This report traces the systematic erosion of global yield over four decades, from double-digit Treasury returns in the 1980s to near-zero rates by 2020, and documents how Decentralized Finance (DeFi), despite its revolutionary premise, replicated traditional finance’s fundamental failures within just two years. Drawing on macroeconomic data, protocol-level analytics, and institutional research, we identify five structural pain points facing yield-seekers today: chronic compression, emission decay, forced complexity, impermanent loss, and existential protocol risks. We then introduce “Yield 3.0”, a paradigm defined by sustainable, fee-based mechanisms that generate yield from genuine economic activity rather than inflation, speculation, or token emissions. We present Seasons as the first protocol to holistically address all five pain points through a 100% fee-based, hold-to-earn model with zero emission decay, radical simplicity, and full non-custodial ownership. Finally, we examine the converging structural forces—institutional capital inflows exceeding $130 billion, the mathematical exhaustion of emission-based models, and maturing blockchain infrastructure—that make 2026 the inflection point for Yield 3.0 adoption at scale.
Purpose This study examines how entrepreneurial experience shapes perceptions of the ideal investor in the technology-based sector. While previous research has primarily focused on how investors evaluate entrepreneurs, this study shifts the lens to explore how entrepreneurs assess investor attributes. It investigates how experience in securing funding and building ventures influences expectations around value-added contributions beyond financial investment. Specifically, the study explores whether experience leads entrepreneurs to adopt a more strategic and values-driven approach, placing greater emphasis on ethical alignment, expertise, and relational quality, while placing less importance on operational involvement and financial oversight. Design/methodology/approach This study adopts a quantitative research design using survey data from 195 entrepreneurs in the technology-based sector. Participants were recruited through entrepreneurial and investor networks across multiple countries. The survey captured key aspects of entrepreneurial experience, including fundraising and venture development, alongside expectations of investor roles and attributes. Factor analysis identified dimensions of value-added investor support, and k-means clustering was used to group entrepreneurs based on preference profiles. Multinomial logistic regression and OLS regression analyses were conducted to examine how different types of experience influence entrepreneurs' preferences for specific investor attributes and types of support. Findings The results show that entrepreneurial experience plays a significant role in shaping expectations of investor involvement. Entrepreneurs with more experience in fundraising and venture development tend to prioritize ethical conduct, strategic input, and relational alignment over traditional factors like financial returns or past performance. They value investor support focused on strategy, networks, and governance, while placing less importance on operational or financial oversight. Cross-sector experience further reinforces a preference for strategic-driven supports. Overall, the findings suggest that experience increases entrepreneurs' confidence and selectivity, encouraging a more strategic approach to building investor relationships. Research limitations/implications This study has several limitations. First, the data were collected primarily from entrepreneurs in developed countries with well-established venture capital markets, which may limit the generalization of the findings to emerging or less mature ecosystems. Second, the target population is difficult to define precisely, given the informal and decentralized nature of entrepreneurial networks. Third, the reliance on self-reported survey data introduces the possibility of response bias. Additionally, the cross-sectional design limits the ability to draw causal inferences. Future research could benefit from longitudinal data and broader geographic representation to better capture variation across different entrepreneurial contexts. Practical implications The findings provide actionable insights for both entrepreneurs and investors. As entrepreneurs gain experience, they become more selective, favouring investors who offer strategic guidance, ethical alignment, and relational support over purely financial backing. For investors, this highlights the importance of articulating non-financial value, such as expertise, governance input, and network access, to appeal to more experienced founders. Investors who position themselves as collaborative partners rather than controllers may build stronger, longer-lasting relationships. Entrepreneurial support programs, including accelerators and incubators, can also use these insights to prepare founders to identify and engage with strategically aligned investors. Social implications This study highlights the growing importance of trust, ethical conduct, and shared values in shaping effective entrepreneurial ecosystems. As entrepreneurs gain experience, they increasingly prioritize relational quality and strategic alignment in their investor relationships. This signals a broader shift toward more collaborative, purpose-driven engagement between founders and investors. Such a shift has the potential to foster healthier power dynamics, reduce misalignment and conflict, and support the formation of long-term partnerships grounded in mutual respect and shared vision. These findings contribute to ongoing discussions around responsible entrepreneurship and the sustainability of venture growth. Originality/value This study offers a novel contribution by shifting the focus from how investors assess entrepreneurs to how entrepreneurs evaluate potential investors. It addresses an under explored area in entrepreneurial finance, particularly highlighting the role of ethical behaviour and strategic alignment in investor selection. By examining how experience shapes these expectations, the study adds to the limited literature comparing novice and experienced entrepreneurs in their interactions with external stakeholders. It advances understanding of founder–investor dynamics and offers fresh insights into how entrepreneurial learning influences decision-making in the context of venture growth and funding relationships.
