Matteo Loporchio, Damiano Di Francesco Maesa, Anna Bernasconi, Laura Ricci
Abstract The ERC-1155 standard introduced on the Ethereum blockchain allows for managing multiple tokens, both fungible and non-fungible, within a single contract. It also supports batch transfers, thereby reducing transaction costs and enabling a more efficient use of blockchain resources. To assess its impact and level of adoption, this paper presents a comprehensive analysis of the ERC-1155 token ecosystem. First, we examine the activity of ERC-1155 contracts and compare the evolution of transfer volumes with those of the two alternative most popular token management standards. Next, we model the economy of each ERC-1155 contract as a directed graph, where nodes represent users and edges denote token transfers. We then study the topological properties of such graphs, analyzing approximately 40,000 networks until the end of 2024. Results indicate that, within our dataset, the adoption of ERC-1155 is growing, although its functionalities are not being fully utilized. Additionally, about 60% of the networks exhibit a completely centralized topology, while the remaining ones are generally sparse and lack small-world characteristics. Finally, the degree distribution analysis shows that preferential attachment is only present in a minority of the networks and the graphs also display a mild disassortative behavior.
This paper examines the directional connectedness between the returns of Bitcoin and Ethereum and the supply of stablecoins across different market conditions. Using a Quantile Vector Autoregression (QVAR) model, we analyze daily log-returns of major cryptocurrencies and changes in stablecoin supply from January 2021 to November 2024, capturing dynamics at the 5th, 50th, and 95th quantiles. Our findings show that the Total Connectedness Index (TCI) nearly triples under extreme conditions, with Bitcoin and Ethereum transitioning from passive roles in normal periods to dominant transmitters of influence during downturns. Stablecoins behave heterogeneously across regimes, with roles varying significantly even within the same subclass. Tether exhibits state-dependent behavior, acting as a net receiver of shocks in most conditions but emerging as a transmitter during bull markets. We also assessed the impact of the Terra-LUNA collapse, revealing a regime shift in the transmission of shocks: connectedness rises under normal and negative conditions but declines in positive markets. These patterns suggest that, under certain conditions, major cryptocurrencies can influence stablecoin issuance in distinct ways, leading to asymmetric adjustments in supply across individual stablecoins and shaping liquidity dynamics throughout the ecosystem. While we do not attempt to model the underlying mechanisms behind these shifts, our results point to the importance of monitoring state-dependent relationships and recognizing the diverse behaviors of stablecoins. The findings motivate the development of regime-sensitive monitoring tools and support ongoing policy discussions around stablecoin design, issuance frameworks, and market transparency.
This dissertation explores how entrepreneurial and policy decisions shape the performance of decentralized digital platforms (DDPs). It shows that token governance affects fundraising success, public listings catalyze user growth and engagement by amplifying network effects, and global regulations shape token risk-return profiles. The findings highlight the need for regulatory clarity and careful market entry strategies by entrepreneurs.
Bitcoin Ordinals and inscriptions facilitate the on-chain storage of arbitrary data on the Bitcoin blockchain. In this study, we analyse the impact of inscriptions on the Bitcoin network. We find that inscriptions have significantly increased network activity, created additional demand for blockspace, and influenced Bitcoin’s fee market dynamics. Furthermore, we find that the rise of inscriptions coincided with an increased utilisation of Taproot, a notable increase in block size, and the longest sustained period of high blockspace utilisation in Bitcoin’s history. Our study shows that inscriptions have reshaped how Bitcoin’s blockchain is utilised and underscores the growing number of use cases beyond its original function as a peer-to-peer financial network.
Bitcoin derivatives trading regularly exceeds $200 billion daily, yet participants must trust centralized exchanges-the same exchanges that have repeatedly failed, from BitMEX's regulatory crisis in 2020 to FTX's collapse in 2022. This paper provides the first comparative analysis of three approaches that enable long/short Bitcoin exposure without exchange custody: Discreet Log Contracts (DLCs), Stable Channels, and Stablesats (included as a custodial comparison). Each mechanism allows two parties to take opposite sides of BTC/USD price movements-one hedging (short), one speculating (leveraged long)-settled entirely in Bitcoin. We analyze the mechanism design, trust assumptions, and trade-offs of each approach. These are not stablecoins; they are bilateral derivatives contracts. They sacrifice liquidity and convenience-the cost of trustlessness-serving participants unwilling to accept exchange counterparty risk.
