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on Payment Systems and Financial Technology |
| By: | Kundan Mukhia; Sabat Rai; Vivek Shrivastav; Imran Ansari; Md. Nurujjaman |
| Abstract: | Stablecoins have rapidly emerged as an important class of digital assets and a component of the digital financial ecosystem. Despite their growing importance, the statistical properties of stablecoin transaction activity remain largely unexplored. To the best of our knowledge, this is the first study to investigate scaling behavior in stablecoin transaction data, focusing on USDT and USDC. We analyze approximately 370 million USDT and USDC transactions recorded on the Ethereum blockchain across six periods spanning June 2024 to February 2026. Based on interactions between Externally Owned Accounts (EOAs) and Smart Contracts (SCs), we classify transactions into four categories: EOA-EOA, EOA-SC, SC-EOA, and SC-SC. Using maximum-likelihood estimation of power-law exponents, we find that transaction value distributions exhibit heavy-tailed scaling for both stablecoins across all periods and interaction categories. We identify two distinct scaling regimes: EOA-involved categories cluster around 1.45-1.60, whereas SC-SC transactions exhibit higher exponents of approximately 1.72-1.73. Sensitivity analysis confirms that this separation is robust across periods, stablecoins, and fitting sample sizes. Counterfactual analysis shows that changes in category weights alone cannot explain the observed variation in the overall exponent. Across different sample sizes, the counterfactual path accounts for only about 10%-35% of the total temporal range observed in the actual data. Overall, our results indicate two broadly differentiated scaling regimes in the tail of stablecoin transaction values. Power-law tail behavior is observed throughout stablecoin transaction activity, but the exponent depends on whether transactions are driven by EOAs or SCs. These findings provide a basis for further research on scaling behavior and transaction heterogeneity in blockchain-based financial systems. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.09378 |
| By: | Berg, Tobias; Keil, Jan; Martini, Felix; Puri, Manju |
| Abstract: | We analyze the effect of a major central bank digital currency (CBDC) – the digital euro – on the payment industry to find remarkably heterogeneous effects. Stock prices of U.S. payment firms decrease, while stock prices of European payment firms increase in response to positive announcements on the digital euro. Bank stocks do not react. We estimate a loss in market capitalization of USD 127 billion for U.S. payment firms, vis-a-vis a gain of USD 23 billion for European payment firms. Our results emphasize the medium-of-exchange function of CBDCs and point to a novel geopolitical dimension of CBDCs: enhanced autonomy in payments. |
| JEL: | G21 E41 E42 E51 E52 E58 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19367 |
| By: | Marco Bianchetti; Camilla Ricci; Marco Scaringi |
| Abstract: | The growth of peer-to-peer exchanges and the blockchain technology has led to a proliferation of cryptocurrencies and to a massive increase in the number of investors who actually negotiate digital money. Cryptocurrencies trade at prices mainly driven by investor sentiment, becoming a potential source of financial bubbles and instabilities. In this work, we apply quantitative models to the study of Bitcoin and Ether, two of the most famous cryptocurrencies. Our bubble detection methodology combines the Log Periodic Power Law (LPPL) model, originally created by Johansen, Ledoit and Sornette (JLS), and the statistical model developed by Phillips, Shi, and Yu (PSY). In particular, we employ three different versions of JLS model, i.e. Ordinary Least Square (OLS), Generalised Least Squares (GLS) and Maximum Likelihood Estimation (MLE), and two PSY statistical tests (BSADF and BSADF*). We find that, during the sample period 1st December 2016 - 16th January 2018, Bitcoin shows typical hallmarks of a bubble phase in mid December 2017 and in the first half of January 2018, anticipating the large crashes observed thereafter. Also the Ether price dynamics reveals bubble evidence in mid June 2017, anticipating the crash observed on 12th June, and a weaker signal around 12th January 2018, anticipating the crash observed in the same days. This paper confirms the high risk of speculative bubbles associated with cryptocurrencies, related to investor exuberance pumping market prices far away from their fundamental values, thus creating critical situations subject to possible crashes. Our methodology is general and can be applied to virtually any financial time series, and may support investing and risk management strategies. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.21826 |
| By: | Sofia Priazhkina |
| Abstract: | This policy note examines how a non-interest-bearing retail central bank digital currency (CBDC) could affect the financial stability of Canada’s systemically important banks during a severe recession. Stress test results show that the banks remain resilient, maintaining key regulatory ratios even under high CBDC demand. To manage funding outflows, banks scale back balance sheet growth and replace some lost deposits with alternative funding. Profitability stays strong overall, though short-term volatility may occur. To reduce potential risks, the note recommends a gradual CBDC rollout with holding limits, well-timed capital buffer adjustments, liquidity regulation updates, early communication of regulatory changes, and coordination with central bank balance sheet policies. |
| Keywords: | Financial system; Financial stability and systemic risk; Models and tools; Economic models; Money and payments; Digital assets and fintech; Structural challenges; Digitalization and productivity |
| JEL: | E44 E58 E61 G01 G21 G28 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocsap:26-30 |
| By: | Itamar Drechsler; Hyeyoon Jung; Weiyu Peng; Dominik Supera; Guanyu Zhou |
