This paper explores stability, volatility and structural change in Bitcoin using an Archive Framework that distinguishes between normal ("Archive") and abnormal ("Evental") market states. Using more than eleven years of daily Bitcoin data, the study investigates whether measures of structural tension help explain periods of market instability. While most predictive relationships prove weak after correcting for methodological bias, the analysis identifies a significant shift in Bitcoin's behaviour during the post-ETF era, characterised by lower realised volatility and substantially greater occupancy of structurally stable market states. The findings suggest that the principal value of the Archive Framework may lie in describing market regimes rather than predicting them.
Purpose To analyze shock transmission, shock absorption and systemic interconnectedness in decentralized cryptocurrency markets by examining how structural differences across cryptocurrency subcategories (green, energy and Bitcoin Gold) influence contagion dynamics and network resilience. Design/methodology/approach This study employs an R-squared decomposed connectedness approach to investigate contemporaneous and lagged spillovers among eight cryptocurrencies that have been classified as green (Cardano, XRP, Polygon and Stellar), energy-centric (Powerledger, Electrify Asia and Sun Contract) and Bitcoin Gold for the period ranging from December 31, 2019 to July 22, 2024. It evaluates directional shock transmission (“TO”), shock absorption (“FROM”) and net connectedness to identify the role of individual assets as transmitters and receivers within the network. Additionally, hedge ratios and portfolio weights are calculated to offer insights into diversification potential and hedging effectiveness across cryptocurrency subcategories. Findings The findings indicate a high degree of systemic interconnectedness among closely linked decentralized networks. Contemporaneous connectedness is more pronounced than lagged connectedness, indicating rapid information diffusion within cryptocurrency platforms. Network diffusion analysis identifies Stellar and Cardano as net transmitters (sneezers), and Sun Contract and Electrify Asia as net receivers (catchers), exhibiting systemic risk elevation and diversification capabilities, respectively. Originality/value This study contributes to Information Systems research by integrating digital contagion theory and a socio-technical perspective into the empirical analysis of cryptocurrency platforms. It introduces network-based decomposition of connectedness to differentiate between immediate and persistent contagion and offers one of the initial empirical analyses of heterogeneity across cryptocurrency subcategories. This study connects infrastructure design with contagion dynamics and provides innovative perspectives on governance-by-design, network resilience and systemic vulnerabilities in developing a digital ecosystem.
This article develops a finance-oriented conceptual assessment of Sui, an object-centric Layer-1 blockchain. The analysis draws on peer-reviewed research on scalability, smart contract execution, tokenomics, decentralized finance risk, market microstructure, sustainability, and regulation. It also uses a limited set of Sui-specific academic and official technical sources to interpret protocol design. The review focuses on three features: an object-centric state model that can support parallel execution when transaction states remain sufficiently partitioned; the Move language, which uses resource-oriented semantics to constrain selected asset-handling risks; and a directed acyclic graph-based consensus pipeline intended to reduce unnecessary coordination for suitable workloads. These features are linked to finance-relevant outcomes, including execution reliability, liquidity formation, adoption persistence, market resilience, and institutional investability. The assessment remains conditional. Shared-object contention may weaken realized performance, composability may preserve important classes of smart contract risk, and token emissions may dilute the value created by ecosystem growth. Regulatory uncertainty and sustainability scrutiny also influence the institutional perimeter of the asset. The article contributes an evaluation matrix, a conceptual framework, and a set of propositions for future empirical testing. No causal or statistical inference is claimed. The central conclusion is that Sui's architecture is economically relevant only when technical performance, assurance capacity, tokenomics discipline, and institutional conditions develop together. Received: 14 April 2026 | Revised: 8 July 2026 | Accepted: 27 July 2026 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Low Jun Yan: Conceptualization, Methodology, Formal analysis, Investigation, Writing – original draft. Md Sharif Hassan: Methodology, Validation, Writing – review & editing, Supervision, Project administration. Nguyen Mai: Resources, Writing – original draft, Visualization.
