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on Payment Systems and Financial Technology |
| By: | Yanfei Dong; Jiayin Hu; Yiping Huang; Han Qiu; Yingguang Zhang |
| Abstract: | How does information sharing affect consumers' usage of FinTech credit? Using a unique dataset of "Buy Now, Pay Later (BNPL)" users from a large digital platform and exploiting a credit reporting policy change, we document that consumers significantly reduce BNPL usage when the BNPL lender becomes subject to credit reporting regulation. This reduction is particularly pronounced among borrowers with default histories, who also show improved repayment behaviors compared to those without such records. The decrease in BNPL usage also leads to a reduction in online consumption, supporting the financial constraint hypothesis. Our findings indicate that information sharing can help mitigate overborrowing and overspending, with stronger effects seen among younger borrowers, those who previously spent more, or those with credit cards. We also highlight the synergies between BNPL lending and Big Tech platforms' ecosystems, which imperfectly substitute for formal enforcement institutions. |
| Keywords: | fintech, BNPL, consumer credit, information sharing, credit reporting, overborrowing, big tech platforms |
| JEL: | G21 G28 G51 G53 |
| URL: | https://d.repec.org/n?u=RePEc:bis:biswps:1239 |
| By: | Lukasz Grzybowski (University of Warsaw, Faculty of Economic Sciences); Valentin Lindlacher (TU Dresden); Onkokame Mothobi (University of Witwatersrand) |
| Abstract: | In this paper, we utilize survey data collected in 2017 from 12, 735 individuals across nine Sub-Saharan African countries. We merge the survey data with geographic information related to the proximity of mobile network towers and banking facilities, based on the geo-locations of the respondents. Our estimation approach comprises a two-stage model. In the first stage, consumers make choices between adopting a feature phone or a smartphone. In the second stage, they make decisions regarding the use of mobile money services. Our findings reveal that network coverage significantly influences the adoption of mobile phones. Moreover, we observe that mobile money services are more favored by younger and relatively wealthier individuals for sending money, while older individuals and those with lower incomes tend to use mobile wallets for receiving money. Consequently, mobile money services facilitate younger migrant workers residing in areas with better infrastructure in providing support to their older relatives in less developed regions. |
| Keywords: | Mobile money, Sub-Saharan Africa, Financial inclusion |
| JEL: | O12 O16 O18 O33 L86 L96 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2024-20 |
| By: | João Almeida; João Alves; Carlos Bettencourt; Maria Bettencourt; Madalena Borges; Filipa Castilho; Sónia Correia; Gisela Fonseca; Mariana Júdice; André Leal; Afonso Marques; Carla Marques; Carlos Martins; Katja Neugebauer; Anaísa Oliveira; Céline Pereira; Joana Pratas; Leonor Queiró; Ricardo Sá; Joana Santos; Dina Teixeira; Pedro Tomés; Isabel Vasconcelos |
| Abstract: | Decentralised Finance (DeFi) has gained significant attention in recent years. It aims to replicate the functions of the traditional financial system in a disintermediated way leveraging on the interplay between blockchain technology, smart contracts and stablecoins. This paper provides an overview of the underlying components of this relatively new ecosystem, as well as its associated risks from the perspective of a financial supervisory authority. While DeFi inherits the risks present in traditional finance, some of these risks could be amplified due to the lack of a clear regulatory framework and the intrinsic features of the DeFi space. Therefore, this paper also takes a closer look at the regulatory challenges involved, including the promise of self-regulation, and explores potential avenues for addressing these challenges without stifling the innovation that DeFi can foster. |
| JEL: | E42 G18 G19 O33 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ptu:wpaper:o202402 |
| By: | Walter Engert; Oleksandr Shcherbakov; André Stenzel |
| Abstract: | We investigate the introduction of a central bank digital currency (CBDC) into the market for payments. Focusing on the point of sale, we develop and estimate a structural model of consumer adoption, merchant acceptance and usage decisions. We counterfactually simulate the introduction of a CBDC, considering a version with debit-like characteristics and one encompassing the best of cash and debit, and characterize outcomes for a range of potential adoption frictions. We show that, in the absence of adoption frictions, CBDC has the potential for material consumer adoption and merchant acceptance, along with moderate usage at the point of sale. However, modest adoption frictions substantially reduce outcomes along all three dimensions. Incumbent responses required to restore pre-CBDC market shares are moderate to small and further reduce the market penetration of CBDC. Overall, this implies that an introduction of CBDC into the market for payments is by no means guaranteed to be successful. |
| Keywords: | Bank notes; Digital currencies and fintech; Econometric and statistical methods; Financial services |