| Abstract: | Credit card interest rates currently average 22%, an 18% spread over the short rate. This spread far exceeds that on any other loan or bond, yet nearly half of households are credit card borrowers. Why are credit card rates so high? To understand this, and the economics of credit card banking, we use regulatory account-level data to analyze the lifetime cash flows of 550 million monthly accounts, representing 90% of the US credit card market. While charge-off rates are comparatively high, averaging around 6%, they explain only a fraction of cards' spread. Reward payments and non-interest expenses are more than offset by interchange and non-interest income. Operating expenses, particularly marketing, are very large, and are used to generate pricing power. Yet, after deducting them, card lending still earns a 6.8% return on assets (ROA), more than four times the banking sector's ROA. Using the cross section of accounts, we estimate that credit card rates price in a 4.3% default risk premium, similar to high-yield bonds. Accounting for this, card lending earns an alpha of around 1.5% relative to the aggregate bank sector. |
| JEL: | E21 E42 E50 G12 G21 G23 G41 G5 G51 M3 M31 M37 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:35607 |
| By: | Cornelli, Giulio; Gambacorta, Leonardo; Garratt, Rod; Reghezza, Alessio |
| Abstract: | Decentralised finance (DeFi) lending protocols have experienced significant growth recently, yet the motivations driving investors remain largely unexplored. We use granular, transaction-level data from Aave, a leading player in the DeFi lending market, to study these motivations. Our findings reveal that search for yield predominantly drives liquidity provision in DeFi lending pools, whereas borrowing activity is mainly influenced by speculative and, to some extent, governance motives. Both retail and large investors seek high returns through price speculation, however the latter engage in DeFi borrowing relatively more than the former also to influence protocol decisions and accrue more significant governance rights. |
| Keywords: | Cryptocurrency; Decentralised Finance; lending |
| JEL: | G18 G23 O39 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19358 |
| By: | Remo Isch-Taudien (University of Bern and Study Center Gerzensee); Cyril Monnet (University of Bern and Study Center Gerzensee) |
| Abstract: | An intrinsically useless asset can have value not because it serves as a medium of exchange today, but because it could in the future— this is the option value of money. We characterize the private and social option values of cryptocurrency in a model with a possibly selfinterested government controlling the cash supply. The social value is ambiguous: negative because cryptocurrency raises the cost of holding cash, yet positive when it disciplines the government. Calibrating the model, we find households would forgo 0.10%-0.81% of consumption to live in an economy where Bitcoin carries option value. |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:szg:worpap:2602 |
| By: | Jaesung Kim; Changhee Cho; Jae Woo Lee |
| Abstract: | This study investigates whether the macroscopic statistical maturity of cryptocurrencies implies dynamical equivalence with traditional equity markets. We analyze high-frequency data (2020--2025) using the Complexity--Entropy Causality Plane (CECP) and directed horizontal visibility graphs (directed HVG) to uncover complex temporal patterns and time-directed structures in the return series. While conventional stylized facts show striking convergence across all assets, structural diagnostics reveal a compelling paradox: cryptocurrencies appear more locally random than the equity benchmark during ordinary periods, yet exhibit significantly stronger directional time-irreversibility around high-visibility return events. The absolute-return results show that large cryptocurrency fluctuations tend to begin abruptly and remain elevated afterward. Separate analyses of positive returns and negative-return magnitudes show that this pattern is shared across cryptocurrencies on the upside but varies across assets on the downside. We conclude that statistical maturity is only skin-deep; the underlying dynamical processes of mature cryptocurrencies remain fundamentally distinct from traditional benchmarks. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.10852 |
| By: | Wasti, Hiba Syeda Asad |
| Abstract: | Women’s entrepreneurship in Pakistan is shaped by intersecting social, institutional, and economic constraints, including gender norms, household bargaining structures, mobility restrictions, limited access to finance, unequal digital access, and low participation in formal labor markets. As digital platforms, mobile payments, social commerce, and online marketplaces expand across emerging economies, they create new opportunities for women’s enterprise participation while also reproducing existing inequalities in skills, visibility, trust, and institutional support. This paper reviews social-science literature on women’s economic agency, entrepreneurship, digital inclusion, and gendered labor-market barriers, using Pakistan as a country case. Rather than treating digital market access only as a business-growth opportunity, the paper examines how digital access interacts with social norms, family expectations, market institutions, and women’s ability to exercise economic choice. The paper proposes a conceptual framework linking five dimensions of women’s enterprise participation: digital capability, financial inclusion, market access, social legitimacy, and institutional trust. It argues that women-led enterprise development in Pakistan requires attention not only to platforms and markets but also to the social conditions that shape women’s agency, mobility, and legitimacy as economic actors. |
| Date: | 2026–07–13 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:5azn2_v2 |
| By: | Rischan Mafrur; Fadli Ikhsan Pratama; Khadijah |
| Abstract: | Indonesia has established a regulated carbon market supported by national registry infrastructure and the IDXCarbon exchange. Carbon units can be issued, recorded, traded, and retired within this framework. IDXCarbon currently uses a private blockchain for its trading infrastructure. This creates an opportunity to examine how Indonesian carbon credits could also be represented and traded through public blockchain infrastructure. This study proposes an architecture for tokenizing Indonesian carbon credits as real-world assets (RWAs), with particular focus on Sertifikat Pengurangan Emisi Gas Rumah Kaca (SPE-GRK). The proposed architecture retains the Sistem Registri Unit Karbon (SRUK) as the authoritative source of carbon-unit status. It introduces a public-blockchain layer for token representation and programmable transactions. The architecture is designed to support lifecycle management, token-based asset representation, public observability of token activity, interoperability, wallet-based transactions, and programmable settlement. The architecture consists of four layers: the authoritative carbon layer, the registry interoperability and tokenization layer, the public-blockchain RWA layer, and the market and application layer. Access to the tokenized carbon assets remains regulated. Token issuance and transfers are linked to participant eligibility and registry status. Retirement also remains dependent on the authoritative carbon registry. The proposed architecture provides a framework for introducing public-blockchain RWA infrastructure into Indonesia's existing carbon market while maintaining SRUK authority and existing market-integrity controls. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.15597 |
