Art Freeport

With the soaring interest in art as an alternative investment approach and an asset class, there has been a remarkable rise in the volume of artwork transactions globally. However, trading in the art market differs from the traditional financial market; the cost of taxes, logistics, storage, and other transaction services is enormous for collectors, stimulating the emergence of related businesses, such as warehousing, bonded exhibitions, and art financial services. As an exceptional area serving the offshore economy, art freeports have become an essential venue for art trading and a ‘one-stop-shop’ centre that converges all art market participants. This article critically analyses the current literature and conducts empirical research on Shanghai FTZ International Culture Investment and Development Co., Ltd. (FTZART). It can be concluded that the current research on art freeports is limited and excludes FTZART from those that specialise in storing artworks, overlooking its potential influence in the Asian market. The art freeport has distinctive features that differ from traditional freeport models, and the context, business model, and operations of FTZART match these characteristics. Therefore, as a hub in the art market, the global art freeport agenda should not overlook FTZART, and it is essential to complement this gap in knowledge.

Decentralized micro-energy storage capacity sharing within the residential community: an enhanced uniform price-based bidding framework

“Sharing economy” refers to a transformative socio-economic phenomenon where individuals or institution with idle resources transfer the right to use resources for economic compensation. With the widespread adoption of distributed photovoltaic generation and energy storage (ES) device in residential communities, there is a growing interest in establishing a suitable platform for residential users to share their ES capacity with community shared equipment controllers (CSECs). This paper proposes a local ES capacity sharing market, and presents the market trading process, pricing and allocation rules using an iterative uniform-price bidding mechanism Acknowledging the selfish-interest of both RUs and CSECs, we introduce the resource management organization (RMO) as a regulated third-party organization responsible for administering the market. To evaluate the proposed scheme, we conduct case studies based on real-life data from Pecan Street. The numerical experiment results demonstrate the effectiveness and applicability of our approach.

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system

To build a comprehensive framework for virtual power plant (VPP) development aligned with market dynamics and to devise effective strategies to foster its growth, this study undertakes several key steps. Firstly, it constructs a VPP development framework based on market conditions, to drive the evolution of new power systems and facilitating energy transformation. Secondly, through a blend of theoretical analysis and model construction, the fundamental principles of VPP are systematically elucidated, and a decision model for the VPP development framework, focusing on price demand response, is formulated. Lastly, an optimal scheduling model for the new power system is developed, with its efficacy validated across three distinct scenarios. The findings underscore the critical importance of integrating energy storage technologies, particularly pumped storage hydropower systems, for achieving balance and optimization within new power systems. Model verification reveals that the incorporation of energy storage power stations significantly enhances system stability and efficiency, particularly in addressing the volatility associated with renewable energy sources. Additionally, the analysis indicates that while the adoption of energy storage technologies may marginally increase overall power generation costs, the total power generation cost declines with the integration of battery storage and pumped storage hydropower stations. This suggests that leveraging energy storage technologies not only enhances system operational reliability but also contributes to reducing the overall cost of power production to a certain extent. In summary, this study presents an economic and environmentally sustainable scheduling model for new power systems within the context of market trading environments. By offering both theoretical insights and practical guidance, it aims to support sustainable development and energy transformation initiatives. Ultimately, the study is poised to foster the adoption of clean energy, facilitate the establishment of smart grids, and bolster the sustainable utilization of energy resources, thereby advancing environmental conservation efforts.

A two-tier bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism for coupled electricity and carbon markets

To facilitate the coupling of electricity and carbon markets, a two-layer bidding model considering a multi-stage offer‑carbon joint incentive clearing mechanism is proposed. The upper layer models the bidding strategies of renewable energy units and thermal power generating units, and the lower layer is the market clearing layer. A multi-stage offer‑carbon joint incentive clearing mechanism is proposed. In the pre-clearing stage, the environmental benefit factor of the carbon market is introduced to adjust the bidding strategy of the units, the carbon emission intensity enters the market in the form of price, the environmental benefit of the generating units is fully considered, and the carbon quota allocation model of units is established; in the second stage, carbon trading cost is added based on the pre-clearing model to further optimize the unit output; in the third stage, the clearing model with the minimum cost of electricity energy is established for tracking the clearing price. Under this mechanism, the carbon trading cost is traded on the market and unit offers are combined with carbon element to participate in market trading. Three bidding models with different clearing mechanisms are set up, and the results of the arithmetic example show that the proposed model can realize the balance between the economic and low-carbon goals of market clearing, and can achieve the maximum carbon emission reduction based on no increase in the total cost of electric-carbon coupling. As the share of renewable energy increases, the clearing price will decrease. A reasonable offer from renewable energy sources can avoid their interests being jeopardized. Concurrently, increasing the initial carbon price can effectively guide the electricity market to develop in a cleaner direction.

