Alexandru Ursu, Petru Lucian CurÈeu, Sabina Trif, Alina Maria FleĆtea
Cryptocurrencies are rapidly transforming digital finance and entrepreneurship, yet their adoption by entrepreneurs remains rather poorly understood. Drawing on the Threat-Rigidity Model (TRM) and the opportunity recognition literature, this study examines how entrepreneurial experience, financial literacy, perceived opportunities, and perceived threats influence entrepreneurial intention to use cryptocurrencies. We tested a moderated mediation model in which the association between financial literacy and experience, on the one hand, and intention to use cryptocurrencies, on the other, was mediated by perceived opportunities. In this model, perceived threats served as a moderator on the relationship between financial literacy and intention, as well as between perceived opportunities and adoption intention. Data were collected from a sample of 133 Romanian entrepreneurs across diverse industries. The results supported the mediating role of perceived opportunities in the relationship between financial literacy and intention to use cryptocurrencies in business and showed that the positive association between financial literacy and intention was attenuated by perceived threats. Entrepreneurial experience did not significantly influence perceived opportunities, while women entrepreneurs reported lower intention to adopt cryptocurrencies in business. This study is among the first to use the TRM to explore how the interplay of perceived opportunities and threats shapes cryptocurrency adoption in entrepreneurship. Other implications, limitations, and directions for future research are also discussed.
This paper investigates the dual impact of Decentralized Finance (DeFi) and smart contracts on European Union (EU) market stability, with a focus on the role of regulation. The research problem centers on understanding how the rapid growth of DeFi interacts with emerging regulatory frameworks to shape financial stability. The purpose is to provide an integrated analysis that combines quantitative data with qualitative legal insights to inform policy. The methodology employs a fixed-effects panel data model to analyze the effect of DeFi market capitalization, smart contract deployments, and transaction volumes on a market stability index across EU member states, while also incorporating a qualitative review of the EUâs regulatory landscape, including the Markets in Crypto-Assets (MiCA) Regulation [1]. Key findings indicate that while DeFiâs growth correlates with increased market volatility, regulatory interventions like MiCA appear to have a stabilizing effect. The paper concludes that a clear and harmonized regulatory framework is crucial for mitigating the risks associated with DeFi while fostering responsible innovation. The relevance of this study lies in its timely contribution to the ongoing policy debate on DeFi regulation and its implications for financial stability in the EU [2].
We analyze 15,097 blocks proposed for inclusion in Ethereum's blockchain over an eight-minute window on December 3, 2024, during which 38 blocks were added to the chain. We classify transactions as exclusive -- appearing only in blocks from a single builder -- or private -- absent from the public mempool but included in blocks from multiple builders. We find that, depending on the methodology, exclusive transactions account for between 77.2% and 84% of the total fees paid by transactions in winning blocks. Moreover, we show that exclusivity cannot be fully attributed to persistent relationships between senders and builders: only between 7% and 8.4% of all on-chain exclusive transaction value originates from senders who route exclusively to one builder. Finally, we observe that transaction exclusivity is dynamic. Some transactions are exclusive at the start of a bidding cycle but later appear in blocks from multiple builders. Other transactions remain exclusive to a losing builder for two or three cycles before appearing in the public mempool. These transactions are therefore delayed and then exposed to potential attacks.
Abstract This article focuses on the Network State movement as embodying the venture capital (VC) logic of exit. Exit constitutes both a strategy for lucrative returns and an ideology seeking out new territories for financial and technological speculation. This movement has emerged around Balaji Srinivasan and the technologies of Web3 that encode the imperatives of exit. In the construction of liberated zones for the Network State, VC operates through a territorial logic, under the leadership of the founderâphilosopher and with the affordances of the American state. These logics evince the discursive power at the heart of the political economy of VC. The desires of the VC class shape âfuture social necessityâ (Howard 2024; Finance and Society 10) and are âimprintedâ (Cooiman 2024; Environment and Planning A 56) upon the social and technological networks of the Network State. The valorisation through exit seeks to produce âhyperstitiousâ (Lynch and MuñozâViso 2023; Progress in Human Geography 48) value creation in which VC is the fount of civilisation.
