Bitcoin'in 2009 yılında ortaya çıkmasıyla birlikte, birçok sektör üzerindeki etkileri gözlemlenmiştir. Ancak, kripto para piyasalarındaki yüksek volatilite ve merkezi bir kontrol olmaması, kripto paraların geleceği konusunda belirsizlik yaratmaktadır. Bu anlamda, finansal sektörlerin dinamik yapısı gereği diğer sektörlerden daha hızlı etkilendikleri doğal olarak kabul edilmektedir. Bu araştırmanın temel amacı, Bitcoin, Ethereum, Litecoin ve Ripple gibi dört kripto para biriminin yatırım aracı olarak potansiyelini değerlendirmektir. Bu amaç doğrultusunda, 1 Ocak 2018 - 1 Ocak 2023 tarihleri arasında, seçili kripto para birimlerinin getiri oranlarının volatilite özellikleri modellenmeye çalışılmıştır. Otoregresif koşullu değişen varyans modelleri (Autoregressive conditional heteroskedasticity - ARCH) analizi kullanılarak yapılan çalışmada, modelin volatilite tahmininin anlamlı sonuçlar vermesi üzerine VAR analizi ve Granger nedensellik ilişkileri eklenerek desteklenmiştir. Bu testlerin sonucunda kripto para birimlerinin risk profili incelenmiş ve gelecekteki fiyat hareketlerine ilişkin bir tahmin sağlanması amaçlanmıştır. Bu şekilde, kripto para birimlerinin potansiyel bir yatırım aracı olarak değerlendirilmesi konusunda tespitler yapılarak literatüre katkıda bulunulmuştur. Bu bağlamda, serilerde ARCH etkisi gözlemlenmiştir. Yapılan VAR ve Granger Nedensellik testleri sonucunda, Bitcoin'deki bir değişikliğin diğer altcoin'leri önemli ölçüde etkilediği ancak Ripple'da anlamlı bir etkinin olmadığı sonucuna varılmıştır.
The rapid expansion of real-time payment networks—such as FedNow, the RTP network, and other instantsettlement infrastructures—has accelerated the pace of financial transactions but exposed structural limitationsin the underlying settlement processes. Current systems primarily rely on prefunded accounts, end-of-dayreconciliation, or deferred transfers of central bank reserves, creating liquidity fragmentation, intraday creditexposure, and operational inefficiencies. As transaction volumes grow and financial institutions demandcontinuous 24/7 settlement, these constraints inhibit scalability, resilience, and competition.This paper proposes a Blockchain-Enabled Real-Time Settlement Framework designed to enhance thesettlement capabilities of FedNow and other instant payment ecosystems. The framework leverages apermissioned distributed ledger to provide immutable, cryptographically verifiable, and atomic settlementfinality, while maintaining strict regulatory oversight and interoperability with existing payment rails. Byrepresenting central bank reserves or interbank settlement obligations as on-chain, regulator-supervised digitaltokens, institutions gain the ability to settle transactions instantly with reduced prefunding requirements andimproved liquidity efficiency
This paper introduces cryptocurrency into a two-country open-economy model. Based on the theoretical model, we employ the TVP-VAR model to study the dynamic interdependence among interest rate spread (a proxy in the monetary market), exchange rate (a proxy in the forex market), and Bitcoin transactions (a proxy in the cryptocurrency market). The key finding is that Bitcoin has an effect of de-fiatization in the global financial market. When there is a higher divergence in monetary policy between the US and China, Bitcoin attracts greater attention with a higher price, posing a competing force against USD. When there are greater fluctuations in the exchange rate of USD/CNY, Bitcoin diverts investors from CNY. The fiat currencies of the two largest economies are both losers while Bitcoin gains. Therefore, cryptocurrency not only decentralizes the role of commercial banks as a medium of payment, but also decentralizes the role of central banks as a monetary policymaker. In face of this challenge, it is suggested that central banks should embrace blockchain technology and develop their own digital currency to restore the trust lost in the global financial crisis. International collaborations in terms of regulation are necessary given its borderless and authority-less feature.
