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on Payment Systems and Financial Technology |
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Issue of 2020‒09‒21
29 papers chosen by |
| By: | Rod Garratt; Maarten van Oordt |
| Abstract: | We assess how the cost structure of cryptocurrency mining affects the response of miners to exchange rate fluctuations and the immutability of cryptocurrency ledgers that rely on proof-of- work. We show that the amount of mining power supplied to currencies that rely on application-specific integrated circuits (ASICs), such as Bitcoin, responds less to adverse exchange rate shocks than other currencies respond to such shocks, a fact that is instrumental to avoiding double-spending attacks. The results may change if mining equipment used for one cryptocurrency can be transferred to another. For smaller currencies with low exchange rate correlation, transferability eliminates the protection that fixed costs provide. Our results weaken doomsday predictions for Bitcoin and other cryptocurrencies with declining block rewards. |
| Keywords: | Digital currencies and fintech, Payment clearing and settlement systems |
| JEL: | G10 L11 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:20-27&r=all |
| By: | James Caddy (Reserve Bank of Australia); Luc Delaney (Reserve Bank of Australia); Chay Fisher (Reserve Bank of Australia) |
| Abstract: | Since 2007 the Reserve Bank has conducted a Consumer Payments Survey (CPS) every three years, which provides comprehensive information on how Australians make their payments. The 2019 CPS was conducted just before the emergence of COVID-19 in Australia and gives a detailed snapshot of consumer payment behaviour prior to the changes in spending patterns induced by the pandemic. The survey provided further evidence that Australian consumers increasingly prefer to use electronic payment methods rather than cash for their day-to-day payments. Many people now tap their cards (or sometimes phones) even for small purchases. When paying with a card in person or online, consumers are more often choosing to use a debit card rather than a credit card. As a result, debit cards were the most frequently used consumer payment method in the 2019 survey. Consumers are also increasingly taking advantage of the ability to make payments using a range of innovative new payment services that have emerged in recent years, often facilitated by mobile technology and the use of digital payment credentials. Despite the trend towards electronic payments, cash still accounted for a significant share of lower-value payments and a material proportion of the population continue to make many of their payments in cash. |
| Keywords: | consumer payment choice; consumer survey; method of payment; payment systems |
| JEL: | D12 D14 E42 |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:rba:rbardp:rdp2020-06&r=all |
| By: | Tut, Daniel |
| Abstract: | This paper investigates the effects of the Covid-19 pandemic on financial institutions and consumers’ adoption of FinTech in payments. We find that the pandemic: [1] Initially had a negative impact on the adoption of FinTech, but favorable short-term regulatory changes have reversed some of the negative effects [2] The use of all electronic payment cards has significantly declined during the pandemic except for charge cards. We find an increase in the use of charge cards as consumers shift towards cheaper forms of payment [3] The pandemic has magnified interbank contagion and liquidity risks and has reduced both domestic and international electronic fund transfers via RTGS. The pandemic has also resulted in a deterioration in the quality of commercial banks’ assets and balance sheets [4] Remittance inflows via FinTech platforms have significantly declined reflecting contractions in global economic activities. |
| Keywords: | Covid-19, Coronavirus, Fintech, Mobile Payment, Central Banks, Financial Intermediaries, Financial Technologies, Banks, Interbank transfers, Diaspora Remittances, Settlement and Liquidity risks, clearing houses, financial stability, Pandemic, M-PESA, Digital Banking. |
| JEL: | E32 E52 E58 G21 G28 G32 O16 O31 O32 O33 O38 O55 |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102401&r=all |
| By: | Tomić, Bojan |
| Abstract: | Cryptocurrencies represent a new type of digital asset that cannot be linked to the framework of fundamental and systematic factors of existing financial instruments of the traditional capital market. Due to the lack of strictly defined fundamental indicators, supported by the results of research by the academic community, considering cryptocurrencies as investment opportunities can put investors in a subordinate position, a situation of complete uncertainty. Cryptocurrencies and their entire technical infrastructure are still a kind of unknown to the general public. Due to this, but also the lack of a regulatory framework, investors have to rely on sometimes uncertain information gathered through various media platforms. However, regardless of the type of assets and the mentioned shortcomings, when constructing