This paper substantiates the theoretical and applied foundations of investment management for forming and developing resilient distribution networks in agribusiness. Under global food market transformations, systemic macroeconomic instability, and geopolitical shocks, conventional linear investment models prove ineffective for long-term planning. To bridge this gap, this research adapts advanced economic frameworks directly to agricultural supply chains, shifting the focus from discrete physical asset valuation to ecosystem-wide synergy. This is achieved by combining classic capital planning with portfolio diversification, real options valuation (ROV), behavioral finance, stakeholder-driven ESG metrics, and decentralized financial tools (DeFi). The study proposes a hierarchical digitization model of the investment process powered by artificial intelligence (AI) and Big Data. This system operates at three spatial levels: national (for comprehensive stress-testing against geopolitical shocks), regional (deploying predictive digital twins of logistics clusters to optimize infrastructure placement), and local (facilitating agile capital allocation and behavioral consumer analysis). This structure ensures capital flows efficiently into highperforming channels while minimizing bottlenecks. To address the trade-off between environmental requirements and financial risks, the study introduces the "Two-Factor Balanced Development Matrix." This model links financial credit scoring with multidimensional ESG profiling. Counterparties are categorized into operational quadrants (e.g., Green Leaders, Traditional Pragmatists, Eco-Startups) to determine customized trade credit lines and commercial terms. Finally, the research outlines integrated risk mitigation instruments, including green trade finance (IFC, EBRD), eco-premium forward contracts, and parametric climate insurance. These measures reduce non-performing loans, lower the cost of capital, and improve the Scope 3 emission rating for distributors.
The financial sustainability of small and medium-sized enterprises (SMEs) has become increasingly important in the context of economic volatility, technological disruption, and growing sustainability demands. However, existing studies remain fragmented and often examine financial, organizational, technological, and environmental factors in isolation. This study systematically reviews 49 articles indexed in the Scopus and Web of Science databases published between 2014 and 2026 to identify the dominant determinants, thematic patterns, and conceptual structure of financial sustainability in SMEs. Using the PRISMA protocol and NVivo-based bibliometric and thematic analyses, this study examines publication trends, geographic distribution, lexical structures, and thematic relationships across the literature. The results show that research is concentrated primarily in Asia and Europe, reflecting increasing scholarly attention to financial literacy, governance quality, resilience, digital transformation, FinTech adoption, ESG practices, and green finance. Thematic synthesis reveals three interconnected pillars—Internal Capability, Adaptive Resilience, and Digital–Green Transformation—which collectively form an architecture of endurance framework that explains how SMEs maintain financial viability under conditions of uncertainty and change. This framework advances prior reviews by integrating organizational capability, resilience-building mechanisms, and sustainability-oriented transformation into a unified model of financial sustainability for SMEs. Practically, the findings highlight the importance of strengthening financial literacy, governance quality, risk management capability, digital adoption, and sustainability-oriented financing, while emphasizing the role of policy support and financial inclusion in fostering SME resilience. Future research should further explore the implications of generative artificial intelligence, blockchain-based finance, and decentralized finance (DeFi) on SME financial sustainability.
Lending protocols in decentralized finance have traditionally relied on over-collateralization mechanisms, where investor protection is primarily ensured through the automatic liquidation of collateral. While effective from an operational perspective, this approach limits the economic role of credit when compared with under-collateralized structures. In such settings, the prudential management of credit risk becomes a central element for protocol sustainability. This paper proposes a prudential framework for decentralized lending protocols by introducing an additional protection layer based on the distinction between tokenized loss-absorbing capital, an operational buffer, and a prudential reserve. The model defines three classes of subordinated instruments-First Loss Token, Contingent Capital Token, and Subordinated Backstop Token-arranged according to a progressive loss waterfall. The model is first applied to public data from Goldfinch and then extended to a TrueFi dataset, with the aim of assessing the ability of the policy to reduce losses borne by senior liquidity providers. The model shows a net reduction in losses. The sensitivity analysis confirms that the mechanism maintains a positive net benefit across variations in instrument costs, risk weights, and loss severity. The results suggest that an explicit prudential layer may contribute to strengthening the resilience of DAO-based credit protocols by making the prudential cost of risk-taking more transparent and by distinguishing between available liquidity, loss-absorbing capital, and protective reserves.