| By: | Boyer, Pierre; Gauthier, Germain; Le Yaouanq, Yves; Rollet, Vincent; Schmutz-Bloch, Benoît |
| Abstract: | We propose a theory of protest dynamics with heterogeneous protest technology and intensity. The ability to mobilize online reduces the likelihood of coordination failures at both the extensive (engagement) and intensive (violence) margins. Social media can initially help launch massive protests, but then encourage radical factions to turn violent and drive out moderates. Using both online and offline data, we show that the 2018 Yellow Vest uprising in France followed such a crowd-in-then-crowd-out sequence: early online and offline mobilizations reinforced each other, but online discussions quickly radicalized, moderates left, and a handful of violent protesters took over the streets. |
| Keywords: | Protests; Crowding-out; Violence; Social media |
| JEL: | D72 D74 L82 Z13 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19355 |
| By: | Emmanuel Nahimana; Ya\'e Ulrich Gaba |
| Abstract: | Mobile money has widened financial access across Sub-Saharan Africa and enlarged the surface for money-laundering and terrorism-financing (ML/TF) activity in ecosystems dominated by high-volume, low-value transactions. Rwanda is a case in point: several million active mobile-money users, telecom-led wallets on the MTN and Airtel networks, and a Financial Intelligence Centre (FIC) supervising transaction streams whose scale exceeds static rule-based monitoring. This paper develops and evaluates a transaction-monitoring framework aligned to the Rwandan AML/CFT regime under (i) extreme class imbalance (~0.1% prevalence), (ii) scarce and delayed labels, and (iii) bounded investigator capacity. Using SAML-D, a synthetic dataset of 9, 504, 852 transactions with 17 laundering typologies, we engineer account-centric behavioural features (rolling velocity, net-flow directionality, counterparty diversity, burstiness) and benchmark supervised classifiers (Logistic Regression, Random Forest, LightGBM), unsupervised anomaly detectors (Isolation Forest, Local Outlier Factor), a dense autoencoder, and a late-fusion meta-learner. Evaluation is operational: PR-AUC, recall at a calibrated ~90%-precision point, recall at top-K%, and alerts per 10, 000. On the chronologically held-out test period, LightGBM attains PR-AUC = 0.0469, capturing 64 laundering cases at precision ~0.89 with 0.51 alerts per 10, 000; the fusion stacker reaches PR-AUC = 0.0477 at precision ~0.91 and 0.46 alerts per 10, 000, recovering 59 true positives. We map score bands to Rwanda-relevant analyst workflows and STR/SAR escalation, and outline a staged path from synthetic prototyping to real-data validation with the National Bank of Rwanda and FIC. The contribution is operational: a governance-aware pipeline and evaluation protocol calibrated to the constraints of an African mobile-money regulator, not a new algorithm. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.15447 |
| By: | Heidhues, Paul; Köster, Mats; Köszegi, Botond |
| Abstract: | We develop a theory of digital ecosystems built on the premise that a multi-market firm can steer users it has in one market toward its products in other markets. Due to this "cross-market leverage, " a leader in an "access-point'' market (where users begin their online journeys) derives a high value from offering services in connected markets (where users continue their journeys), and can thus make profitable takeovers. Indeed, because the firm has the outside option of acquiring, and steering users toward, its target's competitor, it can take over the target at a discount. In contrast, other firms have no or smaller incentives for takeovers, explaining why ecosystems grow out of market leaders at access points. Conversely, cross-market leverage also implies that once an ecosystem has grown, it has an increased value of controlling access points, so it may go to great lengths to dominate these markets. Our theory suggests that ecosystems have mixed implications for consumer welfare. Under plausible assumptions, a to-be ecosystem takes over market leaders, and this consolidation of good services across markets benefits consumers in the short run. But an ecosystem's takeovers and dominance of access points lower incentives for entry and innovation, and lower the efficiency of access-point markets with superior alternatives. Hence, the long-run welfare implications of ecosystems are often negative. |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19524 |
| By: | Julia Ko\'nczal; Rafa{\l} Po{\l}ocza\'nski |
| Abstract: | Cryptocurrency exchange-traded products (ETPs) listed on European exchanges provide a regulated environment for studying intraday market anomalies. We study four Bitcoin and Ethereum ETPs traded on Xetra and Nasdaq Stockholm over the period January 2024 - December 2025 using one-minute bars. As a benchmark, we adopt an extreme value theory approach in which anomalous bars are defined as returns falling below a threshold estimated by fitting a generalised Pareto distribution to left-tail exceedances. We then propose three new binary anomaly indicators. The first, a cross-venue divergence anomaly, identifies venue-specific price divergence between the two exchanges. The second is a no-recovery anomaly that identifies extreme price drops followed by little or no recovery over the next ten active bars. The third is a momentum-reversal anomaly that identifies extreme price drops following positive short-term momentum. Although each anomaly type represents fewer than 1% of one-minute bars, statistical analysis using Mann-Whitney U tests shows that anomaly observations exhibit significantly higher effective spreads, higher values of liquidity-related ratios, and more pronounced order-flow imbalances than non-anomalous bars. Furthermore, employing an out-of-sample prediction methodology with four classifiers - random forest, logistic regression, extreme gradient boosting, and light gradient boosting machine - shows that all four anomaly types are predictable one bar ahead, with AUC-ROC values of up to 0.82. Permutation importance indicates that short-term volatility and drawdown measures are generally more useful for prediction than microstructure variables. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.09576 |
