We study the demand for safety and liquidity in the crypto ecosystem. In an environment lacking frictionless access to traditional safe assets, we examine whether stablecoin lending pools provide liquidity services to investors. To do so, we develop a model in which a representative investor allocates liquidity between stablecoin lending pool deposits and traditional safe assets (e.g., MMF shares). The model delivers three predictions: (i) the stablecoin premium co-moves positively with the Treasury premium when investors value liquidity services of stablecoin pools, (ii) Treasury supply decreases the stablecoin premium, and (iii) declines in the perceived liquidity of stablecoin pools --- e.g., due to de-pegs or hacker attacks --- reduce their premium. Our empirical results provide evidence consistent with these predictions. They suggest that investors treat stablecoin lending pools as money-like instruments and that shocks to traditional safe assets transmit to crypto markets. Our findings contribute to the literature on safe assets by showing how safety is intermediated in crypto markets. They also offer new insights into the segmentation and structure of decentralized finance (DeFi) as it evolves alongside traditional financial systems.
This paper examines how the rapid growth of real-world asset (RWA) tokenization interacts with decentralized finance (DeFi) to create new channels of systemic risk. By early 2026, tokenized RWAs had reached an estimated $36 billion in value, concentrated primarily in private credit and U.S. Treasury exposures, and are increasingly serving as collateral in on-chain lending and stablecoin structures (RWA.xyz, 2026). The paper reviews the foundations of DeFi and the role of stablecoins, then analyzes the TerraUSD and USD Coin episodes as early examples of peg instability and cross-market contagion between crypto and traditional finance (Bank for International Settlements, 2023; Financial Stability Board, 2023). It develops a risk taxonomy for tokenized RWA markets covering liquidity, oracle, collateral, legal, and contagion risk, and explains how leveraged looping amplifies shocks in collateralized lending protocols (Acemoglu et al., 2015; Gai & Kapadia, 2010). The paper then uses the First Brands Group bankruptcy and associated fabricated receivables as a case study of liquidity illusion, credit fraud, and on-chain fire sales in tokenized credit pools (ABF Journal, 2026). It concludes by discussing emerging regulatory responses and design principles intended to mitigate these vulnerabilities. The analysis underscores that RWA tokenization can improve capital efficiency but simultaneously creates a transmission belt that propagates offchain credit stress into DeFi liquidation cascades.
• DeFi stablecoin yields track FFR/SOFR, but with a distinct T+3 structural lag. • A settlement-friction framework links fiat rails to the T+3 transmission lag. • The lag is universal for both compliant USDC and offshore, unregulated USDT. • Basis regressions reveal a predictable settlement wedge after policy moves. • Robust tests rule out protocol outliers, macro trends, and weekend artifacts. Decentralized Finance (DeFi) stablecoin markets increasingly function as a shadow overnight dollar system, yet the speed at which U.S. monetary policy transmits to on-chain yields remains unclear. Focusing on the recent “High-for-Long” regime (2023–2025), I study this pass-through using daily Aave V3 deposit rates for USDC and USDT. Guided by a simple conceptual framework of settlement frictions and arbitrage constraints, I estimate an ordered VAR that controls for equity- and crypto-market cycles. The results show that DeFi yields are tightly anchored to the Federal Funds Rate (and, in robustness, SOFR), challenging the “crypto-decoupling” narrative. However, transmission exhibits a distinct T+3 structural latency, universal across both compliant USDC and unregulated USDT, indicating an infrastructural, systemic friction rather than issuer-specific constraints. Robustness tests, alternative-explanations analysis, and quantity-based mechanism checks rule out protocol outliers, broader macro trends, and weekend artifacts, supporting an interpretation based on delayed settlement and execution across fiat rails. Complementary basis regressions provide a direct pricing implication: the on/off-chain spread exhibits a significant, predictable wedge during the settlement window that dissipates thereafter. The findings imply that despite algorithmic immediacy, DeFi remains constrained by fiat infrastructure, and that improving on-chain capital efficiency may require modernizing payment rails alongside issuer-focused regulation.
