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on Payment Systems and Financial Technology |
| By: | Hunter Ng |
| Abstract: | Wash trading, the practice of simultaneously placing buy and sell orders for the same asset to inflate trading volume, has been prevalent in cryptocurrency markets. This paper investigates whether wash traders in Bitcoin act deliberately to exploit market conditions and identifies the characteristics of such manipulative behavior. Using a unique dataset of 18 million transactions from Mt. Gox, once the largest Bitcoin exchange, I find that wash trading intensifies when legitimate trading volume is low and diminishes when it is high, indicating strategic timing to maximize impact in less liquid markets. The activity also exhibits spillover effects across platforms and decreases when trading volumes in other asset classes like stocks or gold rise, suggesting sensitivity to broader market dynamics. Additionally, wash traders exploit periods of heightened media attention and online rumors to amplify their influence, causing rapid but short-lived spikes in legitimate trading volume. Using an exogenous demand shock associated with illicit online marketplaces, I find that wash trading responds to contemporaneous events affecting Bitcoin demand. These results advance the understanding of manipulative practices in digital currency markets and have significant implications for regulators aiming to detect and prevent wash trading. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.08720 |
| By: | Bindseil, Ulrich; Marrazzo, Marco; Sauer, Stephan |
| Abstract: | As digital payments become increasingly popular, many central banks are looking into the issuance of retail central bank digital currency (CBDC) as a new central bank monetary liability in addition to banknotes and commercial bank reserves. CBDC will have broadly the same balance sheet and profit implications as the issuance of banknotes. While the decision to issue CBDC is often thought to likely increase the size of central banks’ balance sheets, the net impact of digitalisation on balance sheet size could also be negative, as the number of banknotes in circulation may decline and CBDC’s design features could limit its take-up as a store of value. We use scenario analyses to illustrate the key drivers of the impact of CBDC on central bank profitability, with the part of CBDC that does not derive from an exchange of banknotes being an important factor. The financial risk implications of CBDC for central banks can be managed via well-established frameworks and relate primarily to the impact on balance sheet size and asset composition. The paper concludes with a discussion on how the profit and risk channels affect central bank capital. JEL Classification: E58 |
| Keywords: | central bank capital, central bank digital currency, digital money, financial risk management, seigniorage |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:ecb:ecbops:2024360 |
| By: | Marcin W\k{a}torek; Marcin Kr\'olczyk; Jaros{\l}aw Kwapie\'n; Tomasz Stanisz; Stanis{\l}aw Dro\.zd\.z |
| Abstract: | Multifractality is a concept that helps compactly grasping the most essential features of the financial dynamics. In its fully developed form, this concept applies to essentially all mature financial markets and even to more liquid cryptocurrencies traded on the centralized exchanges. A new element that adds complexity to cryptocurrency markets is the possibility of decentralized trading. Based on the extracted tick-by-tick transaction data from the Universal Router contract of the Uniswap decentralized exchange, from June 6, 2023, to June 30, 2024, the present study using Multifractal Detrended Fluctuation Analysis (MFDFA) shows that even though liquidity on these new exchanges is still much lower compared to centralized exchanges convincing traces of multifractality are already emerging on this new trading as well. The resulting multifractal spectra are however strongly left-side asymmetric which indicates that this multifractality comes primarily from large fluctuations and small ones are more of the uncorrelated noise type. What is particularly interesting here is the fact that multifractality is more developed for time series representing transaction volumes than rates of return. On the level of these larger events a trace of multifractal cross-correlations between the two characteristics is also observed. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.05951 |
| By: | Náñez Alonso, Sergio Luis (Universidad Católica de Ávila); Echarte Fernández, Miguel Ángel (Universidad Católica de Ávila); Kolegowicz, Konrad (Universidad de Economía de Cracovia); Sanz-Bas, David (Universidad Católica de Ávila); Jorge-Vázquez, Javier (Universidad Católica de Ávila) |
| Abstract: | Los países de la región del Caribe, Centroamérica y Sudamérica han irrumpido con fuerza e indiscutible liderazgo en la adopción del dinero digital, ya sea apostando por las monedas digitales emitidas y respaldadas por un banco central (CBDC) o por las monedas virtuales descentralizadas (DEFI), lideradas por Bitcoin y Ether. El objetivo del artículo es identificar las razones que llevan a un país o zona monetaria a decantarse por alguno de estos sistemas. Una vez estudiadas las ventajas y desventajas del uso de las divisas virtuales centraremos el análisis en doce variables sobre el uso de dinero móvil extraídas del GFI (Global Findex Indicator) de los años 2011, 2014, 2017 y 2021 de todos estos países. El presente artículo demuestra, entre otras cuestiones, que la apuesta por un dinero digital basado en CBDC o DEFI depende más de la elección política de los dirigentes del país en cuestión que de criterios socioeconómicos. |