| By: | Muhammad Abdullah Haroon |
| Abstract: | Bitcoin price prediction on sub-daily timescales is a hard open problem in computational finance. Bitcoin exhibits fat-tailed returns, non-stationary dynamics, and a price discovery process influenced by social discourse on Reddit and Twitter. Conventional approaches fuse OHLCV technical features with sentiment via static concatenation, applying identical fusion weights regardless of market state. This is inconsistent with the behavioural finance literature, which shows that retail sentiment is most predictive during volatile periods and noisy during calm ones. This paper proposes Regime-Aware Multi-Modal Learning (RAML), which conditions fusion of sentiment and price features on a dynamically detected binary market regime. Rolling 24-hour volatility partitions observations into stable and volatile regimes; a learnable sigmoid gate adjusts the weight of the sentiment embedding relative to the price embedding, trusting sentiment more during volatility and price dynamics more during stable phases. The system is evaluated on 3, 491 hourly observations (July 2024-September 2025), combining Bitcoin OHLCV data with Reddit /r/Bitcoin FinBERT sentiment. Four models are compared - price-only BiLSTM, sentiment-only classifier, static-concatenation BiLSTM, and RAML - across 3-hour and 6-hour horizons, with an ablation study isolating the sentiment branch, regime detection, and adaptive fusion. RAML achieves macro-F1 of 0.5474 (3h) and 0.5513 (6h), with the highest AUC at 3 hours (0.5084), indicating better calibration. Ablation confirms every component is necessary, and replacing adaptive weighting with concatenation causes recall collapse at 6 hours (F1: 0.14). These results establish regime-conditioned adaptive fusion as a necessary design principle for multi-modal financial forecasting. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.23370 |
| By: | International Monetary Fund |
| Abstract: | The Brazilian financial system has undergone significant change since the 2018 FSAP. While the system remains bank-dominated, with two of the six largest banks state-owned, technology-driven change has brought new digital entrants and stronger competition in banking services. Financial markets have grown significantly, with strong growth in corporate bond markets and derivatives, and a nascent but fast-growing structured credit market alongside intensifying retail trading. Payment services have been revolutionized by the Pix system, and crypto market activity is growing. Household and corporate indebtedness have increased despite elevated borrowing costs. |
| Keywords: | financial system interconnectedness; Fsap analysis; derivatives market; market infrastructure; sovereign bond market; Fsap finding; financial market; Banco Nacional; Financial sector stability; Financial Sector Assessment Program; Stress testing; Anti-money laundering and combating the financing of terrorism (AML/CFT); Credit; Global; Middle East |
| Date: | 2026–07–23 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfscr:2026/192 |
| By: | Gambato, Jacopo; Peitz, Martin |
| Abstract: | We analyze consumers' voluntary information disclosure in a platform setting. For given consumer participation, the platform and sellers tend to prefer limited disclosure of consumer valuations, in contrast to consumers. With endogenous consumer participation, seller and platform incentives may be misaligned, and sellers may be better off when consumers can disclose their valuations. A regulator acting in the best interest of consumers and/or sellers may want to intervene and force the platform to employ a disclosure technology that enables consumers to voluntarily disclose information from a richer message space. |
| Keywords: | E-commerce |
| JEL: | L12 L15 D21 D42 M37 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19359 |
| By: | Leonardo Bursztyn (University of Chicago & NBER); Angela Duckworth (University of Pennsylvania); Rafael Jiménez-Durán (Bocconi University, IGIER, CEPR, CESifo, & Stigler Center); Aaron Leonard (University of Chicago); Filip Milojević (University of Chicago); Christopher Roth (University of Cologne, ECONtribute, NHH Norwegian School of Economics, MPI for Behavioral Economics, & CEPR); Cass R. Sunstein (Harvard Law School) |
| Abstract: | Four months after Australia banned under-16s from major social media platforms, only about a quarter of affected teenagers comply, and the way the ban is designed makes that share more likely to erode than to grow. In December 2025, Australia became the first country to ban under-16s from holding accounts on major social media platforms, and comparable legislation has since been adopted, drafted, or proposed in more than a dozen other countries. We surveyed roughly two thousand Australian teenagers four months after the ban took effect. Compliance is low, around 25%, and is unlikely to consolidate. Teenagers say they would need roughly two-thirds of their peers to comply before complying themselves, and they perceive compliers as less popular than non-compliers. Sustaining higher compliance will require pairing the ban with instruments that act on social norms and individual incentives directly. |
| Keywords: | Social media ban, tipping points, coordination, compliance, network effects, peer effects, social norms, adolescents, technology regulation, Australia |
| JEL: | D85 D91 I18 L51 |
| Date: | 2026–06 |
| URL: | https://d.repec.org/n?u=RePEc:ajk:ajkpbs:072 |
| By: | Jeon, Doh-Shin; Rey, Patrick |
| Abstract: | We study the development of apps on competing platforms. We show that competition leads to commissions exceeding those maximizing consumer surplus (and, a fortiori, social welfare) whenever raising one commission reduces rivals' app bases. We relate this finding to economies of scope in app development and, to illustrate it, consider a setting in which some developers can port their apps at no cost: as their proportion increases, app development is progressively choked-off. Fostering platform competition or interoperability may therefore fail to produce the desired results. Within-platform app store competition, together with appropriate access conditions, may constitute a more promising avenue. |
