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on Payment Systems and Financial Technology |
| By: | Marie-Hélène Felt; Anna Chernesky; Angelika Welte |
| Abstract: | The Methods-of-Payment (MOP) Survey tracks consumer use of cash and other methods of payment. We present core findings from the 2024 MOP Survey, highlighting results from both the survey questionnaire and subsequent three-day shopping diary. Although cash holdings have increased in nominal terms, we find that cash usage remains unchanged since 2020. Mobile and other alternative payment methods continue to grow in importance. The 2024 MOP Survey also collects new data on how consumers perceive bank note quality. |
| Keywords: | Bank notes; Digital currencies and fintech; Financial services |
| JEL: | D83 E41 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocadp:25-12 |
| By: | Kevin McNamara; Rhea Pritham Marpu |
| Abstract: | The global financial system stands at an inflection point. Stablecoins represent the most significant evolution in banking since the abandonment of the gold standard, positioned to enable "Banking 2.0" by seamlessly integrating cryptocurrency innovation with traditional finance infrastructure. This transformation rivals artificial intelligence as the next major disruptor in the financial sector. Modern fiat currencies derive value entirely from institutional trust rather than physical backing, creating vulnerabilities that stablecoins address through enhanced stability, reduced fraud risk, and unified global transactions that transcend national boundaries. Recent developments demonstrate accelerating institutional adoption: landmark U.S. legislation including the GENIUS Act of 2025, strategic industry pivots from major players like JPMorgan's crypto-backed loan initiatives, and PayPal's comprehensive "Pay with Crypto" service. Widespread stablecoin implementation addresses critical macroeconomic imbalances, particularly the inflation-productivity gap plaguing modern monetary systems, through more robust and diversified backing mechanisms. Furthermore, stablecoins facilitate deregulation and efficiency gains, paving the way for a more interconnected international financial system. This whitepaper comprehensively explores how stablecoins are poised to reshape banking, supported by real-world examples, current market data, and analysis of their transformative potential. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.11395 |
| By: | Qifeng Tang; Yain-Whar Si |
| Abstract: | With the advancement of digital payment technologies, central banks worldwide have increasingly begun to explore the implementation of Central Bank Digital Currencies (CBDCs). This paper presents a comprehensive review of the latest developments in CBDC system design and implementation. By analyzing 135 research papers published between 2018 and 2025, the study provides an in-depth examination of CBDC design taxonomy and ecosystem frameworks. Grounded in the CBDC Design Pyramid, the paper refines and expands key architectural elements by thoroughly investigating innovations in ledger technologies, the selection of consensus mechanisms, and challenges associated with offline payments and digital wallet integration. Furthermore, it conceptualizes a CBDC ecosystem. A detailed comparative analysis of 26 existing CBDC systems is conducted across four dimensions: system architecture, ledger technology, access model, and application domain. The findings reveal that the most common configuration consists of a two-tier architecture, distributed ledger technology (DLT), and a token-based access model. However, no dominant trend has emerged regarding application domains. Notably, recent research shows a growing focus on leveraging CBDCs for cross-border payments to resolve inefficiencies and structural delays in current systems. Finally, the paper offers several forward-looking recommendations for future research. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.08880 |
| By: | Kim Huynh; Oleksandr Shcherbakov; André Stenzel |
| Abstract: | We study consumer cash inventory behavior by developing a dynamic model of forward-looking consumers and estimating structural parameters of the model using detailed consumer survey data. Consumers facing holding and withdrawal costs solve a discrete-time continuous-control dynamic programming problem to optimally use cash at the point of sale. Our findings suggest that it is crucial to account for persistent heterogeneity in consumer preferences to accurately measure the demand for cash and consumer welfare. We show that deteriorating access to cash triggers a bi-modal response. Some consumers substantially reduce or even stop the use of cash in favor of digital means of payment, while others exhibit a limited response and instead withdraw and hold larger amounts. |
| Keywords: | Bank notes, Digital currencies and fintech, Econometric and statistical methods, Financial services |
| JEL: | D12 D14 E41 E42 G21 |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocawp:25-22 |