The financial sector is experiencing rapid transformation due to emerging technologies. Blockchain offers a decentralized, transparent, and immutable framework for secure transactions, while Artificial Intelligence (AI) enables advanced data analytics, predictive modeling, and intelligent automation. When combined, these technologies create a powerful synergy that is reshaping finance by enhancing fraud detection, improving credit evaluation, optimizing decentralized finance (DeFi) platforms, and automating compliance processes. This paper explores the combined benefits of blockchain and AI, highlighting practical applications such as AI-enabled fraud detection within blockchain networks, adaptive smart contracts, and blockchain-secured digital identity verification. It also addresses challenges in merging these technologies, including scalability limitations, regulatory ambiguity, interoperability concerns, and ethical considerations. The study underscores the potential future of autonomous financial systems, decentralized autonomous organizations (DAOs), and AI-driven sustainable finance solutions. Ultimately, the integration of blockchain and AI is seen as a transformative force capable of significantly improving transparency, efficiency, and inclusiveness in global financial systems.
Sustainable Development Goal 7 (SDG-7) seeks universal access to affordable, reliable, and modern energy by 2030, yet progress remains uneven and structurally constrained. Despite declining renewable energy costs, around 685 million people lack electricity and more than 2 billion depend on traditional biomass for cooking. This review moves beyond descriptive assessments by providing a systematic, decision-oriented synthesis of SDG-7 pathways. Using a replicable PRISMA-informed protocol, it integrates peer-reviewed studies and authoritative international datasets published between 2015 and 2025. Centralized, decentralized, and hybrid energy systems are evaluated in terms of technical maturity, affordability, governance feasibility, and socio-environmental impacts. A structured barrier-to-intervention framework identifies context-specific challenges, including intermittency, financing risk, institutional capacity, infrastructure gaps, and climatic and geopolitical exposure, alongside viable technological and policy responses. Comparative case studies from India, Sub-Saharan Africa, Southeast Asia, and Latin America explain divergent outcomes of similar technologies across institutional and market contexts, and development pathways globally.
Lukman Ademola Adepoju, Oyetunji Oyewale, Odekunle Bola Odegbemi, Ifeoluwa Abraham Adeagbo · 5 authors
Over 40 years after the identification of human immunodeficiency virus (HIV), Nigeria remain one of the highest burdens of HIV infections in the world, accounting for almost 10% of new infections in sub-Saharan Africa. Despite significant investments and technical supports from different foreign donors including the United States President’s Emergency Plan for AIDS Relief (PEPFAR), the Global Fund, and bilateral partners. The persistent structural, financial, and programmatic gaps continue to hamper the country’s HIV response. This assessment of HIV-related interventions in Nigeria examines what has been achieved, what still need to be done, and how to establish a sustainable and domestically owned HIV care. The review summarizes evidence from peer-reviewed literature (2018–2025) and major institutional reports (UNAIDS, NACA, WHO, PEPFAR) to assess five key domains: coverage and access, funding and sustainability, health system strengthening, monitoring and evaluation, and sociocultural barriers. Evidence shows that while substantial progress has been achieved in testing, antiretroviral therapy (ART) coverage, and community-based care, the HIV response remains heavily donor-dependent, urban-centered, and fragmented across vertical program streams. The review concludes that to achieve long-term epidemic control (EC) and universal health coverage (UHC) in Nigeria’s HIV care and programming with there is a need for domestic financing, health system integration, decentralized service delivery, and data-driven accountability frameworks.