This study investigates whether cryptocurrency adoption has affected Argentina’s bilateral trade flows within a gravity-model framework. While blockchain-based technologies are often expected to reduce transaction costs and facilitate international trade, quantitative evidence on their actual impact remains limited. Using panel data on Argentina’s trade with its main partners, the analysis combines standard gravity variables with country-level measures of cryptocurrency activity and estimates fixed effects, random effects, and high-dimensional fixed effects models.The results confirm the continued relevance of traditional trade determinants. Distance shows a robust negative effect on bilateral trade, with an elasticity ranging from −0.54 to −1.65 (p<0.05) across specifications. Country contiguity is associated with a 3.5-fold increase in bilateral trade (coefficient: +1.25, p<0.01). The effect of cryptocurrency adoption, by contrast, varies across specifications: in the random effects model, it is negatively associated with formal trade (−0.049, p<0.01), while in the correctly specified PPML model with origin-destination-year fixed effects, the contemporaneous effect is statistically insignificant. However, when cryptocurrency adoption is lagged one period, it shows a positive and highly significant association with trade (+0.061, p<0.01), suggesting that the trade-facilitating effect of crypto infrastructure may operate with a delay. We also find marginal evidence (p≈0.10) that cryptocurrency adoption attenuates the trade-reducing effect of distance. This counterintuitive result may indicate that cryptocurrency adoption substitutes for formal trade channels or reflects periods of economic instability, including the COVID-19 pandemic. However, this relationship is not robust to more demanding specifications that control for unobserved heterogeneity.Overall, the findings suggest that blockchain-based technologies have not yet translated into measurable trade-facilitating effects, partly due to limited institutional support and legal uncertainty. The paper highlights the gap between the potential benefits of blockchain for international trade and its actual adoption, emphasising the role of coordinated institutional frameworks in enabling technological diffusion.
Papers 12 and 13 establish, in prose, that the Qoin economy grows through voluntary adoption driven by a structural incentive (the double remuneration asymmetry) and a self-reinforcing network effect, and that its distributed ledger architecture protects it from institutional destruction. Both claims are narrative. Neither is modelled. This paper treats the Qoin economy as what it already is beneath the ledger’s bookkeep- ing: agents with a local Qoin balance that rises on wealth creation and falls on wealth consumption, connected by a dynamic graph recording the physical delivery of wealth between them — not a payment network in which Qoin itself moves along edges, but closer to a reaction network, in which local state changes are triggered by relationships the graph records. Node arrival is the boundary event of Paper 12; edge arrival is each completed delivery. Three results follow. First, the qualitative adoption story of Papers 12–13 is a Bass diffusion process: an ordinary differential equation with a derivable S-curve, an inflec- tion point, and two coefficients — one tied to the unconditional attribution advantage available to currently unmonetised creators, the other to the compounding profile ad- vantage of existing participants. Second, profile-based selection (Paper 3, Paper 4) is a preferential-attachment mechanism, and preferential attachment produces heavy-tailed, plausibly scale-free degree distributions — which carries a specific, testable consequence: such networks are robust to random node loss but fragile to targeted removal of high- degree hubs. This bears directly and unfavourably on the claim, made in Paper 13, that the ledger’s technical decentralisation protects the Qoin economy from institutional at- tack: the ledger and the delivery network built on top of it are different graphs, and only one of them has been shown to be attack-resistant. Third, Paper 6’s community-bounded federation is, in network terms, a modularity-preserving design choice, and modularity is precisely the structural property that bounds the damage a targeted attack on one community can do to the others. This paper is analytical throughout: closed-form and asymptotic results, not simulation or empirical calibration against real Marketplace data. That is deliberately left as the next piece of work.