Private credit has grown into a multi-trillion-dollar asset class embedded within modern financial networks, yet the pathways through which stress in that sector can propagate into digital asset markets remain poorly understood. This paper examines two distinct contagion channels linking macroeconomic shocks to decentralized finance (DeFi): a macro deleveraging channel in which broad risk-off behavior spreads from traditional markets into cryptocurrencies, and a direct tokenization channel in which blockchain-based tokens representing private credit portfolios serve as collateral within automated DeFi lending protocols. Drawing on recent empirical developments, including the redemption restrictions imposed by a large BlackRock private credit fund in early 2026, the bankruptcy of First Brands Group in September 2025, and the associated stress in tokenized credit instruments on the Morpho lending protocol, the analysis constructs a conceptual contagion framework. The paper also situates these dynamics within the shadow banking theory of Gennaioli, Shleifer, and Vishny (2013), arguing that tokenized private credit instruments exhibit a liquidity paradox: while blockchain infrastructure enables continuous trading, the underlying credit exposures remain illiquid. The paper concludes that as tokenization expands the integration between traditional and digital finance, regulatory frameworks must evolve to monitor cross-market contagion channels, enforce transparency in tokenized asset structures, and account for the systemic implications of automated liquidation mechanisms.
The integration of decentralized finance (DeFi) and traditional finance (TradFi) through fiat-backed stablecoins has created a composite financial system exposed to new channels of systemic risk. This Article analyzes how arbitrage breakdowns, synchronized outflows, and thinning liquidity can interact to amplify selling pressure and trigger regime shifts that spill into short-term funding markets. Building on ideas from traditional market structure and regulation, it translates familiar tools into seven design principles for minimizing tail risk and then examines the distinctive constraints that arise when those principles are implemented through DeFi architectures such as automated market makers, lending protocols, and bridges. Recognizing that core DeFi protocols often lie beyond direct supervisory reach, the Article advances a regulatory strategy centered on "connection conditions" at supervised junctions. By tying access to banks, custodians, and centralized exchanges to clear standards for governance, risk management, and architecture, this strategy combines benefits and constraints so that Law, Market, Norms, and Architecture work together to align profit-seeking with financial stability and to replace opaque de-banking with a transparent pathway for safe DeFi connectivity.
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.
Decentralized finance and stablecoin systems rely Stablecoins increasingly incorporate freeze, pause, and blacklist mechanisms to satisfy regulatory, compliance, and risk-management requirements. However, these controls introduce a critical temporal vulnerability when enforcement actions compete with transaction finality. This paper defines <b><i>Stablecoin Freeze Race Conditions</i></b> as a class of failures in which transfers, redemptions, or collateral movements execute successfully during the latency window between risk detection and freeze enforcement. We analyze how asynchronous control paths enable value escape even in fully permissioned stablecoins and demonstrate why governance authority alone is insufficient. A validator-level, logic-layer enforcement model is proposed to ensure atomicity between risk triggers and monetary state transitions under MiCA-aligned frameworks.
This paper analyzes the institutional and organizational differences between traditional finance and decentralized finance (DeFi), with a focus on public, permissionless blockchains. In traditional markets, intermediaries provide custody, authentication, settlement, and regulatory compliance. By contrast, the option of self-custody and open access on blockchains fundamentally reshapes the organization of financial services and challenges the foundations of current regulatory approaches. These structural differences alter trading, lending, and derivatives markets while introducing risks such as smart contract failures and infrastructure concentration. At the same time, DeFi's openness reduces entry barriers, improves transparency and access, and fosters competition and efficiency. Because self-custody removes intermediaries as enforcement points, regulation cannot simply extend existing frameworks. I conclude with policy recommendations emphasizing self-custody rights, privacy protection, adaptive regulation, and integration pathways for traditional intermediaries.