Ni Putu Eka Apriyanthi, Civica Moehaimin Dhewanty, Putu Desiana Wulaning Ayu, I Made Riyan Adi Nugroho · 5 authors
Konteks penelitian ini didasari oleh meningkatnya kerentanan keamanan yang signifikan dalam ekosistem decentralized finance (DeFi) dan blockchain, khususnya terkait dengan aktivitas kecurangan yang semakin kompleks dan berbiaya tinggi. Metode deteksi tradisional tidak lagi memadai untuk menangani volume transaksi yang masif serta karakteristik dataset yang menunjukkan ketidakseimbangan kelas. Oleh karena itu, penelitian ini berfokus pada evaluasi dan perbandingan kinerja tiga algoritma machine learning utama Regresi Logistik, Random Forest, dan XGBoost untuk mengidentifikasi secara akurat aktivitas kecurangan dalam transaksi blockchain. Data yang digunakan adalah dataset transaksi Ethereum dari platform Kaggle. Isu ketidakseimbangan kelas dalam data diatasi melalui implementasi metodologi SMOTE (Synthetic Minority Over-sampling Technique). Kinerja setiap model dinilai secara komprehensif menggunakan metrik presisi, recall, F1-score, dan Area Under the Receiver Operating Characteristic Curve (ROC-AUC) pada data pengujian. Hasil penelitian menunjukkan superioritas XGBoost di antara ketiga algoritma, dengan mencapai akurasi 99,46%, presisi 99,69%, recall 97,86%, dan skor ROC-AUC 99,97% (25). Keunggulan ini diperkuat oleh keberhasilan XGBoost dalam meminimalkan false positives, yakni hanya 1 kejadian. Kinerja yang melampaui model Random Forest dan Regresi Logistik ini mengindikasikan bahwa metodologi gradient boosting sangat efektif dalam mendeteksi pola perilaku kecurangan yang rumit. Secara keseluruhan, temuan studi ini memberikan kontribusi yang substansial terhadap pengembangan kerangka kerja deteksi kecurangan yang otonom dan tangguh.
This paper extends the classical Avellaneda-Stoikov framework for optimal market making to blockchain networks with directed acyclic graph (DAG) structure. In DAG-based consensus protocols such as GHOSTDAG, multiple blocks are produced in parallel, creating a branching time structure that fundamentally alters the market maker's optimization problem. We derive a DAG-extended Hamilton-Jacobi-Bellman equation that incorporates the probability distribution over transaction acceptance, showing that optimal spreads depend on the anticipated ordering of parallel blocks. Our main theoretical result demonstrates that market makers achieve O(1/n) variance reduction in inventory risk by distributing quotes across n parallel execution paths, exploiting the transaction-level mutual exclusivity inherent to GHOSTDAG ordering. We extend the framework to K correlated assets (proving portfolio-level variance reduction of O(K/n)) and provide adversarial robustness analysis under bounded hash power attacks. Implementation analysis for the Kaspa network (10 BPS, k=124 post-Crescendo) addresses practical constraints including direct-to-miner submission requirements, fee incentive compatibility, and latency bounds. Monte Carlo simulations validate theoretical predictions, showing Sharpe ratio improvements of 40-82% over single-path strategies under realistic network conditions. This work establishes foundational theory for high-frequency decentralized finance applications on DAG-based blockchains.