| JEL: | C51 D12 E42 L14 L52 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocawp:24-52 |
| By: | de Brauw, Alan; Gilligan, Daniel O.; Herskowitz, Sylvan; Roy, Shalini |
| Abstract: | Mobile money can be a vehicle for improving financial access, particularly among disadvantaged populations. For mobile money systems to play this role, though, members of disadvantaged groups must both enroll in and begin to use mobile money systems. In this paper, we describe a randomized trial conducted in collaboration with a bank in Somali region, Ethiopia, that attempted to stimulate use among recent mobile money enrollees in areas near refugee camps. We provide one group with a small transfer to their mobile money account and another group is told they will receive a small transfer if they first make three transactions of any type within a promotional period. The unconditional transfer induces a 9.3 percentage point increase in customers making at least one transaction, while the conditional transfer has no significant effect. The effect is larger among men, but there is evidence that it also induces use among women. |
| Keywords: | access to finance; refugees; gender; digital technology; currencies; finance; mobile phones; Eastern Africa; Africa; Ethiopia |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:2295 |
| By: | Daniela Balutel; Walter Engert; Christopher Henry; Kim Huynh; Doina Rusu; Marcel Voia |
| Abstract: | In the rapidly evolving landscape of digital asset markets, measuring cryptoasset knowledge alongside financial knowledge enhances our understanding of individuals' decisions to purchase cryptoassets. Using microdata from the Bank of Canada’s Bitcoin Omnibus Survey, we measure familiarity with crypto concepts using a set of three questions covering basic aspects of Bitcoin. Familiarity with financial concepts is measured using a set of three questions covering basic aspects of conventional finance. We also consider gender differences across these measures. A novel aspect of this paper is an empirical joint analysis that allows us to consider the interrelationship between these two measures of crypto and financial knowledge. |
| Keywords: | Central bank research; Digital currencies and fintech; Econometric and statistical methods |
| JEL: | C81 D14 D91 G53 O51 |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocawp:24-48 |
| By: | Lukasz Grzybowski (University of Warsaw, Faculty of Economic Sciences); Valentin Lindlacher (TU Dresden); Onkokame Mothobi (University of Witwatersrand) |
| Abstract: | In this paper, we investigate the effects of non-exclusive agreements between networks of mobile money agents on mobile network operator choices, using survey data from Tanzania conducted in 2017. By combining survey responses with geo-location data and information on agent proximity, we employ discrete choice models to analyze consumers’ decisions in subscribing to mobile network operators and their corresponding mobile money providers. Our findings highlight the significant influence of the distance to mobile money agents on consumers’ subscription choices. To explore the impact of interoperability (non-exclusivity) at the mobile money agent level, where consumers can use the nearest agent from any mobile money provider, we assess its effects on market shares of mobile network operators. Our results indicate that interoperability at the agent level has only a minor impact on market shares. Smaller operators experience marginal gains as their consumers can now utilize agents of larger providers, which are often closer in proximity. In conclusion, we find that interoperability at the agent level does not considerably alter the market structure in the context Tanzania during the period under consideration. |
| Keywords: | Mobile money, interoperability |
| JEL: | O16 O18 O33 L86 L96 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2024-22 |
| By: | Miguel Risco; Manuel Lleonart-Anguix |
| Abstract: | This paper builds a theoretical model of communication and learning on a social media platform, and describes the algorithm an engagement-maximizing platform implements in equilibrium. This algorithm overexploits similarities between users, locking them in echo chambers. Moreover, learning vanishes as platform size grows large. As this is far from ideal, we explore alternatives. The reverse-chronological algorithm that social platforms reincorporated after the DSA was enacted turns out to be insufficient, so we construct the "breaking-echo-chambers" algorithm, which improves learning by promoting opposite viewpoints. Finally, we advocate for horizontal interoperability as a regulatory measure to align platform incentives with social welfare. By eliminating platform-specific network effects, interoperability incentivizes platforms to adopt algorithms that maximize user well-being. |
| Keywords: | personalized feed, social learning, network effects, interoperability |
| JEL: | D43 D85 L15 L86 |
| Date: | 2024–08 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2024_580v2 |
| By: | Rakesh Arora; Han Du; Raza Ali Kazmi; Duc-Phong Le |