Initial Coin Offerings (ICOs) have emerged as an innovative mechanism for raising capital, particularly for blockchain-based projects. However, the lack of regulatory oversight and the prevalence of low-quality information raise important questions about what truly drives ICO success. While existing literature focuses predominantly on technical and signalling variables, the role of investor decision-making remains theoretically underdeveloped and empirically underexplored. This paper addresses this gap by pursuing two objectives. First, we identify the drivers of ICO success using a probit model applied to an original sample of 535 ICOs conducted between January 2016 and May 2021. Second, we investigate investor decision-making patterns using a novel dataset of 200 active crypto-forum participants over the same period. Our results have three main findings, though with modest statistical strength than initially estimated. (I) Marketing channels are the most consistent predictor of ICO success across the sample period, clearing conventional significance thresholds only in the pooled sample (z = 1.90, p&lt;0.10), with each additional channel raising the probability of soft-cap achievement by approximately 1.0 percentage point. (II) Team presentation and video presentation show no meaningful influence on success in any period. (III) Whitepaper availability is not statistically significant even in pooled sample, reinforcing rather than qualifying its irrelevance as a predictor; the number of accepted cryptocurrency price speculation rather than project fundamentals, consistent with mood and sentiment dominating information-based decision making in ICO markets, though this finding should be read alongside the data limitations discussed in 3.B. These findings contribute to the behavioural finance literature by providing an operational definition of ‘investor mood’ and demonstrating its empirical relevance in crypto markets. We conclude that understanding investor mood is not a secondary question but a necessary complement to technical analysis of ICO success.
Tokenized representations of cash-like instruments, comprising stablecoins, tokenized money market funds, and tokenized real-world assets, are increasingly positioned as core on-chain financial infrastructure, yet empirical evidence on how these instruments behave in practice remains limited. This paper reports a comparative empirical examination of public transaction-level blockchain data, covering adoption patterns, usage dynamics, and operational characteristics across three parallel case studies: USDC (stablecoin, Circle), BENJI (tokenized money market fund, Franklin Templeton), and BUIDL (tokenized U.S. Treasury, BlackRock via Securitize). On-chain metrics covering issuance and redemption activity, transfer behavior, wallet concentration, velocity proxies, and cross-chain deployment are interpreted against a four-layer reference architecture (asset representation, control-plane governance, settlement and finality, and composability). Results reveal systematic behavioral differences aligned with product intent and governance design: stablecoins function as high-velocity settlement instruments with broad address distribution, while tokenized investment products exhibit batch-oriented issuance, low circulation intensity, and concentrated holdings consistent with institutional custody and regulatory constraints. A live-pipeline extraction for BUIDL on Ethereum over the 90-day window ending 31 January 2026 yields a holder-level Gini coefficient of 0.8706 with a bootstrap 95% confidence interval of [0.7672, 0.9208] and a top-ten concentration share of 98.96%. Cross-chain deployment expands access but preserves reliance on dominant settlement layers. These patterns constitute an evidence-based framework for evaluating tokenized finance as production-grade financial market infrastructure.
The tokenization of Real-World Assets (RWAs) represents a paradigm shift in bridging traditional financial instruments with decentralized infrastructures. However, as the market transitions from proof-of-concept to institutional scale, it faces a critical structural bottleneck: the "walled garden" liquidity crisis. Driven by stringent regulatory requirements, tokenized assets are currently deployed across fragmented, permissioned blockchain networks utilizing static, hard-coded compliance logic. This siloed architecture inherently restricts cross-chain mobility, fracturing secondary market liquidity and necessitating redundant authentication processes across jurisdictions. This paper proposes a comprehensive architectural framework to resolve the interoperability trilemma inherent in regulated digital assets. By synthesizing recent advancements in cross-chain messaging protocols and Zero-Knowledge Proofs (ZKPs), we present a model for dynamic compliance. This framework utilizes Decentralized Identifiers (DIDs) and off-chain verifiable credentials to decouple regulatory logic from underlying asset ledgers, enabling seamless asset transfer across heterogeneous blockchains without compromising privacy or jurisdictional adherence. Ultimately, this research provides a technical and regulatory roadmap for policymakers and protocol developers to foster a unified, globally liquid market for tokenized RWAs.