| Keywords: | CBDC; monedas digitales; política monetaria; inclusión financiera; innovación de bancos centrales; dinero digital |
| JEL: | E42 E44 E52 F40 |
| Date: | 2023–09–13 |
| URL: | https://d.repec.org/n?u=RePEc:col:000418:021224 |
| By: | Yeguang Chi (Ruihua); Qionghua (Ruihua); Chu; Wenyan Hao |
| Abstract: | We investigate the return-forecasting and volatility-forecasting power of intraday on-chain flow data for BTC, ETH, and USDT, and the associated option strategies. First, we find that USDT net inflow into cryptocurrency exchanges positively forecasts future returns of both BTC and ETH, with the strongest effect at the 1-hour frequency. Second, we find that ETH net inflow into cryptocurrency exchanges negatively forecasts future returns of ETH. Third, we find that BTC net inflow into cryptocurrency exchanges does not significantly forecast future returns of BTC. Finally, we confirm that selling 0DTE ETH call options is a profitable trading strategy when the net inflow into cryptocurrency exchanges is high. Our study lends new insights into the emerging literature that studies the on-chain activities and their asset-pricing impact in the cryptocurrency market. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.06327 |
| By: | Evgenii Onishchuk; Maksim Dubovitskii; Eduard Horch |
| Abstract: | This empirical study presents the Decentralized Exchanges Comparison Service (DECS), a novel tool developed by 1inch Analytics to assess exchange efficiency in decentralized finance. The DECS utilizes swap transaction monitoring and simulation techniques to provide unbiased comparisons of swap rates across various DEXes and aggregators. Analysis of almost 1.2 million transactions across multiple blockchain networks demonstrates that both 1inch Classic and 1inch Fusion consistently outperform competitors. These findings not only validate 1inch's superior rates but also provide valuable insights for continuous protocol optimization and underscore the critical role of data-driven decision-making in advancing DeFi infrastructure. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.01950 |
| By: | Francis Annan |
| Abstract: | We study the direct and indirect effects of randomized entry. In partnership with the two largest service providers in Ghana, we implement a three-step design that randomizes the entry of new financial mobile money vendors, who also sell non-financial goods/services, across local markets. This mixed financial and non-financial services setting is widespread and naturally emerges as the market entry approach for several real-world financial markets. Randomized entry increases firm conduct and service quality and decreases price-cost markups, indicating positive consumer surplus. We find evidence of within-market revenue reallocation and expansion for mobile money and a large services multiplier: revenues for non-financial goods/services increased (+20%), with aggregate service industry revenues increasing. These improvements emphasize the “real effects” of financial markets on the local economy, and come from adoption externalities and aggregate increase in household expenses. Entry increases local economic activity, and it does so not only by changing markets for digital financial services, but also by transforming the non-financial services sector. These effects are key ingredients for advancing basic and applied knowledge on firm entry in industry equilibrium. |
| JEL: | D18 D62 G20 G50 L22 L26 O12 |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33134 |
| By: | Jana S. Hamdan; Tim Kaiser; Lukas Menkhoff; Yuanwei Xu |
| Abstract: | We study the effects of scaling up a financial- and business education program in a randomized saturation experiment in Uganda. We randomly assign the program at the cluster-level, and then randomize the share of treated individuals within treated clusters. 15 months later, we find that treated entrepreneurs are more likely to use mobile money savings accounts and payments, increase their mobile money and bank savings at the intensive and extensive margins, and invest more. We find little evidence of spillovers on untreated peers, but as the share of treated entrepreneurs increases, beneficial effects on the treated decline. |
| Keywords: | scaling, business training, financial literacy, micro-entrepreneurs, mobile money, spillover effects, saturation effects |
| JEL: | C93 D14 G53 O12 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11431 |
| By: | Hugo Schnoering; Michalis Vazirgiannis |
