Trade Opportunities Research Articles

Digital Grading Company: Deep Neural Networks for Predictive Analytics for Alternative Asset Portfolio Management

In this study, we investigate the application of deep neural networks for predictive analytics in the realm of alternative asset portfolio management, focusing on Trading Card Games (TCGs) like Pokemon. Our primary objective is to understand the optimal trading cards for investment and to determine the appropriate timing for divestment and retention of these assets. Drawing on the successful implementation of machine learning predictive analytics in traditional financial markets, we aim to extend these techniques to alternative investments. To achieve this, we employ a two-pronged approach using a comprehensive dataset of historical sales values for Pokemon TCGs spanning five years, comprising over 200 million unlabeled data points. The first approach utilizes a semi-supervised sequence learning method, where a Long Short-Term Memory (LSTM) model is initially trained as a sequence autoencoder. The pre-trained model's weights are then used in a supervised phase to fine-tune the predictions for future trading card values. The second approach involves heuristic pretraining, which leverages market-derived indicators from existing literature to bridge the gap between traditional feature engineering and deep learning methods. Our technology stack is designed to handle end-to-end data collection, analytics generation, and execution of recommended trading strategies. Simulated backtesting results demonstrate that our Digital Grading Company (DGC) portfolio model outperforms traditional indices, achieving a 357% return compared to the 61% return of the S&P 500 Index over the same period. Real-time analysis further indicates that our model consistently identifies profitable trading opportunities in the TCG market using hourly data and proprietary algorithmic trade logic, executing trades 24/7. The DGC Predictive Portfolio, based on ungraded Pokemon TCG trading cards, also shows superior performance when compared to the Nasdaq 100 Index (Invesco QQQ ETF). Our analytics framework not only predicts the direction of price movement but also provides insights into the magnitude of changes, enabling a more dynamic and responsive trading strategy. The findings suggest that the integration of deep learning models with heuristic indicators has the potential to revolutionize portfolio management in alternative investments, paving the way for more accurate and profitable decision-making in niche markets. This research highlights the promising role of machine learning in enhancing alternative asset management strategies, suggesting future applications in other asset classes. We conclude that deep neural networks, when combined with data-driven heuristics, can significantly enhance trading outcomes, making them valuable tools for investors in the evolving landscape of alternative investments.

The Economic Effects of Globalization on Developing Countries

Globalization is the dramatic change in the world economy, a situation in which across the border exchange activities and economic integration are becoming more intense between nations across a worldwide economic system. The paper discusses the multifaceted faces of globalization pressure on developing countries and identifies key benefits that result from such growth, as well as significant challenges. It illustrates how technology development, improved communication, and growing international trade are some of the more obvious drivers of globalization, as well as bring out the complex interface between global forces and local conditions. The main focus of this research is to present a comprehensive review of the negative and positive impacts of globalization on developing nations. The study epitomizes the enormous benefits accruable from increased market access, foreign direct investment, transfer of technology, and improvement in living standards. Opening to larger international markets helps the developing countries to diversify their economies and accelerate growth. For instance, both China and India use globalization to achieve high rates of economic growth by increasing trade and investment opportunities. It has also made vital capital and technological expertise available and has promoted much-needed industrialization and productivity enhancement. Technology transfer has enabled developing nations to step into the modernization of their industry for a more productive integration of the country into global value chains. This, in turn, will enable them to achieve higher economic growth rates and an improved standard of living. Despite such positive contributions from globalization, there are still some challenges that come along and really inhibit development. It addresses crucial backwardness, including increasing income disparity, high vulnerability to external economic shocks, and environmental degradation. In as much as globalization may result in economic growth, the accruing benefits are usually distributed very unequally, and often heighten disparities between urban and rural areas, thereby occasioning social tensions. Developing countries that are heavily dependent on exports or foreign investment may face severe economic instability during a global financial crisis. These impacts were clearly felt in most developing economies when the global financial decline occurred in 2008. Their quests for economic growth, however, have often been accompanied by unsustainable practices that bring with them environmental degradation in the form of deforestation, pollution, and the depletion of resources. Considering these benefits and challenges of globalization, some recommendations in the study for developing countries include:. These comprise domestic institution building to manage the increased complexities from globalization, investment in education and skills development to improve human capital and reduce job displacement, sustainable practices that reduce environmental impacts, and inclusive growth that allows the fruits of globalization to be equitably distributed. This will enable developing nations to manage the increased complexities from globalization and ensure sustainable economic development for their citizens. This study, in short, tried to reflect on various dimensions of globalization concerning developing countries, explaining how these could unleash economic growth, while their challenges naturally came with the process. Grasping these dynamics is crucial for policy makers, researchers, and stakeholders who seek to capitalize on the opportunities of globalization so that its fruits are equitably distributed and the negative impacts well mitigated.