Francis Chigozie Emmanuel, Ogaziechi Tobechi Anold, Obidinma Christian Alozie, Ikenna Tonna Adiele
The global freelance economy has experienced rapid growth, yet existing payment and escrow systems remain constrained by structural inefficiencies inherent in both centralized fiat-based and decentralized cryptocurrency-based models. Centralized escrow systems, while widely adopted due to their regulatory compliance and usability, suffer from custodial opacity, information asymmetry, high transaction costs, and limited verifiability. Conversely, purely decentralized blockchain-based escrow systems offer transparency and trust-minimized execution through smart contracts but face barriers including cryptocurrency price volatility, limited fiat integration, steep technical learning curves, and inadequate dispute resolution mechanisms for subjective deliverables. This article, a hybrid escrow system integrates traditional fiat payment infrastructure with decentralized Ethereum-compatible smart contract execution. The system adopts a three-layer architecture comprising a centralized service layer, a middleware synchronization layer, and a decentralized execution layer. A Finite State Machine (FSM) model governs escrow state transitions across both fiat-funded and cryptocurrency-funded transactions, ensuring determinism, auditability, and consistency. The system further incorporates a human-in-the-loop dispute resolution framework anchored to blockchain execution, enabling fair and transparent adjudication of subjective conflicts. Evaluation results demonstrate that the proposed hybrid architecture successfully bridges the gap between traditional finance and decentralized systems. The system achieved 100% correct FSM state enforcement with zero unauthorized fund releases across all test scenarios. Fiat-funded contracts were synchronized to the blockchain with an average latency of 8.4 seconds, while cryptocurrency-funded contracts confirmed on-chain within a median of 3.2 seconds on the Polygon testnet. All three dispute resolution outcomes were correctly enforced on-chain within an average of 5.1 seconds following adjudication, and API response times remained below 420 milliseconds under concurrent user loads. An ablation study further confirmed that all three architectural layers are individually necessary, as removing any single layer degraded transparency, payment flexibility, dispute resolution capability, or user accessibility. This research contributes a scalable and adaptable hybrid escrow blueprint applicable to fintech development, digital labour platforms, and cross-border payment systems.
Why does a market structure built on radical transparency paradoxically foster the proliferation of low-quality assets? Open-source crypto markets make information public but not necessarily usable. We develop a model in which investors allocate scarce attention before deciding whether to verify project quality. Technical complexity reduces the informativeness of processed public disclosure, while narrative assets can build salience through attention feedback. As a result, complex projects may fail to enter the verification set even when they would be valuable conditional on evaluation. Financing then falls because visibility expands market reach but only screened projects convert attention into capital. The model delivers a transparency paradox: more public information need not improve allocation when investors cannot process it at scale. Low-dimensional narrative assets can crowd out high-quality innovation, generating a complexity trap. The results imply that disclosure policy may be ineffective when it increases information volume without improving processability. Market regulation requires disclosure to be standardized, machine-readable, and certifiable, so that public information can be converted into valuation-relevant signals.
This paper studies whether fast-settlement payment layers can replace secure baselayer blockchains in a search-theoretic monetary model. The Chain provides secure but costly and probabilistic settlement, while the Network provides instant, cost-free payments but exposes users to cyberattacks and requires sellers to incur adoption costs. In the Chain-only benchmark, buyers choose settlement intensity after bargaining. Because they do not internalize the full trade surplus, settlement intensity is inefficiently low, reducing trade efficiency and weakening the monetary value of tokens. Introducing the Network generates multiple payment equilibria. Under exogenous cyberattack risk, Chain and Network payments may coexist: the Network provides fast settlement and fallback liquidity when Chain settlement fails, while the Chain remains valuable for its security and universal acceptance. If cyberattack risk is sufficiently low, pure Network payments can arise, although pure Chain payments may also persist because Network acceptance is costly for sellers. When cyberattack risk is endogenous, broader Network adoption increases exposed balances and strengthens hackers’ incentives. This security externality weakens the Network’s value as fallback liquidity and eliminates the pure Network-payment equilibrium. The Chain, therefore, survives as a secure settlement anchor. The welfare analysis shows that Network adoption is not always welfare improving: its payment-efficiency gains must outweigh seller adoption costs and, under endogenous attacks, the resource costs of hacking. Fast-settlement layers can improve payment efficiency, but they do not generically replace secure base-layer settlement.