| Abstract: | Bitcoin, launched in 2008 by Satoshi Nakamoto, established a new digital economy where value can be stored and transferred in a fully decentralized manner - alleviating the need for a central authority. This paper introduces a large scale dataset in the form of a transactions graph representing transactions between Bitcoin users along with a set of tasks and baselines. The graph includes 252 million nodes and 785 million edges, covering a time span of nearly 13 years of and 670 million transactions. Each node and edge is timestamped. As for supervised tasks we provide two labeled sets i. a 33, 000 nodes based on entity type and ii. nearly 100, 000 Bitcoin addresses labeled with an entity name and an entity type. This is the largest publicly available data set of bitcoin transactions designed to facilitate advanced research and exploration in this domain, overcoming the limitations of existing datasets. Various graph neural network models are trained to predict node labels, establishing a baseline for future research. In addition, several use cases are presented to demonstrate the dataset's applicability beyond Bitcoin analysis. Finally, all data and source code is made publicly available to enable reproducibility of the results. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.10325 |
| By: | Qiang Wan; Jun Cui |
| Abstract: | This paper explores the impact of banking fintech on reducing financial risks in the agricultural supply chain, focusing on the secondary allocation of commercial credit. The study constructs a three-player evolutionary game model involving banks, core enterprises, and SMEs to analyze how fintech innovations, such as big data credit assessment, blockchain, and AI-driven risk evaluation, influence financial risks and access to credit. The findings reveal that banking fintech reduces financing costs and mitigates financial risks by improving transaction reliability, enhancing risk identification, and minimizing information asymmetry. By optimizing cooperation between banks, core enterprises, and SMEs, fintech solutions enhance the stability of the agricultural supply chain, contributing to rural revitalization goals and sustainable agricultural development. The study provides new theoretical insights and practical recommendations for improving agricultural finance systems and reducing financial risks. Keywords: banking fintech, agricultural supply chain, financial risk, commercial credit, SMEs, evolutionary game model, big data, blockchain, AI-driven risk evaluation. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.07604 |
| By: | Kristina Trajkovic (National Bank of Serbia) |
| Abstract: | Prevention of money laundering and other abuses in the digital assets sector is a major step in the preservation of financial system stability. Non-alignment of regulatory regimes in an environment of rapid market development creates a potential for abuse and illicit activities. Monitoring the market requires systematic analysis in order to define clear guidelines for mitigating identified risks. Regular implementation of risk assessment and the regulator’s supervisory function facilitate the identification of the riskiness of the entire digital assets sector. In addition to an overview of regulations and standards governing the prevention of money laundering, the paper looks into the risks to which the digital assets sector is exposed, including the conduct of supervision and, in this sense, implementation of the risk-based approach. |
| Keywords: | regulation, digital assets, virtual currency, supervision, money laundering, abuse |
| JEL: | E30 K20 K23 G18 |
| Date: | 2023–09 |
| URL: | https://d.repec.org/n?u=RePEc:nsb:bilten:17 |
| By: | Magdalena Schindl; Felix Reichel |
| Abstract: | According zu Kadir et al. (2023) online marketplaces are used to buy and sell products and services, as well as to exchange money and data between users or the platform. Due to the large product selection, low costs and the ease of shopping without physical restrictions as well as the technical possibilities, online marketplaces have grown rapidly Kadir et al. (2023). Online marketplaces are also used in the consumer-to-consumer (C2C) sector and thus offer a broad user group a marketplace, for example for used products. This article focuses on Willhaben.at (2024), a leading C2C marketplace in Austria, as stated by Obersteiner, Schmied, and Pamperl (2023). The empirical analysis in this course essay centers around the offer ads of Woom Bikes, a standardised product which is sold on Willhaben. Through web scraping, a dataset of approximately 826 observations was created, focusing on mid-to-high price segment bicycles, which are characterized by price stability and uniformity as we claim. This analysis aims to create analyse ad listing prices through predictive models using willhaben product listing attributes and using the spatial distribution of one of the product attributes. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.07808 |
| By: | Shamima Nasrin Tumpa; Kehelwala Dewage Gayan Maduranga |
| Abstract: | This study explores the use of Recurrent Neural Networks (RNN) for real-time cryptocurrency price prediction and optimized trading strategies. Given the high volatility of the cryptocurrency market, traditional forecasting models often fall short. By leveraging RNNs' capability to capture long-term patterns in time-series data, this research aims to improve accuracy in price prediction and develop effective trading strategies. The project follows a structured approach involving data collection, preprocessing, and model refinement, followed by rigorous backtesting for profitability and risk assessment. This work contributes to both the academic and practical fields by providing a robust predictive model and optimized trading strategies that address the challenges of cryptocurrency trading. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.05829 |