Because Bitcoin typically exhibits higher volatility than traditional assets, evaluating and managing its risk is essential. We estimate Bitcoin’s potential maximum drawdowns (MDDs) using Monte Carlo simulations based on a stochastic jump process and assess the likelihood of substantial declines in the coming years. Based on our results, the simulation results suggest that an MDD of at least 60% is highly probable within three to four years, while an MDD of at least 70% appears plausible within five years. Moreover, our sensitivity analysis indicates that the MDD of Bitcoin is most strongly influenced by jump intensity. These results offer critical insights for market participants seeking to analyze Bitcoin’s downside risk and formulate strategies to navigate potential market downturns.
Paying online often means sharing card details with merchants, advertising platforms, software providers, and payment processors. For freelancers, agencies, online sellers, and small teams, that can create unnecessary exposure: a compromised merchant account, an unexpected renewal, or a card number reused across several services may turn into a difficult cleanup project. A virtual card funded through a USDT top up offers another way to separate online spending from a primary bank account while keeping budgets easier to manage. This approach is not a promise of anonymity, approval, or freedom from verification. A responsible provider may still require identity checks, transaction monitoring, and information about the source of funds. The practical benefit is financial separation and control. Instead of giving every website direct access to a bank-linked card, you can use a dedicated card for approved online purchases, review the conversion terms, and keep records for accounting and compliance. Why use USDT to fund a virtual card USDT is a dollar-pegged digital asset commonly used to move value between supported wallets and platforms. When a card provider accepts USDT, it may convert the deposited amount into the card's spending balance, subject to its network, supported blockchain, confirmation requirements, fees, and compliance procedures. This can be useful for users who already hold USDT and want to pay merchants that accept ordinary card payments rather than cryptocurrency directly. The main operational advantage is separation. A dedicated virtual card can be assigned to advertising, SaaS subscriptions, supplier purchases, or a single project. If the card must be frozen or replaced, the issue may be contained to that spending channel instead of requiring changes across a personal bank account and every recurring payment connected to it. How the funding process usually works A typical flow has three stages: you create or select a card, send USDT to a deposit addre Full article attached as Markdown. Published for vccbusiness.com.
We construct the Settlement Modernisation Index, a panel dataset of 809 reform events across 24 advanced economies between 1993 and 2024, decomposed into three economic channels and three adoption phases. We document an S-curve in inside money elasticity with two interior turning points at SMI = 0.27 and 0.93, separating a liberation phase, a post-global-financial-crisis compliance valley, and a mature-infrastructure recovery phase. We show that settlement modernisation generates network-conditional balance sheet efficiencies through a T2S event-study with year-by-year EMIR decomposition (saturation beta = +0.557, p < 0.01) and an out-of-sample synthetic control null on Switzerland's post-2021 SDX deployment. Applied along the BIS three-layer connectivity taxonomy, the framework forecasts +13.4 percent efficiency recovery from the ECB's Pontes initiative over 2027-2032. Conditional UK and US accession to the Appia composability layer (2028) raises the ceiling to +37.5 percent. Balance-sheet efficiencies from atomic settlement are a property of the bilateral pair, not the node.
Fei Wu, Thomas Thiery, Stefanos Leonardos, Carmine Ventre
Block production in modern blockchains is increasingly shaped by economic gains that arise from control over transaction ordering. These gains—known as Maximal Extractable Value (MEV)—have led to concerns about centralization and market power among blockchain consensus participants. To address these concerns, Ethereum introduced Proposer-Builder Separation (PBS), in which specialized block builders compete in block building auctions to construct blocks on behalf of validators. The current implementation of PBS, MEV-Boost, mediates this competition through an open-bid first-price ascending auction, termed the MEV-Boost auction. This paper analyzes the strategic incentives of builders in MEV-Boost auctions. We develop an agent-based simulation framework and apply empirical game-theoretic analysis to study how asymmetries in network latency and access to MEV opportunities shape bidding behavior and market concentration. Our findings show that while latency differences mildly affect builder incentives, MEV opportunity access fundamentally alters equilibrium strategies: builders with privileged access to MEV opportunities bid less aggressively, maintain higher profit margins, dominate market share, and reduce proposer revenue. These effects contribute to centralization and oligopolistic outcomes in the builder market. To validate these findings, we further analyze an idealized symmetric benchmark market where builders have comparable latency and MEV access. Under such settings, the auction behaves as expected—bidding is competitive, proposer revenue is higher, and the market is more decentralized—confirming that the observed inefficiencies arise specifically from the asymmetries present in practice.