Abstract Corporate treasury departments face growing challenges created by liquidity fragmentation, inefficient cash management, and delayed cross-border settlements-a perfect storm for increased financial risks for the firms and for operational difficulties. The present-day treasury systems rely on centralized banking and manual processes. A traditional one thus lacks the flexibility and the transparency needed in today’s very uncertain global environment.Decentralized finance (DeFi) is presented in this paper as an essential infrastructure layer that has the potential to transform how businesses handle liquidity. DeFi offers programmable, real-time, and international financial execution through the use of smart contracts, algorithmic liquidity pools, decentralized exchanges, and tokenized assets. Conceptual modeling links DeFi mechanics to essential treasury functions, comparative analysis examines DeFi and traditional systems, and scenario simulations explore practical examples of corporate use cases.It is found that DeFi can enhance access to liquidity, reduce transaction costs, and automate treasury operations, especially with respect to intercompany fund flows, short-term financing, and FX execution. However, adoption needs strong governance frameworks, regulatory agreement, and technical compatibility with existing systems. This study offers a practical framework for CFOs, fintech developers, and policymakers to evaluate DeFi’s role in corporate treasury environments. It positions decentralized infrastructure as a useful tool for next-generation liquidity strategies.
This paper empirically investigates the determinants and performance implications of capital structure for two dominant Indian conglomerates, Reliance Industries Limited (RIL) and the diversified Tata Group, utilizing annual data spanning the critical 2011–2021 period. The study addresses the ambiguity regarding optimal financing choices in large emerging market firms, focusing on the contrasting centralized, capital-intensive structure of RIL versus the industry-aligned, decentralized financing strategies of major Tata subsidiaries (TCS, Tata Steel, Tata Motors). A dynamic panel data approach, utilizing the System Generalized Method of Moments (Sys-GMM), is employed across the 11-year period to address issues of endogeneity, unobserved firm heterogeneity, and, critically, to accurately estimate the speed of leverage adjustment, given the observed persistence of financing decisions. The results confirm a dual-theory application dictated by corporate strategy and industry alignment. RIL’s financing choices, particularly its aggressive leveraging followed by deleveraging toward zero net debt by 2021, are predominantly explained by the Pecking Order Theory (POT), where high profitability negatively predicts reliance on external debt. Conversely, the Tata Group’s sub-entities strongly align with the Trade-Off Theory (TOT), with asset tangibility significantly dictating debt capacity (e.g., high debt for Tata Steel vs. minimal debt for TCS). Crucially, the analysis confirms that leverage generally showed a significant negative impact on RIL’s operational performance [Return on Assets (ROA) and Return on Equity (ROE)], validating its strategic shift towards an equity-heavy model. The findings underscore the critical role of strategic corporate philosophy (centralized flexibility versus decentralized industry alignment) in shaping capital structure efficiency and shareholder value creation within complex conglomerates.