| By: | Klaus M. Miller; Karlo Lukic; Bernd Skiera |
| Abstract: | This study explores the impact of the General Data Protection Regulation (GDPR), introduced on May 25th, 2018, on online trackers, vital elements in the online advertising ecosystem. Using a difference-in-differences approach with a balanced panel of 294 publishers, we compare publishers subject to the GDPR with those unaffected (the control group). Drawing on data from WhoTracks.me, which spans 32 months from May 2017 to December 2019, we analyze how the number of trackers used by publishers changed before and after the GDPR. The findings reveal that although online tracking increased for both groups, the rise was less significant for EU-based publishers subject to the GDPR. Specifically, the GDPR reduced about four trackers per publisher, equating to a 14.79% decrease compared to the control group. The GDPR was particularly effective in curbing privacy invasive trackers that collect and share personal data, thereby strengthening user privacy. However, it had a limited impact on advertising trackers and only slightly reduced the presence of analytics trackers. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.06862 |
| By: | Philippe Bergault; Louis Bertucci; David Bouba; Olivier Gu\'eant; Julien Guilbert |
| Abstract: | In this paper, we introduce a novel framework to model the exchange rate dynamics between two intrinsically linked cryptoassets, such as stablecoins pegged to the same fiat currency or a liquid staking token and its associated native token. Our approach employs multi-level nested Ornstein-Uhlenbeck (OU) processes, for which we derive key properties and develop calibration and filtering techniques. Then, we design an automated market maker (AMM) model specifically tailored for the swapping of closely related cryptoassets. Distinct from existing models, our AMM leverages the unique exchange rate dynamics provided by the multi-level nested OU processes, enabling more precise risk management and enhanced liquidity provision. We validate the model through numerical simulations using real-world data for the USDC/USDT and wstETH/WETH pairs, demonstrating that it consistently yields efficient quotes. This approach offers significant potential to improve liquidity in markets for pegged assets. |
| Date: | 2024–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2411.08145 |
| By: | Sonja Aleksic, Nikola Škondric; Sonja Aleksic (National Bank of Serbia); Nikola Škondric (National Bank of Serbia) |
| Abstract: | The technology balance of payments represents a statistical overview of international market transactions between residents and non-residents, resulting from technology transfers realised through intangible assets (patents, licenses, knowhow, etc.) and the provision of services with a dominant technological component (research and development, technical assistance, engineering services, etc.). It is based on balance of payments and international trade in services statistics, in accordance with the international statistical standards. In this paper, the authors developed and examined the technology balance of payments of the Republic of Serbia, in order to determine the basic trends of technology trade with foreign countries and observe the analytical value of the technology balance of payments as an indicator of international technology trade. |
| Keywords: | inflation technology balance of payments, technology transfer, balance of payments, services account |
| JEL: | F14 O33 L84 L86 |
| Date: | 2023–03 |
| URL: | https://d.repec.org/n?u=RePEc:nsb:bilten:15 |
| By: | Alex Armand (Institute for Fiscal Studies); Britta Augsburg (Institute for Fiscal Studies); Antonella Bancalari (Institute for Fiscal Studies); Kalyan Kumar Kameshwara (Institute for Fiscal Studies) |
| Date: | 2023–12–07 |
| URL: | https://d.repec.org/n?u=RePEc:ifs:ifsewp:23/39 |
| By: | Donghoon Lee; Daniel Mangrum; Wilbert Van der Klaauw; Crystal Wang |
| Abstract: | We examine the impact of financial education on credit decisions during COVID-19. The pandemic presented economic challenges, but policy responses provided opportunities for savvy borrowers. Using variation in state-mandated financial education during high school, we find that mandated borrowers reduced their credit card balances by larger amounts after stimulus checks were distributed and were more likely to buy homes and to refinance mortgages at low rates during the pandemic. The larger credit card balance reduction was driven by middle-income areas and subprime borrowers, while prime borrowers drove mortgage refinancing. Our findings underscore the importance of financial education for economic resilience. |
| Keywords: | financial education; high school curriculum; financial decision-making; household debt; COVID-19 pandemic |
| JEL: | D14 G51 G53 |
| Date: | 2024–10–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednsr:99058 |