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on Payment Systems and Financial Technology |
| By: | Ozili, Peterson K |
| Abstract: | This study presents an overview of digital financial inclusion research and developments around the world. The literature has paid little attention to the uneven digital financial inclusion developments in different regions of the world. There is a need for an overview of the existing digital financial inclusion research and developments around the world to gain insight into digital financial inclusion trends and to chart some directions for future research. It was shown that digital financial inclusion has a beneficial positive effect on wellbeing and society. There are uneven positive developments in digital financial inclusion across regions. The determinants of digital financial inclusion are varied according to regions. Every region is faced with a unique set of challenges that limit progress in digital financial inclusion. |
| Keywords: | financial inclusion, digital financial inclusion, digital technology, fintech, Africa, Europe, Asia, Australia, America. |
| JEL: | G21 G23 G28 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125394 |
| By: | Iustina Alina Boitan (Bucharest University of Economic Studies); Thomas Paulovici (Bucharest University of Economic Studies, Doctoral School of Finance) |
| Abstract: | The paper investigates the potential of Central Bank Digital Currencies (CBDCs) to enhance financial inclusion by improving access to digital financial services for unbanked populations, particularly in developing economies where the issue of financial exclusion and low access to financial services is endemic. Our analytical interest substantiates inthe growing interest exhibited by central banks and international financial institutions regarding the emergence of this new type of state-backed digital currency. CBDCs represent digital forms of central bank money that may serve as complement to cash and other payment instruments in a secure, efficient, and accessible payment environment, unlike cryptocurrencies, which operate on decentralized networks. While CBDCs offer promising features such as cost efficiency, security, and accessibility, several challenges, including design deficits, digital and financial literacy barriers, and regulatory considerations must be addressed to ensure their effectiveness. Through a systematic review of existing academic literature, empirical evidence and case studies from some developing or emerging economies, this study examines positive impacts as well as the challenges of these CBDCs in promoting financial inclusion. In particular, it investigates the theoretical mechanisms through which CBDCs could enhance access to financial services, and the challenges that may hinder their effectiveness. Furthermore, the analysis draws on a series of case studies from some of the early CBDC adopters, to identify the real-world impact of CBDCs on financial inclusion. The findings suggest that while CBDCs have the potential to bridge financial gaps, their success depends on strategic design and implementation as well as on complementary policies. The paper further discusses policy recommendations for designing CBDCs that maximize their potential as an inclusion-enhancing tool. |
| Keywords: | Central Bank Digital Currencies, Central Banks, Financial Inclusion, Digital Payments, Developing Economies, eNaira, Sand Dollar |
| JEL: | E50 |
| URL: | https://d.repec.org/n?u=RePEc:sek:iefpro:15116731 |
| By: | Chenghao Liu; Aniket Mahanti; Ranesh Naha; Guanghao Wang; Erwann Sbai |
| Abstract: | As cryptocurrencies gain popularity, the digital asset marketplace becomes increasingly significant. Understanding social media signals offers valuable insights into investor sentiment and market dynamics. Prior research has predominantly focused on text-based platforms such as Twitter. However, video content remains underexplored, despite potentially containing richer emotional and contextual sentiment that is not fully captured by text alone. In this study, we present a multimodal analysis comparing TikTok and Twitter sentiment, using large language models to extract insights from both video and text data. We investigate the dynamic dependencies and spillover effects between social media sentiment and cryptocurrency market indicators. Our results reveal that TikTok's video-based sentiment significantly influences speculative assets and short-term market trends, while Twitter's text-based sentiment aligns more closely with long-term dynamics. Notably, the integration of cross-platform sentiment signals improves forecasting accuracy by up to 20%. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.15825 |
| By: | Sławomir Grzelczak; Ewa Balcerowicz |