Open access
Working Capital and Financial Performance
Innovations and Analysis in Business and Education
Актуальность исследования обусловлена стремительным развитием криптовалютного рынка и растущим интересом инвесторов к альтернативным способам получения дохода. Одним из таких инструментов становится стейкинг криптовалют, позволяющий получать вознаграждение за участие в поддержании блокчейн-сетей. Проблематика развития данного инструмента заключается в недостаточной осведомленности инвесторов о механизмах стейкинга, его разновидностях, рисках и потенциальной доходности, особенно на фоне высокой волатильности крипторынка. Цель статьи – проанализировать стейкинг как форму альтернативного инвестирования, определить его преимущества и уязвимости, а также оценить перспективность для различных категорий инвесторов. В рамках исследования авторами применены методы сравнительного анализа, теоретического обзора источников, а также произведена оценка рисков и доходности на примерах конкретных криптовалют и платформ. В статье рассматриваются основные виды стейкинга: фиксированный, гибкий, ликвидный и делегированный. Приведены примеры популярных криптовалют, таких как Tezos, Cardano, Algorand, Polkadot и Ethereum, использующих алгоритм консенсуса Proof-of-Stake (PoS - доказательство доли владения), и сопоставлены их потенциальные доходности. Результаты исследования показывают, что при грамотном подходе стейкинг может быть эффективным инструментом создания пассивного дохода. Выявлены ключевые риски: волатильность, ограниченная ликвидность, угроза потери активов и технические сложности. Научным результатом являются предложенные стратегии минимизации рисков, включающие диверсификацию, выбор ликвидных активов и использование проверенных платформ. Таким образом, стейкинг представляет собой перспективный и гибкий инвестиционный механизм в рамках цифровой экономики. The relevance of the study is due to the rapid development of the cryptocurrency market and the growing interest of investors in alternative ways of generating income. One of these tools is cryptocurrency staking, which allows you to receive rewards for participating in the maintenance of blockchain networks. The problem with the development of this tool lies in the lack of investor awareness about staking mechanisms, its varieties, risks and potential returns, especially against the background of high volatility of the crypto market. The purpose of the article is to analyze staking as a form of alternative investment, identify its advantages and vulnerabilities, and assess its prospects for various categories of investors. As part of the study, the authors applied methods of comparative analysis, a theoretical review of sources, and an assessment of risks and profitability based on examples of specific cryptocurrencies and platforms. The article discusses the main types of staking: fixed, flexible, liquid and delegated. Examples of popular cryptocurrencies such as Tezos, Cardano, Algorand, Polkadot, and Ethereum using the Proof-of-Stake (PoS proof of ownership) consensus algorithm are given, and their potential returns are compared. The results of the study show that, with the right approach, staking can be an effective tool for creating passive income. Key risks have been identified: volatility, limited liquidity, the threat of asset loss and technical difficulties. The scientific result is the proposed risk minimization strategies, including diversification, the choice of liquid assets and the use of proven platforms. Thus, staking is a promising and flexible investment mechanism within the digital economy.
Бүгінде қаржы секторы Биткойн және Эфириум сияқты криптовалюталар басқаратын блокчейн технологиясы мен ақылды келісімшарттар ұсынатын мүмкіндіктермен мүлдем жаңа дәуірге аяқ басты. Осы жаңа дәуірде таратылған құрылымға ие және қауіпсіз, ашық және өзгермейтін жазу жүйесін ұсынатын блокчейн технологиясы арқылы қаржы секторына әкелген ең маңызды жаңалықтардың бірі - DeFi деп аталатын орталықтандырылмаған қаржылық қосымшалар. DeFi дәстүрлі қаржылық жүйені түрлендіретін, орталық органдарды алмастыратын жүйені құруға мүмкіндік беретін және негізінде ашық әрі қолжетімді қаржы жүйесін құру үшін блокчейн технологиясын қолданатын экожүйе ретінде қабылдана бастады. DeFi қосымшалары арқылы банктерге немесе әртүрлі қаржылық делдал институттарына жүгінбей-ақ ашық және қауіпсіз транзакциялар жасауға бағытталған. Орталықсыздандырудың арқасында пайдаланушыларға өз активтерін толық бақылау қамтамасыз етіледі және олардың орталық органдарға тәуелділігі төмендейді. Бұл зерттеудің мақсаты DeFi-дің (Decentralized Finance-орталықтандырылмаған қаржы) негізгі принциптері мен мүмкіндіктерін бағалау және оның CeFi-ден (Centralized Finance-орталықтандырылған қаржы) айырмашылығын көрсету болып табылады. Мақалада талдау, индукция және дедукция, салыстырмалы талдау әдістері қолданылды. Зерттеудің теориялық және әдіснамалық негізі шетелдік ғалымдардың ғылыми еңбектері мен Defillama және CoinMarketCap ұйымдарының статистикалық есептері болып табылады. Зерттеу нәтижесінде DeFi экожүйесінің орталықсыздандыру және делдалдық институтсыз транзакция жасау сияқты артықшылықтары бар болса да, оның әртүрлі жүйелі және жүйелі емес тәуекелдері бар (мысалы, реттеу, тұтынушылық, технологиялық және операциялық). Бұл тәуекелдер пайдаланушыларды инвестициялық шығынға ұшыратады. Жүйедегі негізгі технологияны түсіну және күшті қауіпсіздік шараларын қолдану арқылы пайдаланушылар осы ықтимал қауіптерді азайта алады. DeFi пайдаланушылары осы ықтимал тәуекелдерді білуі, жаңа платформаларға қатысуы және инвестициялауда мұқият болуы керек. Нәтижесінде, орталықтандырылмаған қаржы әкелетін инновациялық мүмкіндіктерді кеңінен тану және жүйе ішіндегі ықтимал тәуекелдерді азайту арқылы тезірек, арзанырақ және қолжетімді қаржылық қызметтер ұсынылып, DeFi экожүйесі кеңірек таралуы мүмкін.