| Keywords: | Platform competition |
| JEL: | D21 D43 L13 L22 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19456 |
| By: | Maredia, Mywish K.; Olubunmi, Adefemi; Olabisi, Michael |
| Abstract: | This paper examines gender disparities in mobile technology access and productive use along Nigeria’s cowpea value chain using a nationally representative survey of nearly 19, 000 value chain actors, including farmers, assemblers, wholesalers, and retailers. While gender gaps in basic mobile phone ownership are relatively modest, substantially larger gaps emerge in smartphone ownership and, more importantly, in business-oriented use of mobile technologies. Women are significantly less likely than men to use phones for making or receiving business orders, particularly through app-based or data-intensive platforms, even when they own mobile devices. The findings provide evidence of a “second-level digital divide, ” where access to technology does not translate into equivalent economic engagement. The analysis further shows that these disparities vary across value chain segments and regions, reflecting differences in market integration, commercialization, and gender norms. The study highlights the importance of moving beyond access-based measures of digital inclusion and emphasizes the need for policies that strengthen women’s digital skills, institutional support, and productive use of technology in agricultural markets. |
| Keywords: | International Development |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea26:404646 |
| By: | Michail Samawi |
| Abstract: | 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 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.22459 |
| By: | Lingxiu Dong; Kaiwen Luo; Fasheng Xu |
| Abstract: | Generative AI is shifting digital commerce from browsing toward agentic search, in which consumers delegate product discovery to AI agents. We compare manual search, which accurately evaluates a limited product set, with agentic search, which screens a broad catalog through noisy representations of preferences and products. Preference complexity is the number of satisfaction-relevant dimensions that are difficult to articulate before search but readily evaluated upon inspection. Consumers have finite attention and choose search intensity: products inspected manually or preference-refinement depth with an agent. We obtain three findings. First, manual search collapses beyond a finite complexity threshold: inspection ceases, mismatch reaches the no-search benchmark, and platform revenue falls to zero. Agentic search avoids this collapse. Once refinement becomes worthwhile, it remains worthwhile as complexity rises; mismatch stays below the no-search benchmark and revenue remains positive, although articulation effort and mismatch may increase. Second, platforms rank the regimes by conversion revenue, whereas consumers also bear search expenditure. When manual inspection is sufficiently inexpensive, agentic search becomes revenue-superior before consumers voluntarily adopt it, creating an adoption lag in which consumers rationally continue manual search. Third, conditional on agentic participation, platforms may assign lower fidelity to consumers with larger attention budgets because they can offset noisier representations through additional refinement, yielding an inverted fidelity allocation. Agentic commerce thus shifts scarcity from product inspection to preference articulation, making consumers' willingness and ability to interact central to voluntary use and platform fidelity design. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.08395 |
| By: | Josh Molnar |
| Abstract: | Every widely followed Bitcoin cycle indicator (Pi Cycle, MVRV, Mayer, Puell) called turns precisely for a decade, then degraded in one sequence: precise, then early, then silent. This is one structural phenomenon. Across the four halving epochs (2011-2026), the per-cycle maxima of five top-calling oscillators decline monotonically while minima end higher, so any threshold calibrated on past cycles must stop firing; short-horizon indicators decay toward zero and several invert sign; yet Bitcoin's time structure stays fixed, with mature-cycle tops 525/546/534 days after their halvings and bottoms 406/364/366 days after their tops. Turns are identified retrospectively by a fixed mechanical rule, not a real-time record. Timing-free nulls put the joint clustering at 5e-6 to 1e-3 across every variant. A harder empirical null (block-bootstrapped paths under the identical rule) never reproduces the top cluster under its deterministic construction (0 of 10, 000); the bottom cluster is largely intrinsic to the drawdown process (31-43% of paths), so the evidence concentrates in top phase-alignment. In block height (the exact 210, 000-block unit) the top null stays 0 of 10, 000 and partial bottom structure emerges; shape and volatility overlays do not improve. A causal power law in time-since-genesis (exponent near 5.6) is the only signal whose sign is stable across mature epochs, replicates on a second source and Ethereum, and whose timing edge over buy-and-hold turns positive in the current cycle (one holdout, suggestive not decisive). We rest nothing on per-epoch significance: a rotation null shows HAC inference over-rejects here (size 0.33 at nominal 0.05; p=0.21). Macro drivers (M2, yield curve) show the same instability and lose a joint horse race. We pre-register falsifiable windows: a 2026 bottom (Oct 5-Nov 16) and a next top 525-546 days after the following halving. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.26188 |
| By: | Clark Granger-Castaño; Jhorland Ayala-García; Fabio Montenegro Aparicio |