| Abstract: | The publication examines the growing popularity and implications of the Buy Now, Pay Later (BNPL) financial model in Poland and globally. It features expert analyses and discussions from a seminar held on March 14, 2024, including insights from key players like PayPo, PKO BP, and the Credit Information Bureau (BIK). |
| Keywords: | online shopping, financial services, deferred payment, deferred payments market, credit market, bank, fintech, Poland |
| JEL: | G21 G23 |
| Date: | 2025–01–17 |
| URL: | https://d.repec.org/n?u=RePEc:sec:mbanks:0180 |
| By: | Fascione, Luisa; Scheubel, Beatrice; Stracca, Livio; Wildmann, Nadya; Jacoubian, Juan Ignacio |
| Abstract: | The March 2023 banking turmoil has intensified discussions whether social media and the digitalisation of finance have become significant factors in driving severe deposit outflows. We introduce the concept of deposits-at-risk and utilize quantile regressions for disentangling determinants of stressed outflows at the lowest tail of the distribution. For a sample of large banks directly supervised by the ECB, our findings indicate that an increased use of online banking services leads to a small amplification of extreme deposit outflows, but this effect is not further exacerbated by the availability of a mobile banking app. Online banking use and availability of a mobile app do not have a causal effect on deposit volatility in normal times. Finally, social media are impactful only in idiosyncratic cases. JEL Classification: G20, G21, G28 |
| Keywords: | banking regulation, bank runs, deposit outflows, liquidity risk |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbwps:20253092 |
| By: | Christopher J. Waller |
| Date: | 2025–08–20 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgsq:101449 |
| By: | Timothy Dombrowski; V. Carlos Slawson Jr |
| Abstract: | Can the general structure of a mortgage-backed security (MBS) contract be programmatically represented through the use of decentralized autonomous organizations (DAOs)? Such an approach could allow for the portfolio of loans to be managed by investors in a trustless and transparent way. The focus and scope of this paper is to explore the potential for applying the tools of modern fintech, such as asset tokenization, smart contracts, and DAOs, to reconstruct traditional structured products that have a greater degree of transparency and traceability. MBS investors face considerable value uncertainty as time increases between the actual occurrence (or non-occurrence) of cash flows and subsequent reporting. Given that an MBS is a financial contract, it should be expressible logically using the Algorithmic Contract Types Unified Standards (ACTUS). Since each underlying mortgage in an MBS derives its cash flows in a prescribed way over the life of the contract, implementation on a public blockchain could enable real-time ratings systems, improving market efficiency. We explore the potential for creating formal algorithmic designs of MBS-DAOs that incorporate individual mortgages, the underlying real estate assets (collateral), and any loan guarantees. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.05439 |
| By: | Michelle W. Bowman |
| Date: | 2025–08–19 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgsq:101443 |
| By: | Xinyu Li |
| Abstract: | Persistent financial frictions - including price volatility, constrained credit access, and supply chain inefficiencies - have long hindered productivity and welfare in the global agricultural sector. This paper provides a theoretical and applied analysis of how fiat-collateralized stablecoins, a class of digital currency pegged to a stable asset like the U.S. dollar, can address these long-standing challenges. We develop a farm-level profit maximization model incorporating transaction costs and credit constraints to demonstrate how stablecoins can enhance economic outcomes by (1) reducing the costs and risks of cross-border trade, (2) improving the efficiency and transparency of supply chain finance through smart contracts, and (3) expanding access to credit for smallholder farmers. We analyze key use cases, including parametric insurance and trade finance, while also considering the significant hurdles to adoption, such as regulatory uncertainty and the digital divide. The paper concludes that while not a panacea, stablecoins represent a significant financial technology with the potential to catalyze a paradigm shift in agricultural economics, warranting further empirical investigation and policy support. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.14970 |
| By: | Grzegorz Dudek; Witold Orzeszko; Piotr Fiszeder |