| Abstract: | With the rapid digitization of financial transactions, central banks have given considerable focus in recent years to the research and development of central bank digital currencies (CBDCs). While CBDCs could offer several advantages, there are concerns about end-user privacy. Traditional methods of protecting confidentiality in banking and financial systems have primarily relied on data encryption and access control techniques. However, these techniques alone are inadequate, especially in cases where data are shared across different entities because privacy in such situations is typically governed by legal frameworks. Privacy-enhancing technologies (PETs) can offer robust protection for data throughout their lifecycle, whether stored, in transit or during processing, and ensure privacy is maintained even when data are extensively shared or analyzed. This study explores the use of PETs in the design of CBDC systems, potentially paving the way for solutions that better safeguard end-user privacy and meet rigorous data protection standards. While PETs promise significant advancements in privacy protection, they present some challenges in implementation. They can introduce performance overheads and add complexity to systems, and their effectiveness and applicability are currently limited due to their early stage of development. As these technologies evolve, it is crucial for organizations to carefully consider these factors to fully leverage PET benefits while managing associated challenges. This paper provides a comprehensive overview of how PETs can transform privacy design in financial systems and the implications of their broader adoption. |
| Keywords: | Central bank research; Digital currencies and fintech; Financial system regulations and policies; Payment clearing and settlement systems |
| JEL: | E4 E42 O3 O31 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocadp:25-01 |
| By: | Jeff Larrimore; Alicia Lloro; Zofsha Merchant; Anna Tranfaglia |
| Abstract: | Buy now, pay later (BNPL) is a fast-growing credit product that allows consumers to split payments over time. BNPL gained popularity as a new alternative credit product for online retail purchases over the past decade and has become available for in-person purchases as well as post-purchase credit card installment payment plans. |
| Date: | 2024–12–20 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfn:2024-12-20-4 |
| By: | Giulio Caldarelli |
| Abstract: | The Bitcoin Network is a sophisticated accounting system that allows its underlying cryptocurrency to be trusted even in the absence of a reliable financial authority. Given its undeniable success, the technology, generally referred to as blockchain, has also been proposed as a means to improve legacy accounting systems. Accounting for real-world data, however, requires the intervention of a third party known as an Oracle, which, having not the same characteristics as a blockchain, could potentially reduce the expected integration benefit. Through a systematic review of the literature, this study aims to investigate whether the papers concerning blockchain integration in accounting consider and address the limitations posed by oracles. A broad overview of the limitations that emerged in the literature is provided and distinguished according to the specific accounting integration. Results support the view that although research on the subject counts numerous articles, actual studies considering oracle limitations are lacking. Interestingly, despite the scarce production of papers addressing oracles in various accounting sectors, reporting for ESG already shows interesting workarounds for oracle limitations, with permissioned chains envisioned as a valid support for the safe storage of sustainability data. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.20447 |
| By: | Wenjie Lan |
| Abstract: | This paper distinguishes between risk resonance and risk diversification relationships in the cryptocurrency market based on the newly developed asymmetric breakpoint approach, and analyzes the risk propagation mechanism among cryptocurrencies under extreme events. In addition, through the lens of node association and network structure, this paper explores the dynamic evolutionary relationship of cryptocurrency risk association before and after the epidemic. In addition, the driving mechanism of the cryptocurrency risk movement is analyzed in a depth with the epidemic indicators. The findings show that the effect of propagation of risk among cryptocurrencies becomes more significant under the influence of the new crown outbreak. At the same time, the increase in the number of confirmed cases exacerbated the risk spillover effect among cryptocurrencies, while the risk resonance effect that exists between the crude oil market and the cryptocurrency market amplified the extent of the outbreak's impact on cryptocurrencies. However, other financial markets are relatively independent of the cryptocurrency market. This study proposes a strategy to deal with the spread of cryptocurrency risks from the perspective of a public health crisis, providing a useful reference basis for improving the regulatory mechanism of cryptocurrencies. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.19983 |
| By: | Clara Filosa; Marin Jovanovic; Lara Agostini; Anna Nosella |