LOULID Adil -, GADMI Mariam -, LOTFI Siham, BEN DARKAWI Zakaria -
This paper explores the evolving landscape of SME financing in a context marked by the progressive tightening of traditional bank credit and the emergence of innovative funding alternatives. Small and medium-sized enterprises (SMEs), widely recognized as key drivers of innovation and employment, face increasing difficulties in accessing conventional financial resources due to heightened risk aversion among banks, stricter regulatory requirements, and macroeconomic instability. In response, SMEs are progressively turning to alternative financing solutions, such as crowdfunding, venture capital, peer-to-peer lending, and blockchain-based mechanisms, including smart contracts. The study highlights the dual dynamics shaping the current financing environment: while traditional sources like bank credit and government grants remain essential, they are no longer sufficient on their own. New technologies and decentralized platforms are redefining the financial ecosystem, offering greater flexibility, transparency, and inclusion. However, these alternatives also come with challenges, such as regulatory uncertainty, market saturation, and the need for strategic adaptation. Through a comparative and analytical approach, the paper underscores the importance of fostering a diversified, resilient, and innovation-oriented financial framework. It calls for coordinated efforts between public policy, financial institutions, and technological actors to support the sustainable development and competitiveness of SMEs in an increasingly complex economic environment.
In a time of growing environmental issues and climate change, the drive toward sustainability is more important than ever. Startups and small businesses are expected to be more instrumental in forming a sustainable future as world economies move toward greener paradigms. For many of these businesses, though, the financial load related to sustainable infrastructure, eco-innovation, and clean technology still be a major obstacle. For sustainable businesses trying to bring environmentally friendly ideas to market without sacrificing financial viability, green financing options including grants, subsidies, and green loans provide essential lifelines. Emphasizing the need of access to specific funding resources that support environmentally friendly practices, this abstract investigates the several green financing options open to startups. Examining both public and private sector projects emphasizes how green finance closes the innovation gap with implementation, especially for early-stage businesses trying to scale their green solutions. Grants and subsidies represent among the most well-known sources of green money. Usually governments, international organizations, and environmental NGOs supply these financial support to inspire creativity in fields including waste management, green manufacturing, sustainable agriculture, and renewable energy. Grants are a great choice for startups with limited cash flow since they unlike loans do not demand repayment. Many environmental grantinitiatives to support clean tech development have been started in areas including the European Union, North America, and portions of Asia. As part of the EU's larger goal to reach net-zero emissions by 2050, the European Green Deal, for instance, provides billions in support to sustainable businesses. To lower the initial costs of green investments, numerous local and national governments also provide direct subsidies and tax breaks. These could include financing for research and development of low-carbon technologies, subsidies for fleets of electric vehicles, or rebates for solar panel installations. In addition to fostering the growth of green startups, these policies hasten the market uptake of sustainable goods and services. Green loans have become a powerful instrument for sustainable finance in addition to grants. These are loans specifically designated for environmentally beneficial projects, and they frequently have favorable conditions like reduced interest rates, extended payback periods, or repayment plans that are based on performance. To assist with climate-resilient projects, organizations such as the World Bank, the Green Climate Fund, and several green investment banks provide specialized green loan programs. In order to specifically serve small and medium-sized businesses (SMEs) with environmental missions, some commercial banks have also entered this market by introducing green loan portfolios. Accessing green loans or grants for startups in need of these funds necessitates both a strong business plan and an unambiguous proof of environmental impact. The majority of funding organizations assess applications using standards like energy