| Abstract: | Cryptocurrency markets are characterized by extreme volatility, making accurate forecasts essential for effective risk management and informed trading strategies. Traditional deterministic (point) forecasting methods are inadequate for capturing the full spectrum of potential volatility outcomes, underscoring the importance of probabilistic approaches. To address this limitation, this paper introduces probabilistic forecasting methods that leverage point forecasts from a wide range of base models, including statistical (HAR, GARCH, ARFIMA) and machine learning (e.g. LASSO, SVR, MLP, Random Forest, LSTM) algorithms, to estimate conditional quantiles of cryptocurrency realized variance. To the best of our knowledge, this is the first study in the literature to propose and systematically evaluate probabilistic forecasts of variance in cryptocurrency markets based on predictions derived from multiple base models. Our empirical results for Bitcoin demonstrate that the Quantile Estimation through Residual Simulation (QRS) method, particularly when applied to linear base models operating on log-transformed realized volatility data, consistently outperforms more sophisticated alternatives. Additionally, we highlight the robustness of the probabilistic stacking framework, providing comprehensive insights into uncertainty and risk inherent in cryptocurrency volatility forecasting. This research fills a significant gap in the literature, contributing practical probabilistic forecasting methodologies tailored specifically to cryptocurrency markets. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.15922 |
| By: | Austin Kennedy |
| Abstract: | This paper examines fiscal policy spillovers through informal international financial channels, using the US stimulus checks as a positive, sudden, and direct fiscal shock. I utilize granular, transaction-level cryptocurrency data combined with an algorithm to probabilistically identify cross-border "crypto vehicle" transactions to construct bilateral cryptocurrency flows between countries. Using a difference-in-differences strategy, I compare cryptocurrency outflows between the US and other high-income countries and find a sharp but temporary increase in cryptocurrency outflows as a result of the direct stimulus. I quantify the fiscal spillover relative to expenditure and place an upper bound of 2.52% through this channel. This implies that fiscal spillovers through remittance channels are likely modest in size. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.06662 |
| By: | Schubart, Constantin; Glaubert, Nele |
| Abstract: | Corporate communication is becoming more important, especially in the digital space. Social media platforms are key channels for professional interaction, and the way executives present themselves online strongly influences public perception. This study examines the LinkedIn communication of Sparkassen board members, who, as leaders, have a special responsibility for clear and professional communication. To analyze their communication, the study uses the models of Paul Watzlawick and Friedemann Schulz von Thun. These models help assess how well board members present their roles, responsibilities, and corporate values on LinkedIn. Based on these theories, specific criteria are developed to evaluate their communication. The results show both strengths and areas for improvement. While some board members use LinkedIn effectively to communicate their professional role and engage with others, some aspects of their communication could be improved. Based on these findings, the study develops a code of conduct. This guideline, built on the research results, aims to improve the professional and responsible digital communication of Sparkassen board members. It provides recommendations for a consistent, trustworthy, and transparent online presence. |
| Keywords: | Digital corporate communication, Sparkassen, board members, ethical and social responsibility, code of conduct |
| JEL: | M12 M14 M31 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:iubhhr:324645 |
| By: | Kong, Ray Wai Man (Eagle Nice Ltd) |
| Abstract: | This research proposes integrating real-world assets (RWAs) into a blockchain-based supply chain to address traditional challenges of transparency, inefficiency, and security. The framework supports both centralized and decentralized operations within a consortium, ensuring flexibility for diverse organizational needs. Security features include private transactions via Quorum and Hyperledger Besu clients, asymmetric encryption for app-to-app messaging, and confined nodes/services to specific environments. Scalability is achieved through multiple blockchain networks with firewall isolation, while optional cloud integrations enhance efficiency. Organizational identities are managed securely using digital certificates, and a granular block explorer ensures transparency and accountability. This integration improves efficiency, transparency, and trust in food supply chains, benefiting all stakeholders. The proposed RWAs system in the case study is designed with flexibility in mind, allowing for both centralized and decentralized consortium operations. This dual capability ensures that organizations can choose the operational structure that best suits their needs, whether controlled by a single entity or shared across multiple participants. Additionally, the system supports tiered subscriptions within a consortium, enabling diverse organizations with varying requirements to coexist harmoniously. In conclusion, this research demonstrates how integrating real-world assets into a blockchain-based food supply chain can significantly improve efficiency, transparency, and trust. By addressing critical challenges through innovative use of technology, the proposed system offers a robust framework for modernizing food supply chains, ultimately benefiting all stakeholders from producers to consumers. |