This paper introduces AURORA, a predictive institutional risk intelligence architecture designed to detect market manipulation and systemic fragility within decentralized finance ecosystems. The framework integrates multi-chain blockchain monitoring, behavioral graph analytics, liquidity stress modeling, and causal verification to identify engineered market abuse and cross-protocol contagion risks. AURORA further translates technical detection outputs into structured compliance classifications aligned with emerging regulatory regimes including the UK Market Abuse Regime for Cryptoassets (MARC) and the EU Markets in Crypto-Assets Regulation (MiCA). The study contributes to financial regulation, market microstructure analysis, and systemic risk modeling by proposing a unified institutional surveillance architecture for decentralized financial markets.
This note examines the role of 'tokenization' of monetary deposits-holding them on programmable, decentralized ledgers-in achieving automated, real-time processing of financial transactions. It compares this with the alternative of automated processing on conventional account-based centralized ledgers. It finds that the only use case which require such 'tokenized' monetary deposits are in realtime pre-funded financial trading of financial assets (along the same lines as the prefunded trading in decentralized finance). Here the 'tokenized' deposits must be 100% reserved to support settlement between institutions. All other use cases can be equally well supported using conventional account-based centralized ledgers. Programmability and automation can be equally well implemented with either architecture. For most use cases (the principal exception is global corporate cash management) the incentives for adoption are likely to be stronger with conventional centralized rather than decentralized architecture. JEL codes: E42, G21, G23, O33
The rapid expansion of private credit markets over the past decade has reshaped the structure of corporate lending and created a large parallel credit system operating outside traditional banking institutions. At the same time, developments in blockchain technology have enabled decentralized finance platforms to tokenize real-world credit assets, allowing investors to gain exposure to lending pools through digital tokens. These developments raise important questions about whether tokenization meaningfully changes the economic risks associated with private lending or simply redistributes traditional credit exposures through new technological infrastructure. This paper examines emerging signs of stress in the private credit market during 2025 and 2026 and evaluates whether these developments may transmit to decentralized finance lending platforms that provide exposure to tokenized credit assets. Drawing on literature related to shadow banking, liquidity risk, financial contagion, and decentralized finance, the analysis explores structural similarities between traditional private credit funds and blockchain-based lending pools. The findings suggest that although tokenization can improve transparency and settlement efficiency, it does not eliminate the fundamental credit risks associated with illiquid lending markets. Borrower default risk, leverage, sector concentration, and macroeconomic cycles continue to shape outcomes in both traditional and tokenized credit markets.
This thesis examines the implications of market frictions in international finance and macroeconomics in three contexts. The first chapter documents the effect of trading relationships on client trading outcomes in the over-the-counter (OTC) foreign exchange (FX) derivatives market. The second chapter documents the effect of nominal wage setting frictions on employment. The third chapter examines the behavior of non-U.S. central banks when firms engage in currency mismatch, borrowing more in dollars than given by their dollar operating exposures, emphasizing how imperfect regulation may affect U.S. dollar interest rates. In the first chapter, joint with Gerardo Ferrara, I study whether clients that rely more heavily on a dealer in the OTC FX derivatives market have worse trading outcomes after the dealer is adversely shocked. Using granular transaction-level data, we document that trading relationships are persistent—in an active trading week, clients are more likely to trade with a dealer that they had a relationship with and relied on more heavily. Then, we exploit the March 2023 collapse of Credit Suisse as an exogenous shock to exposed clients’ set of trading alternatives when relationships are persistent. Using difference-in differences analyses, we find that, although Credit Suisse’s EURUSD notional traded and trade count declined, clients that relied less heavily on Credit Suisse did not differentially reduce their Credit Suisse-specific trading activity relative to more reliant clients. Instead, more reliant clients continued trading at the client level and increased activity with other existing dealer relationships without incurring additional costs, relative to less reliant clients. These findings suggest that search and bargaining frictions were not particularly costly for heavily reliant clients after the shock—relationship persistence did not differentially prevent them from reallocating activity