| Abstract: | The landscape of digital servitization in the manufacturing sector is evolving, marked by a strategic shift from traditional product-centric to platform business models (BMs). Manufacturing firms often employ a blend of approaches to develop business-to-business (B2B) platforms, leading to significant reconfigurations in their BMs. However, they frequently encounter failures in their B2B platform development initiatives, leading them to abandon initial efforts and pivot to alternative platform strategies. Therefore, this study, through an in-depth case study of a manufacturer in the energy sector, articulates a three-phase pivoting framework for B2B platform BMs, including platform development and platform strategy. Initially, the manufacturer focused on asset-based product sales supplemented by asset maintenance services and followed an emergent platformization strategy characterized by the rise of multiple, independent B2B platforms catering to diverse functions. Next, focusing on the imposed customer journey strategy, the firm shifted towards a strategic multi-platform integration into an all-encompassing platform supported by artificial intelligence (AI), signaling a maturation of the platform BM to combine a wide range of services into an energy-performance-based contract. Finally, the last step of the firm's platform BM evolution consisted of a deliberate platform strategy open to external stakeholders and enveloping its data-driven offerings within a broader platform ecosystem. This article advances B2B platform BMs and digital servitization literature, highlighting the efficacy of a progressive approach and strategic pivoting. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.19931 |
| By: | Martin Peitz; Anton Sobolev |
| Abstract: | A seller can offer an experience good directly to consumers and indirectly through an intermediary. When selling indirectly, the intermediary provides recommendations based on the consumer’s match value and the prices at which the product is sold. The intermediary faces the trade-off between extracting rents from consumers who strongly care about the match value versus providing less informative recommendations but also serving consumers who do not. We analyze the allocative and welfare effects of prohibiting price parity clauses and/or regulating the intermediary’s recommender system. Prohibiting price parity clauses is always welfare decreasing in our model. |
| Keywords: | intermediation, digital platforms, price parity, recommender system, MFN clause, e-commerce |
| JEL: | L12 L15 D21 D42 M37 |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2024_595v2 |
| By: | Michael King (Department of Economics, Trinity College Dublin); Daniel Putman (University of Pennsylvania Center for Social Norms and Behavioral Dynamics); Shane Byrne (Department of Economics, Trinity College Dublin); Chaning Jang (Busara Center for Behavioral Economics) |
| Abstract: | The high prevalence of digital financial fraud stresses businesses' ability to distinguish between real communications from digital financial service (DFS) providers and fraudulent impersonations. Besides the financial and psychological costs to businesses, fraud may erode trust in, and usage of DFS. We test two strategies for preventing non-institutional fraud: a series of anti-fraud learning interventions and a technical solution to authenticate inbound communications from a digital platform. Using a pre-registered behavioural laboratory experiment in Nigeria, we find evidence that timely educational interventions increased trust in DFS, its likely future usage, and improved knowledge about fraud four weeks post intervention. However, when we task micro business owners with evaluating the authenticity of a series of fictionalised scenarios, we do not find evidence of improvement in fraud detection, either overall, or when considering only genuine or fraudulent scenarios. Surprisingly, we find increased self-confidence in fraud detection ability, highlighting the risk of overconfidence. |
| Keywords: | Financial Behavior; Digital Finance; Fraud; Trust; Consumer Protection; Financial Inclusion; Financial Development |
| JEL: | D18 G41 G53 O12 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:tcd:tcduee:tep1224 |
| By: | Gregory M. Dickinson |
| Abstract: | Current consumer-protection debates focus on the powerful new data-analysis techniques that have disrupted the balance of power between companies and their customers. Online tracking enables sellers to amass troves of historical data, apply machine-learning tools to construct detailed customer profiles, and target those customers with tailored offers that best suit their interests. It is often a win-win. Sellers avoid pumping dud products and consumers see ads for things they actually want to buy. But the same tools are also used for ill -- to target vulnerable members of the population with scams specially tailored to prey on their weaknesses. The result has been a dramatic rise in online fraud that disproportionately impacts those least able to bear the loss. The law's response has been technology centric. Lawmakers race to identify those technologies that drive consumer deception and target them for regulatory restrictions. But that approach comes at a major cost. General-purpose data-analysis and communications tools have both desirable and undesirable uses, and uniform restrictions on their use impede the good along with the bad. A superior approach would focus not on the technological tools of deception but on what this Article identifies as the legal patterns of digital deception -- those aspects of digital technology that have outflanked the law's existing mechanisms for redressing consumer harm. This Article reorients the discussion from the power of new technologies to the shortcomings in existing regulatory structures that have allowed for their abuse. Focus on these patterns of deception will allow regulators to reallocate resources to offset those shortcomings and thereby enhance efforts to combat online fraud without impeding technological innovation. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2412.19850 |