| By: | Kundan Mukhia; SR Luwang; Md. Nurujjaman; Tanujit Chakraborty; Suman Saha; Chittaranjan Hens |
| Abstract: | Scaling laws offer a powerful lens to understand complex transactional behaviors in decentralized systems. This study reveals distinctive statistical signatures in the transactional dynamics of ERC20 tokens on the Ethereum blockchain by examining over 44 million token transfers between July 2017 and March 2018 (9-month period). Transactions are categorized into four types: EOA--EOA, EOA--SC, SC-EOA, and SC-SC based on whether the interacting addresses are Externally Owned Accounts (EOAs) or Smart Contracts (SCs), and analyzed across three equal periods (each of 3 months). To identify universal statistical patterns, we investigate the presence of two canonical scaling laws: power law distributions and temporal Taylor's law (TL). EOA-driven transactions exhibit consistent statistical behavior, including a near-linear relationship between trade volume and unique partners with stable power law exponents ($\gamma \approx 2.3$), and adherence to TL with scaling coefficients ($\beta \approx 2.3$). In contrast, interactions involving SCs, especially SC-SC, exhibit sublinear scaling, unstable power-law exponents, and significantly fluctuating Taylor coefficients (variation in $\beta$ to be $\Delta\beta = 0.51$). Moreover, SC-driven activity displays heavier-tailed distributions ($\gamma |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.04671 |
| By: | Bruce Mizrach; Nathaniel Yoshida |
| Abstract: | Two MEV builders now produce nearly 80\% of Ethereum blocks. Block builders have the ability to reorder transactions on the blockchain in a way that can be harmful to participants. We estimate they would pay in the aggregate nearly \$14 million per month to ensure that they remained in the first quartile of the block. Sandwich attacks, in which a transaction is front-run, are frequent, averaging more than one per block. Gas fees on these transactions pay for nearly 15\% of the MEV payments to the validator. These attacks have especially large marginal effects and skew the distribution. Reforms such as gas fee priority or private transaction pools might be helpful. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.04003 |
| By: | Makoza, Frank |
| Abstract: | Digital transformation has attracted attention of Government of Malawi and development partners in supporting the development of inclusive digital economy and society. However, studies on the landscape of digital transformation to establish the level of maturity of Malawi are still lacking. This paper explored the current state of inclusive digital transformation using the UNDP Digital Transformation Framework. The study analysed secondary data from gov-ernment departments and international development online databases using content analysis. The findings showed that the country was improving in pillars for digital public infrastructure, regulation of technologies and government role in leading technology developments despite not having a coordinated strategy. There were challenges in dealing with the pillars for econo-my (e.g. financial services and innovation ecosystem), connectivity (e.g. physical infrastructure) and people (e.g. low usage and adoption due to high cost of devices and low digital skills). The study offer useful insights into areas where implementation agencies, policymakers and development partners may concentrate on to achieve high maturity of digital transformation. |
| Keywords: | Digital transformation, Inclusion, Digitalization, Digital technology, Malawi |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:esprep:324136 |
| By: | Johannes Johnen; Shiva Shekhar |
| Abstract: | This paper proposes a simple yet useful framework for evaluating vertical mergers in digital markets by distinguishing between product-specific and ecosystem-specific network effects. Vis-a-vis no network effects, product-specific network effects amplify foreclosure and steering incentives, as a rival’s growth directly undermines the platform’s product value. Conversely, ecosystem-specific effects dampen foreclosure incentives, since rivals contribute to the overall value of the platform ecosystem. We develop a formal model illustrating how this distinction shapes platform behavior and competitive outcomes. We apply this distinction to real-world examples to illustrate its potential usefulness. Our distinction implies that regulators may want to adopt a stricter standard with no presumption of efficiencies where product-specific effects dominate. In contrast, when ecosystem-specific effects prevail, merger evaluation should mirror traditional vertical merger analysis. Thus, offering a more nuanced approach to merger evaluation by presenting a practical screening tool to identify problematic vertical mergers in markets featuring network effects. |
| Keywords: | network externalities, platforms, vertical integration |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12040 |
