The rapid growth of the cryptocurrency market has raised the need for an effective model to predict opening prices and assist investors and policymakers in decision-making. Traditional econometric models often struggle with the high volatility and nonlinear patterns inherent in digital asset prices. Long short-term memory networks are effective at recognizing complex patterns, yet they lack interpretability. This study bridges this gap by integrating the error correction model with long short-term memory to improve prediction of Ethereum’s opening price. Using daily price data from January 2018 to June 2024, the model captures both long-term equilibrium relationships and short-term fluctuations, resulting in more accurate forecasts. The findings confirm a significant long-run equilibrium relationship between Bitcoin and Ethereum prices. The integrated model outperforms standalone models, by achieving a mean absolute error of 46.76, a mean squared error of 5,544.05, and an R-squared of 88%. This study contributes to both econometric and deep learning literature, highlighting Bitcoin’s influence on Ethereum, and offering a practical framework for financial forecasting. Future research could expand this work by incorporating additional macroeconomic variables, exploring alternative deep learning architectures, and testing the robustness of the model across time and market conditions.
Decentralized Finance (DeFi) emerged with the promise of eliminating traditional financial intermediaries and hierarchies, replacing them with trustless, automated, and decentralized systems. However, the reality of DeFi governance shows that disintermediation does not eliminate conflicts of interest or the need for trust. Cryptoenterprises—financial Decentralized Autonomous Organizations (DAOs)—operate without conventional governance structures such as boards of directors or managerial oversight, relying instead on code-based mechanisms. This absence of internal governance frameworks creates fertile ground for misaligned incentives, governance opacity, and unchecked internal controls, ultimately exacerbating conflicts between insiders (cryptopromoters) and investors (cryptoasset holders). This Article examines the emerging role of cryptogatekeepers: a new category of cryptointermediaries that counterbalances these governance failures. It explores the structural deficiencies of cryptoenterprises, including the absence of internal monitoring mechanisms, and identifies the conflicts. The analysis highlights how cryptopromoters—those in control of DeFi protocols—retain significant decision-making power while obscuring accountability, which leads to agency problems reminiscent of traditional finance, sans regulatory safeguards. By assessing the function of cryptointermediaries as potential de facto governance enforcers, this Article argues that cryptogatekeepers can introduce a layer of oversight that compensates for the current governance void in DeFi. It outlines best practices for mitigating conflicts of interest, enhancing disclosure standards, and improving the monitoring of cryptointermediaries. The Article also considers transnational regulatory approaches to bolster accountability in DeFi by proposing mechanisms such as cryptointermediary registries, mutual recognition of licensed cryptointermediaries, and standardized reporting frameworks. Ultimately, this Article contends that while DeFi presents an innovative model for financial services, it cannot escape fundamental governance challenges. The rise of cryptogatekeepers suggests that some level of reintermediation is inevitable and necessary to balance decentralization with investor protection and market integrity.
Decentralized autonomous organizations (DAOs) crowdfunds to invest in various projects. The decentralization feature of DAOs submits that decision-making is a collective democratic action of all DAO members. The autonomy feature of DAOs suggests that decision-making is an algorithmic process governed by self-executing smart contracts. However, in reality, DAOs are neither perfectly decentralized nor completely autonomous. Our empirical analysis shows that deviations from the ideals of decentralization and autonomy are costly. Non-algorithmic off-chain voting governance of decision-making leads to a substantial discount in DAO value. Non-decentralized aspects such as large voting coalitions also affect DAO value. Interaction effects are also shown. The study implies that platform governance design choices are crucial for DAO success. • DAOs with off-chain voting raise 87% less funding. • Larger communities worsen the valuation hit from off-chain voting. • Big voting coalitions deepen off-chain governance drawbacks. • On-chain transparency is key to DAO success—especially in large technical teams.