Stablecoins, cryptocurrencies engineered to maintain a stable value relative to fiat currencies, have become one of the fastest-growing segments of the digital asset ecosystem. While early research focused primarily on their role in cryptocurrency trading and decentralized finance, stablecoins are increasingly being used for real-world payments. One of the most notable developments in this transition is the emergence of stablecoin-linked payment cards, which allow consumers to spend digital dollars at traditional merchants through established card networks such as Visa and Mastercard. This paper documents the rapid growth of stablecoin card spending and examines its implications for payment infrastructure, merchant economics, consumer fee structures, and regulatory policy. Drawing on data from Artemis Analytics, industry reporting, and payment network disclosures, the analysis shows that monthly crypto-card transaction volumes expanded from approximately $100 million in early 2023 to more than $1.5 billion by late 2025, reaching an annualized spending rate exceeding $18 billion. The paper also examines how stablecoin cards alter fee dynamics for merchants and consumers, how traditional card networks have responded to blockchain-based payment instruments, and what regulatory and competitive implications may follow from continued adoption. Although still modest relative to the global payments market, the rapid expansion of stablecoin card usage suggests that stablecoins may be transitioning from speculative trading instruments into a new form of digital payment infrastructure.
Censorship resistance is widely viewed as a core attribute of distributed ledgers. Censorship resistance refers to the inability to selectively exclude technically valid but undesirable transactions from the blockchain. We examine blockchain censorship in a game-theoretic framework that allows for both primary and secondary censorship. The analysis identifies scenarios in which both inclusion and censorship equilibria can arise. Once an equilibrium with strategic secondary censorship is implemented, it may be hard to revert to inclusion: Censorship equilibria are perfectly coalition-proof if the negative impact of an undesirable transaction on block producers is sufficiently large. These results suggest an expanding role for research into methods shaping censorship resistance at the technical layer.
The rapid evolution of 5G and the growing complexity of digital services have increased the need for robust, transparent, and automated Service Level Agreement (SLA) management. Traditional management methods across different sectors like telecommunications and cloud computing frequently suffer from a lack of transparency and a heavy reliance on centralized third parties, which can lead to disputes and delayed enforcement. To address these challenges, smart contracts using blockchain technology offer a transformative solution, automating SLA execution and ensuring decentralized, tamper-proof enforcement. This paper provides a comprehensive survey and critical analysis of existing traditional SLA management systems and smart contract-based management. By studying and examining various frameworks across 5G, cloud computing, IoT, and telecommunications, we highlight common strategies, technical trade-offs, and existing gaps in current research. Through a structured classification and comparative analysis, this study offers an overview of blockchain-based SLA management current state while providing a strategic roadmap for the future of SLA representation and automated lifecycle management.
This paper introduces the SDA (Structured Digital Assets) methodology for tokenizing value creation chains — a novel approach to Real World Asset (RWA) tokenization where the object of tokenization is not a static asset but the dynamic process of economic value creation. Unlike conventional tokenization models that digitize ownership rights to existing assets, SDA treats each stage of a production chain as a separate tokenizable unit with mathematically defined value accumulation. The methodology integrates value chain theory, structured finance principles, institutional economics, and distributed ledger technology into a unified framework for engineering digital economic constructions.