This paper proposes an integrated fintech–insurtech architecture that embeds insurance directly into logistics and trade workflows using digital networks, distributed ledger technologies, and real-time risk analytics. Drawing on network effects, game theory, and empirical observations from inland transport and cargo insurance markets in India, the paper models strategic interactions among insurers, shippers, transporters, and trade finance providers. The study introduces an ordinal risk classification framework and a self-sustaining quarterly cargo claims cycle designed to stabilize liquidity, optimize premium pricing, and reduce information asymmetry, particularly for MSMEs operating in fragmented supply chains. By repositioning insurance as a continuously embedded financial infrastructure rather than a post-loss settlement mechanism, the framework demonstrates how digitally native insurance systems can improve trust, capital efficiency, and resilience across integrated logistics and trade ecosystems.
This paper examines the effect of overconfidence on financial decisions in a capital-constrained distribution channel where an upstream supplier with sufficient working capital produces goods for a downstream retailer who has limited working capital and may request trade credit from the upstream supplier. We obtain several interesting results. First, in a centralized financially constrained channel (CFCC) setting, we show that overconfidence has the results that both the optimal order quantity is tied to the mean of the uncertain market demand and that the supply chain is worse off. Second, in a decentralized financially constrained channel (DFCC) setting, the optimal order quantity with overconfidence is either higher or lower than that without overconfidence. When the retailer needs to ask for trade credit from the supplier, overconfidence means that the retailer’s order quantity is less affected by the wholesale price. We further numerically show that under market demand uncertainty, overconfidence may benefit a DFCC composed of an overconfident supplier and retailer. We also analyze the impacts of varying overconfidence levels on our results and find that the retailer may benefit when the retailer is more overconfident than the supplier.
Zadatak ovog diplomskog rada bio je proučiti različite metode strojnog učenja u svrhu predviđanja cijena kripto valuta. Najprije je dan kratak uvod kako su nastale i čemu služe kripto valute te koja je njihova poveznica sa strojnim učenjem. U nastavku su objašnjeni osnovni koncepti odabranih metoda i evaluacijskih metrika, a potom je dan uvid u praktični dio rada. U praktičnom dijelu rada korištena su četiri različita modela predikcije, uključujući regresijske modele, modele vremenskih serija i modele temeljene na neuronskim mrežama. Implementacija modela je realizirana u Python programskom jeziku uz uporabu poznatih biblioteka kao što su Pandas, NumPy, scikit-learn, itd. Na kraju su prikazani i uspoređeni rezultati evaluacijskih metrika za sva četiri modela.