This article examines how “brandless by design” strategies in Web3, particularly among digital nomads and creators of non-fungible tokens (NFTs), reshape consumer behavior, market intermediation, and governance. Using a structured thematic synthesis of interdisciplinary academic and gray literature, we integrate five analytical lenses: affordances (provenance, programmability, composability, and token-gated access), signaling (credibility through on-chain histories and disclosures), consumer identity (the extended self in digital ownership and display), parasocial interaction (attachment without human embodiment), and governance (smart contract terms, platform policies, and community charters). Three primary themes emerge. First, creative autonomy and disintermediation, as NFTs enable direct creator-to-consumer exchange and programmable provenance. Second, engagement and authenticity, as communities cohere around transparent access and shared utility rather than traditional brand logos. Third, sustainability and decentralization, which highlight tensions around environmental impact, intellectual property, cultural legitimacy, and consumer protection. Cross-cutting subthemes, including parasocial credibility, accessibility and cultural sensitivity, and brand control versus co-creation, explain why brandlessness can appear simultaneously intimate and precarious. We propose a conceptual framework that links brandlessness to decentralized identity and on-chain governance, clarifying when provenance signals, token-bound permissions, and community norms substitute effectively for legacy brand cues. The review concludes with implications for practice and policy, such as standardized licenses, clear disclosures, participatory design, on-chain royalty registries, and interoperable memberships that balance value capture with oversight. Future research should prioritize cross-cultural adoption, sustainability auditing that incorporates off-chain infrastructure, and mixed-methods designs combining on-chain telemetry with ethnography and experiments to assess trust, authenticity, and wellbeing.
The article examines the evolution of venture business from its inception to contemporary trends driven by digital transformation. It outlines the key stages of development, starting from the mid-20th century and explores the influence of Web 3.0 innovations, including blockchain, decentralized finance (DeFi), and decentralized autonomous organizations (DAOs), on investment processes. The structure of venture funds is analyzed in detail, highlighting the roles of key stakeholders, funding mechanisms such as SAFE (Simple Agreement for Future Equity), SAFT (Simple Agreement for Future Tokens), and convertible notes, as well as the stages of the venture lifecycle. The study emphasizes how emerging approaches to asset tokenization and the implementation of smart contracts are transforming capital management models and contributing to the globalization of venture business. Special attention is given to the legal aspects of venture investments, particularly the role of the Term Sheet in shaping deal conditions. Furthermore, the article discusses how digital technologies reshape traditional practices, facilitate cross-border investments, and enable new stakeholder collaboration. It underscores the potential of Web 3.0 to democratize access to venture capital, create innovative funding opportunities, and foster sustainable growth in the global venture ecosystem. By examining case studies and providing a comprehensive overview of current practices, the study concludes that the integration of Web 3.0 technologies is not only revolutionizing venture capital processes but also redefining the future of the investment landscape.
In the rapidly evolving landscape of GameFi, a fusion of gaming and decentralized finance (DeFi), there exists a critical need to enhance player engagement and economic interaction within gaming ecosystems. Our GameFi ecosystem aims to fundamentally transform this landscape by integrating advanced embodied AI agents into GameFi platforms. These AI agents, developed using cutting-edge large language models (LLMs), such as GPT-4 and Claude AI, are capable of proactive, adaptive, and contextually rich interactions with players. By going beyond traditional scripted responses, these agents become integral participants in the game's narrative and economic systems, directly influencing player strategies and in-game economies. We address the limitations of current GameFi platforms, which often lack immersive AI interactions and mechanisms for community engagement or creator monetization. Through the deep integration of AI agents with blockchain technology, we establish a consensus-driven, decentralized GameFi ecosystem. This ecosystem empowers creators to monetize their contributions and fosters democratic collaboration among players and creators. Furthermore, by embedding DeFi mechanisms into the gaming experience, we enhance economic participation and provide new opportunities for financial interactions within the game. Our approach enhances player immersion and retention and advances the GameFi ecosystem by bridging traditional gaming with Web3 technologies. By integrating sophisticated AI and DeFi elements, we contribute to the development of more engaging, economically robust, and community-centric gaming environments. This project represents a significant advancement in the state-of-the-art in GameFi, offering insights and methodologies that can be applied throughout the gaming industry.