Blockchain technology, originally devised to support the peer-to-peer transfer of Bitcoin, has evolved into a multipurpose digital infrastructure with far-reaching implications for business and finance. This paper undertakes a conceptual and exploratory examination of how blockchain is reshaping financial services, corporate governance, and commercial transactions. Drawing upon secondary literature, industry reports, and case illustrations, the study investigates blockchain applications across banking, cross-border remittances, supply chain finance, trade finance, capital markets, insurance, and decentralized finance (DeFi). It also discusses the enabling features of blockchain — decentralization, immutability, transparency, and smart contracts — that differentiate it from conventional centralized systems. The paper highlights the strategic benefits accruing to firms that adopt blockchain, including reduced transaction costs, faster settlement, enhanced traceability, and improved trust among counterparties, while also identifying barriers such as regulatory ambiguity, scalability constraints, energy consumption, and limited interoperability. The discussion synthesizes findings from extant studies to present an integrated view of blockchain’s transformative potential and its practical limitations. The paper concludes that while blockchain is unlikely to replace traditional financial infrastructure entirely in the near term, its selective and hybrid adoption is poised to redefine business processes, financial intermediation, and value exchange across industries.
In this paper, we develop an open-economy macroeconomic model of a Proof-of-Stake network to analyze nominal token-price dynamics and the systemic effects of speculative capital. We first consider a network populated solely by active utility users, who finance network activity through a steady exogenous inflow of fiat currency. We prove the existence of a unique, globally asymptotically stable steady-state equilibrium with a well-defined nominal token price and derive a closed-form expression for the network's relaxation time. Calibrating the model using parameters representative of the current Ethereum network, we estimate a relaxation half-life of approximately 46 years. This extreme macroeconomic inertia implies that the token price may remain persistently displaced from its evolving steady-state benchmark, producing sustained price overshooting as the network adjusts to changing fundamentals. We then introduce an Investor class to examine the effects of passive and active speculative capital. We show that passive institutional staking compresses the native staking yield and creates a structural imbalance that systematically raises the nominal token price while shifting consensus ownership away from active utility users. Active speculative capital has a qualitatively different effect. In response to capital shocks, the Consumer class's rigid preference for fiat-denominated consumption generates an endogenous constant-value strategy. This mechanism shifts staked-token ownership from the Investor class toward active utility users, with potentially favorable implications for consensus decentralization.
Abstract -This paper introduces and develops Neutral Value Movement (NVM) — a conceptual and operational framework in which the economic value of a financial instrument is deliberately decoupled from any single settlement rail, network, or ledger technology. Under an NVM posture, the identity, legal standing, and economic attributes of a financial claim are treated as properties of the instrument itself, not of the infrastructure through which it happens to be held or transferred at any given moment. The imperative for such a framework arises from the simultaneous coexistence of legacy central securities depository infrastructure (DTCC, Euroclear, Clearstream), permissioned distributed ledger platforms (JPMorgan Kinexys, Broadridge DLR, Canton Network), emerging public chain deployments (Ethereum Layer 2 networks), and conventional payment rails (Fedwire, SWIFT). In this fragmented landscape, the settlement of a cross-rail transaction today requires bespoke, bilateral engineering — an approach that scales neither operationally nor legally. This paper makes four principal contributions: (1) a rigorous definition of rail-agnostic settlement and its distinction from interoperability; (2) the concept of cross-chain equivalence and the Equivalence Certificate as a legal-technical construct; (3) the Canonical Digital Artifact as the foundational representational standard for multi-rail financial instruments; and (4) a Multi-Rail Governance Stack with