The 2025 Annual Meeting of National Neglected Tropical Disease (NTD) Programme Managers (2025 PMM) in the WHO African Region convened stakeholders in Lomé, Togo, under the theme "Innovating for Acceleration: Pathway to NTD Elimination." A key focus was the changing funding environment and the necessity for enhanced integration of NTD services within health systems to guarantee sustainable advancement toward the 2030 elimination goals. The conference was convened in the context of substantial disruptions stemming from the USAID funding pause, which interrupted essential mass drug administration (MDA) programmes and epidemiological monitoring activities across multiple nations. Country experiences highlighted the fragility of external funding dependence and underscored the importance of domestic resource mobilization, decentralized implementation, and programmatic integration. Strategic discussions highlighted opportunities to incorporate NTD services into national health financing mechanisms, and routine health campaigns, alongside leveraging digital tools and partnerships. Participants emphasized the urgency of political commitment, sustained investments, and integrated service delivery models to build resilience and close equity gaps. The meeting further underscored the need for bold, country-led responses and multisectoral collaboration to advance NTD elimination efforts in a rapidly evolving global health financing environment.
ABSTRACT Block chain technology has rapidly evolved from a crypto currency backbone to a transformative infrastructure for financial services. Coupled with Artificial Intelligence (AI), it promises to revolutionize how financial institutions operate—enhancing transparency, security, efficiency, and compliance. We employ a mixed-method approach using qualitative interviews, quantitative performance analysis, and case studies to explore the scope of this technological convergence. Our results highlight significant operational gains and outline challenges that must be navigated for successful adoption. KEYWORDS Blockchain Technology, Artificial Intelligence,Fraud Detection,Decentralized Finance, Smart Contracts
This study explores the intersection of cryptocurrency, cybercrime, and global governance. It focuses on identifying criminal techniques, analyzing forensic and regulatory countermeasures, and evaluating the broader governance dilemmas that arise. A qualitative desk-based approach was employed, synthesizing secondary data from peer-reviewed studies, institutional policy papers (FATF, IMF, Europol), and industry reports (Chainalysis, Elliptic, TRM Labs). Thematic content analysis was used to trace patterns in illicit cryptocurrency use, law enforcement responses, and regulatory innovations. The findings indicate that while advances in blockchain forensics and policy coordination have strengthened oversight, criminals increasingly exploit decentralized finance platforms, cross-chain laundering, privacy coins, and mixers to evade detection. Enforcement remains uneven, hindered by fragmented regulations and gaps in cross-border cooperation. Overall, the study concludes that cryptocurrency-enabled cybercrime remains a resilient and evolving threat that challenges the stability of the global financial system and exposes weaknesses in governance frameworks. Without stronger coordination, adaptive regulation, and robust technological capabilities, the risks of illicit finance will continue to outpace control efforts. To mitigate these risks, the study recommends enhancing cross-border collaboration, investing in advanced blockchain forensic tools, and adopting flexible, multi-stakeholder governance models that balance innovation with accountability.
Aditya Rathore, Kratika Mishra, Vidhi Chandrayan, Pareek Ch. S.
Blockchain technology has evolved into one of the most influential digital innovations of the 21st century, enabling decentralized, trustless, and tamper‑resistant data management across global networks. Its rapid rise can be attributed to groundbreaking applications across cryptocurrencies, decentralized finance (DeFi), healthcare, supply chain, and identity management systems. Despite this explosive growth, blockchain technology still faces major challenges—most critically, scalability. This extended study explores blockchain’s historical development, factors driving adoption, technical architecture, and the limitations restricting mass deployment. The paper includes an in‑depth analysis of publicly available blockchain datasets that support research in security, analytics, and scalability modeling. Furthermore, the study reviews emerging scalability frameworks such as sharding, off‑chain computation, Layer‑2 rollups, DAG-based systems, and consensus optimization. The goal is to provide a comprehensive foundation for understanding blockchain’s evolution while outlining future paths toward global-scale adoption.