efficiency, circularity, social sustainability, and carbon footprint reduction. Thus, it is essential to have solid environmental metrics and data to support assertions. Furthermore, obtaining certifications such as B-Corp status or compliance with ESG (Environmental, Social, and Governance) standards can boost one's credibility and chances of getting funding. Additionally, startups now have more opportunities to interact with mission-driven investors who value sustainability in addition to financial returns thanks to the growth of impact investing. Green-minded venture capital firms and angel investors frequently offer seed money to eco-innovative companies, seeking high-growth prospects in line with long-term environmental objectives. Additionally, by reaching out to eco-aware communities, crowdfunding websites such as Kickstarter and Indiegogo are being used to fund green startups. Notwithstanding these encouraging advancements, obstacles still exist. Many startups are not equipped with the knowledge, skills, or resources necessary to successfully negotiate the intricate world of green finance. Grant and loan application procedures may be extremely competitive and cumbersome. Additionally, global scalability is hampered by the uneven distribution of green funding across various regions. Governments, financial institutions, and the private sector must work together more closely to close these gaps in addition to implementing policy changes and raising entrepreneur financial literacy. To address these challenges, startup incubators, accelerators, and advisory organizations are increasingly offering green finance consulting services, helping early-stage companies identify suitable funding options, prepare compelling applications, and build investor-ready sustainability strategies. Digital tools and platforms are also emerging to match green startups with appropriate funding sources, thereby streamlining the connection between innovative ideas and capital. In conclusion, green financing is not merely a niche category of economic support; it is an essential enabler of the global transition toward a more sustainable economy. By making green finance more accessible, equitable, and aligned with the realities of early-stage startups, stakeholders can unlock a wave of innovation that tackles some of the worldâ s most pressing environmental issues. Whether through grants, subsidies, green loans, or impact investing, the opportunities for sustainable entrepreneurship have never been more abundant, but seizing them requires a well-informed, strategic, and purpose-driven approach.
This paper investigates the unresolved intellectual property challenges posed by non-fungible tokens (NFTs), a rapidly growing class of digital assets that blend decentralized technologies with creative content distribution. Despite widespread adoption across art, entertainment, and gaming sectors, the legal infrastructure surrounding NFTs remains fragmented, creating uncertainty for creators, buyers, and platforms alike. The objective of this study is to critically evaluate existing theoretical modelsâincluding property-based, contract-based, and provenance-centered approachesâand assess their adequacy in governing NFT-related rights and obligations. Methodologically, the paper employs a comparative legal analysis of current NFT licensing practices, supported by interdisciplinary review of blockchain architecture, smart contract functionalities, and relevant international IP frameworks. Based on legal theory, technical standards, and case studies, the paper identifies critical gaps in enforceability, rights attribution, and jurisdictional clarity. In response, the study proposes a hybrid legal-technical framework comprising seven interconnected components: Smart Licensing Infrastructure (SLI), an On-Chain Provenance and Rights Registry, Embedded Royalty Clauses with Legal Backing, Token-Linked Legal Contracts (TLCs), along with dispute resolution and jurisdictional compatibility. These elements collectively aim to bridge decentralized code execution with enforceable legal standards, facilitating clearer licensing arrangements, more reliable royalty enforcement, and scalable dispute resolution mechanisms. It presents a novel blueprint for technical capabilities of NFTs with the foundational requirements of intellectual property law. By incorporating legal metadata, verifiable authorship records, and jurisdictional parameters directly into NFT structures, the framework strengthens legal predictability without restricting innovation. This research contributes to academic discourse by advancing a multidimensional governance approach for digital assets, offering actionable pathways toward regulatory coherence and sustainable development within the NFT ecosystem moving forward.