A path to cleaner energy: The nexus of technological regulations, green technological innovation, economic globalization, and human capital

Ensuring environmental sustainability is paramount for achieving sustainable development and leaving a habitable world for future generations. In this regard, the transition to green energy plays a critical role by reducing environmental impacts associated with fossil fuel use and promoting environmentally friendly energy sources. Technological regulations, green technological innovation, economic globalization, and human capital are pivotal factors influencing the success of the green energy transition. Technological regulations can encourage the adoption of environmentally friendly practices through the establishment and enforcement of environmental standards. Economic globalization expands international trade and investment opportunities, supporting the transition to green energy. Human capital development ensures the availability of skilled labor and can foster knowledge creation to advance green energy initiatives. This study examines the influence of human capital, green technological innovation, technological regulations, and economic globalization on the green energy transition in 19 OECD countries from 1990 to 2019. According to the results, human capital reduces the transition in Germany and increases it in Poland; green technological innovation boosts the green energy transition in Belgium; technological regulations support it in Finland, Poland, and Panel; economic globalization reduces it in Italy. OECD countries should diversify their environmental policies with technological regulations to achieve SDG7.

Exploring possibilities of broccoli (Brassica oleracea L. var. italica) production under organic management

Broccoli (Brassica oleracea L. var. italica) was introduced as part of the Indian government's efforts to diversify and modernize agriculture in the region. Its introduction has helped J&K farmers to increase their income through higher market prices and to gain access to new markets and trade opportunities. It being a nutrient-demanding crop, farmers use high doses of chemical fertilizers, pesticides and herbicides and if consumed as salad or half-boiled in many culinary dishes, these chemicals are likely to impact the health of consumers and affect the environment. Therefore, alternative usage to these chemicals using combinations of organic inputs was aimed at producing a healthy crop of broccoli. It was concluded that the application of FYM@ 25 t/ha as a basal dose in the presence of seedling dip treatment of biofertilizers (Azotobacter @ 0.5 kg/ha + Phosphate-Solubilizing Bacteria @l kg/ha + Potassium-Mobilizing Bacteria @ 750 ml/ha) along with the scheduled application of Neem oil +Baeuveria bassiana at 1, 3, 7 and 15 days of interval after disease symptoms was found superior in obtaining higher curd yield (109.57 q/ha) and seed yield (604.96 kg/ha).

Disclosure and Dynamic Risk Sharing with a Large Shareholder

ABSTRACT We study the effects of disclosure in a dynamic market with imperfect competition. The supply of an asset is determined by a large shareholder with price impact, who trades slowly to diversify away from concentrated ownership. Small investors provide capital and thus risk-bearing capacity to the market. Although it is well known that disclosure impedes risk sharing by shifting risk before future trading opportunities, we show that disclosure, at the same time, can enhance risk sharing by promoting more trades. Resolving this tradeoff, an interior level of disclosure quality maximizes the small investors’ surplus as well as the total surplus, but minimizes the large shareholder’s surplus. Further, efficient disclosure policies feature increasing quality over time. JEL Classifications: D80; E21; G12; L13; M41.