As cryptocurrency is increasingly adopted, regulators must consider whether regulations are needed to protect investors and consumers. In prior research involving a behavioral experiment, we identified the existence of a face value effect when people use cryptocurrency in transactions. Just as prior researchers have found a face value effect when people use foreign cryptocurrency,we found a face value effect with the use of cryptocurrency. People predictably anchor on the nominal amount indicated by the cryptocurrency and fail to accurately convert the amount into their home currency. This cognitive bias results in significant overspending when the cryptocurrency is stronger than the U.S. dollar (USD). This Article examined whether different interventions could reduce this cognitive bias. Based on the results of another behavioral experiment we conducted, we found two interventions did so. First, when prices for a transaction are displayed in both USD and cryptocurrency values, the face value effect and overspending were mitigated. Second, in situations involving bidding on an item with no fixed price, requiring people to write out their bid or payment in USD before bidding in cryptocurrency was even more effective in reducing the face value effect and overspending. Accordingly, we propose the adoption of (1) domestic currency pricing (DCP) for items sold in cryptocurrency that requires the corresponding USD amount to be included for any price in cryptocurrency; and (2) for bidding on items in cryptocurrency, a simple requirement for people to “type out the price” of their bid first in USD, or the “TOP price” for short. These interventions are modest, but they may help reduce unintended overspending due to the face value effect.
V Vishnu Prasad, Meta Dev Prasad Murthy, Rishika Jain
Premium non-fungible token (NFT) collections often fail to attract liquidity, while modest but coherent ones thrive, presenting an anomaly that classical signaling cannot explain. We reframe market-making as a coordination problem and introduce a Brand × Topology × Dispersion (BTD) framework, arguing that participation follows weakest-link clarity: the least clear signal dimension, not the average, governs action. A high-realism 2 × 2 × 2 experiment (N = 336) shows that brand capital, ownership topology, and value dispersion each raise willingness to trade, yet the minimum across them dominates conversion; discordant signals depress engagement more than concordant signals lift it; and signals act as complements in thin markets but substitutes in mature ones. A 6-month Ethereum panel, analyzed with fractional logit and Cox hazard models, replicates these patterns in the field. The studies extend signaling theory from dyadic quality revelation to multilateral coordination and yield a bottleneck-governance principle for marketers and platforms, suggesting that the weakest clarity dimension be repaired first.
Цифровая трансформация страховой отрасли и внедрение продуктов параметрического страхования требуют пересмотра подходов к обеспечению доверия между участниками сделки. Ключевым вызовом становится выбор архитектуры доверенной третьей стороны, которая могла бы гарантировать не только юридическую значимость транзакций, но и их защищенность в условиях растущих угроз. Существующие централизованные модели, доказавшие эффективность в массовом сегменте, часто не отвечают требованиям прозрачности и безопасности, критически важным для крупных сделок перестрахования и рынков связанного со страхованием капитала. Целью работы является сравнительный анализ трех архитектурных подходов к построению доверенной третьей стороны: традиционной централизованной на базе инфраструктуры открытых ключей, децентрализованной на базе блокчейна и гибридной. Для объективизации выбора применяется двухэтапная методика системного анализа: метод главных компонент для снижения размерности и визуализации компромиссов, а также многокритериальный анализ решений для ранжирования архитектур. Особое внимание уделено теоретическим ограничениям распределенных систем («трилемма блокчейна», «проблема оракула»), моделированию векторов атак и стратегиям их минимизации. Источником данных послужили экспертные оценки, полученные методом «Дельфи». Исследование показало, что архитектура на базе блокчейна является оптимальной для задач перестрахования благодаря высокой скорости мобилизации ликвидности. В то же время для массового розничного сегмента экономически наиболее эффективной остается централизованная модель. Обоснована необходимость перехода к гибридным архитектурам, использующим криптографические доказательства с нулевым разглашением и доверенные среды исполнения. Такой подход позволяет сочетать высокую пропускную способность с проверяемой безопасностью, что подтверждается опытом реализации национальных цифровых валют, в частности, цифрового The digital transformation of the insurance industry and the introduction of parametric insurance products require a rethinking of approaches to ensuring trust between transaction parties. A key challenge is choosing a trusted third party architecture that can guarantee not only the legal validity of transactions but also their security in the face of growing threats. Existing centralized models, while proven