| By: | Balana, Bedru; Olanrewaju, Opeyemi |
| Abstract: | This paper examines the effects of financial inclusion on adoption and intensity of use of agricultural inputs and household welfare indicators using data from the nationally representative Nigerian LSMS wave-3 (2015/2016) survey. For this, we constructed a financial inclusion index from four formal financial services access indicators (bank account, access to credit, insurance coverage, and digital transaction) using multiple correspondence analysis (MCA). We used Cragg’s two-step hurdle, instrumental variables for binary response variables, and a Generalized Method of Moments (GMM) models in the econometric analysis. Results show that households with access to formal financial services are more likely to adopt agricultural inputs and to apply these more intensively. These same households are less likely to experience severe food insecurity and are more likely to consume diverse food items. We also find that these effects are less for female farmers regardless of formal financial inclusion, suggesting that they may bear more non-financial constraints than their male counterparts. The results suggest a need for targeted interventions to increase access to formal financial services of farm households and gender-responsive interventions to address the differential constraints women farmers face. |
| Keywords: | farm inputs; financial inclusion; food security; households; inorganic fertilizers; seeds; Africa; Western Africa; Nigeria |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:fpr:ifprid:2293 |
| By: | Carlos A. Piccioni; Saulo B. Bastos; Daniel O. Cajueiro |
| Abstract: | We measure municipal-level inequality based on electronic payment data, specifically credit card and Pix payments, which we consider as a proxy for consumption. Our consumption inequality measure is correlated with income inequality calculated using census data, and it exhibits similar regional behavior, although it indicates higher inequality on average, given the nature of the data used. As an application, we assess the relationship between our inequality measure and the Economic Complexity Index (ECI) at the municipal level. We find a negative relationship, indicating that higher economic complexity is associated with lower consumption inequality. Additionally, the relationship is non-linear: with increasing ECI, the influence on consumption inequality becomes more significant. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:bcb:wpaper:608 |
| By: | Lukasz Grzybowski (University of Warsaw, Faculty of Economic Sciences); Zubair Maghmood Patel (University of Cape Town) |
| Abstract: | In this paper we analyse whether having a mobile phone impacts chances of getting employed. We use five waves of panel data from the National Income Dynamic Survey (NIDS), which was conducted in South Africa between years 2008 and 2017. In the estimation we include a vector of observable individual and household characteristics and account for unobserved heterogeneity amongst individuals. The estimation results suggest that mobile phone ownership has a positive impact on the change in employment status from unemployed to employed. On the other hand, ownership of a computer by a household and computer literacy do not increase the likelihood of getting employed. The average probability of becoming employed increases from 54.2% when no one among unemployed adults has a mobile phone to 57.4% when all of them have a mobile phone, which is an increase of 5.9%. |
| Keywords: | Mobile phones, Employment, NIDS, South Africa |
| JEL: | L13 L50 L96 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2024-21 |
| By: | Barboni, Giorgia (Warwick University); de Roux, Nicolás (Universidad de los Andes); Perez-Cardona, Santiago (University of Chicago) |
| Abstract: | We conducted a telephonic survey experiment with 2, 214 Venezuelan migrants to examine how their perceptions of Colombian’s social acceptance influence their engagement with the financial system. We find that 66% of the subjects we interviewed underestimate the extent to which natives are open towards migrants. We then show that providing accurate information reduces belief errors by 23 percentage points. This correction increases migrants’ willingness to interact with the financial system. In particular, individuals who initially underestimated Colombian’s acceptance of migrants are 15% more likely to visit a bank and request financial information in the next two months relative to the control group. These individuals also show a 12% increase in the willingness to open a digital wallet and an 18% increase in the willingness to open a savings account. These effects are concentrated among individuals who have not experienced episodes of discrimination in Colombia. We find no effects on the willingness to apply for a loan or an insurance product, consistent with the idea that supply barriers play a significant role for the financial inclusion of vulnerable populations. Using an instrumental variable strategy, we show that the increased willingness to engage with the financial system is driven by belief updating. Our findings highlight that misperceptions about native’s social acceptance of migrants can drive self-exclusion from the financial system. |