Decentralized finance (DeFi) entities represent collections of smart contracts (i.e. code) that execute autonomously. Many of these protocols comprise two separate sets of smart contracts. On the operational side a protocol, say a DEX, consists of an automated market maker (AMM), which implements liquidity pools and fee mechanisms. On the governance side, protocols use decentralized DAOs to support operations with an institutional structure that includes a collective governance mechanism. A central function of smart contracts at both layers is to lock funds (i.e. crypto assets) in the ecosystem. User funds that are deposited into liquidity pools are commonly measured through the TVL metric. It captures the amount of self-custodial funds, that is, user controlled assets in a protocol. Yet, several protocols maintain a separate set of DAO-controlled funds at the governance layer, to finance development. This study takes a corporate finance perspective in classifying on-chain token holdings, exploring the relationship between cash holdings and protocol valuations in a panel vector autoregression (VAR) . The study contributes insights to the blockchain and corporate finance literature.
DEX like Uniswap v3 has gained significant attention in the blockchain industry, and understanding the driving factors behind liquidity provision is crucial for the platform’s success and adoption in the decentralized finance space. This study investigates liquidityproviders (LPs) behaviour in Uniswap v3 and their response to key events and developments,such as the EIP-1559 and the FTX collapse, to provide a comprehensive picture ofthe dynamics in the DeFi ecosystem. We explore LPs behaviour by assembling a datasetof 746,438 pool-day records associated with 2,228 Uniswap smart contracts. Two hypotheses,the ”Fee reward hypothesis” and the ”Impermanent loss avoidance hypothesis”are examined to understand LPs’ motivations and strategies. We further study the impactof EIP-1559 on liquidity provision, revealing a convergence in capital efficiency betweenlow and high-efficiency swap pools following its implementation. Last, we assess howthe FTX collapse affected trading volume, uncovering a more notable decline in tradingactivity among pools comprising exclusively of unstable coins as opposed to those withstablecoins only.
Flash loans enable uncollateralized borrowing within a single transaction, providing capital efficiency and arbitrage opportunities in decentralized finance (DeFi). However, when combined with composable protocols and reactive state changes, flash loans can induce feedback loops that amplify liquidity, manipulate pricing signals, and bypass economic safeguards. This paper defines Flash Loan Feedback Loops as recursive transaction patterns in which temporary liquidity repeatedly influences protocol state, enabling extraction of value without proportional risk exposure. We analyze structural conditions that permit such loops, demonstrate why existing mitigations are insufficient, and propose a logic-layer enforcement framework that constrains state-dependent recursion. The approach restores causal integrity between capital commitment and protocol outcomes, addressing a core systemic vulnerability in DeFi architectures.
The tokenization of real-world assets (RWAs) has emerged as one of the most consequential developments at the intersection of traditional finance and decentralized finance (DeFi). By representing ownership or economic rights in instruments such as government bonds, private credit, and real estate through blockchain-based tokens, tokenization has enabled traditional assets to be integrated into decentralized lending platforms. As these markets have matured, participants have developed increasingly sophisticated yield-enhancement strategies, among the most notable of which is leveraged looping. This recursive yield-amplification technique involves depositing tokenized RWAs as collateral, borrowing stablecoins against that collateral, and reinvesting the borrowed funds to purchase additional RWA tokens. Through successive iterations, investors create and expand leveraged exposure to the underlying asset's yield while maintaining the same initial capital. This paper examines the mechanics and economic rationale of leveraged looping strategies, analyzes the structural risks arising from the integration of traditional financial assets into decentralized financial infrastructure, and evaluates the regulatory and financial stability implications of these strategies. Particular attention is directed toward the mismatch between the continuous operation of DeFi platforms and the slower settlement, valuation, and liquidity characteristics of the underlying assets. The analysis draws on recent market data, protocol-level case studies, and relevant academic literature. The paper concludes that leveraged looping represents a technologically innovative adaptation of traditional leverage and carry-trade strategies but may introduce new forms of systemic risk if liquidity constraints and valuation opacity are not adequately addressed by market participants and regulators.