TRANSPORT SYSTEMS AS ESSENTIAL PART OF GOVERNMENT POLICY

The paper discusses the significance of transport systems as a crucial compone nt of public policy in the majority of countries worldwide. Transport policy aims to achieve various objectives, including promoting economic growth, enhancing accessibility, improving safety, reducing environmental impacts, and promoting social equity. A significant aspect is the substantial funding required to construct and maintain transportation infrastructure, includin g roadways, railway tracks, airports, harbors, and publictransportation systems.Special emphasis is placed on international transport corridors such as the Trans-Caspia n International Transportation Route, which complements the Chinese Belt and Road initiative and presents new opportunities for trade between China and European nations. The paper emphasize s the importance of collaboration between different levels of government and internationa l stakeholders to address cross-border transportation challenges and harmonize regulations. The authors also discuss the role of the Shanghai Cooperation Organization in the development of regional transportation infrastructure and logistics. They highlight key issues such as outdate d infrastructure, high transportation costs, low efficiency, and the need for increased transit capacity. Additionally, they discuss other international initiatives, such as the Eurasian Economic Union and Central Asian Regional Economic Cooperation that aim to improve regional connectivity and facilitate trade.In conclusion, they emphasize the importance of strategic planning and investment in transportation systems to promote sustainable economic growth and enhance transportation links between Central Asian countries and other regions of the world.

Mapping trade opportunities in Central and South Asia: an exploration through trade indices and metrics

Purpose This study aims to explore the possibilities for regional (intra and inter) trade between Central Asia and South Asia (CASA) by examining several frameworks that impact the economic integration of these regions. Design/methodology/approach The study uses five indices, specifically the export diversification index, export survival rates, export sophistication, revealed comparative advantage and intra-industry trade index in South and Central Asia, from 2005 to 2021. Findings The findings show a twofold increase in the potential trade value between the two regions compared to the actual level. The intra-regional trade in Central Asia accounts for less than 5% of trade with all countries, whereas the intra-regional trade in South Asia accounts for 1.5%, and the inter-regional trade accounts for between 0.2 and 4% of total trade to all destinations. The intensity of trade measurements shows that inter-regional trade flows are modest because they make up a relatively small percentage of the entire trade volume, which includes all destinations, ranging from 0.2 to 4 %. Research limitations/implications These findings have a significant impact on the successful implementation of trading-related measures, initiatives and institutional mechanisms for encouraging improved trade between and within both regions. Practical implications Export diversification initiatives aim to provide favourable outcomes for all parties involved, focusing on expanding the range of goods and services exchanged. CASA countries with higher diversification have shown more favourable outcomes than those relying on a restricted range of products. The authors expect policies promoting a broader array of exports to boost market shares, while maintaining a narrow focus may hinder new export prospects. In addition, regional value chains and policy initiatives promoting trade and investment could lead to increased value additions to exports, technological transfers and job creation. Social implications The study emphasises the significance of trade-related policies, programmes and institutional mechanisms in promoting trade between CASA. It emphasises the need for policies that support investment and trade, adopt new requirements of the Agreement on Trade Facilitation and promote diversity and latency. Originality/value Based on economic analysis, the study offers practical insights and strategies for businesses in the CASA regions. It also provides analytical tools for academics and decision makers, as well as policy and programme recommendations for government agencies, development partners, researchers and individuals interested in trade dynamics in these regions.

The Brussels effect in Ankara: the case of climate policy

Abstract Turkey’s Europeanization process provides a particularly interesting case study of the extra-jurisdictional impact of European Union (EU) law, both through policy convergence and through the so-called Brussels effect. Formally, Turkey must adopt certain EU rules due to its status as an EU candidate country, but its candidacy process has been lengthy and uncertain, resulting in partial and uneven adoption of EU rules. Nevertheless, EU-style policymaking has persisted in various policy areas, including environmental and climate policy. This paper aims to analyze the convergence of climate change policies between the EU and Turkey by employing multidimensional scaling, a method that enables the visualization and examination of the connectivity and intensity of cooperation between states. For the period from 2007 to 2023, our comparative analysis demonstrates that policy divergence occurs when the EU’s share of Turkey’s total trade decreases and when political challenges are experienced. On the other hand, periods of policy convergence coincide with periods of increased trade volume and expanded trade opportunities. The results suggest that through its market size and regulatory capacity, the EU exerts soft power which forces Turkey to align its climate policies with the EU to protect and maintain its competitiveness in the European marketplace.