| Keywords: | Financial Inclusion; Migration; Beliefs; Social Acceptance |
| JEL: | D83 D91 F22 G51 |
| Date: | 2024–12–13 |
| URL: | https://d.repec.org/n?u=RePEc:col:000089:021278 |
| By: | IKEDA Yuichi; AOYAMA Hideaki; HATSUDA Tetsuo; HIDAKA Yoshimasa; SHIRAI Tomoyuki; SOUMA Wataru; IYETOMI Hiroshi; Abhijit CHAKRABORTY; FUJIHARA Akihiro; NAKAYAMA Yasushi; ARAI Yuta; Krongtum SANKAEWTONG |
| Abstract: | Realizing a cyber-physical economy requires dealing with the problems of the digital society that have arisen with the development of information technology. This study systematizes the mathematical basis for detecting anomalies for a dynamic graph, a network representation of relationships among nodes of crypto asset transactions and changes as time passes, based on graph theory, topology, and high-dimensional statistical analysis, to answer the three research questions: (1) Are there leading indicators of transactions that precede prices? (2) Is there a correlation between the velocity of circulation and prices? (3) Is there a herding phenomenon in the transaction network? Here, we define “anomaly†as large price fluctuations that affect transactions. The multiple methods above are applied to dynamic graphs during higher priced periods of crypto asset transactions to estimate individual anomaly indicators. We verify the effectiveness of the various anomaly detection methods by answering the three research questions for a major crypto asset. Finally, we propose a concept for an anomaly detection AI that estimates a comprehensive anomaly indicator by inputting various features from individual analysis methods. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:eti:dpaper:24085 |
| By: | Nathan Blascak; Anna Tranfaglia |
| Abstract: | Credit cards are the most widely held consumer debt product in the United States. Over 191 million Americans have at least one account (Haughwout et al., 2022) and nearly half of those with a credit card revolve a balance on at least one of their accounts (Federal Reserve Board, 2024). |
| Date: | 2024–12–20 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfn:2024-12-20-5 |
| By: | Yichen Luo; Yebo Feng; Jiahua Xu; Paolo Tasca; Yang Liu |
| Abstract: | Cryptocurrency investment is inherently difficult due to its shorter history compared to traditional assets, the need to integrate vast amounts of data from various modalities, and the requirement for complex reasoning. While deep learning approaches have been applied to address these challenges, their black-box nature raises concerns about trust and explainability. Recently, large language models (LLMs) have shown promise in financial applications due to their ability to understand multi-modal data and generate explainable decisions. However, single LLM faces limitations in complex, comprehensive tasks such as asset investment. These limitations are even more pronounced in cryptocurrency investment, where LLMs have less domain-specific knowledge in their training corpora. To overcome these challenges, we propose an explainable, multi-modal, multi-agent framework for cryptocurrency investment. Our framework uses specialized agents that collaborate within and across teams to handle subtasks such as data analysis, literature integration, and investment decision-making for the top 30 cryptocurrencies by market capitalization. The expert training module fine-tunes agents using multi-modal historical data and professional investment literature, while the multi-agent investment module employs real-time data to make informed cryptocurrency investment decisions. Unique intrateam and interteam collaboration mechanisms enhance prediction accuracy by adjusting final predictions based on confidence levels within agent teams and facilitating information sharing between teams. Empirical evaluation using data from November 2023 to September 2024 demonstrates that our framework outperforms single-agent models and market benchmarks in classification, asset pricing, portfolio, and explainability performance. |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2501.00826 |
| By: | Filip Stefaniuk (University of Warsaw, Faculty of Economic Sciences); Robert Ślepaczuk (University of Warsaw, Faculty of Economic Sciences, Department of Quantitative Finance and Machine Learning, Quantitative Finance Research Group) |