E-COMMERCE IN INTERNATIONAL BUSINESS

Divers may find plenty of opportunities in the international business world, but staying afloat can be challenging. In addition to the fact that this integration of IB with e-commerce will lead to an increase in complexity, it will also facilitate trade and remove many other obstacles that were previously present. A tremendous asset that one may learn and grow from is the quick growth of partnerships across countries worldwide as a consequence of IB, which has led to the best of each other's land and the flow of products and services. International business encompasses any profitable endeavours that promote the international transfer of goods, services, people, ideas, and technology. What are known as "internal business operations"? They occur within the borders of a nation. When companies buy and sell items, commodities, and services over international boundaries, it's called international commerce. This kind of firm is called an international business. The government or a commercial entity may own such trading techniques. Additionally, the country's economy remains steady. There are no competitors in a perilous nation. A global corporation's tools, goals, and objectives should inform its strategy development process.

The Impact of Trading Volume on Stock Price Volatility

In the capital markets, research on the impact of market trading volume on asset prices and returns has been ongoing since the 1960s, and remains a focus of attention for scholars and investors both domestically and internationally. Studies on the relationship between volume and price primarily concentrate on the volatility of stock prices in relation to trading volume, and the correlation between stock return rates and trading volume. In empirical research on the volume-price relationship, the main theories are inseparable from the study of market information. Trading volume encompasses the market's reaction speed to information and the extent of information's impact on the market, which are significant reasons why trading volume can affect stock market prices and returns.

Dual holdings and shareholder–creditor agency conflicts: Evidence from the syndicated loan market

AbstractWe examine implications from the expansion of private equity (PE) firms into the collateralized loan obligation (CLO) (i.e., leveraged lending) business. Due to similarities in the investment universes of CLO managers and PE firms, asset managers running both of them frequently hold debt and equity claims of the same company. Our results indicate lower credit costs for these companies through the mitigation of shareholder–creditor agency conflicts. The lower funding costs imply increased equity returns for the sponsoring PE firms. In addition, our findings suggest that PE‐affiliated CLO managers benefit from informed trading in the secondary leveraged loan market.

Enhancing renewable energy certificate transactions through reinforcement learning and smart contracts integration

Given the complexity of issuing, verifying, and trading green power certificates in China, along with the challenges posed by policy changes, ensuring that China’s green certificate market trading system receives proper mechanisms and technical support is crucial. This study presents a green power certificate trading (GC-TS) architecture based on an equilibrium strategy, which enhances the quoting efficiency and multi-party collaboration capability of green certificate trading by introducing Q-learning, smart contracts, and effectively integrating a multi-agent trading Nash strategy. Firstly, we integrate green certificate trading with electricity and carbon asset trading, constructing pricing strategies for the green certificate, carbon, and electricity trading markets; secondly, we design a certificate-electricity-carbon efficiency model based on ensuring the consistency of green certificates, green electricity, and carbon markets; then, to achieve diversified green certificate trading, we establish a multi-agent reinforcement learning game equilibrium model. Additionally, we propose an integrated Nash Q-learning offer with a smart contract dynamic trading joint clearing mechanism. Experiments show that trading prices have increased by 20%, and the transaction success rate by 30 times, with an analysis of trading performance from groups of 3, 5, 7, and 9 trading agents exhibiting high consistency and redundancy. Compared with models integrating smart contracts, it possesses a higher convergence efficiency of trading quotes.

When ownership and copyright are separated: Economics of non-fungible token marketplaces with secondary markets