a portfolio, investors should consider the dynamics of returns of potential components of the portfolio in order to identify and quantify the assumed investment risk and define the expected return. Cryptocurrencies are based on the idea of decentralization initially introduced by bitcoin blockchain technology and as such have their own historical sequence of origin. Since bitcoin is the first digital currency based on asymmetric cryptography, the change in its value can serve as a leading indicator of the movement of the cryptocurrency market as a whole. Accordingly, this paper will formally identify and describe the performance of the cryptocurrency portfolio with different optimization goals taking into account the assumption of a significant systematic impact of bitcoin cryptocurrency on the dynamics of the value of the aggregate secondary cryptocurrency market. For this purpose, six optimization targets will be formed: MinVar, MinCVaR, MaxSR, MaxSTARR, MaxUT and MaxMean. The results of the formed portfolios will be compared with the results of portfolios with the same allocation objectives, but which include a limitation on the impact of BTC as a systematic factor. The results suggest that by controlling the exposure by factor, better overall portfolio performance can be achieved through higher returns and Sharpe Ratio in four of the six implemented optimization strategies, while in terms of absolute risk measure five out of six portfolios achieved lower overall risk. Also, the obtained results confirm that the bitcoin transaction system plays a major role in defining the future movement of the value of the secondary cryptocurrency market. |
| Keywords: | cryptocurrencies, portfolio choice, factor investing, risk management, portfolio return |
| JEL: | E49 G11 P45 |
| Date: | 2020–05–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:101290&r=all |
| By: | Nicholas Economides (Professor of Economics, NYU Stern School of Business, New York, New York 10012); Ioannis Lianos (Professor of Global Competition Law and Public Policy, Faculty of Laws, University College London, and Hellenic Competition Commission) |
| Abstract: | We discuss how the acquisition of private information by default without compensation by digital platforms such as Google and Facebook creates a market failure and can be grounds for antitrust enforcement. To avoid the market failure, the default in the collection of personal information has to be changed by law to “opt-out.” This would allow the creation of a vibrant market for the sale of users’ personal information to digital platforms. Assuming that all parties are perfectly informed, users are better off in this functioning market and digital platforms are worse off compared to the default opt-in. However, just switching to a default opt-in will not restore competition to the but for world because of the immense market power and bargaining power towards an individual user that digital platforms have acquired. Digital platforms can use this power to reduce the compensation that a user would receive for his/her personal information compared to a competitive world. Additionally, it is likely that the digital platforms are much better informed than the user in this market, and can use this information to disadvantage users in the market for personal information. |
| Keywords: | personal information; Internet search; Google; Facebook; digital; privacy; restrictions of competition; exploitation; market failure; hold up; merger; abuse of a dominant position; unfair commercial practices; excessive data extraction; self-determination; behavioral manipulation; remedies; portability; opt-in; opt-out. |
| JEL: | K21 L1 L12 L4 L41 L5 L86 L88 |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:net:wpaper:2005&r=all |
| By: | Andres, Raphaela; DeStefano, Timothy; Niebel, Thomas; Viete, Steffen |
| Abstract: | The following paper assesses whether current policy environments are appropriate for the emergence of cloud computing technology. In particular, this research uses firm-level data for Germany and the UK to examine the impact of capital incentive programmes (a common policy present in most OECD countries) on cloud adoption. The design for many of these policies target investments in physical capital while excluding digital services like the cloud. Firms view digital investments and digital services as substitutes, therefore narrowly define dincentive programmes may actually discourage the use of emerging tools like cloud computing, which are found to enable the growth and performance of young entrants. Overall, the results find that while capital incentive policies encourage firm investments in ICT and other forms of capital, they actually reduce the probability of cloud adoption. Policy makers may therefore need to reconsider the design of capital incentive programmes within their jurisdictions. |
| Keywords: | Cloud Computing,Investment Scheme,ICT Adoption,Technology Diffusion,Policy Evaluation |
| JEL: | L22 O33 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:20036&r=all |