| Abstract: | The thesis investigates the usage of Informer architecture for building automated trading strategies for high frequency Bitcoin data. Two strategies using Informer models with different loss functions, Quantile loss and Generalized Mean Absolute Directional Loss (GMADL), are proposed and evaluated against the Buy and Hold benchmark and two benchmark strategies based on technical indicators. The evaluation is conducted using data of various frequencies: 5 minute, 15 minute, and 30 minute intervals, over the 6 different periods. Although the Informer-based model with Quantile loss did not manage to outperform the benchmark, the model that uses novel GMADL loss function turned out to be benefiting from higher frequency data and beat all the other strategies on most of the testing periods. The primary contribution of this study is the application and assessment of the Quantile and GMADL loss functions with the Informer model to forecast future returns, subsequently using these forecasts to develop automated trading strategies. The research provides evidence that employing an Informer model trained with the GMADL loss function can result in superior trading outcomes compared to the buy-and-hold approach. |
| Keywords: | Machine Learning, Financial Series Forecasting, Automated Trading Strategy, Informer, Transformer, Bitcoin, High Frequency Trading, Statistics, GMADL |
| JEL: | C4 C14 C45 C53 C58 G13 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:war:wpaper:2024-27 |
| By: | Mr. Kalin I Tintchev; Kady Keita |
| Abstract: | We document novel evidence that confidence in macrofinancial stability has a positive impact on financial inclusion in CCA countries and more broadly. This channel is particularly important for CCA countries, with confidence gains of 1 unit leading to 0.7 unit improvement in financial inclusion. Institutional factors such as level of governance and reliance on transparent policy rules and robust financial safety nets explain a large fraction of the variability in confidence in the region. We find that governance reforms are critical for deepening financial inclusion while the impact of inflation targeting, fiscal rules and deposit insurance schemes is positive and material only when governance levels exceed certain thresholds. |
| Keywords: | Financial inclusion; confidence; governance; inflation targeting; fiscal rules; deposit insurance |
| Date: | 2024–12–20 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imfwpa:2024/257 |
| By: | Happ, Marina; Harpenau, Franziska; Wiewiorra, Lukas |
| Abstract: | Pornographic websites represent a significant component of the digital ecosystem; however, comparatively limited research has been conducted on this subject in comparison to other websites. This paper aims to gather and enrich the extant literature on the subject. For this purpose, a comprehensive analysis of the diverse business models is conducted, regarding factors such as their design, content uploaded and revenue generation. Furthermore, an analysis of the market structure of the various companies operating within this sector is undertaken, which reveals a high degree of vertical and horizontal integration, with several tube websites as well as websites employing interactive models demonstrating particular significance. The utilisation of such services is frequent across the population, which raises several societal concerns. These include the presence of illegal content such as copyright-infringing material, child sexual abuse material (CSAM) and non-consensually shared intimate material (NCSM), potential issues regarding the protection of privacy, potential negative effects due to harmful material, access by minors and potential negative effects on the mental health. Several potential mitigation measures are presented and current approaches outlined, including age verification, verification of uploaders and performers, content moderation and changes in functionality. Especially tube websites appear to have little intrinsic motivation to remove illegal content and should therefore be examined more closely. |
| Abstract: | Pornografische Websites stellen eine signifikante Komponente des digitalen Ökosystems dar, jedoch wurde im Vergleich zu anderen Websites nur eine vergleichsweise geringe Menge an Forschung zu ihnen betrieben. Das Ziel dieses Papiers besteht darin, die vorhandene Literatur zu diesem Thema zu sammeln und zu ergänzen. Zu diesem Zweck wird eine umfassende Analyse der verschiedenen Geschäftsmodelle in Bezug auf Faktoren wie Design, hochgeladene Inhalte und Umsatzgenerierung durchgeführt. Darüber hinaus wird eine Analyse der Marktstruktur der verschiedenen in diesem Sektor tätigen Unternehmen vorgenommen, die ein hohes Maß an vertikaler und horizontaler Integration erkennen lässt, wobei mehrere Tube-Websites sowie Websites mit interaktiven Modellen von besonderer Bedeutung sind. Die Nutzung solcher Dienste ist in der Bevölkerung weit verbreitet, wodurch sich mehrere gesellschaftliche Bedenken ergeben. Dazu gehören das Vorhandensein illegaler Inhalte wie urheberrechtsverletzendes Material, Kindesmissbrauchsmaterial und nicht einvernehmlich geteiltes intimes Material, potenzielle Fragen des Schutzes der Privatsphäre, potenzielle negative Auswirkungen aufgrund von schädlichem Material, der Zugang von Minderjährigen und potenzielle negative Auswirkungen auf die psychische Gesundheit. Es werden mehrere potenzielle Abhilfemaßnahmen vorgestellt und die derzeitigen Vorgehensweisen skizziert, darunter Altersverifizierung, Überprüfung von Uploadern und Darstellern, Inhaltsmoderation und Änderungen der Funktionalität. Insbesondere Tube-Websites scheinen wenig intrinsische Motivation, illegale Inhalte zu entfernen, zu haben und sollten daher genauer untersucht werden. |