Abstract Initial coin offerings (ICOs) have emerged as a new form of digital and decentralized finance. They have the potential to disrupt conventional finance sources and expand capital-raising alternatives. However, their decentralized nature, lack of regulation, and market complexity, along with fraud events, have led to a crisis of trust. This crisis jeopardizes firms' fundraising success. This study examines the role of specialized venture capitalists (VCs) in overcoming transparency issues and restoring trust in the market and ICO issuers. Based on data from 191 ICOs, our results show that VC-backed firms have higher ICO success. This success is more pronounced for firms affiliated with VCs specializing in blockchain technologies, especially if ICO issuers are opaque and riskier. Specialist VC affiliation leads investors to buy more tokens. This effect increases with additional affiliations with other specialized VCs. For early-stage firms with a product/service, generalist VC affiliation also plays a certification role, enhancing the probability of ICO success.
Mojtaba Eshghie, Viktor Åryd, Cyrille Artho, Martin Monperrus
Structured code differencing is the act of comparing the hierarchical structure of code via its abstract syntax tree (AST) to capture modifications. AST-based source code differencing enables tasks such as vulnerability detection and automated repair where traditional line-based differencing falls short. We introduce SoliDiffy, the first AST differencing tool for Solidity smart contracts with the ability to generate an edit script that soundly shows the structural differences between two smart-contracts using insert, delete, update, move operations. In our evaluation on 353,262 contract pairs, SoliDiffy achieved a 96.1% diffing success rate, surpassing the state-of-the-art, and produced significantly shorter edit scripts. Additional experiments on 925 real-world commits further confirmed its superiority compared to Git line-based differencing. SoliDiffy provides accurate representations of smart contract evolution even in the existence of multiple complex modifications to the source code. SoliDiffy is made publicly available at https://github.com/mojtaba-eshghie/SoliDiffy.
Dat Tien Nguyen, Dung Cam Huynh, Tran Bao Anh Nguyen
The Industrial Revolution 4.0 and modern technology have had a significant impact on Vietnam’s economy. One of the most notable developments is the emergence of blockchain technology. “Smart contracts” or “virtual contracts” have become an important term on the Blockchain platform, offering many advantages and being widely deployed in areas such as finance, business, trade, and insurance. Although smart contracts have potential benefits, businesses are still hesitant to establish them. The article employs analytical methods and synthesizes data to provide evaluative insights. Additionally, this article analyzes the concept and characteristics of smart contracts, the trend of applying smart contracts in some countries worldwide, and provides suggestions for Vietnamese businesses on how to apply smart contracts, along with notes and recommendations.
Decentralized Finance (DeFi) has revolutionized lending by replacing intermediaries with algorithm-driven liquidity pools. However, existing platforms like Aave and Compound rely on static interest rate curves and collateral requirements that struggle to adapt to rapid market changes, leading to inefficiencies in utilization and increased risks of liquidations. In this work, we propose a dynamic model of the lending market based on evolving demand and supply curves, alongside an adaptive interest rate controller that responds in real-time to shifting market conditions. Using a Recursive Least Squares algorithm, our controller tracks the external market and achieves stable utilization, while also controlling default and liquidation risk. We provide theoretical guarantees on the interest rate convergence and utilization stability of our algorithm. We establish bounds on the system's vulnerability to adversarial manipulation compared to static curves, while quantifying the trade-off between adaptivity and adversarial robustness. We propose two complementary approaches to mitigating adversarial manipulation: an algorithmic method that detects extreme demand and supply fluctuations and a market-based strategy that enhances elasticity, potentially via interest rate derivative markets. Our dynamic curve demand/supply model demonstrates a low best-fit error on Aave data, while our interest rate controller significantly outperforms static curve protocols in maintaining optimal utilization and minimizing liquidations.