This research aims to empirically investigate the portfolio risk associated with crypto assets. In other words, we want to investigate whether the inclusion of crypto assets in a portfolio can minimize the portfolio risk or not, because it is argued that there is a lower degree of correlation between crypto assets and traditional assets. In order to achieve our research objectives, we employ the Vector Autoregressive Model (VAR) by using five different asset classes. The first two variables are taken from the crypto assets, Bitcoin and Ethereum, and the remaining three variables for Gold, Crude Oil and VIX (Chicago Board Options Exchange's (CBOE) volatility index). Our research strategy will be based on an analysis for unit root, optimal lag selection, coefficient matrix, checking VAR stability, the Granger causality test, and impulse response function (IRF). Our findings suggest that none of the indicators of traditional assets drive and explain Bitcoin. We also found that only Bitcoin is significantly related to Ethereum. while none of the other variables are statistically useful to explain the variation in the Ethereum. Based on these findings it can be recommended that the inclusion of crypto assets into a portfolio reduces risk because none of the indicators of crypto assets are significantly related to the indicators of traditional assets.
Staking has emerged as a crucial concept following Ethereum’s transition to Proof-of-Stake consensus. The introduction of Liquid Staking Derivatives (LSDs) has effectively addressed the illiquidity issue associated with solo staking, gaining significant market attention. This paper analyzes the LSD market dynamics from the perspectives of both liquidity takers (LTs) and liquidity providers (LPs). We first quantify the price discrepancy between the LSD primary and secondary markets. Then we investigate and empirically measure how LTs can leverage such discrepancy to exploit arbitrage opportunities, unveiling the potential barriers to LSD arbitrages. In addition, we evaluate the financial profit and losses experienced by LPs who supply LSDs for liquidity provision. Our results show that 66% of LSD liquidity positions generate returns lower than those from simply holding the corresponding LSDs.
Stablecoins are increasingly important in decentralized finance (DeFi) and crypto asset markets, and their prominence has led to greater scrutiny of their unique role as expressions of the U.S. dollar running on blockchain networks. Stablecoins attempt to perform a mechanically complex function – to remain pegged to the dollar, even during periods of market volatility.
With the expansion of digitalization into the financial sector, emerging technology has also demonstrated new applications within the traditional financial system. This rapid change in the financial system was not limited only to the applications in the central financial system and the emergence of financial assets, but then steps were taken to the decentralized financial system. The aim of this study is to examine the Decentralized Finance (DeFi) system, which has emerged as an independent alternative to the traditional finance system, and to reveal the opportunities and threats in this field. In this context, the focus was first on the traditional central financial system, which consists mostly of banking and financial institutions. Then, digital assets, cryptocurrencies, FinTech and RegTech which are the antecedents of decentralized finance system were explained. This study examines DeFi, an independent and pioneering technology, highlighting its distinctive features and explaining the opportunities and threats it presents. While the important opportunities emerging with DeFi are accessibility, globality, cost effectiveness and transparency, the main threats are listed as exclusion of the central financial system, volatility, legal problems and security risk.
This study provides a comprehensive analysis of Decentralized Finance (DeFi) within the U.S. economy, focusing on its rise, challenges, and implications. The primary objective is to unravel the concept of DeFi, delineate its role in the U.S. financial landscape, and explore its historical evolution from traditional to blockchain-based finance. Employing a systematic literature review and content analysis, the study synthesizes data from academic journals, industry reports, and regulatory publications. The methodology involves a meticulous selection process, adhering to specific inclusion and exclusion criteria to ensure the relevance and quality of the literature. Key findings reveal that DeFi, underpinned by blockchain technology and smart contracts, offers innovative financial services, enhancing inclusivity and efficiency. However, it faces challenges such as regulatory uncertainties, security concerns, and scalability issues. The study highlights the significant impact of DeFi on the U.S. economy, including technological advancements, economic integration, and regulatory shifts. It also underscores the implications for various stakeholders, including investors, institutions, and regulators. The future landscape of DeFi is poised for growth, marked by technological innovations and potential integration with traditional financial systems. The study concludes with recommendations for industry stakeholders and policymakers, emphasizing the need for clear regulatory frameworks, enhanced security protocols, and consumer education. Future research directions include exploring DeFi's integration with emerging technologies and its role in addressing global financial challenges. This study contributes to the academic discourse on DeFi and offers insights for policymakers, investors, and financial institutions navigating this evolving landscape.