effective in the mass market, often fail to meet the transparency and security requirements critical for large-scale reinsurance transactions and insurance-linked capital markets. This paper aims to comparatively analyze three architectural approaches to building trusted third parties: a traditional centralized approach based on a public key infrastructure, a decentralized approach based on a blockchain, and a hybrid approach. To objectively evaluate the choice, a two-stage system analysis method is applied: principal component analysis for dimensionality reduction and tradeoff visualization, and multicriteria decision analysis for ranking architectures. Particular attention is paid to the theoretical limitations of distributed systems (the "blockchain trilemma" and "oracle problem"), attack vector modeling, and mitigation strategies. The data source was expert assessments obtained using the Delphi method. The study showed that a blockchain-based architecture is optimal for reinsurance applications due to its high liquidity mobilization speed. However, for the mass retail segment, a centralized model remains the most cost-effective. The study substantiates the need to transition to hybrid architectures using zero-knowledge cryptographic proofs and trusted execution environments. This approach combines high throughput with verifiable security, as evidenced by the experience of implementing national digital currencies, in particular, the Bank of Russia's digital ruble.
Crypto's dominant narrative—tokenizing treasuries, equities, and lending products—cedes value to incumbents who will treat any blockchain as a replaceable backend. The real opportunity is alternative markets: economic coordination problems that Wall Street structurally cannot or will not solve. We catalog 50 alternative markets across six categories, identify the ~20 that are genuinely blockchain-necessary, and estimate $200B–$1T in new annual GDP (0.2–1.0% of global output). We then argue that Ethereum will not pursue these markets—its ecosystem is structurally captured by the tokenization narrative, as evidenced by the shutdown of pioneering projects like Goldfinch and a broader exodus of builders from the ecosystem. We propose that a purpose-built, privacy-native blockchain is the correct vehicle, and lay out the architecture, cold-start sequencing, and talent recruitment strategy to build it.
Artificial intelligence (AI) and blockchain are two of the most transformative technologies of our time, each facing distinct challenges. Blockchain struggles with scalability and efficiency, while AI depends on the integrity of the data it consumes. Yet their proximity in the data value chain enables them to complement one another: AI can optimize blockchain systems through fraud detection, smart contract auditing, or enhanced analytics, while blockchain provides AI with secure, verifiable data crucial for accuracy. The technological convergence of AI and blockchain already reshapes industries such as supply chain management, finance, healthcare, energy, and intellectual property. Emerging solutions—ranging from decentralized data infrastructures to autonomous AI agents—illustrate the growing importance of this technological synergy. Companies implementing AI–blockchain solutions demonstrate enhanced performance, new data monetization opportunities, and even revenue growth. However, convergence raises challenges such as interoperability, reliance on trusted oracles, decentralized data inefficiencies, or regulatory uncertainty. This chapter builds on theories of technological convergence and disruptive innovation to assess the potential of AI–blockchain integration. Drawing on case studies and expert insights, it provides practical frameworks and roadmaps for decision-makers aiming to leverage this convergence as a driver of the next wave of digital transformation.
This working paper introduces selected findings from Flow Extraction Theory (FET), an independent research program studying economic-state representation in decentralized financial systems. The paper argues that event history is not equivalent to state, and that observed pressure is not equivalent to explained pressure. Using a bounded Aave V3 case study at Ethereum block 20,000,000, the paper distinguishes historical event evidence, frozen protocol state, token-level representation, account-level aggregate outputs, inference, and unknowns. The study shows that event-derived reconstruction can disagree with exact frozen state, and that health-factor distance can be observed with high confidence while the evidence required to explain that distance remains incomplete. The paper introduces representation risk as the risk created when different evidence classes are collapsed into one operational view of “state.” This public version summarizes selected findings only. It does not disclose implementation details, private tooling, execution logic, complete artifacts, or trading signals.