Creators have long strived to secure royalties for their works but with little success. In the digital realm, monetization presents an even greater challenge, as traditional digital assets frequently suffer from piracy issues, primarily due to the lack of verifiable ownership. Recently, non-fungible token (NFT), a blockchain-enabled tradable digital asset, has aroused great public attention for its potential to address this long-standing issue. Specifically, NFTs empower creators by enabling them to earn resale royalties from post-primary-sale transactions and by providing verifiable ownership that facilitates consumer trading in a secondary market. In this paper, we employ a two-stage game-theoretic model to examine this innovative business model. Here, an NFT creator makes optimal pricing and royalty rate decisions, while consumers make their purchase and resale decisions accordingly. Our study reveals that the creator inevitably reduces the selling price when a secondary market is introduced, even without imposing royalties. Moreover, contrary to conventional wisdom that NFT-enabled royalties always benefit creators, our research uncovers that the introduction of a secondary market leads to unintended revenue loss for the creator, particularly when most consumers only engage in secondary transactions. Furthermore, we find that the platform's profitability diminishes with the introduction of a secondary market, especially when most consumers are uninformed and the platform relies primarily on the primary market for commission collection. Finally, we find that the introduction of a secondary market may leave consumers worse off, despite the resale opportunities it offers. Our findings carry crucial managerial implications for platforms, creators, consumers, and policymakers.

Optimizing Stock Markets Trading with Poisson Process Simulation

Industrial and Operations Research (IEOR) is an interdisciplinary field that leverages mathematical, statistical, and computational techniques to design, analyze, and optimize complex systems. In the context of the Simulation for Enterprise-Scale Systems course, the knowledge gained from IEOR can be applied to address a range of issues related to financial modeling, risk analysis, and decision- making within financial corporations. One area where simulation is particularly prevalent is in the financial markets, where price fluctuations can create significant arbitrage opportunities. The focus of this inquiry is on utilizing simulation systems to facilitate stock market trading, considering factors such as market noise, information asymmetry due to information lag, and other elements in order to optimize portfolio performance through arbitrage operations in the current market state.

Optimization model of monthly continuous bidding transaction in electricity market considering risk hedging

In order to further alleviate the problems of large assessment deviations, low efficiency of trading organisation and difficulties in system optimisation in medium- and long-term market trading, the article proposes an optimisation model for continuous intra-month bidding trading in the electricity market that takes into account risk hedging. Firstly, the current situation of market players’ participation in medium and long-term trading is analysed; secondly, the impact of contract trading on reducing operational risks is analysed based on the application of hedging theory in the primary and secondary markets; finally, the continuous bidding trading mechanism is designed and its optimisation effect is verified. The proposed model helps to improve the efficiency of contract trading in the secondary market, maintain the stability of market players’ returns and accelerate the formation of a unified, open, competitive and well-governed electricity market system.

Hierarchical Coordinated Control Strategy for Active Power in Distribution Networks with Scaled Distributed Generation Access

Promoting scaled distributed wind turbines and photovoltaic, and other distributed generations access to the distribution network is an important measure for realize the goal of carbon peaking and carbon neutrality and to build new-type power systems. However, as the installed capacity of wind turbine, photovoltaic and other intermittent renewable energy sources climbs dramatically, the security and consumption problems of the distribution network are becoming increasingly prominent, and there is an urgent requirement to improve the active power control capability of distributed generation. To optimize the operation stability and consumption economy of the distribution network, a hierarchical coordinated control strategy for active power of scaled distributed generation is proposed based on the principle of unified control and hierarchical management, including peaking control, frequency control, mesh control and market trading control, to coordinate and optimize the system operation safety and consumption economy. The proposed strategy optimizes active power control instructions in the layer of distribution network layer, mesh layer, and functional area layer, thus fully expanding the depth and breadth of the consumption for distributed generation. The effectiveness of the proposed strategy is proved by the actual operation of Liaoning power grid.

Rapid and Sensitive Detection of Inactivated SARS-CoV-2 Virus via Fiber-Optic and Electrochemical Impedance Spectroscopy Based Aptasensors.

The development of rapid detection tools for viruses is vital for the prevention of pandemics and biothreats. Aptamers that target inactivated viruses are attractive for sensors due to their improved biosafety. Here, we evaluated a DNA aptamer (named as 6.9) that specifically binds to the inactivated SARS-CoV-2 virus with a low dissociation constant (KD = 9.6 nM) for the first time. Based on aptamer 6.9, we developed a fiber-optic evanescent wave (FOEW) biosensor. Inactivated SARS-CoV-2 and the Cy5.5-tagged short complementary strand competitively bound with the aptamer immobilized on the surface of the sensor. The detection of the inactivated SARS-CoV-2 virus was realized within six minutes with a limit of detection (LOD, S/N = 3) of 740 fg/mL. We also developed an electrochemical impedance aptasensor which exhibited an LOD of 5.1 fg/mL and high specificity. We further demonstrated that the LODs of the FOEW and electrochemical impedance aptasensors were, respectively, more than 1000 and 100,000 times lower than those of commercial colloidal gold test strips. We foresee that the facile aptamer isolation process and sensor design can be easily extended for the detection of other inactivated viruses.