U ovom diplomskom radu implementiran je decentralizirani sustav kreditiranja i štednje koristeći tehnologiju raspodijeljene glavne knjige. Rad počinje uvodom u osnovne koncepte raspodijeljene glavne knjige, kriptografiju i konsenzusne mehanizme. Analiziran je Ethereum lanac blokova, transakcije i razvoj pametnih ugovora koristeći Solidity i Hardhat. Glavni dio rada fokusira se na implementaciju pametnih ugovora za kreditiranje i štednju, uključujući izdavanje kredita s kolateralom i štednju stabilnih kriptovaluta uz kamate. Razvijeni su vanjski servisi za likvidaciju i ažuriranje kamatnih stopa, te interaktivno korisničko sučelje izrađeno s React.js i TypeScriptom.
In the ever evolving landscape of decentralized finance automated market makers (AMMs) play a key role: they provide a market place for trading assets in a decentralized manner. For so-called bluechip pairs, arbitrage activity provides a major part of the revenue generation of AMMs but also a major source of loss due to the so-called 'informed orderflow'. Finding ways to minimize those losses while still keeping uninformed trading activity alive is a major problem in the field. In this paper we will investigate the mechanics of said arbitrage and try to understand how AMMs can maximize the revenue creation or in other words minimize the losses. To that end, we model the dynamics of arbitrage activity for a concrete implementation of a pool and study its sensitivity to the choice of fee aiming to maximize the revenue for the AMM. We identify dynamical fees that mimic the directionality of the price due to asymmetric fee choices as a promising avenue to mitigate losses to toxic flow. This work is based on and extends a recent article by some of the authors.
We study how trading fees and continuous-time arbitrage affect the profitability of liquidity providers (LPs) in Geometric Mean Market Makers (G3Ms). We use stochastic reflected diffusion processes to analyze the dynamics of a G3M model under the arbitrage-driven market [Milionis et al. 2022a. “Automated Market Making and Loss-Versus-Rebalancing.” arXiv e-prints]. Our research focuses on calculating LP wealth and extends the findings of Tassy and White [Tassy and White. 2020. “Growth Rate of a Liquidity Provider's Wealth in xy = c Automated Market Makers.”] for the constant product market maker (Uniswap v2) to a broader range of G3Ms, including Balancer. This allows us to calculate the long-term expected logarithmic growth of LP wealth, offering new insights into the complex dynamics of AMMs and their implications for LPs in decentralized finance.
C. Vinoth Kumar, Poongundran Selvaprabhu, Nivetha Baska, Vivek Menon U · 7 authors
The Know Your Customer (KYC) process is a fundamental prerequisite for any financial institution’s compliance with the regulatory framework. Blockchain technology has emerged as a revolutionary solution to enhance the effectiveness of the KYC procedure. It ensures that the KYC process is transparent, secure, and immutable, thereby offering a robust solution to combat fraudulent activities. The potential of blockchain technology in revolutionizing the KYC process has been acknowledged globally. Blockchain technology provides a decentralized platform for storing customer data, enabling financial institutions to access the information seamlessly. Using ethereum blockchain technology in KYC procedures can enhance the efficiency of financial institutions, significantly reducing the time and cost associated with the process. This work aims to provide a viable and sustainable solution to the challenges that banks experience in implementing KYC procedures and onboarding new customers. The proposed solution involves the central bank maintaining a comprehensive register of all registered banks while closely monitoring their adherence to the existing regulations governing KYC and customer acquisition.
Double-entry accounting has been used globally for the past six hundred years and has become the base for all corporate financial reporting. Blockchain technology with distributed ledger now provides a new method of accounting termed “triple-entry accounting”. This method consists of recording and storage of business transactions, as a third entry on the blockchain. This third entry is expected to deliver a system that is trustworthy, immutable, and transparent. This study conducts a detailed review of the present literature on triple-entry accounting with blockchain technology and its impact on fraudulent practices. The review shows current literature has limited information on how this methodology will deter financial and accounting fraud. Drawing on the case studies of twenty-four companies involved in fraudulent practices globally, this paper describes common practices in manipulating financial statements, falsifying accounting records, and fraudulent banking transactions. The study explains the mechanics of how these practices can be prevented using triple-entry accounting in the blockchain environment and how the technique will bring about changes in the audit process and in the roles of internal and external auditors in the organization. The study recommends research propositions focused on governance and financial performance of a company when this method is adopted.