| By: | Diego Rojas; Juan Estrada; Kim Huynh; David T. Jacho-Chávez |
| Abstract: | The efficient distribution of bank notes is a first-order responsibility of central banks. We study the distribution patterns of bank notes with an administrative dataset from the Bank of Canada's Currency Information Management Strategy. The single note inspection procedure generates a sample of 900 million bank notes in which we can trace the length of the stay of a banknote in the market. We define the duration of the bank note circulation cycle as beginning on the date the note is first shipped by the Bank of Canada to a financial institution and ending when it is returned to the Bank of Canada. In addition, we provide information regarding where the bank note is shipped and later received, as well as the physical fitness of the bank note upon return to the Bank of Canada's distribution centres. K-prototype clustering classifies bank notes into types. A hazard model estimates the duration in circulation of bank notes based on their clusters and characteristics. An adaptive elastic net provides an algorithm for dimension reduction. It is found that while the distribution of the duration is affected by fitness measures, those effects are negligible when compared with the influence exerted by the clusters related to bank note denominations. |
| Keywords: | Bank notes; Econometric and statistical methods; Payment clearing and settlement systems |
| JEL: | E51 C81 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:20-33&r=all |
| By: | Nicole Jonker; Anneke Kosse |
| Abstract: | The entry of Big Tech firms in the financial ecosystem might affect financial stability through the opportunities and challenges they create for financial inclusion. In this paper we survey the literature to determine the effectiveness of financial education in improving financial literacy and financial inclusion and to assess the impact of financial inclusion on financial stability. Based on our findings, we argue that new empirical research is needed to determine whether financial education can play a role in ensuring that everyone is able to reap the financial-inclusion benefits that Big Tech may bring. We also conclude that financial-inclusion opportunities created by Big Tech might potentially introduce risks for overall financial stability. Because of this, we underline the importance of proper supervision and regulation. |
| Keywords: | Development economics; Digital currencies and fintech; Financial markets; Financial services; Financial stability |
| JEL: | D92 G23 O16 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocawp:20-32&r=all |
| By: | Simplice A. Asongu (Yaounde, Cameroon); Mushfiqur Rahman (University of Wales, London, UK); Joseph Nnanna (The Development Bank of Nigeria, Abuja, Nigeria); Mohamed Haffar (University of Bradford, Bradford, UK) |
| Abstract: | This study investigates how enhancing information and communication technology (ICT) affects value added across sectors in 25 countries in Sub-Saharan Africa using data for the period 1980-2014. The empirical evidence is based on the Generalised Method of Moments. The following findings are established. First, the enhancement of mobile phone and internet penetrations respectively have net negative effects on value added to the agricultural and manufacturing sectors.Second, enhancing ICT (i.e. mobile phone penetration and internet penetration) overwhelmingly has positive net effects on value added to the service sector. From an extended analysis, enhancing ICT in the agricultural and manufacturing sectors should exceed certain thresholds for value added, notably: 114.375 of mobile phone penetration per 100 people for added value in the agricultural sector and 22.625 of internet penetration per 100 people for added value in the manufacturing sector. |
| Keywords: | Economic Output; Information Technology; Sub-Saharan Africa |
| JEL: | E23 F21 F30 L96 O55 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:agd:wpaper:20/064&r=all |
| By: | Jian Pei |
| Abstract: | It is well recognized that data are invaluable. How can we assess the value of data objectively, systematically and quantitatively? Pricing data, or information goods in general, has been studied and practiced in dispersed areas and principles, such as economics, marketing, electronic commerce, data management, data mining and machine learning. In this article, we present a unified, interdisciplinary and comprehensive overview of this important direction. We examine various motivations behind data pricing, understand the economics of data pricing and review the development and evolution of pricing models according to a series of fundamental principles. We cover both digital products and data products. Last, we discuss a series of challenges and directions for future work. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.04462&r=all |
| By: | Alla A. Petukhina; Raphael C. G. Reule; Wolfgang Karl H\"ardle |