The prevalence of maximal extractable value (MEV) in the Ethereum ecosystem has led to a characterization of the latter as a dark forest. Studies of MEV have thus far largely been restricted to purely on-chain MEV, i.e., sandwich attacks, cyclic arbitrage, and liquidations. In this work, we shed light on the prevalence of non-atomic arbitrage on decentralized exchanges (DEXes) on the Ethereum blockchain. Importantly, non-atomic arbitrage exploits price differences between DEXes on the Ethereum blockchain as well as exchanges outside the Ethereum blockchain (i.e., centralized exchanges or DEXes on other blockchains). Thus, non-atomic arbitrage is a type of MEV that involves actions on and off the Ethereum blockchain. In our study of non-atomic arbitrage, we uncover that more than a fourth of the volume on Ethereum's biggest five DEXes from the merge until 31 October 2023 can likely be attributed to this type of MEV. We further highlight that only eleven searchers are responsible for more than 80% of the identified non-atomic arbitrage volume sitting at a staggering $132 billion and draw a connection between the centralization of the block construction market and non-atomic arbitrage. Finally, we discuss the security implications of these high-value transactions that account for more than 10% of Ethereum's total block value and outline possible mitigations.
Chit fund is a peer-to-peer saving and borrowing scheme operated among trusted groups of people. It is a reliable source of funds in emergencies with no guarantor and low-interest rate. Despite their enduring benefits, chit funds face challenges related to trust, transparency, and security. At present, unscrupulous subscribers might join chit-funds, borrow money, and make payment defaults. This leads to disruptions in contribution cycle and affects overall functioning. Additionally, non-transparent record-keeping and transaction processes, hinder participants from verifying fund activities, creating a susceptible environment for fraud and malpractice. These challenges are an obstacle to the sustainability and trustworthiness of the chit-fund system. Therefore, to overcome aforementioned challenges, this paper proposes TruChit, a blockchain-based chit fund system with creditworthiness evaluation framework. It leverages the Adaptive Neuro-Fuzzy Inference System (ANFIS) to assess the creditworthiness of subscribers, which ensures the credibility and reliability of individual participants. Further, proposes permissioned blockchain-assisted chit-fund framework with role-based access control to instill trust, security, and transparency within chit-fund operations. Moreover, the efficacy of TruChit is evaluated by analyzing credit score dataset and achieves 93.5% accuracy, which is better than other approaches.
The implementation of the Know Your Customer (KYC) strategy by banks within the financial sector enhances the operational efficiency of such establishments. The data gathered from the client during the KYC procedure may be applied to deter possible fraudulent activities, money laundering, and other criminal undertakings. The majority of financial institutions implement their own KYC procedures. Furthermore, a centralized system permits collaboration and operation execution by multiple financial institutions. Aside from these two scenarios, KYC processes can also be executed via a blockchain-based system. The blockchain’s decentralized network would be highly transparent, facilitating the validation and verification of customer data in real-time for all relevant stakeholders. In addition, the immutability and cryptography of the blockchain ensure that client information is secure and immutable, thereby eradicating the risk of data breaches. Blockchain-based KYC can further improve the client experience by eliminating the requirement for redundant paperwork and document submissions. After banks grant consumers loans, a blockchain-based KYC system is proposed in this study to collect limit, risk, and collateral information from them. The approach built upon Ethereum grants financial institutions the ability to read and write financial data on the blockchain network. This KYC method establishes a transparent, dynamic, and expeditious framework among financial institutions. In addition, solutions are discussed for the Sybil attack, one of the most severe problems in such networks.