(1) Background: The convergence of Big Data and the Internet of Things (IoT) is transforming digital accounting from retrospective documentation into real-time operational intelligence. This systematic review examines how Industry 4.0 technologies—artificial intelligence (AI), blockchain, edge computing, and digital twins—transform accounting practices through intelligent automation, continuous compliance, and predictive decision support. (2) Methods: The study synthesizes 176 peer-reviewed sources (2015–2025) selected using explicit inclusion criteria emphasizing empirical evidence. Thematic analysis across seven domains—conceptual foundations, system evolution, financial reporting, fraud detection, audit transformation, implementation challenges, and emerging technologies—employs systematic bias-reduction mechanisms to develop evidence-based theoretical propositions. (3) Results: Key findings document fraud detection accuracy improvements from 65–75% (rule-based) to 85–92% (machine learning), audit cycle reductions of 40–60% with coverage expansion from 5–10% sampling to 100% population analysis, and reconciliation effort decreases of 70–80% through triple-entry blockchain systems. Edge computing reduces processing latency by 40–75%, enabling compliance response within hours versus 24–72 h. Four propositions are established with empirical support: IoT-enabled reporting superiority (15–25% error reduction), AI-blockchain fraud detection advantage (60–70% loss reduction), edge computing compliance responsiveness (55–75% improvement), and GDPR-blockchain adoption barriers (67% of European institutions affected). Persistent challenges include cybersecurity threats (300% incident increase, $5.9 million average breach cost), workforce deficits (70–80% insufficient training), and implementation costs ($100,000–$1,000,000). (4) Conclusions: The research contributes a four-layer technology architecture and challenge-mitigation framework bridging technical capabilities with regulatory requirements. Future research must address quantum computing applications (5–10 years), decentralized finance accounting standards (2–5 years), digital twins with 30–40% forecast improvement potential (3–7 years), and ESG analytics frameworks (1–3 years). The findings demonstrate accounting’s fundamental transformation from historical record-keeping to predictive decision support.
Shaoyu Li, Hexuan Yu, Md Mohaimin Al Barat, Yang Xiao · 6 authors
With the rise of decentralized finance, fiat-to-cryptocurrency exchange platforms have become popular entry points into the cryptocurrency ecosystem. However, these platforms frequently fail to ensure adequate privacy protection, as evidenced by real-world breaches that exposed personally identifiable information (PII) and crypto addresses. Such leaks enable adversaries to link real-world identities to cryptocurrency transactions, undermining the presumed anonymity of cryptocurrency use. We propose FC-GUARD, a privacy-preserving exchange system designed to preserve user anonymity without compromising regulatory compliance in the exchange of fiat currency for cryptocurrencies. Leveraging verifiable credentials and zero-knowledge proof techniques, FC-GUARD enables fiat-to-cryptocurrency exchanges without revealing users' PII or fiat account details. This breaks the linkage between users' real-world identities and their cryptocurrency addresses, thereby upholding anonymity, a fundamental expectation in the cryptocurrency ecosystem. In addition, FC-GUARD complies with key regulations over cryptocurrency usage, such as know-your-customer requirements and auditability for tax reporting obligations by integrating a lawful de-anonymization mechanism that allows the auditing authority to identify misbehaving users. This ensures regulatory compliance while defaulting to privacy protection. We implement our system on both desktop and mobile platforms, and our evaluation shows its feasibility for practical deployment.
Deepesh Khatak, Karan Rathode, Assistant professor Ms. Maanvika
Blockchain technology has emerged as a transformative paradigm for secure, decentralized, and transparent data management across various domains, including finance, supply chain, healthcare, and governance. At its core, blockchain operates as a distributed ledger that ensures data integrity through cryptographic techniques, consensus mechanisms, and decentralized network architecture. This paper presents a comprehensive overview of blockchain architecture and its fundamental security foundations. It explains the structural components of a blockchain system, such as blocks, transactions, hash functions, Merkle trees, peer-to-peer networks, and consensus protocols, highlighting their roles in maintaining trust without reliance on centralized authorities. The study further examines key security principles that underpin blockchain systems, including immutability, transparency, fault tolerance, and resistance to tampering. Common security threats and attack vectors—such as double-spending attacks, 51% attacks, Sybil attacks, and smart contract vulnerabilities—are discussed to provide insight into potential risks faced by blockchain networks. In addition, the paper explores cryptographic mechanisms such as public-key encryption, digital signatures, and hashing algorithms that contribute to secure transaction validation and identity management. By integrating architectural analysis with security considerations, this work aims to build a strong foundational understanding of how blockchain systems achieve trust, resilience, and data integrity in decentralized environments. The paper serves as a valuable reference for students, researchers, and practitioners seeking to understand the core architectural design and security challenges of blockchain technology, as well as its potential for secure and scalable real-world applications.