Shipping Market Forecasting Considering the Individual Investor Emotions: A Novel Twofold Partial Swarm Optimization Based Stacked Long Short-Term Memory Model

ABSTRACT Purpose The general purpose of shipping market prediction is to help shipping analysts design a strategy to make shipping strategies. Previous studies have pointed out human emotions has an obvious impact on markets, however, few research focus on utilizing human emotions to improve the shipping market forecasting issue. This paper fills the gap in the literature of considering industrial individual emotions to shipping market prediction issue Methodology We proposed a conceptual framework of an emotion-based shipping market prediction (ESMP) system focused on considering the multidimensional emotions of individual investors. To make it precisely, a two-fold Particle Swarm Optimization (TFPSO) algorithm is proposed conduct the shipping forecasting under the framework of ESMP, with advantages of automatically finding the architecture and hyperparameters of the Deep Long Short-Term Memory (DLSTM) simultaneously in the shipping market forecasting the values of the Baltic Dry, Dirty Tanker and Container indices of ocean transportation in the world ocean during the crisis period 2010–2022 Findings The prediction accuracy of the ESMP was higher than that of the models using the conventional factors in all learning periods of the study, and it was determined that the results complement the sentiment indicator employed to predict the shipping indices. Additionally, the accuracy of the proposed method is superior to conventional neural network models in all used error metrics. Additional Mann–Whitney U test on MSE difference between TFPSO-DLSTM and compared models demonstrates that the significant advantages boosted by TFPSO-DLSTM Originality Shipping sentiment has provided further proof that shipping decisions are significantly driven by emotions. our study shows that individual shipping investors’ sentiment are able to improve shipping rate forecasts significantly, although the magnitudes of the improvements are relatively small from an economic point of view Research implications This study undertook the initiative to procure BDI, BDTI, BCTI, COVID-19 data and shipping sentiment index data through in-depth interviews to provide first-hand perspectives into whether shipping sentiments impact the shipping market trend. It builds upon existing literature on the present stance of deep learning models, which largely relies non-sentiment factors. The study also extends prior literature on hyperparameter searching methods by highlighting the structure of searching method. Besides this, the contribution of this study also aligns with the prior discussions on evolving methodologies in temporal forecasting research Practical implications This study implies that shipping sentiments enables to make better shipping marketing trends, and foster sustainable growth. Shipping fear index serves for measuring investors’ attitude and mood toward shipping markets in terms of the general and certain sectors or assets, possibly promoting the movement of price and providing long-term investors and active traders with trading or arbitrage opportunities. Due to the complexities and regulations of the shipping market, it is essential to collaborate exclusively with shipping sentiment indices with artificial intelligent model in shipping market forecasting research

Impact Of International Trade On Regional Economic Growth

This study aims to analyze the impact of international trade on regional economic growth through literature studies. International trade is one of the main drivers of economic growth in the era of globalization. Despite a significant increase in the volume of global trade, the distribution of benefits is not always evenly distributed across regions. Some regions with adequate infrastructure access and supportive economic policies experience rapid economic growth, while other less developed regions face limitations in taking advantage of international trade opportunities. This study shows that international trade contributes significantly to increasing Gross Regional Domestic Product (GRDP), investment, and job creation, although these impacts depend on the readiness of infrastructure and the competitiveness of each region. Factors such as government policies and access to global markets also play a role in influencing the benefits obtained. This study recommends policies for infrastructure development and strengthening the competitiveness of local products to ensure that all regions can feel the optimal benefits of international trade. The results of this study provide direction for the government in formulating policies that encourage inclusive and sustainable economic growth at the regional level.