| Abstract: | This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market. We study trading quantitatives such as returns, traded volumes, volatility periodicity, and provide summary statistics of return correlations to CRIX (CRyptocurrency IndeX), as well as respective overall high-frequency based market statistics with respect to temporal aspects. Our results provide mandatory insight into a market, where the grand scale employment of automated trading algorithms and the extremely rapid execution of trades might seem to be a standard based on media reports. Our findings on intraday momentum of trading patterns lead to a new quantitative view on approaching the predictability of economic value in this new digital market. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.04200&r=all |
| By: | Tetsuya Takaishi |
| Abstract: | While relevant stylized facts are observed for Bitcoin markets, we find a distinct property for the scaling behavior of the cumulative return distribution. For various assets, the tail index $\mu$ of the cumulative return distribution exhibits $\mu \approx 3$, which is referred to as "the inverse cubic law." On the other hand, that of the Bitcoin return is claimed to be $\mu \approx 2$, which is known as "the inverse square law." We investigate the scaling properties using recent Bitcoin data and find that the tail index changes to $\mu \approx 3$, which is consistent with the inverse cubic law. This suggests that some properties of the Bitcoin market could vary over time. We also investigate the autocorrelation of absolute returns and find that it is described by a power-law with two scaling exponents. By analyzing the absolute returns standardized by the realized volatility, we verify that the Bitcoin return time series is consistent with normal random variables with time-varying volatility. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.06874&r=all |
| By: | Bruno Jullien; Wilfried Sand-Zantman |
| Abstract: | We propose an analysis of platform competition based on the academic literature with a view towards competition policy. First, we discuss to which extent competition can emerge in digital markets and show which forms it can take. In particular, we underline the role of dynamics, but also of platform differentiation, consumers multi-homing and beliefs to allow competition in platform markets. Second, we analyse competition policy issues and discuss how rules designed for standard markets can perform in two-sided markets. We show that multi-sided externalities create new opportunities for anti-competitive conducts, often related to pricing and contractual imperfections. |
| Keywords: | networks, platforms, markets, competition policy |
| JEL: | L13 L41 L86 D82 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8463&r=all |
| By: | David Bounie (Télécom ParisTech); Antoine Dubus (Télécom ParisTech); Patrick Waelbroeck (Ecole Nationale Supérieure des Télécommunications de Bretagne) |
| Abstract: | This article investigates the strategies of a data broker selling information to one or to two competing firms. The data broker combines segments of the consumer demand that allow firms to third-degree price discriminate consumers. We show that the data broker (1) sells information on consumers with the highest willingness to pay; (2) keeps consumers with low willingness to pay unidentified. The data broker strategically chooses to withhold information on consumer demand to soften competition between firms. These results hold under first degree price discrimination, which is a limit case when information is perfect. |
| Keywords: | Data broker,Information Structure,Price-discrimination |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01794886&r=all |
| By: | Liu, Dan; Jin, Yanhong; Pray, Carl; Liu, Shuang |
| Keywords: | Agricultural Finance, Agribusiness, Community/Rural/Urban Development |
| Date: | 2020–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea20:304238&r=all |
| By: | Lehuedé, Héctor J. |
| Abstract: | This paper presents and discusses the relation between cybersecurity and corporate governance in the context of Latin America and the Caribbean. It notes that progress has been made in improving corporate cybersecurity within the region mostly from a data protection perspective, either as a result of internally driven or regulatory motivated corporate initiatives, but that not enough headway has been made regarding the cyber risks affecting critical infrastructure and essential services in the hands of private or State-owned companies. The paper describes some of the best corporate governance practices and guidance for boards of directors to address cybersecurity issues, as well as a selection of the regulatory incentives that lawmakers and regulators are deploying to incentivize boards to adopt proper cyber risk management. Three case studies are presented as examples of these types of policy interventions in the region. |
| Keywords: | INTERNET, TECNOLOGIA DE LA INFORMACION, TECNOLOGIA DE LAS COMUNICACIONES, SEGURIDAD DE DATOS COMPUTARIZADOS, ESTUDIOS DE CASOS, ESTRATEGIA EMPRESARIAL, INTERNET, INFORMATION TECHNOLOGY, COMMUNICATION TECHNOLOGY, COMPUTER SECURITY, CASE STUDIES, CORPORATE STRATEGIES |
| Date: | 2020–09–04 |
| URL: | http://d.repec.org/n?u=RePEc:ecr:col026:45988&r=all |
