L. Ali, M. Imran Azim, Jan Peters, Nabin B. Ojha ¡ 6 authors
This paper presents the integration of third generation (Gen3) blockchain technology into a transactive energy market (TEM) for enabling secure and efficient peer-to-peer (P2P) energy trading among diverse participants, including prosumers with photovoltaic (PV) systems and battery energy storage systems (BESS), as well as electric vehicle (EV) owners. The primary motivation behind this work is to streamline transactive energy markets by reducing reliance on third-party intermediaries and enhancing energy self-sufficiency. The TEM utilizes blockchain's decentralized ledger for transparent transactions, with an advanced trading engine that matches participants' energy and price bids based on forecasted profiles and optimizes local energy use while minimizing costs. The major contributions of this study include: (1) the development of a scalable and efficient P2P trading framework leveraging Proof of Stake (POS) and Proof of History (POH) consensus mechanisms based on Gen3 blockchain, and (2) a comprehensive performance analysis resulting in considerable transaction time, throughput and cost reductions compared to traditional business-as-usual models. Numerical simulations reveal a 24% and 23% reduction in peak grid imports and exports, translating into financial and environmental benefits for all stakeholders, including prosumers, network operators, and retailers.
Abstract From Nakamotoâs genesis block, 15 years of technological advancements, new financial instruments, regulations, and emerging participants have defined the Crypto Ecosystem. This paper chronicles its development from the creation of Bitcoin to the present-day landscape of cryptocurrencies, tokens, and decentralized finance applications. It explores the foundational technologies, financial instruments, key players, and regulatory frameworks in Europe and the US. By critically assessing the current state of the crypto market, the paper identifies both the promises fulfilled and the challenges that remain. It contributes to the existing literature by providing a synthesized understanding of the crypto ecosystem, highlighting the interplay between technological advancements and financial market dynamics.
David Cisar, Benjamin Schellinger, Jens-Christian Stoetzer, Nils Urbach ¡ 7 authors
Abstract Corporate bonds are an attractive option for corporate financing. However, current bond markets face many challenges and inefficiencies, resulting in high transaction costs (TAC). In recent years, technological advancements like blockchain technology have enabled the possibility of reducing TAC in bond markets. Even though practice experiments with such solutions, academic literature lacks generic design knowledge under the TAC lens to design blockchain-based bonds. Thus, our research follows the design science research (DSR) paradigm to design and develop a bond prototype using the Ethereum blockchain protocol. Our results highlight the capability of blockchain-based bond markets to reduce TAC in the three dimensions of asset specificity, uncertainty, and transaction frequency. Further, our research provides design principles to contribute to both practice and the academic discourse on developing blockchain-based bond markets with reduced TAC.
A detailed analysis of the potential of DLT (Distributed Ledger Technology) that can be used in investment projects, especially in capital-intensive investments, is carried out in Chapter 2 , where the essential properties of the technology and the resulting tools are examined. Potential processes and services that can be used in the process of financing investment projects are also analysed, as are the concepts of using DLT in such projects, as described in the literature. Furthermore, an examination of the legal framework for the mechanism of financing capital-intensive investments using DLT, which is elaborated in Chapters 3 â6, is also conducted. This analysis provides the basis for the construction of the model described in Chapter 7 .
This chapter deals comprehensively with the legal issue of a Decentralized Autonomous Organization (DAO), which is central to the theme of the book. In general, Chapters 3 â6 analyse the practical and legal applicability of certain seemingly promising business and technological solutions offered by DLT for financing capital-intensive and long-term investments, assuming a global and cross-border nature. This primarily refers to the possibility, under the law in force at the time of submitting the book for publication, of applying company law provisions to the DAO without creating a legal risk that is significant for the project to be successful (including a detailed analysis in Chapter 6 ). In this chapter, particular attention is paid to the legal issues of âwrappingâ a DAO in a company.
Irving Jared Villanueva, Madhusudan Srinivasan, Faqeer Ur Rehman
Blockchain smart contracts play a crucial role in automating and securing agreements in diverse domains such as finance, healthcare, and supply chains. Despite their critical applications, testing these contracts often receives less attention than their development, leaving significant risks due to the immutability of smart contracts post-deployment. A key challenge in the testing of smart contracts is the oracle problem, where the exact expected outcomes are not well defined, complicating systematic testing efforts.Metamorphic Testing (MT) addresses the oracle problem by using Metamorphic Relations (MRs) to validate smart contracts. MRs define how output should change relative to specific input modifications, determining whether the tests pass or fail. In this work, we apply MT to test an Ethereum-based crowdfunding smart contract, focusing on core functionalities such as state transitions and donation tracking.We identify a set of MRs tailored for smart contract testing and generate test cases for these MRs. To assess the effectiveness of this approach, we use the Vertigo mutation testing tool to create faulty versions of the smart contract. The experimental results show that our Metamorphic Relations (MRs) detected 25.65% of the total mutants generated, with the most effective MRs achieving a mutant-killing rate of 89%. These results highlight the utility of MT to ensure the reliability and quality of blockchain-based smart contracts.