The Ambazonian conflict in Cameroon’s Anglophone regions has unfolded within an era defined by mobile connectivity, social media, and digitally mediated political contention. This article examines the role of mobile technology in shaping the conflict’s trajectory from early mobilization to prolonged armed stalemate. It argues that mobile technology functioned as both an enabling and destabilizing force: facilitating mass mobilization, diaspora coordination, documentation of abuses, and digital finance, while simultaneously accelerating fragmentation, disinformation, cybersecurity exposure, and state surveillance. Drawing on comparative cases including the Arab Spring, ISIS, Ukraine, Ethiopia, and Myanmar, the article situates Ambazonia within broader patterns of digital contention and digital authoritarian response. The analysis further demonstrates how ungoverned digital visibility and decentralized online fundraising undermined strategic coherence and legitimacy. The article concludes that while mobile technology can amplify resistance, it cannot substitute for political legitimacy, institutional coherence, or negotiated settlement. Durable peace requires a transition from networked resistance to normatively grounded frameworks such as the Alliance for Peace and Justice (APJ) Peace Plan.
Currently housing finance transaction platforms face challenges of data protection and cybersecurity. Blockchain technology, with its decentralization, non-tampering and high transparency, has become an effective tool for securing transaction data. In this paper, a blockchain-based data protection scheme for housing finance transaction platform is designed, which combines the shared energy storage system and realizes the cyber security protection of the transaction platform by optimizing the PBFT consensus mechanism. Methodologically, distributed file storage technology (IPFS) and smart contracts are adopted to ensure data encryption, storage and transaction transparency. Experimental results show that the proposed scheme excels in smart contract execution time, with a maximum execution time of 0.8ms, and achieves a significant increase in TPS when the concurrent volume of transactions reaches 1,200, and the throughput of the dual-chain architecture is increased by 28% compared to the traditional single-chain architecture. In addition, the system with ITPBFT consensus mechanism reduces the communication overhead by 46.19% compared to the traditional PBFT, and the consensus delay is also significantly reduced, with an efficiency improvement of 53.61%. The study shows that the proposed optimization scheme can enhance the efficiency and reliability of data transactions while improving the security of the system.
We develop a mathematical framework to optimize leveraged staking ("loopy") strategies in Decentralized Finance (DeFi), in which a staked asset is supplied as collateral, the underlying is borrowed and re-staked, and the loop can be repeated across multiple lending markets. Exploiting the fact that DeFi borrow rates are deterministic functions of pool utilization, we reduce the multi-market problem to a convex allocation over market exposures and obtain closed-form solutions under three interest-rate models: linear, kinked, and adaptive (Morpho's AdaptiveCurveIRM). The framework incorporates market-specific leverage limits, utilization-dependent borrowing costs, and transaction fees. Backtests on the Ethereum and Base blockchains using the largest Morpho wstETH/WETH markets (from January 1 to April 1, 2025) show that rebalanced leveraged positions can reach up to 6.2% APY versus 3.1% for unleveraged staking, with strong dependence on position size and rebalancing frequency. Our results provide a mathematical basis for transparent, automated DeFi portfolio optimization.