ENVIRONMENTAL SITUATION AS A FACTOR IN ENSURING THE ECONOMIC SECURITY OF THE REGION (similar to the Volga federal district)

The article presents the results of a study of the impact of environmental safety on the economic security of the region. The economy of a country and its regions is inextricably linked to the state and functioning of its elements, including the environmental situation. This factor has an impacton the resource supply of production, life expectancy and working capacity of the population, aswell as on trade opportunities in both domestic and foreign markets. Without ensuring environmental safety, it is impossible to ensure the safety of economic processes. Assessment of regional environmental safety is currently an urgent area of research, since many regions of Russia are characterized by a high proportion of industrial production, high anthropogenic load and the presence of environmental problems that can negatively affect the economic security of the region. The article presents the results of an assessment of the environmental safety of the regions of the Volga Federal District using various methods. The authors analyzed the state of environmental safety of the regionson the basis of a number of indicators outlined in the Strategy of Environmental Safety of Russia. The results of the evaluation using the indicative method are presented. In addition, a cluster analysis was carried out over several years, which, based on official statistical data, allowed the formation of groups of regions according to the level of environmental safety. The authors identified the following are as for neutralizing threats to environmental safety: improvement of legislation in the field of environmental safety; development and implementation of new technologies that will be more environmentally friendly; creation of programs for environmental cleanup and restoration of natural resources; strengthening control over compliance with environmental norms and standards. The identification of the interrelationships between environmental and economic security will allow us to develop effective strategies to ensure the sustainable development of the region, reduce the negative impacton the environment and increase the level of environmental safety.

Patterns in the Chaos: The Moving Hurst Indicator and Its Role in Indian Market Volatility

Estimating the impact of volatility in financial markets is challenging due to complex dynamics, including random fluctuations involving white noise and trend components involving brown noise. In this study, we explore the potential of leveraging the chaotic properties of time series data for improved accuracy. Specifically, we introduce a novel trading strategy based on a technical indicator, Moving Hurst (MH). MH utilizes the Hurst exponent which characterizes the chaotic properties of time series. We hypothesize and then prove empirically that MH outperforms traditional indicators like Moving Averages (MA) in analyzing Indian equity indices and capturing profitable trading opportunities while mitigating the impact of volatility.

India's Tea Export Potential: Stirring up Global Trade Opportunities

India's tea industry, a significant player in the global market, is poised for growth amidst evolving trade dynamics. This paper explores India's tea export potential by examining production, export trends, and competitiveness on a global scale. In 2022, global tea production reached 6,422 million kilograms, with China and India being the largest producers, while Kenya led in exports. India, the second-largest producer and fourth-largest exporter, shipped tea worth approximately USD 706 million, primarily to the UAE, Iraq, Russia, the USA, and the UK. Methodologically, this study utilizes a gravity model with PPML estimation to analyze India's tea exports to 173 trading partners from 2004 to 2021, addressing zero trade observations. Revealed Comparative Advantage (RCA) and Revealed Symmetric Comparative Advantage (RSCA) indices are employed to assess competitiveness, revealing an upward trend in India's comparative advantage. Transitional probabilities provide insights into shifting trade patterns, indicating significant market instability in countries like Germany and the UK. The analysis also includes estimation results highlighting the impact of GDP, geographical distance, population, and other factors on India's tea exports. Results demonstrate that India has considerable potential to expand tea exports to 118 countries, with high prospects in Uzbekistan, the USA, France, Hong Kong, and Italy. Current export strategies focus on saturated markets, underscoring the need to explore untapped regions to maximize trade opportunities. This study highlights the necessity for India to diversify its export destinations to enhance its global trade footprint and leverage its growing competitiveness in the tea sector.