Ni Gusti Ayu Pitria, Winola Wijayanti, Grace T. Pontoh, Aini Indrijawati
This research aims to conduct a comparative study between the peer-to-peer lending system and the traditional loan model. The method used is a systematic literature review study of 61 relevant scientific papers published between 2015 and 2024. The parameters analyzed include the provision of access to finance, transaction costs, the speed of the lending process, as well as the level of transparency and consumer protection. The results show that the peer-to-peer lending system has advantages in terms of providing easier and faster access to financing for individuals and small businesses because it uses a simple and uncomplicated digitization process. This model is also able to reduce transaction costs and speed up the process through the application of blockchain technology that streamlines the flow of transactions. The study also found that blockchain technology supporting peer-to-peer lending plays an important role in increasing the transparency of transactions through decentralized digital records that cannot be manipulated. However, the challenges of immature financial regulations and rapidly evolving cybersecurity risks still need to be addressed to support the wider adoption of peer-to-peer lending as a new alternative in the financial services industry. Therefore, further research is needed to find solutions to these barriers so that peer-to-peer lending can be optimally utilized as an inclusive future financial solution.
Market participants and policy makers have shown strong interest in DLT-based financial applications such as tokenisation. However, despite growing enthusiasm by market participants and the emergence of a clearer divide between crypto-assets and regulated tokenised assets, adoption of tokenisation remains scarce. This report analyses possible reasons for the absence of a market for tokenised assets and puts forward policy considerations for financial supervisors and policy makers.
Enterprise innovation investment is influenced by the actions of innovation subjects, whereas regulating shareholders' equity pledge behavior facilitates innovation investment and finance but also carries dangers and affects enterprise innovation investment. Methods:This paper builds an unbalanced panel model to empirically analyze the impact of controlling shareholders' equity pledges on corporate innovation and its heterogeneous characteristics. It also looks at the moderating role of corporate financing constraints and the mediating role of equity incentives, using data from A-share listed companies in China's pharmaceutical manufacturing industry from 2015 to 2022. Innovation investment is substantially inversely correlated with controlling shareholders' equity pledge; that is, firms' creative behavior and intensity are inhibited by equity pledge. Results and conclusions:The results also show that controlling shareholders' equity commitments have a more pronounced negative impact on enterprises' ability to innovate than non-state-owned and decentralized equity firms. The relationship between company innovation and the equity pledge of controlling shareholders is somewhat mediated by equity incentives. The relationship between controlling shareholders' equity promises and enterprises' innovation is negatively moderated by financing limitations, which also reduces R&D expenditure and stifles innovation.
According to the latest data from CryptoSlam, as of November 2024, NFT sales have approached USD 7.43 billion, with trading profits exceeding USD 33.303 million. In the buyerâseller market, the potential demand for NFT transactions continues to grow, leading to rapid development in the NFT market and giving rise to various issues, such as price manipulation, counterfeit products, hacking of investment platforms, identity verification errors, data leaks, and wallet security failures, all of which have caused significant financial losses for investors. Currently, the NFT investment market faces challenges such as legal uncertainty, information security, and high price volatility due to speculation. This study conducted expert interviews and adopted a two-stage research methodology to analyze the most common risk factors when selecting NFT investments. It employed the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP) to explore risk factors such as legal issues, security concerns, speculation, and price volatility, aiming to understand how these factors influence investors in choosing the most suitable NFT investment platform. The survey was conducted between February and June 2023, targeting professionals and scholars with over 10 years of experience in the financial market or financial research, with a total of 13 participants. The empirical results revealed that speculation had the greatest impact compared to legal issues, security concerns, and NFT price volatility. Speculation and price volatility directly influenced other risk factors, potentially increasing the risks faced by NFT investment platforms. In contrast, legal and security issues had less influence on other factors and were more affected by them, indicating a relatively lower likelihood of occurrence. Thus, investors must be cautious of short-term speculation, particularly when dealing with rare NFTs. The best approach is to set an exit price to minimize potential losses if the investment does not proceed as planned.
Decentralized Finance (DeFi) lending protocols currently rely on fixed collateralization ratios, leading to inefficiencies such as over-collateralization, frequent liquidations, and suboptimal capital utilization. This paper proposes a novel framework integrating machine learning (ML) with DeFi lending protocols to dynamically adjust collateral requirements in realtime based on borrower behavior, market volatility, and on-chain data. By analyzing historical loan performance, social sentiment, and macroeconomic indicators, the ML model optimizes collateral ratios to minimize liquidations while maintaining protocol security. We simulate the model using data from major DeFi platforms (e.g., Aave, Compound) and demonstrate a 30-50