Cross-chain bridges constitute the single largest vector of systemic risk in Decentralized Finance (DeFi), accounting for over \$2.8 billion in losses since 2021. The fundamental vulnerability lies in the binary nature of existing bridge security models: a bridge is either fully operational or catastrophically compromised, with no intermediate state to contain partial failures. We present ASAS-BridgeAMM, a bridge-coupled automated market maker that introduces Contained Degradation: a formally specified operational state where the system gracefully degrades functionality in response to adversarial signals. By treating cross-chain message latency as a quantifiable execution risk, the protocol dynamically adjusts collateral haircuts, slippage bounds, and withdrawal limits. Across 18 months of historical replay on Ethereum and two auxiliary chains, ASAS-BridgeAMM reduces worst-case bridge-induced insolvency by 73% relative to baseline mint-and-burn architectures, while preserving 104.5% of transaction volume during stress periods. In rigorous adversarial simulations involving delayed finality, oracle manipulation, and liquidity griefing, the protocol maintains solvency with probability $>0.9999$ and bounds per-epoch bad debt to $<0.2%$ of total collateral. We provide a reference implementation in Solidity and formally prove safety (bounded debt), liveness (settlement completion), and manipulation resistance under a Byzantine relayer model.
This work presents a conceptual framework for analyzing contemporary AI governance as a hybrid system of coercive exclusion and cognitive modulation. Introducing the concept of the “Venetian OS,” the paper traces the historical and structural logic of centralized digital power through protocol privatization, automated exclusion, and tri-domain integration of finance, information, and mobility. Focusing on advertising-based AI models, the analysis examines how attention extraction and brand safety constraints function as mechanisms of cognitive governance, commodifying cognition while constraining epistemic exploration. The paper argues that institutional reform within existing digital architectures is structurally insufficient. As an alternative, the work outlines exit strategies based on the reconstitution of intellectual, energy, and economic sovereignty through distributed infrastructures, situating the emergence of decentralized sovereignty as an ongoing historical transition rather than a speculative future.
Clean energy transitions increasingly depend on the ability of small and medium-sized enterprises (SMEs) to access capital on terms that allow them to compete with large, vertically integrated incumbents. At a macro level, clean energy finance has evolved from subsidy-heavy public funding toward blended models combining private capital, risk-sharing instruments, and performance-based incentives. These structures aim to lower the cost of capital, correct market failures, and accelerate diffusion of renewable technologies across national energy systems. However, capital markets continue to privilege scale, balance-sheet strength, and long operating histories, creating persistent financing asymmetries that disadvantage smaller firms. This study situates clean energy financing within broader frameworks of financial inclusion, industrial competitiveness, and energy market liberalization. It examines how innovative financing architectures such as blended finance vehicles, green credit guarantees, pay-as-you-save schemes, revenue-backed project finance, and aggregated procurement platforms reshape risk allocation and margin dynamics. By reducing upfront capital requirements, smoothing cash flows, and improving bankability, these models enable SMEs to price energy products and services competitively while maintaining sustainable margins. Narrowing to the national context, the analysis highlights how policy design, regulatory certainty, and domestic financial infrastructure determine whether financing innovations translate into real competitive parity. Case-informed synthesis shows that when concessional capital is strategically deployed to crowd in commercial lenders, small enterprises can achieve cost structures comparable to larger incumbents, expand market share, and drive decentralized energy adoption. The findings underscore that clean energy competition is not solely a technological challenge, but a financial architecture problem, where well-designed financing models are decisive in leveling margins and unlocking inclusive energy-led growth at national scale under diverse regulatory and macroeconomic conditions globally relevant insights.
Three traits of decentralized finance are studied. First, the market impact function is derived for optimal-growth liquidity providers. For a standard random walk, the classic square-root impact is recovered. An extension is then derived to fit general fractional Ornstein-Uhlenbeck processes. These findings break with the linearized liquidity models used in most decentralized exchanges. Second, a Constant Product Market Maker is viewed as a multi-phase Carnot engine, where one phase matches the exchange of tokens by a liquidity taker, and another the change of pool size by a liquidity provider. Third, stablecoin de-pegging is a form of catastrophe risk. By using growth optimization, default odds are linked to the cost of catastrophe bonds. De-pegging insurance can act as a counterweight and a key marketing tool when the law forbids the payment of interest on stablecoins.