| Date: | 2025–08–12 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:2wh5y_v1 |
| By: | Milan Pontiggia (MAGEFI - University of Bordeaux, France) |
| Abstract: | We assess the applicability of rough volatility models to Bitcoin realised volatility using the normalised p-variation framework of Cont and Das (2024). Applying this model free estimator to high-frequency Bitcoin data from 2017 to 2024 across multiple sampling resolutions, we find that the normalised statistic remains strictly negative throughout, precluding the estimation of a valid roughness index. Stationarity tests and robustness checks reveal no significant evidence of non-stationarity or structural breaks as explanatory factors. Instead, convergent evidence from three complementary diagnostics, namely multifractal detrended fluctuation analysis, log-log moment scaling, and wavelet leaders, reveals a multifractal structure in Bitcoin volatility. This scale-dependent behaviour violates the homogeneity assumptions underlying rough volatility estimation and accounts for the estimator's systematic failure. These findings suggest that while rough volatility models perform well in traditional markets, they are structurally misaligned with the empirical features of Bitcoin volatility. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.00575 |
| By: | Qizhao Chen |
| Abstract: | This paper presents a dynamic cryptocurrency portfolio optimization strategy that integrates technical indicators and sentiment analysis to enhance investment decision-making. The proposed method employs the 14-day Relative Strength Index (RSI) and 14-day Simple Moving Average (SMA) to capture market momentum, while sentiment scores are extracted from news articles using the VADER (Valence Aware Dictionary and sEntiment Reasoner) model, with compound scores quantifying overall market tone. The large language model Google Gemini is used to further verify the sentiment scores predicted by VADER and give investment decisions. These technical indicator and sentiment signals are incorporated into the expected return estimates before applying mean-variance optimization with constraints on asset weights. The strategy is evaluated through a rolling-window backtest over cryptocurrency market data, with Bitcoin (BTC) and an equal-weighted portfolio of selected cryptocurrencies serving as benchmarks. Experimental results show that the proposed approach achieves a cumulative return of 38.72, substantially exceeding Bitcoin's 8.85 and the equal-weighted portfolio's 21.65 over the same period, and delivers a higher Sharpe ratio (1.1093 vs. 0.8853 and 1.0194, respectively). However, the strategy exhibits a larger maximum drawdown (-18.52%) compared to Bitcoin (-4.48%) and the equal-weighted portfolio (-11.02%), indicating higher short-term downside risk. These results highlight the potential of combining sentiment and technical signals to improve cryptocurrency portfolio performance, while also emphasizing the need to address risk exposure in volatile markets. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.16378 |
| By: | Ivan Letteri |
| Abstract: | The detection of outliers within cryptocurrency limit order books (LOBs) is of paramount importance for comprehending market dynamics, particularly in highly volatile and nascent regulatory environments. This study conducts a comprehensive comparative analysis of robust statistical methods and advanced machine learning techniques for real-time anomaly identification in cryptocurrency LOBs. Within a unified testing environment, named AITA Order Book Signal (AITA-OBS), we evaluate the efficacy of thirteen diverse models to identify which approaches are most suitable for detecting potentially manipulative trading behaviours. An empirical evaluation, conducted via backtesting on a dataset of 26, 204 records from a major exchange, demonstrates that the top-performing model, Empirical Covariance (EC), achieves a 6.70% gain, significantly outperforming a standard Buy-and-Hold benchmark. These findings underscore the effectiveness of outlier-driven strategies and provide insights into the trade-offs between model complexity, trade frequency, and performance. This study contributes to the growing corpus of research on cryptocurrency market microstructure by furnishing a rigorous benchmark of anomaly detection models and highlighting their potential for augmenting algorithmic trading and risk management. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.14960 |