| By: | Cai, Huan (College of Business, Southern University of Science and Technology (SUSTech), Shenzhen, China); Dong, Lu (College of Business, Southern University of Science and Technology (SUSTech), Shenzhen, China); Xie, Jian (College of Business, Southern University of Science and Technology (SUSTech), Shenzhen, China) |
| Abstract: | This paper examines gender disparities in parenting in the digital domain, using a novel dataset that records the gender composition of users across more than 6, 000 app-level observations in China. Two patterns stand out. First, parenting apps are strongly feminized: women account for nearly two-thirds of users, compared to fewer than half for the typical non-parenting app. Second, the female share is highest in cities where women enjoy greater income and educational attainment, and lowest in areas marked by more entrenched gender inequality. The women most engaged in digital caregiving are therefore those best positioned to transcend traditional roles. Mechanism analysis suggests that this is not driven by broader digital fluency among affluent women, but rather reflects their intentional choice for intensive parenting practices. |
| Keywords: | Gender Inequality, Digital Technology, Parenting, Unpaid labor, China JEL Classification: J13, J16, O33 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:cge:wacage:765 |
| By: | Georges V. Houngbonon; Marc Ivaldi; Emil Palikot; Davide Strusani |
| Abstract: | Nearly half the world remains offline, and capital scarcity stalls new network buildouts. Sharing existing mobile towers could accelerate connectivity. We assemble data on 107 tower-sharing deals in 28 low-income countries (2008-20) and estimate staggered difference-in-differences effects. Two years after a transaction covering over 1, 000 towers, the PPP-adjusted mobile-price index falls USD 1.60 (s.e. 1.10) from a baseline of USD 3.16, while data prices drop USD 1.00 (0.29), baseline USD 3.41 per GB. The number of mobile connections increases. Rural internet access increases by 4.7 pp and female-headed households by 3.6 pp. Tower-sharing agreements increase product market competition as measured by Herfindahl-Hirschman Index. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.19693 |
| By: | Akhayad Loubna (ESSDL, FSJES, UMPO - Laboratoire ESSDL, faculté des sciences juridiques economique et sociale , UMP oujda) |
| Abstract: | Résumé: Ce travail de recherche examine le rôle significatif des paradigmes financiers éthiques dans la promotion de l'inclusion économique et la lutte contre la pauvreté au Maroc, où 4, 8 % de la population continue de vivre en dessous du seuil de pauvreté. Trois modèles principaux sont passés au crible : la finance islamique (ancrée dans la charia, avec des produits tels que murabaha), la microfinance éthique (illustrée par des institutions comme Al Amana) et l'investissement socialement responsable (ISR) (qui intègre des critères ESG). Ces méthodologies visent à proposer des alternatives aux systèmes bancaires classiques, qui restent souvent inaccessibles aux populations marginalisées, tout en respectant les principes de transparence, d'équité et de durabilité. Néanmoins, les progrès de la finance éthique se heurtent à de nombreux obstacles, notamment le manque de sensibilisation concernant les instruments financiers éthiques, un cadre règlementaire incomplet (notamment en ce qui concerne la microfinance et l'ISR) et la concurrence des banques traditionnelles, perçues comme plus avantageuses en termes de rentabilité. Par exemple, Al Amana, bien qu'elle ait permis à 600 000 bénéficiaires d'améliorer leurs conditions de vie et qu'elle ait créé plus de 100 000 emplois, doit faire face au risque de surendettement de sa clientèle. Pour relever ces défis, l'article propose des stratégies telles que l'innovation technologique (y compris la fintech et la blockchain), le renforcement de la littératie financière et le raffinement des réglementations pour définir les pratiques éthiques. En conclusion, l'essor de la finance éthique au Maroc dépendra de sa capacité à harmoniser performance économique et impact social, renforcée par le soutien des institutions publiques, des acteurs financiers et de la société civile. Un tel paradigme pourrait reconfigurer durablement le paysage économique marocain, le rendre plus inclusif et plus adapté aux considérations sociales et environnementales. |
| Keywords: | inclusion financière développement durable fintech blockhain investissement socialement responsable finance Microfinance, inclusion financière, développement durable, fintech, blockhain, investissement socialement responsable, finance, Microfinance |
| Date: | 2025–07–02 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05170299 |
| By: | Ahmed Mahrous; Maurantonio Caprolu; Roberto Di Pietro |