The traditional content monetization system is plagued by lack of transparency, delays, and inefficiencies in royalty payments. The creators struggle to receive timely and fair compensation for their work, particularly when their content is distributed across various platforms like Spotify, YouTube, and Instagram. This research proposes a novel framework utilizing blockchain technology and smart contracts to simplify and standardize royalty distributions, ensuring they are transparent, efficient, and fair for creators across multiple platforms. We examine the technical structure of the smart contract platform, analyze its financial characteristics, and demonstrate its ability to revolutionize content monetization
The financial services industry has experienced a fundamental transformation through the strategic adoption of distributed systems architecture, fundamentally altering how institutions design, deploy, and scale their product offerings. Traditional banking infrastructure, characterized by monolithic architectures and centralized processing systems, increasingly struggles to meet contemporary demands for real-time processing, continuous availability, and seamless scalability. Distributed systems address these challenges through horizontal scaling capabilities, enabling institutions to accommodate exponential growth in transaction volumes without proportional infrastructure cost increases. The implementation of distributed computing has enabled comprehensive portfolios of digital-first financial products, including mobile banking platforms, real-time transaction processing systems, AI-driven financial advisory services, intelligent customer support solutions, and advanced fraud detection mechanisms. These systems demonstrate superior resilience through redundancy and fault isolation, achieving exceptional availability levels through multi-region deployment strategies. Future developments in distributed financial systems encompass blockchain integration, decentralized finance protocols, advanced artificial intelligence capabilities, and edge computing with IoT integration. However, implementation presents complex technical challenges, including data consistency maintenance, security considerations, regulatory compliance across multiple jurisdictions, operational complexity, and performance optimization requirements that institutions must carefully navigate to realize distributed computing benefits effectively.
In today's digital era, technological advances have brought major changes in various fields, such as the creative economy. The emergence of crowdfunding platforms and Non-Fungible Tokens (NFTs) as creativeoptions for creative funding is one of the latest developments. Artists, musicians, and other creators have seen how they advertise their work by using NFTs which are unique asset holdings on the blockchain. Incontrast, crowdfunding platforms like Patreon and Kickstarter allow creators to get funding directly from their fans without using conventional intermediaries. The purpose of this research is to find the problems and prospects faced by investors and creators when using NFTs and crowdfunding. Qualitative and quantitative methods were used, with case studies and secondary data analysis. The results show that the main challenges to be faced include legal and regulatory uncertainty, marketvolatility, copyright infringement, digital divide, high transaction costs, and environmental impact. Uncertainty regarding ownership rights and consumer protection is caused by regulatory uncertainty.Both creators and investors face significant risks due to the volatility of the NFT market. The case of plagiarism in NFTs shows that copyright must be strengthened. Some creators cannot use this technology due to the limitations of digital technology. A more environmentally friendly solution is also needed due to the high transaction fees and the impact of the Ethereum blockchain on the environment. In addition, many creators still have difficulty maintaining crowdfunding funding.
The emergence of Non-Fungible Tokens (NFTs) â unique, blockchain-based tokens â has introduced a new dimension to the concept of property rights in the digital domain. Recent legal developments in the UK and the proposal of the Property (Digital Assets etc) Bill fuelled the discussion on how to legally conceptualise digital assets, including Non-Fungible Tokens (NFTs). This paper explores the evolving legal landscape surrounding property rights over NFTs, examining the challenges and ambiguities that arise from their intersection with existing property law frameworks. It analyses how property is defined and transferred in the context of NFTs, the implications for creators and acquires, and the best way to protect the latter. By critically assessing these issues, this paper aims to provide some insights regarding the legal principles that should guide the recognition and enforcement of property rights over NFTs, while suggesting new legal paths to accommodate this rapidly evolving technology.
Lending protocols have transformed the Decentralized Finance (DeFi) ecosystem, driving innovation while also introducing new risks. This study develops a machine learning framework to predict user behavior and assess factors influencing changes in health ratios within the Compound V2 protocol. By analyzing user historical data, position metrics, and market conditions, we propose machine learning-based models to predict whether users will adjust their positions or face liquidation. We find that Random Forest and XGBoost models excel in predicting these outcomes, with features like collateral values, historical risk exposure, and asset composition playing significant roles. Additionally, panel regression models reveal insights into health ratio dynamics over time and across asset types, as well as user sophistication. These findings offer a better understanding of user behavior, highlighting opportunities for improved risk modeling and adaptive strategies in DeFi lending.