Josip Zilic, Vincenzo De Maio, Shashikant Ilager, Ivona Brandić
Mobile devices offload latency-sensitive application tasks to edge servers to satisfy applications' Quality of Service (QoS) deadlines. Consequently, ensuring reliable offloading without QoS violations is challenging in distributed and unreliable edge environments. However, current edge offloading solutions are either centralized or do not adequately address challenges in distributed environments. We propose FRESCO, a fast and reliable edge offloading framework that utilizes a blockchain-based reputation system, which enhances the reliability of offloading in the distributed edge. The distributed reputation system tracks the historical performance of edge servers, while blockchain through a consensus mechanism ensures that sensitive reputation information is secured against tampering. However, blockchain consensus typically has high latency, and therefore we employ a Hybrid Smart Contract (HSC) that automatically computes and stores reputation securely on-chain (i.e., on the blockchain) while allowing fast offloading decisions off-chain (i.e., outside of blockchain). The offloading decision engine uses a reputation score to derive fast offloading decisions, which are based on Satisfiability Modulo Theory (SMT). The SMT models edge resource constraints, and QoS deadlines, and can formally guarantee a feasible solution that is valuable for latency-sensitive applications that require high reliability. With a combination of on-chain HSC reputation state management and an off-chain SMT decision engine, FRESCO offloads tasks to reliable servers without being hindered by blockchain consensus. We evaluate FRESCO against real availability traces and simulated applications. FRESCO reduces response time by up to 7.86 times and saves energy by up to 5.4% compared to all baselines while minimizing QoS violations to 0.4% and achieving an average decision time of 5.05 milliseconds.
Abstract State-of-the-art macroeconomic agent-based models (ABMs) include an increasing level of detail in the energy sector. However, the possible financing mechanisms of renewable energy are rarely considered. In this study, an investment model for power plants is conceptualized, in which energy investors interact in an imperfect and decentralized market network for credits, deposits and project equity. Agents engage in new power plant investments either through a special purpose vehicle in a project finance (PF) structure or via standard corporate finance (CF). The model portrays the growth of new power generation capacity, taking into account technological differences and investment risks associated with the power market. Different scenarios are contrasted to investigate the influence of PF investments on the transition. Further, the effectiveness of a simple green credit easing (GCE) mechanism is discussed. The results show that varying the composition of the PF and CF strategies significantly influences the transition speed. GCE can recover the pace of the transition, even under drastic reductions in PF. The model serves as a foundational framework for more in-depth policy analysis within larger agent-based integrated assessment models.
Hala S. Omar, Tamer O. Diab, Wageda I. El sobky, M. A. Elsisy
Abstract This paper presents how smart contracts are based on mathematics. Smart contracts rely on mathematics to guarantee their immutability, security, and enforceability. Cryptographic procedures that are used to safeguard and confirm the contract’s implementation, including hash functions and digital signatures, might be used to illustrate this. Mathematical approaches known as hash functions embrace an input of arbitrary size and generate a fixed-size digest or hash. It is impossible to go backwards the process and ascertain the input from the outcome since the outcome is specific to the input. Digital signature techniques are used for digitally signing smart contracts. The most well-known digital signature schemes—Schnorr, Elgamal, and Elliptic curve schemes—that are employed in smart contracts are described in this research.
Pierluigi Martino, Tom Vanacker, Igor Filatotchev, Cristiano Bellavitis
Abstract Drawing on institutional and demand-side perspectives, we investigate performance implications of (de)centralized governance modes in platform-based new ventures, and the conditions under which (de)centralization generates more value. Using a sample of 1,431 Initial Coin Offerings (ICOs), a new source of entrepreneurial finance, we find that centralization of decision-making is positively associated with platforms’ market value. Further, we consider how platform characteristics affect this relationship, finding that both the presence of an experienced Chief Technology Officer (CTO) and project transparency negatively moderate the positive relationship between centralization and market value. Thus, decentralized platforms need leaders with technical experience and project transparency to generate more value. Overall, this study provides a better understanding of the boundary conditions that increase the value of (de)centralized governance.