| Abstract: | Stablecoins, with a capitalization exceeding 200 billion USD as of January 2025, have shown significant growth, with annual transaction volumes exceeding 10 trillion dollars in 2023 and nearly doubling that figure in 2024. This exceptional success has attracted the attention of traditional financial institutions, with an increasing number of governments exploring the potential of Central Bank Digital Currencies (CBDCs). Although academia has recognized the importance of stablecoins, research in this area remains fragmented, incomplete, and sometimes contradictory. In this paper, we aim to address the cited gap with a structured literature analysis, correlating recent contributions to present a picture of the complex economic, technical, and regulatory aspects of stablecoins. To achieve this, we formulate the main research questions and categorize scientific contributions accordingly, identifying main results, data sources, methodologies, and open research questions. The research questions we address in this survey paper cover several topics, such as the stability of various stablecoins, novel designs and implementations, and relevant regulatory challenges. The studies employ a wide range of methodologies and data sources, which we critically analyze and synthesize. Our analysis also reveals significant research gaps, including limited studies on security and privacy, underexplored stablecoins, unexamined failure cases, unstudied governance mechanisms, and the treatment of stablecoins under financial accounting standards, among other areas. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.13883 |
| By: | Jean-Éric Pelet (IAE - IAE AMIENS); Coralie Haller (EM Strasbourg - École de Management de Strasbourg = EM Strasbourg Business School) |
| Abstract: | Purpose: This paper presents the preparation of a course aimed at enabling students to use the metaverse and TikTok platforms to increase the visibility and marketability of a fictional young winemaker's wine brand. The objective is to facilitate real-world sales of both physical and Non-fungible Tokens (NFTs) of wine bottles, while concurrently promoting the metaverse learning experience through TikTok engagement. Design/Methodology/Approach: Students are tasked with creating immersive scenes on a selected metaverse platform (Spatial) to develop a Learning Management System (LMS) for wine education. The scenes include scenarios such as a wine shop, a vineyard, and an oenology laboratory, each with game-like learning objectives, target audiences, rewards, and rules akin to a game. Findings: The course promotes experiential learning by integrating metaverse technology and social media marketing. Findings include diverse and engaging metaverse scenes, a TikTok campaign fostering brand engagement, and an overall emphasis on realistic and innovative approaches to virtual education and advertising. Practical Implications: Students gain practical experience in metaverse content creation, LMS design, and TikTok marketing. The course emphasizes the applicability of emerging technologies to real-world scenarios, preparing students for evolving professional landscapes in fields such as digital marketing, virtual education, and brand promotion. |
| Keywords: | Virtual Education, Experiential Learning, Digital Marketing, Metaverse, TikTok |
| Date: | 2025–09–01 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05176013 |
| By: | Luyun Lin; Yiqing Wang |
| Abstract: | The increasing development in the consumer credit card market brings substantial regulatory and risk management challenges. The advanced machine learning models applications bring concerns about model transparency and fairness for both financial institutions and regulatory departments. In this study, we evaluate the consistency of one commonly used Explainable AI (XAI) technology, SHAP, for variable explanation in credit card probability of default models via a case study about credit card default prediction. The study shows the consistency is related to the variable importance level and hence provides practical recommendation for credit risk management |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.01851 |
| By: | Junliang Luo; Katrin Tinn; Samuel Ferreira Duran; Di Wu; Xue Liu |
| Abstract: | Tokenized U.S. Treasuries have emerged as a prominent subclass of real-world assets (RWAs), offering cryptographically enforced, yield-bearing instruments collateralized by sovereign debt and deployed across multiple blockchain networks. While the market has expanded rapidly, empirical analyses of transaction-level behaviour remain limited. This paper conducts a quantitative, function-level dissection of U.S. Treasury-backed RWA tokens including BUIDL, BENJI, and USDY, across multi-chain: mostly Ethereum and Layer-2s. We analyze decoded contract calls to isolate core functional primitives such as issuance, redemption, transfer, and bridge activity, revealing segmentation in behaviour between institutional actors and retail users. To model address-level economic roles, we introduce a curvature-aware representation learning framework using Poincar\'e embeddings and liquidity-based graph features. Our method outperforms baseline models on our RWA Treasury dataset in role inference and generalizes to downstream tasks such as anomaly detection and wallet classification in broader blockchain transaction networks. These findings provide a structured understanding of functional heterogeneity and participant roles in tokenized Treasury in a transaction-level perspective, contributing new empirical evidence to the study of on-chain financialization. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.14808 |