| By: | Moïse, Randy Kambana |
| Abstract: | While natural resource wealth should, in theory, fuel development, many extractive economies remain structurally excluded from financial services. This paper investigates the hypothesis of a « financial exclusion curse » in resource-rich African countries, by empirically comparing them to resource-poor but financially inclusive peers. Using Propensity Score Matching, the Synthetic Control Method, and dynamic panel GMM models, we demonstrate a robust negative relationship between resource dependency and financial inclusion. Yet, comparative insights from Southeast Asia and Latin America reveal that inclusive financial ecosystems can flourish—even in rent-driven contexts—when institutional quality, digital innovation, and proactive policy align. Our findings call for a paradigm shift: beyond banking access, states must reshape financial infrastructures to democratize opportunity in resource economies. |
| Date: | 2025–08–09 |
| URL: | https://d.repec.org/n?u=RePEc:osf:socarx:qpz6n_v1 |
| By: | Klarl, Torben; Kritikos, Alexander S.; Poghosyan, Knarik |
| Abstract: | While Equity Crowdfunding (ECF) platforms are a virtual space for raising funds, geography remains relevant. To determine how location matters for entrepreneurs using equity crowdfunding (ECF), we analyze the spatial distribution of successful ECF campaigns and the spatial relationship between ECF campaigns and traditional investors, such as banks and venture capitalists (VCs). Using data from the two leading German platforms - Companisto and Seedmacht - we employ spatial eigenvalue filtering and negative binomial estimations. In addition, we introduce an event study based on the implementation of the Small Investor Protection Act in Germany allowing us to obtain causal evidence. Our combined analysis reveals a significant geographic concentration of successful ECF campaigns in some, but not all, dense areas. ECF campaigns tend to cluster in dense areas with VC activity, while they are less prevalent in dense areas with high banking activity, and are rarely found in rural areas. Thus, rather than closing the so-called regional funding gap, our results suggest that, from a spatial perspective, ECF fills the gap when firms in dense areas seek external financing below the minimum equity threshold offered by VCs and when there are few banks offering loans. |
| Keywords: | Crowdfunding, Finance Geography, Entrepreneurial Finance, Venture Capital (VC) Proximity |
| JEL: | G30 L26 M13 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1654 |
| By: | Ozili, Peterson K |
| Abstract: | This study examines what constitutes social in social finance. It addresses the lack of understanding of the multifaceted ways in which social finance might be social. The common understanding is that social finance is only social in its use. This study challenges this narrow premise and argues that social finance can be social in its attributes both in its source, uses, infrastructure, policy and design. In other words, social finance can be social in (i) its source, (ii) its uses, (iii) the policy that enables social financing, (iv) the infrastructure used to facilitate social financing, and (iv) the nature or design of the contract that produces the financial instruments used to raise social funds. The implication is that social finance mechanisms can be designed to be social in several ways. Understanding the different ways in which social finance can be social will ensure that we do not dismiss emerging social finance innovations that are not social in their use, but are social in other aspects. |
| Keywords: | social finance, green finance, digital finance, society, financial services, loans |
| JEL: | G21 G23 Q01 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125396 |
| By: | Olivia Lu (Hamilton High School) |
| Abstract: | Financial exclusion remains one of the most persistent barriers to economic development, constraining private-sector growth, limiting poverty reduction, and perpetuating economic disparities. Bilateral foreign aid has long been a tool for addressing financial sector deficiencies, yet its impact on financial inclusion remains debated. Can aid meaningfully expand access to credit, increase financial intermediation, and strengthen institutional governance? Or does it merely act as a temporary fiscal injection with limited structural impact? To assess how foreign aid influences financial sector development and financial inclusion, this study analyzes the cases of Bangladesh, Rwanda, and Mozambique from 2012-22, focusing on both formal and informal financial intermediaries. This paper analyzes