to existing alternative dealers, or lead to relatively greater costs, when their relationship dealer came under stress. In the second chapter, joint with Gert Bijnens, Hugo Monnery, and Laura Nicolae, I empirically document the effect of wage changes, driven by wage indexation to inflation, on firm-level employment growth. In Belgium, nearly all employees’ wages are indexed to inflation and firms are grouped into labor agreements that determine the exact timing and frequency at which wages are indexed, e.g. every year or every month. Using firm-level administrative data, we estimate two-stage least squares regressions of firm-level employment growth on wage growth, instrumented by the wage growth implied by the firm’s indexation policy. We find that employment contracts by 0.4% over four quarters for each 1% increase in wages. This result is robust to including NACE sector-date fixed effects and to using only variation in firms’ indexation timing, controlling for their chosen indexation frequency. About one-third of the response comes via anticipation of future wage increases. The elasticity is more than twice as large in magnitude in the post-pandemic period than before it, suggesting strong nonlinearities. Overall, these results show that, by preventing inflation from reducing real wages, inflation indexation reduces employment. In the third chapter, joint with Mitali Das, Gita Gopinath, Taehoon Kim, and Jeremy Stein, I document an externality of central banks’ imperfect regulation of firms that engage in currency mismatch, which results from central banks’ dollar reserve accumulation decisions. We explore how foreign central banks behave when firms engage in currency mismatch. Using a panel of 56 countries, we document that central bank holdings of dollar reserves are correlated with the dollar-denominated bank borrowing of their non-financial corporate sectors. Then, we build a model in which the central bank can deal with private-sector mismatch, and the associated risk of a domestic financial crisis, by: (i) imposing ex ante financial regulations; or (ii) accumulating dollar reserves to serve as an ex post dollar lender of last resort. The model highlights a novel externality: individual central banks may over-accumulate dollar reserves, relative to what a global planner would choose. Under imperfect regulation of currency mismatch, individual central banks do not internalize that their hoarding of reserves exacerbates a global scarcity of dollar-denominated safe assets, which lowers dollar interest rates and encourages firms to further increase the currency mismatch of their liabilities. Relative to the decentralized outcome, a global planner may therefore prefer higher capital requirements and reduced holdings of dollar reserves.
Decentralized exchanges (DEXs) have emerged as a foundational component of blockchain-based financial systems, enabling trustless asset trading without centralized intermediaries. However, the transparency of public mempools introduces significant vulnerabilities, including front-running, sandwich attacks, transaction reordering, and broader information asymmetry. In response, Cryptographic mechanisms such as Zero Knowledge (ZK) based architectures and commit reveal schemes are increasingly proposed as a solution to these vulnerabilities. This research systematically reviews the structural transparency paradox and cryptographic architectures in Decentralized Exchange based Automated Market Makers (DEX-AMM), evaluate their effectiveness in mitigating Maximal Extractable Values (MEVs), analyze computational complexity trade-offs including proof generation/verification costs, gas overhead, latency, and throughput, and identify why commit-reveal may offer superior practical viability despite zk-proofs' stronger theoretical privacy guarantees. A comprehensive search was conducted across arXiv, IEEE Xplore, ACM Digital Library, Scopus, Web of Science, Google Scholar including grey literatures for studies published between 2021 to 2026. Findings indicate that ZK-based approaches provide strong cryptographic privacy guarantees but often incur computational overhead and integration complexity, zk-rollups provide strong validity guarantees through cryptographic proofs, but their practical security depends heavily on the sequencer layer used by ( zkSync, StarkEx, and Loopring) which is responsible for transaction ordering, which can censor, delay, reorder transactions or cause failure of execution, while Commit-reveal schemes may be superior for real-world DEXs due to their constant time hash-based complexity (O(1)), lower gas costs, sub-second latency, and simpler implementation, despite requiring two-transaction UX friction, which can be mitigated through wallet automation. The computational efficiency advantage of commit-reveal becomes critical as DEX transaction complexity increases, where zk-circuit depth grows exponentially. Future research should prioritize optimizing zk-circuit efficiency, developing zk-commit-reveal hybrids system that balance cryptographic strength with computational practicality, and advancing hash-based commit-reveal schemes with UX improvements. DEX developers should prioritize commit-reveal for latency-sensitive applications and zk-proofs only when strongest cryptographic privacy is mandatory.