The research investigates cryptocurrency's function in enhancing Pakistani financial market portfolios while examining the digital asset popularity, surged as an investment choice. The analysis combines cryptocurrencies with conventional financial products to show how they affect both risk performance and risk spread capabilities. The main goal of this research is to understand if adding cryptocurrency investments produces superior returns than standard asset allocation strategies. This study intends to join the current discussion regarding digital asset adoption in emerging economies particularly Pakistan. A time period of six years extending from January 1, 2018 to December 31, 2023 contains daily financial data which includes both traditional assets and cryptocurrencies. The dataset receives preprocessing treatments which include normalization together with outlier removal and missing value imputation. The portfolio optimization process in Jupiter Notebook implements machine learning models under naïve equal weighting and maximum return and maximum Sharpe ratio and minimum variance constraints. Excel was used to run robustness checks for the analysis which demonstrated that cryptocurrency portfolios generate higher risk-adjusted performance than traditional investment collections. This research presents digital assets as a valid investment strategy component by improving portfolio diversity and overall performance while focusing specifically on the Pakistani financial market through combination of machine learning and standard financial modeling. The research enhances available scientific understanding of cryptocurrency integration in emerging market economies while failing to find sufficient existing literature on this subject matter. Succeeding studies should analyze digital asset regulatory measures and economic conditions alongside investor acceptance patterns towards crypto adoption in Pakistan. The research could benefit from additional analysis that incorporates alternative risk management approaches alongside sophisticated portfolio optimization algorithms.
Rob McLaughlin, Nir Chemaya, Dingyue Liu, Dahlia Malkhi
This paper introduces a trade ordering rule that aims to reduce intra-block price volatility in Automated Market Maker (AMM) powered decentralized exchanges. The ordering rule introduced here, Clever Look-ahead Volatility Reduction (CLVR), operates under the (common) framework in decentralized finance that allows some entities to observe trade requests before they are settled, assemble them into "blocks", and order them as they like. On AMM exchanges, asset prices are continuously and transparently updated as a result of each trade and therefore, transaction order has high financial value. CLVR aims to order transactions for traders' benefit. Our primary focus is intra-block price stability (minimizing volatility), which has two main benefits for traders: it reduces transaction failure rate and allows traders to receive closer prices to the reference price at which they submit their transactions accordingly. We show that CLVR constructs an ordering which approximately minimizes price volatility with a small computation cost and can be trivially verified externally.
This research paper delves into the intricate world of smart contract derivatives, aiming to unravel the technical intricacies and explore their applications. Smart contract derivatives represent a burgeoning intersection of blockchain technology and financial instruments, providing decentralized and automated solutions for derivative trading. The paper navigates through the complex landscape of smart contract derivatives, addressing both the technical aspects of their implementation and the diverse range of applications they unlock. Through a comprehensive review of existing literature, case studies, and real-world examples, this research aims to provide a holistic understanding of the challenges, opportunities, and implications associated with smart contract derivatives. By comprehensively addressing both the technical intricacies and practical applications of smart contract derivatives, this study contributes valuable insights into the rapidly evolving field of decentralized finance.