| Abstract: | Las remesas internacionales se han consolidado como una fuente relevante de financiamiento externo para la economía colombiana, con flujos récord en los años recientes y una marcada concentración territorial. Este documento analiza el efecto de las remesas sobre el crecimiento económico departamental en Colombia durante el período 2009-2024, así como su relación con el proceso de convergencia regional del PIB real per cápita. La estrategia empírica combina modelos de panel dinámico estimados mediante GMM en primeras diferencias, que abordan la endogeneidad e incorporan términos de interacción, con un modelo de regresión con transición suave en panel (PSTR), que identifica umbrales de forma endógena. Los resultados revelan evidencia de una dinámica de convergencia entre departamentos y un efecto promedio de las remesas nulo o negativo una vez controlada la heterogeneidad no observada. Sin embargo, el efecto es condicional ya que se torna positivo y significativo en los departamentos que superan umbrales estructurales de profundidad financiera (alrededor del 8, 6% del PIB en cartera de consumo), de cobertura en educación media (cerca del 38%) y de ingreso per cápita inicial. Estos hallazgos indican que las remesas parecen no constituir un motor automático del crecimiento regional, y que su contribución depende de la capacidad de absorción de las economías receptoras, por lo que, en ausencia de políticas complementarias de inclusión financiera y educación, podrían reforzar las disparidades territoriales.*****ABSTRACT: International remittances have become a relevant source of external financing for the Colombian economy, with record flows in recent years and a marked territorial concentration. This paper analyzes the effect of remittances on departmental economic growth in Colombia over the period 2009-2024, as well as their relationship with regional convergence in real GDP per capita. The empirical strategy combines dynamic panel models estimated by first-difference GMM, which address endogeneity and incorporate interaction terms, with a Panel Smooth Transition Regression (PSTR) model that endogenously identifies thresholds. The results show evidence of conditional beta convergence across departments, and a null or negative average effect of remittances once unobserved heterogeneity is controlled for. However, the effect is fundamentally conditional: it becomes positive and significant in departments that exceed structural thresholds of financial depth (around 8.6% of GDP in consumer credit), secondary education coverage (close to 38%), and initial per capita income. These findings indicate that remittances are not an automatic driver of regional growth: their contribution depends on the absorptive capacity of the receiving economies, and, in the absence of complementary financial inclusion and education policies, they could reinforce territorial disparities. |
| Keywords: | Remesas, Crecimiento económico, Convergencia condicional, Capacidad de absorción, no linealidades, Remittances, Economic growth, Conditional convergence, Absorptive capacity, nonlinearities |
| JEL: | O15 R11 O47 C23 |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:bdr:region:347 |
| By: | Jean-Sébastien Fontaine; Vincent Meh; Jayden Plener |
| Abstract: | Banking regulations can shape the asset-management landscape in an underappreciated way. We document that banking regulations push asset managers’ liquid holdings away from bank savings accounts and toward money-market assets. The case of Canadian HISA ETFs sheds light on the mechanism. These ETFs, launched in 2013, gather investors’ funds and invest them in high-interest savings accounts. When policy rates rose sharply after the pandemic, HISA ETFs became a surprisingly effective way for households and institutions to earn competitive deposit-like returns. Funds poured in. Then, in late 2023, OSFI reaffirmed how banks under Basel III must treat deposits from ETFs and asset managers more broadly. The result is a clean quasi-experiment. Banks holding HISA ETF deposits lowered the yields offered to HISA ETFs, which then responded by moving holdings toward money-market securities. We describe what HISA ETFs do, their rapid expansion, the regulatory concerns behind OSFI’s stance, and how regulations ultimately shifted HISA ETFs toward holding money-market securities. This episode reminds us that banking regulations ensure the sound liquidity of banks, but it also highlights broader implications for the liquidity-management decisions of other financial institutions. |
| Keywords: | Financial markets and funds management; Funds management; Financial system; Financial institutions and intermediation |
| JEL: | E44 G11 G18 G23 G28 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocsap:26-32 |
| By: | Ramon Marc Garcia Seuma |
| Abstract: | Do crypto perpetual-futures crashes carry a reproducible early-warning fingerprint of a critical transition, and in which state variable? We study seven major BTC liquidation cascades (2022-2025, including the record 19B USD event of 10 October 2025) using minute-level price and 5-minute leverage/order-flow data. On detrended residuals we compute rolling variance and lag-1 autocorrelation and test their pre-cascade trend with the Kendall-tau statistic, sweeping 39 analysis configurations per variable per event. No variable is event-invariant. Price carries the critical-slowing-down signature in five of seven events but is silent in exactly the two sudden-news (tariff) shocks, suggesting a two-type structure: endogenous-buildup versus exogenous-shock cascades. The October 2025 event, whose in-sample analysis suggests the signature lives in leverage rather than price, turns out to be the outlier, not the rule. The one regularity surviving all events with data is a compression of taker order-flow variance, which passes a 300-onset placebo test (Fisher-combined p ~ 5e-6) but is a population-level precursor, not a per-event alarm. Single-event critical-slowing-down claims in crypto derivatives are therefore fragile by construction. We argue the pattern of failures is itself diagnostic: slowing down is absent exactly where the destabilising mechanism is most abrupt, as one would expect if these cascades are discontinuous, shock-driven transitions rather than critical ones. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.27070 |
| By: | Girish G N; Ashutosh Sahoo; Akshay SP; Gurukiran S; Dhanashekar Kandaswamy |