Tokenized deposits settle continuously and nearly instantaneously, but faster withdrawal execution compresses the coordination game among depositors and increases funding fragility even for solvent banks. This paper examines how disclosure design interacts with settlement speed to determine run risk and welfare in tokenized banking environments. We compare conventional disclosure with verifiable compliance disclosure implemented via Zero-Knowledge Proofs (ZKPs), which allow banks to certify regulatory liquidity compliance without revealing precise balance sheet positions. ZKP disclosure eliminates coordination-driven runs on compliant banks by pooling institutions near the regulatory threshold, at the cost of weaker market discipline as sophisticated depositors acquire less private information. A calibrated simulation using FDIC call report data for large US commercial banks, including the five Cari Network members, quantifies run probabilities and welfare across settlement speeds and depositor compositions. Tokenization without enhanced disclosure amplifies fragility; combining fast settlement with verifiable compliance disclosure improves welfare, particularly for retail-oriented funding bases. Disclosure architecture is not ancillary to tokenized deposit regulation, it is central to it.
Lending in decentralized finance (DeFi) relies on collateral and efficient liquidations to manage credit risk. The permissionless and pseudonymous nature of public blockchains precludes reputation-based lending in DeFi and renders liabilities effectively non-recourse. Frictions in collateral liquidations increase the risk of bad debt and may ultimately lead to protocol defaults and losses for liquidity providers. This paper studies liquidation dynamics in the Aave V2 Main Market on Ethereum using block-level data covering 46 months and more than 54 000 borrower positions. While most undercollateralized debt is liquidated almost instantaneously, a non-trivial share of positions remains open for extended periods. Using a state model to distinguish healthy, viable for liquidation, and stale borrower positions, this paper quantifies transition probabilities and identifies factors associated with liquidation success. Logistic regression results show that liquidation size, lower network transaction fees, and relative profitability are associated with the probability of liquidation success in the subsequent block. At the same time, oracle price distortions and asset price volatility are associated with lower liquidation likelihood, consistent with heightened execution risk. The findings provide new high-frequency evidence on liquidation frictions in a large and mature DeFi lending market. The results contribute to the understanding of the microstructure of DeFi liquidations and credit risk in decentralized lending protocols.