| By: | Papatya Duman (Universität Bielefeld); Claus-Jochen Haake (Universität Paderborn); Alexander Koch (Universität Paderborn); Sarah Kühn (Universität Paderborn); Simon Hemmrich (Universität Paderborn); Daniel Beverungen (Universität Paderborn) |
| Abstract: | We examine the problem faced by a buyer seeking to purchase an experience good without prior knowledge of its stochastic quality. An expert who owns the product can be paid to provide a signal about its quality. Our analysis explores the impact of introducing a credible signaling mechanism for the buyer. Specifically, we propose using blockchain technology, which ensures immutability, decentralization, privacy, and transparency, to store the signal. Our findings reveal that this approach reduces the number of possible equilibria while preserving the “good equilibrium”, in which information is both acquired and accurately transmitted. Consequently, the use of blockchain tech-nology mitigates the equilibrium coordination problem and improves the provision of credible information. |
| Keywords: | Blockchain, Signaling, Asymmetric Information |
| JEL: | C72 D82 D47 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:pdn:dispap:152 |
| By: | Mouzoun Zakarya (Kénitra - Ecole nationale de commerce et gestion Ibn Tofail); Samiha Bakkali (Kénitra - Ecole nationale de commerce et gestion Ibn Tofail); Ammi Anouar (Kénitra - Ecole nationale de commerce et gestion Ibn Tofail) |
| Abstract: | This study investigates the impact of financial literacy on promoting financial inclusion in Morocco, specifically examining how individuals' comprehension and management of personal finances influence their access to, and utilization of, formal financial services. Financial literacy is conceptualized as an essential component of human capital that enables individuals to make informed financial decisions. It encompasses multiple interrelated dimensions, including fundamental financial knowledge, financial culture, as well as competencies related to managing and effectively utilizing financial information. To achieve this objective, the study applied a mixedmethod research approach, involving quantitative surveys through structured questionnaires and qualitative semistructured interviews, conducted with a representative sample of Moroccan citizens aged 15 years and older. The data collection phase was conducted over a twelve-month period, from September 2022 to September 2023. For the analysis, SPSS software was employed for quantitative data processing, whereas NVivo software facilitated the qualitative evaluation of interview data. The findings demonstrate that despite respondents exhibiting a satisfactory level of financial literacy, this alone does not result in widespread financial inclusion. Various significant barriers were identified, particularly prohibitive costs associated with financial services, persistent geographical limitations, and a general lack of trust in financial institutions. Furthermore, insufficient financial literacy was highlighted as the primary obstacle impeding access to financial services, followed by geographic constraints and service-related expenses. To address these challenges, the study advocates systematically integrating financial education into educational curricula at all levels and implementing extensive public awareness initiatives. Additionally, it recommends reducing financial service costs, enhancing the quality of financial services, and fostering technological innovation, which collectively could significantly improve financial inclusion within Morocco. |
| Abstract: | L'objectif de cet article est d'examiner les effets de la littératie financière sur le renforcement de l'inclusion financière au Maroc. Plus précisément, l'étude analyse dans quelle mesure la compréhension et la gestion adéquate des finances personnelles influencent l'accès et l'utilisation effective des services financiers formels. La littératie financière y est appréhendée comme une composante centrale du capital humain, permettant aux individus de prendre des décisions financières avisées. À cet égard, plusieurs dimensions essentielles sont abordées, telles que les connaissances financières de base, la culture financière ainsi que les compétences liées à la gestion et au traitement de l'information financière. Afin de répondre à cet objectif, une approche méthodologique mixte combinant enquêtes par questionnaires et entretiens semi-structurés a été mobilisée auprès d'un échantillon représentatif de citoyens marocains âgés de 15 ans et plus. L'étude s'est déroulée sur une période de douze mois, allant de septembre 2022 à septembre 2023. Les données recueillies ont été traitées au moyen du