Hardhik Mohanty, Giovanni Zaarour, Bhaskar Krishnamachari
Everlasting options, a relatively new class of perpetual financial derivatives, have emerged to tackle the challenges of rolling contracts and liquidity fragmentation in decentralized finance markets. This paper offers an in-depth analysis of markets for everlasting options, modeled using a dynamic proactive market maker. We examine the behavior of funding fees and transaction costs across varying liquidity conditions. Using simulations and modeling, we demonstrate that liquidity providers can aim to achieve a net positive PnL by employing effective hedging strategies, even in challenging environments characterized by low liquidity and high transaction costs. Additionally, we provide insights into the incentives that drive liquidity providers to support the growth of everlasting option markets and highlight the significant benefits these instruments offer to traders as a reliable and efficient financial tool.
Hong Qu, Krzysztof Gogol, Florian Grötschla, Claudio J. Tessone
Decentralized Finance (DeFi) lending enables permissionless borrowing via smart contracts. However, it faces challenges in optimizing interest rates, mitigating bad debt, and improving capital efficiency. Rule-based interest-rate models struggle to adapt to dynamic market conditions, leading to inefficiencies. This work applies Offline Reinforcement Learning (RL) to optimize interest rate adjustments in DeFi lending protocols. Using historical data from Aave protocol, we evaluate three RL approaches: Conservative Q-Learning (CQL), Behavior Cloning (BC), and TD3 with Behavior Cloning (TD3-BC). TD3-BC demonstrates superior performance in balancing utilization, capital stability, and risk, outperforming existing models. It adapts effectively to historical stress events like the May 2021 crash and the March 2023 USDC depeg, showcasing potential for automated, real-time governance.
This thesis examines how blockchain-based fundraising mechanisms like ICOs and IEOs reshape startup finance by offering decentralized access to capital. Analyzing 100 projects from 2019â2025, it identifies key success drivers using regression analysis. Findings show that strong community presence, top-tier investor backing, and compliance measures (e.g., KYC) significantly influence fundraising success. ICOs raise more than IEOs, despite looser oversight, highlighting a trade-off between decentralization and trust. Interaction effects reveal that credibility signals are especially effective in fragmented regions like APAC, and that compliance enhances ICO outcomes, while offering minimal added value in IEOs due to existing exchange-level due diligence.
Web3 grant programs are evolving mechanisms aimed at supporting innovation within the blockchain ecosystem, yet little is known on about their effectiveness. This paper proposes the concept of maturity to fill this gap and introduces the Grant Maturity Framework (GMF), a mixed-methods model for evaluating the maturity of Web3 grant programs. The GMF provides a systematic approach to assessing the structure, governance, and impact of Web3 grants, applied here to four prominent Ethereum layer-two (L2) grant programs: Arbitrum, Optimism, Mantle, and Taiko. By evaluating these programs using the GMF, the study categorizes them into four maturity stages, ranging from experimental to advanced. The findings reveal that Arbitrum's Long-Term Incentive Pilot Program (LTIPP) and Optimism's Mission Rounds show higher maturity, while Mantle and Taiko are still in their early stages. The research concludes by discussing the user-centric development of a Web3 grant management platform aimed at improving the maturity and effectiveness of Web3 grant management processes based on the findings from the GMF. This work contributes to both practical and theoretical knowledge on Web3 grant program evaluation and tooling, providing a valuable resource for Web3 grant operators and stakeholders.
Smart contracts are revolutionizing financial transactions by automating contractual agreements through blockchain technology, eliminating the need for intermediaries while enhancing security, efficiency, and accessibility across the financial sector. These self-executing protocols operate on predefined conditions, automatically verifying and executing terms without human intervention. Built on distributed ledger technology, smart contracts inherit key blockchain characteristics, including immutability, transparency, and cryptographic security, creating auditable transaction trails that significantly reduce fraud potential. While offering substantial benefits like reduced operational costs, accelerated settlement times, and enhanced financial inclusion, smart contracts face critical challenges, including security vulnerabilities, regulatory uncertainty across jurisdictions, and scalability limitations. Ongoing developments in security approaches like formal verification and specialized auditing firms are addressing vulnerability concerns, while progressive regulatory frameworks are emerging in forward-thinking jurisdictions. The future integration landscape is being shaped by advancements in cross-chain interoperability, Oracle integration for real-world data feeds, layer-2 scaling solutions, AI-enhanced optimization, and hybrid systems combining traditional legal contracts with automated execution. As blockchain technology matures, smart contracts are positioned to fundamentally transform financial infrastructure, contingent upon the continued evolution of security practices and regulatory frameworks.