Spatial Qualitative Analysis of the Marine Heritage Tourism in Bontoharu-Bontosikuyu District, The Selayar Regency

Marine cultural tourism, a developing tourism mode, has grown in popularity among tourists in recent years, indicating broad market prospects (Zheng et al., 2017). Selayar Islands Regency is an international commerce route believed to have existed since 1820. According to preliminary data, a shipwreck with ceramics and money coins was discovered in the Bontosikuyu District and its surrounds in China. It is believed that these coins circulated throughout the archipelago between the 11th and 14th centuries. However, the vast potential has not been realized. In addition, there is a risk of local populations exploiting maritime cultural heritage objects for economic gain. This study is to investigate the potential of marine heritage as a new tourism destination in the Selayar Islands Regency. This research methodology is spatial qualitative, with spatial analysis using the ArcGIS application followed by qualitative identification of tourism potential using the 3A approach (attractions, amenities, accessibility). The study identified numerous prospective places based on interviews with stakeholders and study literature for marine heritage tourism that could serve as a tourist route. The proposed route has yet to be tested. Its potential is based solely on observation results; literature reviews; and conversations with stakeholders. This research aims to identify prospective maritime heritage routes in the Selayar Islands Regency. The study's findings indicate that the potential for marine heritage tourism packages in Selayar Regency is enormous but due to a lack of attention, it requires significant improvement and development in terms of attractions, accessibility, and amenities.

E-COMMERCE IN INTERNATIONAL BUSINESS

Opportunities abound for divers in the global economic arena, but maintaining a steady footing can be difficult. While combining IB with e-commerce will certainly make things more complicated, it will also make trade easier and eliminate a lot of other problems. The free flow of goods, services, and ideas has flourished as a result of the stronger bonds that have been forged between nations through international trade. Worldwide trade encompasses all economic activities that facilitate the exchange of products, services, people, ideas, and technology beyond national borders. Anything a business does inside its own country is considered to be part of its internal operations. International commerce refers to the purchasing and selling of products and services across international borders, whereas international businesses are those that participate in this activity. Such trade procedures can be owned by a private company or the state. Furthermore, the national economy remains stable. A dangerous country can overcome any obstacle. The strategic planning of a multinational firm should be based on the resources, goals, and objectives of the company. Keywords: International business, e-commerce integration, cross-border trade, rapid development, global relationships, flow of goods and services, cross-border allocation, internal business operations, international commerce, economic stability, strategic development.

Design of Intelligent Political Test Paper Generation Method Based on Improved Intelligent Optimization Algorithm

With the development of artificial intelligence, computer intelligent grouping, as a research hotspot of political ideology examination paper proposition, can greatly shorten the time of generating examination papers, reduce the human cost, reduce the human factor, and improve the quality of political ideology teaching evaluation. Aiming at the problem that the current political ideology examination paper-grouping strategy method easily falls into the local optimum, a kind of intelligent paper-grouping method for political ideology examination based on the improved stock market trading optimisation algorithm is proposed. Firstly, by analyzing the traditional steps of political thought grouping, according to the index genus of the grouping problem and the condition constraints, we construct the grouping model of political thought test questions; then, combining the segmented real number coding method and the fitness function, we use the securities market trading optimization algorithm based on the Circle chaotic mapping initialization strategy and adaptive t-distribution variability strategy to solve the grouping problem of the political thought test. The experimental results show that the method can effectively find the optimal strategy of political thought exam grouping, and the test questions have higher knowledge point coverage, moderate difficulty, and more stable performance.

Optimization method for renewable energy investment planning in the electricity carbon coupling market environment considering economy

China is developing rapidly in renewable energy development, electricity market reform, and carbon market construction, using market mechanisms for efficient planning and investment. The electricity and carbon markets are interrelated for market entities. This context has led to a dual-level optimization model for renewable energy investment planning, considering cost recovery and new power system goals. The model includes deriving electricity carbon coupling quotations for conventional units based on dynamic carbon emission characteristics and proposing an electricity spot market mechanism influenced by carbon quota trading. The model’s upper level maximizes renewable energy investment capacity, determining its size and location, while the lower level simulates electricity spot and voluntary emission reduction market trading to guide investment decisions. The model transformed into a mixed integer linear programming problem for optimal solutions was validated numerically, examining various factors affecting optimal renewable energy investment capacity.