logiciel SPSS pour l'analyse quantitative et du logiciel NVivo pour l'analyse qualitative. Les résultats indiquent qu'un niveau relativement élevé de littératie financière ne conduit pas nécessairement à une inclusion financière généralisée, essentiellement en raison des coûts élevés des services financiers, des barrières géographiques persistantes et d'une confiance limitée dans les institutions financières. En outre, le manque de littératie financière ressort comme principal obstacle à l'accès aux services financiers, suivi par les barrières géographiques et les coûts associés aux services. L'étude propose d'intégrer systématiquement l'éducation financière dans les programmes scolaires et les campagnes de sensibilisation publiques, et recommande une réduction des coûts des services financiers, l'amélioration de leur qualité ainsi que l'encouragement de l'innovation technologique pour renforcer significativement l'inclusion financière au Maroc. |
| Keywords: | Littératie financière Inclusion financière Services financiers Technologies financières Maroc Classification JEL : G53 Type de l'article : Recherche empirique Financial literacy financial inclusion financial services financial technologies Morocco JEL Classification: G53 Paper type: Empirical research, Littératie financière, Inclusion financière, Services financiers, Technologies financières, Maroc Classification JEL : G53 Type de l'article : Recherche empirique Financial literacy, financial inclusion, financial services, financial technologies, Morocco JEL Classification: G53 Paper type: Empirical research |
| Date: | 2025–04–26 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05154529 |
| By: | Gómez-biscarri Javier; López-espinosa Germán; Martinez Santos Fernando (European Commission - JRC) |
| Abstract: | In this paper we investigate the role played by banks in financing European fintech startups. We postulate that this role may be influenced by two conflicting objectives. First, banks could be motivated by value considerations, in that the objective would be to help the fintech scale-up and reach a successful exit, so value can be captured from returns on equity or debt investments. Alternatively, given that fintechs can be viewed as substitutes to banks, investment in fintechs might be motivated by a desire to curb down competition (“buying out competitors”). We examine these conflicting objectives using data on investments made by EU and non-EU banks in fintech startups, and take advantage of an exogenous shock to fintech value provided by the EU’s PSD2 policy. Our results suggest that EU banks are driven by the motive of reducing competition. On the contrary, the behavior of non-EU banks seems to be driven by the value capturing motive, and this may have generated a substitution after PSD2 in non-EU bank financing of EU fintechs towards debt. Our findings suggest that EU fintechs may need to reduce their reliance on bank financing in order to close the financing gap and achieve successful scaling up. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:jrs:wpaper:202507 |
| By: | W\v{e}i Zh\=ang |
| Abstract: | This paper explores neural network-based approaches for algorithmic trading in cryptocurrency markets. Our approach combines multi-timeframe trend analysis with high-frequency direction prediction networks, achieving positive risk-adjusted returns through statistical modeling and systematic market exploitation. The system integrates diverse data sources including market data, on-chain metrics, and orderbook dynamics, translating these into unified buy/sell pressure signals. We demonstrate how machine learning models can effectively capture cross-timeframe relationships, enabling sub-second trading decisions with statistical confidence. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02356 |
| By: | Yihao Ang; Qiang Wang; Qiang Huang; Yifan Bao; Xinyu Xi; Anthony K. H. Tung; Chen Jin; Zhiyong Huang |
| Abstract: | Synthetic time series are essential tools for data augmentation, stress testing, and algorithmic prototyping in quantitative finance. However, in cryptocurrency markets, characterized by 24/7 trading, extreme volatility, and rapid regime shifts, existing Time Series Generation (TSG) methods and benchmarks often fall short, jeopardizing practical utility. Most prior work (1) targets non-financial or traditional financial domains, (2) focuses narrowly on classification and forecasting while neglecting crypto-specific complexities, and (3) lacks critical financial evaluations, particularly for trading applications. To address these gaps, we introduce \textsf{CTBench}, the first comprehensive TSG benchmark tailored for the cryptocurrency domain. \textsf{CTBench} curates an open-source dataset from 452 tokens and evaluates TSG models across 13 metrics spanning 5 key dimensions: forecasting accuracy, rank fidelity, trading performance, risk assessment, and computational efficiency. A key innovation is a dual-task evaluation framework: (1) the \emph{Predictive Utility} task measures how well synthetic data preserves temporal and cross-sectional patterns for forecasting, while (2) the \emph{Statistical Arbitrage} task assesses whether reconstructed series support mean-reverting signals for trading. We benchmark eight representative models from five methodological families over four distinct market regimes, uncovering trade-offs between statistical fidelity and real-world profitability. Notably, \textsf{CTBench} offers model ranking analysis and actionable guidance for selecting and deploying TSG models in crypto analytics and strategy development. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02758 |