Index futures mispricing: a multi-regime approach to the NIFTY 50 Index futures

PurposeThis study investigates the mispricing dynamics of NIFTY 50 Index futures, drawing upon daily data spanning from January 2008 to July 2023.Design/methodology/approachThe study employs both a single regime analysis and a tri-regime model to understand the fluctuations in NIFTY 50 Index futures mispricing.FindingsThe study reveals a complex interplay between various market factors and mispricing, including forward-looking volatility (measured by the NIFVIX index), changes in open interest, underlying index return, futures volume, index volume and time to maturity. Additionally, the relationships are regime-dependent, specifically identifying the regime-dependent nature of the relationship between forward-looking volatility and mispricing, the impact of futures volume on mispricing, the effect of open interest on mispricing, the varying influence of index volume and the influence of time to maturity across the three distinct regimes.Practical implicationsThese findings offer valuable insights for policymakers and investors by providing a detailed understanding of futures market efficiency and potential arbitrage opportunities. The study emphasizes the importance of understanding market dynamics, transaction costs and timing, offering guidance to enhance market efficiency and capitalize on trading opportunities in the evolving Indian derivatives market.Originality/valueThe Vector Autoregression (VAR) and Threshold Vector Autoregression Regression (TVAR) models are deployed to disentangle the interrelationships between NIFTY 50 Index futures mispricing and related endogenous determinants.Research highlights (1)This study investigates the Nifty 50 Index futures mispricing across three distinct market regimes.(2)We highlight how factors like volatility, futures volume, and open interest vary in their impact.(3)The study employs vector auto-regressive and threshold vector auto-regressive models to explore the complex relationships influencing mispricing.(4)We provide valuable insights for investors and policymakers on improving market efficiency and identifying potential arbitrage opportunities.

Momentum and reversal strategies with low uncertainty

We propose augmented momentum and reversal trading strategies that incorporate considerations of market entry timing. Market entry timing is determined by two criteria: (1) low uncertainty of the model used to forecast trading return, and (2) a positive forecasted return. Utilizing daily data from the Chinese stock market, we demonstrate that while canonical momentum and reversal trading strategies typically yield negative returns and skewness, our augmented strategies consistently exhibit positive returns and skewness. Additionally, we show that implementation of the two criteria does not significantly diminish trading opportunities, with identified market entry days evenly distributed throughout the sample period.

Opportunities of hydrogen and ammonia trade between Europe and MENA

This paper examines the potential role of hydrogen and ammonia in the European energy transition to reach net-zero greenhouse gas targets. We analyse trade of green hydrogen and ammonia between Europe and the Middle East and North Africa (MENA), since the latter possesses a high potential for solar power, making it a possible low-cost supplier of these two clean energy carriers. The economic attractiveness of such trade depends on the additional infrastructure and transportation costs required for the roll-out of these clean energy carriers. Using a global integrated assessment model, TIAM-ECN, we evaluate the trade-off between costs and benefits of establishing import-export links between Europe and MENA for hydrogen and ammonia. Our study assumes the availability of hydrogen pipelines from North Africa to Europe, and of liquefied hydrogen and ammonia shipping from the Middle East to Europe. We find that MENA could realize cost savings of over 6% by 2050 through hydrogen and ammonia trade. Furthermore, despite the availability of gaseous green hydrogen from North Africa (via pipelines), for Europe the import of liquefied green hydrogen and ammonia from MENA (through shipping) can also be economically viable. Although this trade could generate cost savings of 40 billion dollars per year by 2050, we conclude that for Europe import diversity, rather than cost savings, could become the main factor driving hydrogen and ammonia imports.

The impact of Chinese investment on access to clean and sustainable energy in Africa

The objective of this study is to examine the relationship between Chinese investment and access to clean and sustainable energy in African countries. We are motivated by the increasing engagement between China and Africa and the priority of sustainable energy for both partners. We employ robust econometric modelling, including fixed effects and the two-step Generalized Method of Moments, on a panel sample of 43 African countries over 19 years. The results show that Chinese energy investment in Africa is significantly associated with increased access to sustainable electricity. This effect is more pronounced in resource-rich countries, suggesting that China is more attracted to these countries due to the opportunities for resource trade in the form of partnerships. The policy implication of this finding is that it highlights the importance of African governments developing favourable strategies and policies to attract more Chinese investments in the energy sector.