macroeconomic data, financial sector indicators, aid disbursement trends, and governance metrics to empirically evaluate the relationship between aid and financial inclusion. Using sectoral disaggregation of aid flows and institutional effectiveness scores, the research traces the pathways through which aid channels into financial systems and whether it translates into higher private-sector credit, reduced borrowing constraints, improved banking efficiency, and sustainable microfinance growth. Aid flows are analyzed across three key subsectors: (1) Financial Policy and Administrative Management, (2) Formal Financial Intermediaries, and (3) Informal Financial Intermediaries, providing a granular assessment of how different forms of aid impact banking stability, microfinance participation, and credit accessibility across varying institutional environments.The impact of foreign aid on financial inclusion depends on how well funding aligns with governments? priorities in existing policies. Bangladesh and Rwanda have seen stronger growth in microfinance, digital banking, and SME credit, while Mozambique has struggled due to weak institutions and economic instability. Policy aid has helped Rwanda strengthen financial regulations, but in Mozambique, even large inflows have failed to improve oversight. But aid to banks does not always increase lending. Bangladesh saw improved efficiency, but Rwanda and Mozambique still face high interest rate spreads, which could point to deeper financial inefficiencies. Finally, microfinance aid is most effective when paired with strong local policies. While Bangladesh and Rwanda sustain growth even as aid declines, Mozambique?s financial access stalls once donor support fades, showing that without strong institutions, financial inclusion remains fragile.Ultimately, this study contributes to the literature on international aid and development by identifying the conditions under which aid strengthens financial systems rather than acting as a temporary economic stimulus. To be truly effective, donor assistance must go beyond short-term interventions and support structural changes that allow financial sectors to grow independently. |
| Keywords: | Foreign aid, Financial inclusion, Microfinance, Governance, Banking efficiency |
| JEL: | F35 O16 G21 |
| URL: | https://d.repec.org/n?u=RePEc:sek:iefpro:15116716 |
| By: | Xue Dong He; Chen Yang; Yutian Zhou |
| Abstract: | Decentralized exchanges (DEXs) are alternative venues to centralized exchanges (CEXs) for trading cryptocurrencies and have become increasingly popular. An arbitrage opportunity arises when the exchange rate of two cryptocurrencies in a DEX differs from that in a CEX. Arbitrageurs can then trade on the DEX and CEX to make a profit. Trading on the DEX incurs a gas fee, which determines the priority of the trade being executed. We study a gas-fee competition game between two arbitrageurs who maximize their expected profit from trading. We derive the unique symmetric mixed Nash equilibrium and find that (i) the arbitrageurs may choose not to trade when the arbitrage opportunity and liquidity is small; (ii) the probability of the arbitrageurs choosing a higher gas fee is lower; (iii) the arbitrageurs pay a higher gas fee and trade more when the arbitrage opportunity becomes larger and when liquidity becomes higher; (iv) the arbitrageurs' expected profit could increase with arbitrage opportunity and liquidity. The above findings are consistent with our empirical study. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.08302 |
| By: | Yueyi Wang; Qiyao Wei |
| Abstract: | In this study, we wish to showcase the unique utility of large language models (LLMs) in financial semantic annotation and alpha signal discovery. Leveraging a corpus of company-related tweets, we use an LLM to automatically assign multi-label event categories to high-sentiment-intensity tweets. We align these labeled sentiment signals with forward returns over 1-to-7-day horizons to evaluate their statistical efficacy and market tradability. Our experiments reveal that certain event labels consistently yield negative alpha, with Sharpe ratios as low as -0.38 and information coefficients exceeding 0.05, all statistically significant at the 95\% confidence level. This study establishes the feasibility of transforming unstructured social media text into structured, multi-label event variables. A key contribution of this work is its commitment to transparency and reproducibility; all code and methodologies are made publicly available. Our results provide compelling evidence that social media sentiment is a valuable, albeit noisy, signal in financial forecasting and underscore the potential of open-source frameworks to democratize algorithmic trading research. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.07408 |