Michael Osinakachukwu Ezeh, Adindu Donatus Ogbu, Augusta Heavens Ikevuje, Emmanuel Paul-Emeka George
Effective contract management is critical for the energy sector, where complex agreements and regulatory requirements demand precision and oversight. Leveraging technology for improved contract management can transform how energy companies manage their contracts, enhancing efficiency, compliance, and strategic alignment. This paper explores the impact of technological advancements on contract management processes in the energy sector, emphasizing digital solutions and automation. The energy sector deals with multifaceted contracts involving various stakeholders, including suppliers, contractors, regulatory bodies, and customers. Traditional contract management methods, often characterized by manual processes and paper-based documentation, are prone to errors, delays, and inefficiencies. Technology, particularly contract lifecycle management (CLM) software, offers comprehensive solutions to these challenges by digitizing and automating contract management processes. CLM software facilitates the entire contract lifecycle, from drafting and negotiation to execution and renewal. These platforms provide centralized repositories for all contract documents, ensuring easy access and retrieval. Advanced features such as automated alerts and notifications for key dates and obligations help companies stay compliant with contractual and regulatory requirements, reducing the risk of penalties and legal disputes. Moreover, artificial intelligence (AI) and machine learning (ML) capabilities integrated into CLM solutions enable intelligent contract analysis and risk assessment. AI-driven tools can extract critical data from contracts, identify potential risks, and suggest mitigative actions. This predictive insight enhances decision-making, allowing energy companies to proactively address issues before they escalate. Blockchain technology also holds significant potential for contract management in the energy sector. Smart contracts, enabled by blockchain, offer a secure and transparent way to automate contractual obligations. These self-executing contracts reduce the need for intermediaries and enhance trust among parties, ensuring that terms are met efficiently and without dispute. In addition to these technologies, cloud-based platforms offer scalability and flexibility, allowing energy companies to manage contracts remotely and collaboratively. This is particularly beneficial in an industry where projects span multiple locations and jurisdictions. In conclusion, leveraging technology for contract management in the energy sector results in streamlined processes, improved compliance, and enhanced strategic alignment. By adopting digital solutions and automation, energy companies can mitigate risks, reduce costs, and drive operational efficiency, ultimately contributing to their sustainability and competitiveness in a rapidly evolving market. Keywords: Leveraging, Technology, Energy Sector, Contract Management, Improved.
As the non-fungible token (NFT) market flourishes, price prediction emerges as a pivotal direction for investors gaining valuable insight to maximize returns. However, existing works suffer from a lack of practical definitions and standardized evaluations, limiting their practical application. Moreover, the influence of users' multi-behaviour transactions that are publicly accessible on NFT price is still not explored and exhibits challenges. In this paper, we address these gaps by presenting a practical and hierarchical problem definition. This approach unifies both collection-level and token-level task and evaluation methods, which cater to varied practical requirements of investors. To further understand the impact of user behaviours on the variation of NFT price, we propose a general wallet profiling framework and develop a COmmunity enhanced Multi-bEhavior Transaction graph model, named COMET. COMET profiles wallets with a comprehensive view and considers the impact of diverse relations and interactions within the NFT ecosystem on NFT price variations, thereby improving prediction performance. Extensive experiments conducted in our deployed system demonstrate the superiority of COMET, underscoring its potential in the insight toolkit for NFT investors.
This systematic literature review explores the role of smart contracts in improving data sharing for drug development, with an emphasis on security and transparency. Using blockchain technology, smart contracts offer a decentralized tracking mechanism for pharmaceutical supply chains, addressing challenges related to drug authentication and supply chain optimization. The review examined 52 studies using the PRISMA methodology, highlighting the automation of data exchange, reduced reliance on external parties, and acceleration of operational processes. Advanced encryption and strict access controls in smart contracts strengthen data security, ensuring patient confidentiality and compliance with medical data regulations. Despite technical and regulatory barriers, smart contracts promise significant improvements in operational efficiency, transparency, and collaboration among stakeholders in drug development. This study emphasizes the need for standardized protocols, further empirical research, and strategic implementation to fully leverage the potential of smart contracts in the pharmaceutical industry. Integration of these technologies can accelerate clinical trials and improve data reliability, thereby enhancing the safety and effectiveness of the drug development process.