This systematic review investigates the transformative impact of artificial intelligence (AI) and financial technology (FinTech) innovations on small and medium-sized enterprise (SME) financing, with a focus on enhancing transparency, efficiency, and financial inclusion. Despite the significant potential of AI and FinTech, substantial gaps remain in understanding their cross-regional and cross-industry effects, as well as in addressing persistent challenges such as AI adoption barriers, regulatory constraints, and decentralized data integration. The review synthesizes findings from peer-reviewed articles published from 2024 onward, sourced from Scopus and Web of Science databases, and examines the role of AI-driven solutions and digital financial platforms in SME financing. Results indicate that AI applications in risk assessment and credit scoring have reduced processing times by approximately 40% and improved loan approval rates by 25%. FinTech innovations have contributed to a 30% increase in financial inclusion, particularly among underserved SMEs in emerging economies. However, critical challenges, including data privacy concerns and limited technological infrastructure, continue to hinder broader adoption. This study contributes to the existing body of knowledge by systematically highlighting the role of AI and FinTech in enhancing SME financial performance and by providing actionable insights for policymakers, financial institutions, and entrepreneurs. The findings underscore the need for future research to address adoption barriers and to conduct cross-country comparative studies. Limitations include the exclusive focus on English-language, peer-reviewed sources, which may restrict the generalizability of the conclusions. Further investigations are recommended to explore the long-term impact of AI and FinTech innovations on SME sustainability and the evolution of regulatory frameworks supporting their implementation.
AI-powered microloans are transforming financial inclusion by enabling microenterprises in financially excluded geographies to access critical capital through innovative technologies. This article examines how artificial intelligence addresses traditional microfinance challenges through alternative credit scoring systems that analyze diverse data sources beyond conventional credit histories. By leveraging mobile usage patterns, transaction histories, psychometric assessments, and other digital footprints, AI algorithms create comprehensive risk profiles that extend financial services to previously excluded entrepreneurs. The technology not only improves initial credit assessments but also enhances ongoing risk management through behavioral analytics that predict repayment issues before they materialize. Despite significant technical implementation challenges in connectivity-limited regions, the article explores promising solutions, including edge computing, explainable AI frameworks, adaptive learning systems, and federated learning approaches. Ethical considerations regarding data privacy, algorithmic bias, and interest rate transparency require careful attention to ensure these innovations promote genuine inclusion. The evolution of this field points toward embedded financial services, decentralized finance integration, and collaborative AI models that could further democratize access to capital for marginalized entrepreneurs worldwide.
Debugging and auditing zero-knowledge-compatible smart contracts remains a significant challenge due to the lack of source mapping in compilers such as zkSolc. In this work, we present a preliminary source mapping framework that establishes traceability between Solidity source code, LLVM IR, and zkEVM bytecode within the zkSolc compilation pipeline. Our approach addresses the traceability challenges introduced by non-linear transformations and proof-friendly optimizations in zero-knowledge compilation. To improve the reliability of mappings, we incorporate lightweight consistency checks based on static analysis and structural validation. We evaluate the framework on a dataset of 50 benchmark contracts and 500 real-world zkSync contracts, observing a mapping accuracy of approximately 97.2% for standard Solidity constructs. Expected limitations arise in complex scenarios such as inline assembly and deep inheritance hierarchies. The measured compilation overhead remains modest, at approximately 8.6%. Our initial results suggest that source mapping support in zero-knowledge compilation pipelines is feasible and can benefit debugging, auditing, and development workflows. We hope that this work serves as a foundation for further research and tool development aimed at improving developer experience in zk-Rollup environments.