Opportunities and Challenges of China’s Economic and Political Development Under the Third Term of Xi Leadership: A Viewpoint of Malaysia

In the face of severe internal economic challenges and rising hostile geopolitical landscape, Xi Jinping’s unprecedented third term has garnered much attention as the way in which these challenges are addressed will not only impact China’s internal governance on development issues but also its foreign policy and strategy. The paper attempts to examine the implications of Xi’s strategy and policy—from its stated goals to actions and outcomes—for Malaysia with respect to opportunities and challenges and its strategic response. The analysis benefits from the insights from the international political economy, which explores how the apparent weak unity government under Anwar Ibrahim’s administration amid tough domestic challenges and rising hostile geopolitical environment strives to reconcile the imperative of its domestic legitimation to prioritize immediate economic benefits over potential security concerns. Despite the reinvigorating Malaysia-China relations has brought tangible results, paving the way for more mutually beneficial trade and investment opportunities and partnerships, the external pressure caused Malaysia under Anwar’s administration to maintain Malaysia’s hedging under uncertainties in structural conditions rather than balancing or bandwagoning. Malaysia’s inclination to hedge is against the various risks associated with the uncertainty inherent in US-China rivalry—e.g. uncertainty in the future of Sino-American relations, uncertainty in Xi Jinping’s long-term strategic goals, uncertainty surrounding China’s slowing economy, diffuse threats, and uncertain reliable and sustainable allied supports. The recent rapid expansion of China’s investment in the country to avoid tariffs imposed by the US on certain products of China could be a double-edged sword. While smaller power like Malaysia with heavy economic dependence on China and the US will confront greater external constraints to maintain strategic ambiguity and keep its strategic options open, managing tradeoffs in foreign policy choices continues to be driven and constrained by the imperative of elite’s domestic legitimation embedded in the state-market-society interactions.

A new business model in the fine arts realm based on NFT certificates and pearl codes

The potential of Non-Fungible Tokens (NFTs) is highly anticipated, particularly in the realm of visual arts. However, current applications within fine arts often involve trivial processes, such as creating digital versions of artworks or replicas of masterpieces as NFT images, and selling only these NFTs. To unlock the full potential of NFTs, more innovative models are needed. This paper introduces a novel model that establishes a permanent link between an NFT and a physical craft object. This linkage is utilized to orchestrate the trade workflow, ensuring a sustained connection between real and digital artifacts. A distinguishing feature is that they can be sold together or seperately and later reunited with a buyer. The NFT serves as a multifunctional certificate, tracing, and communication token.Through a comprehensive analysis, this paper explores diverse scenarios that may arise in the relationship between the physical object and its digital twin. It presents a systematic and formal description of the proposed model and its various cases, marking a pioneering effort in the field. Noteworthy advantages include the ability to detect plagiarism and fraud. By strategically incorporating stakeholder roles, the model preserves the anonymity of art collectors while extracting valuable information about the ownership of physical artworks. The primary objective is to enhance security in the art trade and foster new business opportunities for stakeholders. As a proof-of-concept, the model was implemented in a real-world scenario on a leading NFT marketplace platform.

Kenya’s macroeconomic policies and trade efficiency within the East African Community: A stochastic frontier analysis

Despite Kenya dominating trade volumes in the East African Community (EAC), it has been trading below its potential within the region. This is also in spite of the increased scope of the country’s trade opportunities resulting from the region’s increased market integration. Empirical evidence has shown that macroeconomic policies influence international trade flows. However, there is limited empirical evidence on the effect of macroeconomic policies on trade efficiency. The few existing studies on this topic have also used estimation techniques that depict efficiency as being drawn from an average level of trade and not the optimal level of trade, as well as also not separating the effects of inefficiencies from the statistical noises. This, therefore, creates a knowledge gap that this study aims at investigating by using the stochastic frontier gravity model (SFGM), to determine the effect of Kenya’s macroeconomic policies on its trade efficiency within the EAC. The study used annual panel secondary data for the period 2000 to 2021. This study finds that the GDP of Kenya and that of its EAC trading partners, the geographical distance and border significantly affects trade volume. It also finds that globalization plays a significant role in influencing Kenya’s trade. For the inefficiency model variables, exchange rate depreciation was found to significantly increase trade efficiency, while increase in tariff rate had an adverse and significant effect. Further, the study included corruption as a control variable and found that it significantly increases trade inefficiency. Kenya, though trading at an average efficiency level of 86.91 percent, was found to have high unexploited trade potentials within the region especially with Tanzania and Uganda. The study recommends that Kenya’s policymakers deliberately advance the macroeconomic policies that promote trade efficiency while at the same time closely monitor the ones that hinder efficiency.