| By: | Simon Hemmrich (Paderborn University); Ulvi Ibrahimli (Universität Würzburg) |
| Abstract: | In marketplaces, reputation is built upon observable qualities, such as evidence of customer satisfaction, which signal trustworthiness. Reputation systems, here conceptualized as abstract social systems, leverage systems-theoretical concepts to facilitate trust formation. However, current scholarly discourse on reputation systems is predominantly technical, often neglecting integrated incentive mechanisms of social and technical layers. Addressing this gap, our study employs a systems-theoretical perspective to harmonize social and technical design layers at a unified level of abstraction, offering a novel framework for blockchain-based reputation systems. By applying key concepts from social systems theory—observation, selection, communication, system trust, and elements/relations— we propose a reconceptualization of reputation system design that aligns social and technical layers. Our findings show that systems thinking provides a cohesive abstraction level, making it valuable for crafting new IS artifacts. We contribute to cumulative knowledge of conceptualizing and designing information systems by illustrating how systems concepts can scaffold more integrative IS design. |
| Keywords: | Reputation Systems, Systems Thinking, Blockchain Technology, Conceptualization, Tipping |
| JEL: | M15 D83 L86 O33 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:pdn:dispap:151 |
| By: | Imen Mahmoud; Andrei Velichko |
| Abstract: | This study proposes a novel methodological framework integrating a LightGBM regression model and genetic algorithm (GA) optimization to systematically evaluate the contribution of COVID-19-related indicators to Bitcoin return prediction. The primary objective was not merely to forecast Bitcoin returns but rather to determine whether including pandemic-related health data significantly enhances prediction accuracy. A comprehensive dataset comprising daily Bitcoin returns and COVID-19 metrics (vaccination rates, hospitalizations, testing statistics) was constructed. Predictive models, trained with and without COVID-19 features, were optimized using GA over 31 independent runs, allowing robust statistical assessment. Performance metrics (R2, RMSE, MAE) were statistically compared through distribution overlaps and Mann-Whitney U tests. Permutation Feature Importance (PFI) analysis quantified individual feature contributions. Results indicate that COVID-19 indicators significantly improved model performance, particularly in capturing extreme market fluctuations (R2 increased by 40%, RMSE decreased by 2%, both highly significant statistically). Among COVID-19 features, vaccination metrics, especially the 75th percentile of fully vaccinated individuals, emerged as dominant predictors. The proposed methodology extends existing financial analytics tools by incorporating public health signals, providing investors and policymakers with refined indicators to navigate market uncertainty during systemic crises. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.00078 |
| By: | Chi-Sheng Chen; Aidan Hung-Wen Tsai |
| Abstract: | The rise of decentralized finance (DeFi) has created a growing demand for accurate yield and performance forecasting to guide liquidity allocation strategies. In this study, we benchmark six models, XGBoost, Random Forest, LSTM, Transformer, quantum neural networks (QNN), and quantum support vector machines with quantum feature maps (QSVM-QNN), on one year of historical data from 28 Curve Finance pools. We evaluate model performance on test MAE, RMSE, and directional accuracy. Our results show that classical ensemble models, particularly XGBoost and Random Forest, consistently outperform both deep learning and quantum models. XGBoost achieves the highest directional accuracy (71.57%) with a test MAE of 1.80, while Random Forest attains the lowest test MAE of 1.77 and 71.36% accuracy. In contrast, quantum models underperform with directional accuracy below 50% and higher errors, highlighting current limitations in applying quantum machine learning to real-world DeFi time series data. This work offers a reproducible benchmark and practical insights into model suitability for DeFi applications, emphasizing the robustness of classical methods over emerging quantum approaches in this domain. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.02685 |