| By: | Asongu, Simplice A; Odhiambo, Nicholas M |
| Abstract: | This study investigates the relationship between social media and inclusive human development in 49 African countries for the year 2012. Social media is measured with Facebook penetration whereas inclusive human development is proxied by the inequality- adjusted human development index. The empirical evidence is based on Ordinary Least Squares, Tobit and Quantile regressions. Ordinary Least Squares provided baseline results, Tobit regressions account for the limited range in the outcome variable while Quantile regressions are engaged to control for initial levels of inequality-adjusted human development. From Ordinary Least Squares and Tobit results, Facebook penetration is positively associated with inclusive human development. Quantile regressions confirm this positive nexus and further establish that the positive association is slightly higher in magnitude in the above-median sub-sample. From a comparative assessment, it is apparent that with the exception of the resource-wealth sub-samples, higher levels of Facebook penetration are associated with comparatively higher levels of inclusive human development. Accordingly, the positive association between Facebook penetration and inclusive human development is: (i) a positive function of income levels and (ii) more apparent in Middle East and North African countries (compared to Sub-Saharan African countries), English common law countries (compared to their French civil law counterparts), and coastal countries (in relation to landlocked countries). |
| Keywords: | Social Media; Inclusive development; Income levels; Regions |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:uza:wpaper:26637&r=all |
| By: | Pengfei Xi; Shiyang Lai; Xueying Wang; Weiqiang Huang |
| Abstract: | This article proposed a hybrid detrended deconvolution foreign exchange network construction method (DDFEN), which combined the detrended cross-correlation analysis coefficient (DCCC) and the network deconvolution method together. DDFEN is designed to reveal the `true' correlation of currencies by filtering indirect effects in the foreign exchange networks (FXNs). The empirical results show that DDFEN can reflect the change of currency status in the long term and also perform more stable than traditional network construction methods. |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2008.09482&r=all |
| By: | Andrej Gill; Matthias Heinz; Heiner Schumacher; Matthias Sutter |
| Abstract: | The financial industry has been struggling with widespread misconduct and public mistrust. Here we argue that the lack of trust into the financial industry may stem from the selection of subjects with little, if any, trustworthiness into the financial industry. We identify the social preferences of business and economics students, and follow up on their first job placements. We find that during college, students who want to start their career in the financial industry are substantially less trustworthy. Most importantly, actual job placements several years later confirm this association. The job market in the financial industry does not screen out less trustworthy subjects. If anything the opposite seems to be the case: Even among students who are highly motivated to work in finance after graduation, those who actually start their career in finance are significantly less trustworthy than those who work elsewhere. |
| Keywords: | trustworthiness, financial industry, selection, social preferences, experiment |
| JEL: | C91 G20 M51 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_8501&r=all |
| By: | Assistant, JHET; Baronian, Laurent |
| Abstract: | The paper is dedicated to Suzanne de Brunhoff’s monetary thought and shows how her analysis of very concrete monetary and financial problems of her time led her to develop the most innovative contributions to Marxist theory of money since classical Marxism. Concepts such as noncontemporaneity of capitalism with itself, pseudo-social validation, conflict centralization or State management of money and labor power reflect her profound analysis of the ways capitalism generates very particular relationships to space and time. It is by looking at this spatio-temporal dimension of Brunhoff’s concepts that this paper aims to reveal the novelty, power and fruitfulness of her monetary analysis. The first part of the paper seeks to define the meaning of the notion of general equivalent extracting from her reading of Marx's Capital, before situating her approach in relation to Institutionalist theories of money. The second turns to Brunhoff’s analysis of the particular time-spaces of capitalism. |
| Date: | 2020–08–20 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:vg4h9&r=all |
| By: | Rodrigo Rivera-Castro; Polina Pilyugina; Evgeny Burnaev |