<div xmlns="http://www.tei-c.org/ns/1.0"> The financial industry is undergoing a transformative evolution driven by technological advancements and shifting consumer expectations. "Future Trends and Opportunities: Opportunities for innovation and disruption in the financial industry" provides a comprehensive exploration of key trends shaping the industry's future. From the rise of digital transformation and blockchain to the integration of artificial intelligence and sustainable finance, the abstract highlights the multifaceted opportunities for innovation. Emphasis is placed on enhancing customer experiences, improving operational efficiency, promoting financial inclusion, and addressing the challenges of regulation, cybersecurity, and privacy. The abstract concludes by emphasizing the critical importance of adaptation, continuous innovation, and collaborative efforts between traditional institutions and fintech disruptors to navigate the dynamic landscape and seize the opportunities that lie ahead in the evolving financial ecosystem I. Introduction A. Brief overview of the financial industry B. Importance of innovation and disruption in driving growth C. Purpose of exploring future trends and opportunities II. Current Landscape of the Financial Industry A. Traditional banking and financial services B. Rise of fintech companies C. Emerging technologies (blockchain, artificial intelligence, etc.) D. Regulatory environment and its impact III. Future Trends in the Financial Industry A. Digital transformation and the shift to online platforms 1. Mobile banking 2. Digital wallets 3. Contactless payments B. Blockchain and cryptocurrencies 1. Decentralized finance (DeFi) 2. Central bank digital currencies (CBDCs) 3. Smart contracts C. Artificial Intelligence (AI) and Machine Learning (ML) 1. Robo-advisors 2. Predictive analytics for risk management 3. Chatbots and virtual assistants D. Open banking and API integration 1. Collaboration between traditional banks and fintechs 2. Enhanced customer experience 3. Data sharing and security concerns IV. Opportunities for Innovation and Disruption A. Enhanced customer experience 1. Personalized services 2. Real-time financial insights 3. Seamless onboarding processes B. Improved efficiency and cost savings 1. Automation of repetitive tasks 2. Streamlined back-office operations 3. Enhanced fraud detection and prevention C. Financial inclusion 1. Serving the unbanked and underbanked populations 2. Microfinance and alternative lending solutions D. Sustainable finance 1. ESG (Environmental, Social, Governance) investments 2. Green financing options 3. Social impact investing V. Challenges and Considerations A. Regulatory hurdles B. Cybersecurity concerns C. Privacy and data protection D. Resistance to change in traditional institutions VI. Conclusion A. Summary of key future trends and opportunities B. Importance of adaptation and continuous innovation C. Encouraging collaboration between traditional and new players in the financial industry </div>
Depositing and borrowing in a currency other than the local currency is a well- documented phenomenon. The associated exchange rate and monetary risks, pivotal during the Asian Financial Crisis of 1997, prompted an academic discourse. Financial dollarization literature explains why individuals and corporations domiciled in emerg- ing markets deposit and borrow in hard currencies, mainly in U.S. dollars. This thesis proposes a model for cryptocurrency lending and assesses model predictions with a data set containing more than one million Ethereum transactions. The computational modelling and statistical analysis show that the main theoretical explanations provided by financial dollarization literature may not be directly transferable to cryptocurrencies. The results suggest that the popularity of depositing and borrowing in cryptocurrencies must be largely motivated by other factors.
Charles Bertucci, Louis Bertucci, Mathis Gontier Delaunay, Olivier Guéant · 5 authors
ABSTRACT Contrasting sharply with traditional money, bond, and bond futures markets, where interest rates emerge organically from participant interactions, DeFi lending platforms employ rule‐based interest rates that are algorithmically set. Thus, the selection of an effective interest rate model (IRM) is paramount for the success of a lending protocol. This paper investigates the modeling of agents' behaviors on lending platforms and proposes a theoretical framework for formulating optimal IRMs. We show that, under perfect information, an optimal control model with a state constraint generates an optimal interest rate policy that has a shape similar to that of popular markets. Furthermore, we formally analyze interest rate policies based on PID controllers, which work efficiently based on fewer assumptions. Using public data of popular markets on the Ethereum blockchain, we analyze agents' behavior, build a realistic simulation environment, and highlight the main tradeoffs in the design of interest rates for decentralized lending platforms.