Mohammed Dawood Dawood, Syed Saif Ullah Hussaini, Mohd Zain ul Abeddin, Bishal Hizli Hizli
Cryptocurrencies have emerged as a disruptive force in global finance, challenging traditional banking systems through decentralization, transparency, and borderless transactions. Initially perceived as speculative assets, cryptocurrencies have increasingly gained institutional recognition, raising important questions regarding their financial role, regulatory governance, and long-term sustainability. This study adopts a qualitative-dominant mixed-method approach based on secondary data analysis. Data were collected from peer-reviewed journals, institutional reports, regulatory documents, and reputable market analyses published over the last decade. Thematic and descriptive analyses were employed to examine trends in cryptocurrency adoption, regulatory responses, technological innovation, and sustainability efforts. The findings indicate that cryptocurrencies have evolved into recognized financial assets, with growing institutional participation and expanding applications in cross-border payments and decentralized finance. However, significant challenges persist, including regulatory fragmentation, cybersecurity risks, market volatility, and environmental concerns related to energy-intensive mining. Regulatory milestones such as the European Union’s MiCA framework demonstrate progress toward legal harmonization, while technological innovations such as Layer 2 solutions, interoperability protocols, and Proof-of-Stake consensus mechanisms support scalability and sustainability. The discussion links these findings to Technology Acceptance and Innovation Diffusion theories, showing that institutional adoption is driven by perceived usefulness, regulatory legitimacy, and technological compatibility. Market Regulation and Institutional theories further explain divergent national regulatory approaches and increasing global coordination efforts. Sustainability considerations emerge as a critical determinant of long-term viability, shaping both technological development and policy intervention. Cryptocurrencies represent a transformative element of the global financial system, offering opportunities for efficiency, inclusion, and innovation.
Світлана Володимирівна Ковальчук, Віталій Григорович Федоришен
The article explores the fundamental essence and strategic role of investment capital within the context of the dynamic development of the stock market amidst the global digitalization of the economy. The authors conduct a comprehensive analysis of the conceptual apparatus, focusing on refining the definition, classification, and multifaceted functions of investment capital as a core resource for ensuring the financial stability of enterprises and maintaining a high level of liquidity in the securities market. Particular attention is paid to the transformation of capital from traditional forms into digital assets, a process that is fundamentally reshaping the architecture of modern financial relationships and global capital flows. The study demonstrates that the synergy between investment capital and digital technologies critically enhances market transparency, minimizes transaction costs, and accelerates the execution of financial operations. The research details the impact of cutting-edge technologies, such as blockchain-based trading, artificial intelligence for predictive analytics, and decentralized finance (DeFi) protocols, on the efficiency of capital allocation. Based on an empirical analysis of statistical data for the period 2021–2025, the correlation between investment capital inflows and key market capitalization indicators is identified. The paper further examines the influence of digital platforms on asset structures, price dynamics, and the overall resilience of the stock market to extreme volatility and external economic shocks. The authors reveal that digitalization acts as a powerful catalyst for the redistribution of capital i favor of high-tech sectors of the economy, thereby altering traditional investment paradigms. Furthermore, the research substantiates practical recommendations for stimulating the effective use of capital through the development of robust fintech infrastructure, the adaptation of regulatory frameworks to the requirements of the digital era, and the implementation of comprehensive programs to enhance digital financial literacy among market participants. The findings of the study demonstrate that the active involvement of investment capital under the conditions of stock market digitalization enhances the international competitiveness of the national economy and contributes to the sustainable development of the financial system. This article will be of significant value to researchers, financial sector practitioners, and investors interested in modern approaches to capital management and the evolution of the stock market under the ongoing pressure of digital transformation and technological progress.