| Abstract: | Decentralized lending lacks a credit bureau: a borrower's capacity to repay must be inferred entirely from public on-chain activity, without income verification or a liability record. This paper presents zLend, a deployed cash-flow underwriting framework that reconstructs a wallet's daily balance history from raw token transfers and derives short-duration repayment-capacity signals from it. The reconstruction is performed twice per wallet, once restricted to a fixed stablecoin basket and once over all fungible transfers, on the premise that a wallet's total token holdings and its liquid, spendable balance are distinct quantities whose conflation misprices risk. From each series we derive liquidity coverage against a fixed loan size, cash-flow volatility and regularity, a drawdown-and-recovery statistic adapted from quantitative finance, and a recurring-counterparty detector that identifies salary-like payment cadence from transfer timing alone. The two views are then compared: a wallet with large aggregate holdings whose stablecoin reserve rarely covers the loan size is flagged as a liquidity mismatch irrespective of total wealth. We specify the pipeline formally, document the golden-master methodology used to verify a cross-language production migration to numerical tolerance 1e-9, and characterize the tier function's parameter sensitivity with an independent reimplementation validated to exact agreement (78 of 78 field assertions) against the deployed system's reference fixtures. Tier assignment is governed predominantly by the reference loan size, with four of six reference wallets changing tier across loan sizes from USD 10 to USD 25, 000; the drawdown and coverage criteria bind on disjoint wallets, so neither subsumes the other; and no criterion in the tier rule is inert. zLend is deployed in production, informing real lending decisions via third-party API integrations. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.16856 |
| By: | Zi Wang (IÉSEG School Of Management [Puteaux]); Ruizhi Yuan (University of Nottingham Ningbo [China]); Boying Li (University of Nottingham Ningbo [China]); V. Kumar (Brock University [Canada]); Ajay Kumar (EM - EMLyon Business School) |
| Abstract: | Financial institutions are increasingly employing artificial intelligence (AI) solutions to optimize their financial advice and services for consumers. However, consumers have demonstrated reluctance toward adopting AI technology goods, and the intermediary psychological mechanism of adoption intention in the financial service context is unclear. Using the theoretical lens of technology affordances and constraints, this article proposes the concept of consumer technology vulnerability (CTV) as the mediating mechanism in the affordance–adoption process of AI financial advisors (AFAs). Meanwhile, consumer innovativeness and self‐efficacy are investigated as individual traits that moderate perceptions and psychological impacts of AI affordances. Specifically, the study first conceptualizes AI affordances in a product innovation context by reviewing the burgeoning literature on AI to date. This is followed by a US‐based survey (N = 616), which shows the positive indirect effects of information optimization, customizability, and human‐likeness on AFA adoption intention through CTV. Self‐efficacy and consumer innovativeness are found to enhance the positive effects of AI affordances on AFA adoption intention through CTV but diminish the impact of human‐likeness on CTV. These findings highlight, for the first time, the mediating role of CTV in new technology adoption. This will help technology innovators and financial institutions to identify how consumers perceive and adopt different AI affordances, and therefore to better incorporate AI characteristics into financial product innovations. |
| Keywords: | AI affordance, AI financial advisor, AI product adoption intention, consumer innovativeness, consumer technology vulnerability |
| Date: | 2026–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05708328 |
| By: | Berger, Thor; Ostermeyer, Vinzent |
| Abstract: | This paper documents how the advent of the limited liability corporation contributed to the diffusion of steam technology during Sweden’s industrialization. Using longitudinal establishment-level data, we show that incorporation sharply raised the probability that industrial establishments adopted steam. Incorporation facilitated technology adoption partly by enabling smaller establishments to expand to a greater scale where the use of steam became feasible. These results highlight that low barriers to incorporation may be an important lever to facilitate the diffusion of new technologies. |
| Keywords: | Industrialization; Technology adoption; Steam engine |
| JEL: | O14 O33 D22 L25 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19530 |
| By: | Olivier Lopez (CREST); Daniel Nkameni (CREST) |
| Abstract: | The expansion of the cyber insurance market remains exposed to the threat of accumulation events that could simultaneously affect a large number of policyholders. Although few such catastrophes have been observed so far, apart from worldwide cyberattacks such as WannaCry and NotPetya in 2017, the nature of cyber risk makes their occurrence plausible. Stress-testing tools are therefore needed to assess whether an insurance portfolio can withstand such crises. In this perspective, the European Insurance and Occupational Pensions Authority (EIOPA) has identified cloud outage as one of the key scenarios to consider in cyber insurance stress-testing frameworks. In this paper, we propose a framework to model and calibrate cloud-outage scenarios and to measure the diversification of a cyber insurance portfolio. We also show how this diversification can protect against accumulation risk and provide underwriting guidelines to reduce the vulnerability of a portfolio to cloud-outage scenarios. |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2607.18815 |
| By: | Jesus Feliciano, Cristiano |
| Abstract: | The statutory audit enhances the credibility of financial reporting by expressing an opinion on whether a company’s financial statements present a true and fair view in accordance with generally accepted accounting principles. This role can only be fulfilled if audits are performed to a high professional standard, fostering trust, protecting investors, and lowering companies’ cost of capital. Yet, intense competition in the audit market has driven down fees and put pressure on audit quality. To reconcile the need for reliable assurance with cost efficiency, effective and innovative audit methodologies are essential. The adoption of emerging technologies could help sustain this balance. From cloud computing and artificial intelligence (AI) to drone utilization, digital solutions are progressing rapidly. Advanced information technology (IT) can optimize audit procedures by enabling the handling of big data and streamlining control routines. Additionally, adopting such innovations could reduce the need for staff and help address the shortage of audit professionals. However, it is unclear which of the growing number of automated tools and techniques (ATT) will prove relevant in the medium term and demand specialized expertise. Data-driven methodologies often require proficiency in complex (statistical) techniques, posing a challenge to the technical