| Keywords: | Online Pornography, Adult Entertainment, Societal Issues, Digital Services Act (DSA) |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:wikwps:308077 |
| By: | Zöll, Anne |
| Abstract: | Companies‘ data-driven digital services rely on the collection of personal data and its processing by self-learning algorithms. With the help of machine learning, companies can offer personalized services tailored to customer needs. As a result of the intensive collection of personal information by companies, customers have a sense of loss of control over their own personal information. They also have high privacy concerns about data handling. These concerns are amplified by high-profile data breaches such as the Cambridge Analytica scandal. Consequently, customers are increasingly hesitant to share their personal data with these companies, which could pose a risk to data-driven digital services. A smaller amount of data could compromise the performance of algorithms and thus reduce the quality of data-driven digital services. Therefore, the stated goal of this dissertation is to establish the complex balance between protecting customers‘ privacy and improving value creation processes. Thus, the central research question of this dissertation is how companies can mitigate the dilemma between protecting individual privacy and enhancing data-driven digital services. This dissertation examines the issue from three different perspectives: technological, individual, and organizational. Over the past decades, privacy-enhancing technologies have been developed. These information and communication technologies protect individuals‘ privacy either by removing or minimizing personal information or by preventing unnecessary or unwanted processing of personal information while maintaining the functionality of information systems. Despite the advanced implementation of these privacy-enhancing technologies, they are rarely used in data-driven digital services. Therefore, this dissertation provides an overview of the reasons why these privacy-enhancing technologies are only reluctantly adopted by companies. In particular, it highlights the barriers that arise when integrating these technologies into data-driven digital services. Thus, this dissertation demonstrates that a purely technological solution is not sufficient to fully answer the research question. This is the starting point of this dissertation, which aims to find a solution to mitigate the aforementioned dilemma. As privacy concerns are primarily customer-driven, this dissertation focuses on individuals as a further perspective. This perspective aims to examine how companies should design data-driven digital services to alleviate customer privacy concerns. To achieve this goal, the dissertation draws on theories from privacy research, focusing on individuals‘ control over their personal information and trust in data-driven digital services. Essentially, design principles are developed that are necessary to create data-driven digital services that allow individuals to regain control over their personal data. Furthermore, this dissertation continues to develop design principles to enhance costumers‘ trust in data-driven digital services, especially those based on machine learning. As a third perspective, organizations are included, particularly examining how machine learning can be integrated into companies‘ value creation process to build data-driven digital services. The focus of this research is to identify the factors that either support or hinder the integration of machine learning into companies‘ value creation processes. Although many factors for the adoption of innovations have been examined in previous literature, a re-examination is important because the characteristics of machine learning are significantly different from other technologies. For instance, vast amounts of personal information are processed to generate personalized recommendations for individuals. The ability of machine learning to uncover hidden patterns can lead to the inadvertent disclosure of sensitive personal information, thereby intensifying privacy concerns. Additionally, this dissertation builds on previous research that highlights differences in the acceptance of innovations in different cultures and examines which different factors are important for the adoption of machine learning in data-driven digital services in different cultures. In this regard, this dissertation applies the organizational readiness concept for artificial intelligence within cultural research to gain deeper insights into this intersection. In summary, this dissertation presents three important perspectives that aim to alleviate the dilemma between the protection of individuals‘ privacy and the use of machine learning for value creation in companies. It deals with privacy-enhancing technologies, prioritizes user-centered approaches, and the strategic design of value creation processes within companies. Particularly driven by the three perspectives, this dissertation motivates the development of a multilevel theory that aim to enable a holistic approach to alleviate the dilemma between privacy protection and value creation by bringing together technology, individuals, and organizations. |
| Date: | 2024–12–03 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:150796 |