We examine whether the institutionalization of digital assets through regulated exchange-traded funds changes the transmission of macro-financial risk. Using daily data from January 2019 to March 2026, we study the launch of the spot Ethereum exchange-traded fund on 23 July 2024 as a dated institutional event and test whether Ethereum’s response to United States inflation surprises changed after the introduction of regulated ETF access. A triple-difference design shows that the interaction between headline Consumer Price Index surprises and lagged Ethereum network activity reverses sign around the ETF launch. Before the ETF, the interaction is small and positive (+0.06, p = 0.04), indicating that a more active network amplified Ethereum’s directional response to inflation news. After the ETF, the interaction becomes large and negative (-0.25, p
Battery energy storage sits at the centre of Europe’s low-carbon transition, yet financing these assets remains fraught with uncertainty. This thesis asks a pointed question: how do market volatility, shifting regulations, and the threat of asset stranding jointly shape the ability of investors to fund centralised and decentralised storage projects in Germany and Sweden? Drawing on a comparative case study rooted in pragmatist thinking, the analysis pairs discounted cash flow modelling with a careful reading of policy documents, regulatory rulings, and industry commentary. All market data, wholesale electricity prices from ENTSO-E, ancillary-service auction results from national grid operators, cover the period 2019-2024 and are publicly accessible. What emerges is a stark contrast. German centralised battery energy storage systems (BESS) projects carry the heaviest risk burden: frequency containment reserve (FCR) market saturation, confirmed grid-fee hikes, and a massive connection-queue backlog combine to push the internal rate of return from 11.5% down to 2.8% under stress, rendering projects economically unviable. Swedish centralised projects fare better for now, though their dependence on a handful of ancillary-service markets introduces a concentration risk that warrants close monitoring. Across both countries, decentralised storage proves more financially resilient, revenue diversification across retail savings, frequency markets, and peak shaving translates into lower risk premiums and more favourable debt terms, even where headline returns are lower. Monte Carlo simulations confirm that investment feasibility is highly sensitive to revenue cannibalisation and policy shocks. Theoretically, the study extends asset stranding literature by demonstrating that stranding risk in modern storage infrastructure is fundamentally revenue-driven rather than technologically deterministic, with regulatory interventions capable of eroding cash flows as rapidly as market saturation. From a policy perspective, the findings underscore the urgent need for regulatory clarity on grid tariff structures in Germany, the development of a coherent national storage strategy in Sweden, and the effective implementation of the EU Storage Infrastructure Act. For market participants, the analysis establishes that decentralised, revenue-diversified storage configurations offer a more robust risk-return profile, lowering hurdle rates and facilitating capital allocation in Europe’s evolving flexibility markets.
The tokenization of real-world assets (RWAs) has emerged as a transformative application of blockchain technology, with market projections estimating trillions of dollars in tokenized assets within the coming decade. However, a fundamental challenge remains unaddressed: physical assets such as precious metals, stored commodities, and warehoused goods incur structural negative carry -- custody, insurance, and audit costs that accumulate over time. While existing tokenization models have successfully established the market for digital gold and treasuries, they typically manage operational costs at the issuer level. The FRS introduces a framework to bring these economics directly on-chain, avoiding mechanisms such as token rebasing that compromise fungibility and composability with decentralized finance (DeFi) protocols. This paper proposes the Fungible Reserve Standard (FRS), a deterministic token design framework that encodes carrying costs transparently into on-chain logic. The FRS introduces an asset-per-token variable q(t) that decreases according to a predefined annualized carrying cost rate, coupled with a supply reconciliation mechanism that preserves holder balances and ERC-20 composability. While mathematically inspired by the daily expense ratio accrual in traditional asset management -- which often embed centralized profit margins -- the FRS design specifically encodes actual operational carrying costs to provide pure institutional-grade accounting clarity without compromising DeFi compatibility. The framework is asset-agnostic and applicable to any real-world asset with positive, predictable holding costs.
Do vulnerabilities in Decentralized Finance (DeFi) destabilize traditional short-term funding markets? While the prevailing ``Contagion Hypothesis'' posits that stablecoin reserve liquidations may transmit distress to traditional markets through fire-sale pressure, we document a short-horizon ``Flight-to-Quality'' pattern in the opposite direction. In the wake of major DeFi exploits, spreads on 3-month AA-rated commercial paper (CP) tend to narrow rather than widen. We interpret this pattern as consistent with a ``liquidity-recycling'' channel: capital leaving DeFi may be re-intermediated into traditional cash-management markets, with regulatory segmentation under SEC Rule 2a-7 making prime-eligible paper a plausible marginal destination. Because we do not directly observe daily fund-level routing into prime money market funds, this mechanism is inferred from pricing patterns and monthly holdings evidence rather than directly identified. The result is specific to exploit-driven operational shocks, this U.S. CP spread, and short event windows.