capabilities of audit practitioners. Moreover, the actual application of these technologies remains opaque to external stakeholders. Consequently, while IT-supported procedures may enhance audit quality, they must also be perceived as such by capital market participants. Against this backdrop, my dissertation investigates a set of innovative technologies in auditing. It assesses their future relevance through comparative analysis and evaluates the current level of IT skills among practitioners. This allows for the identification of knowledge gaps, whose closure could improve audit quality and inform future research and practice. Furthermore, I explore how selected technologies influence the perceived audit quality among users of financial statements, acknowledging the audit as a credence good. The findings are presented cumulatively across three empirical studies. The first research project (Paper 1) is based on a survey of 433 external auditors and investigates two aspects: first, which emerging technologies participants believe will be crucial in the medium term, and second, how they assess their current IT skills in utilizing these tools. By comparing both indicators, my study identifies significant gaps between the actual level of expertise and the anticipated relevance of these innovations. The analysis covers 18 technologies, 14 of which are regarded as highly important by the audit profession. However, current IT knowledge is largely insufficient, raising questions about professional development. The smallest gap is observed in online meeting solutions, while the largest deficits appear for prominently discussed technologies like machine learning (ML) and robotic process automation. The IT gaps are notably more pronounced among female and older subjects, whereas a higher level of education correlates with a smaller deficit. Given that the effectiveness and efficiency of external audits also depend on the control processes of the internal audit function, which evolves at its own pace, the second research project (Paper 2) surveys 143 internal auditors to capture their views on the future relevance of emerging technologies and their current expertise. The study analyzes 19 innovations. Respondents rate 15 tools as potentially important, but their self-assessed IT skills are consistently lower. The smallest gaps appear in communication technologies (online meeting solutions and collaboration platforms), which have become well-established since the COVID-19 pandemic. The most substantial gaps concern AI-based applications, particularly ML and natural language processing. Larger deficits are observed among female participants, reinforcing the gender-related disparities noted in the first study and underscoring the need for targeted adult education initiatives. The third research project (Paper 3) is a web-based experiment conducted with 108 financial analysts. It applies a 2×2+1 between-subjects design to explore the impact of audit methodology disclosure (compared to a control group), as well as the influence of advanced IT and shared service centers (SSCs), which increasingly perform IT-enabled audit tasks. Respondents were asked to assess the likelihood of granting credit to a fictitious company, investing in its shares, either professionally or privately, and recommending the shares to third parties. Disclosing audit methodology positively affects their lending and investment decisions. No significant effects emerge for advanced IT or SSCs overall. However, experienced analysts respond more positively to digital innovations when audit procedures are not delegated to SSCs, while information on shared services tends to prompt greater caution. These interaction effects do not appear among novices. The study suggests that advanced technologies are not inherently linked to higher perceived audit quality; rather, their impact depends on who uses the innovation. Taken together, the three studies offer robust empirical insights into the digital transformation of the audit industry and highlight specific areas for regulatory, organizational, academic, and educational intervention to safeguard audit quality and reinforce market confidence. |
| Date: | 2026–01–29 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:160656 |
| By: | Francis J. DiTraglia; Craig McIntosh; Isaac Meza; Joyce Sadka; Enrique Seira |
| Abstract: | Pawn loans offer borrowers a substantial degree of repayment flexibility in exchange for a harsh penalty in case of default: forfeit of collateral worth more than the loan amount along with any payments made toward recovery. Using a large RCT conducted in Mexico City, we document key stylized facts about pawn lending and explore the merits of replacing flexibility with structured repayment contracts in this important but understudied form of credit. Our experimental design includes a mandatory frequent-payments arm, a (status quo) flexible payments arm, and a choice between the two. This design point-identifies not only the average treatment effect, but also the effects of treatment on the treated and the untreated along with the average selection on gains, allowing a rigorous study of mandates versus choice. Although the average treatment effect of assigning borrowers to structured payments is a 19% decrease in their financial cost and a 17.5% decrease in the probability of default, only 11% of borrowers choose structured repayment contracts voluntarily. We show that structured repayment reduces financial costs for nearly all borrowers, including those who would not freely choose it, and find no evidence of selection on gains in cost savings. |
| Date: | 2026–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2608.13775 |
| By: | Borchert, Lea; De Haas, Ralph; Kirschenmann, Karolin; Schultz, Alison |
| Abstract: | We study how terminated correspondent banking relationships affect international trade. Drawing on firm-level export data from emerging Europe, we show that when local banks lose access to correspondent services, their corporate clients - especially small- and medium-sized enterprises - experience significant export declines. Firms only partially offset lost exports with higher domestic sales, resulting in lower total revenues and employment. Other firms cease operations entirely. These firm-level impacts aggregate to lower product-level exports from countries more exposed to correspondent bank retrenchment. |
| Keywords: | Correspondent banking |
| JEL: | F14 F15 F36 G21 G28 L14 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19373 |