Robo-advisors have emerged as a transformative force in wealth management, leveraging artificial intelligence (AI) and machine learning to provide automated financial advisory services. This study conducts a bibliometric analysis of research on robo-advisors using data exclusively from the Scopus database and analyzed through VOSviewer. The findings reveal that research in this field has evolved from foundational discussions on fintech and artificial intelligence to advanced themes such as machine learning, decentralized finance, and algorithmic transparency. The keyword analysis highlights "wealth management," "fintech," and "machine learning" as central themes, while the co-authorship network indicates strong interdisciplinary collaboration among researchers. Additionally, the study identifies key regulatory and ethical challenges, including data privacy, fiduciary responsibility, and algorithmic bias, which require further investigation. The discussion explores the technological advancements, investor behavior, and regulatory landscape shaping the future of robo-advisory services. This research contributes to the growing academic discourse by mapping the intellectual structure of robo-advisor studies and suggesting future research directions, particularly in the areas of explainable AI (XAI), blockchain integration, and personalized financial advisory models.
Syeda Fizza Abbas, Sumiya Tahir, Sayyid Haider Mustafa Rizavi
This study examines the financial performance of diversified portfolios composed of various asset categories, including green cryptocurrencies, non-green cryptocurrencies, energy cryptocurrencies, stocks of leading companies, stocks of top energy companies, and stocks of prominent sustainable companies within the context of G7 nations. Additionally, it investigates the financial performance of green and non-green cryptocurrency portfolios across these regions. It aims to compare returns while examining the initiatives undertaken by these countries to foster sustainable financial systems. The research also explores how investors can leverage portfolio optimization to enhance returns in the rapidly evolving digital currency market. The study employs two machine learning techniques. First, six constraints, including maximum Sharpe ratio, minimum variance, maximum return, Sortino ratio, and Black-Litterman model, were applied to build portfolios for green and non-green cryptocurrencies. The model started with an 80%-20% train-test separation to find suitable allocations that it improved using full dataset retraining. The results explained that the highest Sharpe ratio portfolio generated the finest performance in the U.S. and Japan because of their strong financial market institutions and active participation from institutions. The investment cultures of Canada and Italy led to their selection of minimum variance portfolios. The Black-Litterman model worked well in the UK to produce equilibrium between market expectations and real risk-returns while German investors chose maximum return portfolios due to their risk tolerance. The French financial industry put risk-adjusted returns at the forefront thus the optimized Sortino ratio strategy proved most appropriate. A comparison between green and non-green portfolios shows that green portfolios regularly exhibited lower volatility together with superior risk-adjusted returns especially when sustainability policies were clearly defined in the nation. The higher returns from non-green portfolios came alongside higher speculative risk which made them susceptible to market volatility. This study demonstrated that selecting portfolios should be done based on specific market features that vary from country to country. Those who need stable long-term returns can achieve it through green investing while investors with high tolerance for risks can spend in non-green investments. Future studies should concentrate on developing dynamic rebalancing methods for portfolios while integrating decentralized finance (DeFi) technology to optimize portfolio management systems.
This study explores the transformative potential of blockchain technology in revolutionizing cross-border payment systems. Traditional methods are hindered by inefficiencies such as high transaction fees, prolonged processing times, and opaque operations, which impede seamless global financial interactions. Blockchain, with its decentralized and immutable ledger, offers a secure and transparent alternative that can significantly streamline payment processes. This paper examines how blockchain can facilitate real-time settlements, eliminate intermediaries, and enhance data integrity, thereby reducing costs and improving efficiency. Further, it addresses the practical applications and regulatory challenges associated with integrating blockchain into existing payment infrastructures. Ultimately, this research aims to provide actionable insights for developing a more efficient, transparent, and cost-effective cross-border payment ecosystem.