Reinganum (1986) argued informally that inexpensive time travel would drive nominal interest rates to zero. We formalise that claim in a dated-commodity model built on a Lewisian distinction between calendar time and personal time. Costless two-way transport of dollars across dates makes dated dollars technologically interchangeable, so the law of one price implies a zero nominal risk-free rate. The same logic does not carry over unchanged to native on-chain Bitcoin. A Bitcoin position is a holder-relative control claim over a specific unspent transaction output (UTXO) in the realised blockchain history. A valid dates immediate control claim requires the output already to exist in the dates chain prefix, to be unspent there, and to satisfy all applicable script, witness, timelock, and maturity conditions. Future-created outputs cannot generally be transported backwards. Same-date substitution into older outputs is history-dependent and capacity-constrained; exercise changes the single realised history rather than creating duplicate purchasing power. We define a Bitcoin-denominated zero-coupon claim as a promise of generic native settlement at a later date and give a two-date no-arbitrage counterexample with a non-zero Bitcoin-denominated interest rate. The substantive Bitcoin result is an incompatibility result: no single native on-chain Bitcoin object is simultaneously generic across outputs, immediately exercisable as native settlement, and universally transportable across calendar dates. A restricted same-output law of one price survives for dormant control bundles over already-existing outputs, but that result is too narrow to force Bitcoin-denominated rates to zero in general.
We present evidence that Bitcoin functions, at least in significant part, as a specialized store of value, and that its economic value is statistically related to monetary dilution. Data indicate that Bitcoin’s long-run price tracks the annual expansion of U.S. dollar money supply relative to Bitcoin’s implied market capitalization, a relationship reinforced by Bitcoin’s fixed-supply protocol design. The relationship is statistically significant across the sample tested, though the sample remains limited and the findings should be read as evidence supporting this thesis rather than as proof of it; further data and out-of-sample testing are needed. Backtested against annual year-end prices over the primary 2013–2024 sample, the model yields Pearson r = 0.896 and R² = 0.803 (log₁₀ basis), with all twelve primary-sample years within one order of magnitude of the model price. Directional accuracy is encouraging at 63.6% (7 of 11 transitions), below a simple always-positive benchmark. Beyond its statistical performance, the model has four important implications. First, Bitcoin possesses a quantitative, testable valuation framework: its price tracks the relationship between fiat monetary creation and the capacity of a fixed-supply asset to absorb reallocation demand. This supports the view that Bitcoin’s value is linked to a meaningful extent to monetary dilution. Second, as the empirical record deepens across additional monetary expansion and contraction regimes, confidence in the model’s predictive value should strengthen; each additional annual observation, and further out-of-sample testing, will add evidence one way or the other. Third, broad adoption of a shared pricing model may contribute to reducing Bitcoin’s price volatility over time, consistent with the pattern observed as other asset classes have matured around shared valuation conventions, though this market-structure effect remains a hypothesis rather than a demonstrated result. Finally, the analysis indicates that Bitcoin has shown a stronger relationship to U.S. M2 growth than gold under the methodology tested.
This study explores trade surveillance models especially for wash trading and off-market pricing. These are few fraud behavior patterns that cause persistent threat to market integrity in traditional equity markets, cryptocurrency exchanges and decentralized non-fungible token (NFT) ecosystems. Although there is growing regulatory attention but there is less improvement in the current surveillance systems and remain fragmented and inconsistent in their ability to uncover manipulative behavior for different market structures. This paper summarizes findings electronic copy available at: https://ssrn.com from three peer-reviewed empirical studies to evaluate the effectiveness of current trade surveillance models and proposes an integrated detection framework that combines graph-based network analysis, econometric modeling, machine learning classifiers, and blockchain transparency tools. These reviewed literatures all together demonstrate that: (1) directed graph algorithms achieve more than 95% detection accuracy for collusive wash-trading patterns in traditional regulated markets; (2) around 70% of reported trading volume on certain cryptocurrency platforms is fabricated using coordinated self-transactions; and (3) AI-assisted blockchain analytics can identify wash-trading loops in decentralized NFT markets with more than 95% precision. Researching and studying these findings, this paper proposes a unified, AI driven surveillance architecture integrating real-time graph traversal, cross-exchange auditing, and blockchain forensic analysis. The framework designed to improve detection speed, reduce false positives, and support regulatory enforcement for both centralized and decentralized financial environments. Paper discusses the implications for regulatory policy, financial compliance infrastructure, and future surveillance system design.