| By: | AWOLAJA AYODEJI MUYIDEEN (EKITI STATE UNIVERSITY, ADO-EKITI); AJAYI IBIDOLAPO EZEKIEL (EKITI STATE UNIVERSITY, ADO-EKITI); OSASONA ADEDEJI VISCKER (EKITI STATE UNIVERSITY, ADO-EKITI); OSASONA ADEDEJI VISCKER (EKITI STATE UNIVERSITY, ADO-EKITI) |
| Abstract: | This article investigated the relationship between managerial efficiency and profitability in Deposit Money Banks in Nigeria, focusing on the period from 2014 to 2023. Employing an ex-post facto design, the research analyzed historical data from the audited financial statements of a purposively selected sample of 10 listed banks. This methodology allows for an objective examination of how managerial efficiency impacts profitability metrics such as return on investment (ROI) and return on assets (ROA). The analysis incorporated descriptive statistics, correlation analysis, panel regression, and ANOVA to assess the efficiency-profitability dynamics within the sector. The findings revealed a significant positive relationship between the loan-to-deposit ratio (LDR) and the financial performance of Deposit Money Banks, with a coefficient of 0.6877 (p=0.000 |
| Keywords: | Managerial Efficiency, Profitability, Return on Investment, Loan to Deposit Ratio |
| JEL: | E59 H80 H89 |
| URL: | https://d.repec.org/n?u=RePEc:sek:iefpro:15116637 |
| By: | Ying Chen; Mingyi Li; Jiaming Mao; Jingyi Zhou |
| Abstract: | We study consumption stimulus with digital coupons, which provide time-limited subsidies contingent on minimum spending. We analyze a large-scale program in China and present five main findings: (1) the program generates large short-term effects, with each $\yen$1 of government subsidy inducing $\yen$3.4 in consumer spending; (2) consumption responses vary substantially, driven by both demand-side factors (e.g., wealth) and supply-side factors (e.g., local consumption amenities); (3) The largest spending increases occur among consumers whose baseline spending already exceeds coupon thresholds and for whom coupon subsidies should be equivalent to cash, suggesting behavioral motivations; (4) high-response consumers disproportionately direct their spending toward large businesses, leading to a regressive allocation of stimulus benefits; and (5) targeting the most responsive consumers can double total stimulus effects. A hybrid design combining targeted distribution with direct support to small businesses improves both the efficiency and equity of the program. |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2507.01365 |
| By: | International Monetary Fund |
| Abstract: | Cyber risk is highly relevant to the financial sector and financial stability of Canada. According to the Canadian Centre for Cyber Security (CCCS), in 2021, 23.9 percent of finance and insurance enterprises were impacted by cyber security incidents, placing Finance into the top four of the Critical Infrastructure Sectors being targeted by cyber actors. Cyber-attacks on the financial sector have tripled from 2022 to 2023 and these cyber-attacks against Canadian financial institutions (FIs) are increasing in both frequency and sophistication. |
| Date: | 2025–08–08 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfscr:2025/231 |
| By: | Alexander Hammerl; Georg Beyschlag |
| Abstract: | Stablecoins promise par convertibility, yet issuers must balance immediate liquidity against yield on reserves to keep the peg credible. We study this treasury problem as a continuous-time control task with two instruments: reallocating reserves between cash and short-duration government bills, and setting a spread fee for either minting or burning the coin. Mint and redemption flows follow mutually exciting processes that reproduce clustered order flow; peg deviations arise when redemptions exceed liquid reserves within settlement windows. We develop a stochastic model predictive control framework that incorporates moment closure for event intensities. Using Pontryagin's Maximum Principle, we demonstrate that the optimal control exhibits a bang-off-bang structure: each asset type is purchased at maximum capacity when the utility difference exceeds the corresponding difference in shadow costs. Introducing settlement windows leads to a sampled-data implementation with a simple threshold (soft-thresholding) structure for rebalancing. We also establish a monotone stress-response property: as expected outflows intensify or windows lengthen, the optimal policy shifts predictably toward cash. In simulations covering various stress test scenarios, the controller preserves most bill carry in calm markets, builds cash quickly when stress emerges, and avoids unnecessary rotations under transitory signals. The proposed policy is implementation-ready and aligns naturally with operational cut-offs. Our results translate empirical flow risk into auditable treasury rules that improve peg quality without sacrificing avoidable carry. |
| Date: | 2025–08 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2508.09429 |