| Abstract: | Portfolio management is essential for any investment decision. Yet, traditional methods in the literature are ill-suited for the characteristics and dynamics of cryptocurrencies. This work presents a method to build an investment portfolio consisting of more than 1500 cryptocurrencies covering 6 years of market data. It is centred around Topological Data Analysis (TDA), a recent approach to analyze data sets from the perspective of their topological structure. This publication proposes a system combining persistence landscapes to identify suitable investment opportunities in cryptocurrencies. Using a novel and comprehensive data set of cryptocurrency prices, this research shows that the proposed system enables analysts to outperform a classic method from the literature without requiring any feature engineering or domain knowledge in TDA. This work thus introduces TDA-based portfolio management of cryptocurrencies as a viable tool for the practitioner. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.03362&r=all |
| By: | Löschel, Andreas; Rodemeier, Matthias; Werthschulte, Madeline |
| Abstract: | Non-pecuniary incentives motivated by insights from psychology ("nudges") have been shown to be effective tools to change behavior in a variety of fields. An often unanswered question relevant for public policy is whether these promising interventions can be scaled up. In cooperation with a large public utility in Germany, we develop an energy savings application for mobile phones that can be used by the majority of the population. The app randomizes a goal-setting nudge prompting users to set themselves energy consumption targets. The roll-out of the app is promoted by a mass-marketing campaign and large financial incentives. Results document low demand for the energy app in the general population and a tightly estimated null effect of the nudge on electricity consumption among app users. A likely mechanism of the null effect is unfavorable self-selection into the app: users are characterized by an already low baseline energy consumption and exhibit none of the behavioral biases that typically explain why goal setting affects behavior. We also find that the nudge significantly decreases the likelihood to use the app over time. Structural estimates imply that the average user is willing to pay 7.41 EUR to avoid the nudge and the intervention would yield substantial welfare losses if implemented nationwide. |
| Keywords: | nudging,goal setting,scalability,field experiments,energy,behavioral welfare economics,mobile phones |
| JEL: | C93 D91 Q49 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:20039&r=all |
| By: | Yan Wang; Xuelei Sherry Ni |
| Abstract: | In the peer-to-peer (P2P) lending market, lenders lend the money to the borrowers through a virtual platform and earn the possible profit generated by the interest rate. From the perspective of lenders, they want to maximize the profit while minimizing the risk. Therefore, many studies have used machine learning algorithms to help the lenders identify the "best" loans for making investments. The studies have mainly focused on two categories to guide the lenders' investments: one aims at minimizing the risk of investment (i.e., the credit scoring perspective) while the other aims at maximizing the profit (i.e., the profit scoring perspective). However, they have all focused on one category only and there is seldom research trying to integrate the two categories together. Motivated by this, we propose a two-stage framework that incorporates the credit information into a profit scoring modeling. We conducted the empirical experiment on a real-world P2P lending data from the US P2P market and used the Light Gradient Boosting Machine (lightGBM) algorithm in the two-stage framework. Results show that the proposed two-stage method could identify more profitable loans and thereby provide better investment guidance to the investors compared to the existing one-stage profit scoring alone approach. Therefore, the proposed framework serves as an innovative perspective for making investment decisions in P2P lending. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.04536&r=all |
| By: | Ramos-Sosa, Maria del Pino; Cabrera, Domingo; Moreno, Bernardo |
| Abstract: | Currently, the preparations of the exams are made by the teaching or responsible teams to evaluate the students or applicants through an objective test to subsequently get a grade. We propose a system based on the use of Blockchain technology and smart contracts that would allow an automated preparation of test-type assessment tests, and the registration of the answers in a Blockchain ledger. The record of the answers made is registered chronologically, guaranteeing that the answers and the grades will not be modified, in addition to allowing the student to have access to that information (with prior consent). We also propose that the test’s questions be obtained from a "question pool", previously filled in by experts in the field, and classified by level of difficulty, what would allow the assessors or students to establish the level of difficulty of the test. This would allow the creation of a more enriched curriculum for eachstudent, the student wallet, a wallet containing the scores of exams, and the level in which students have accomplished the competencies and the skills acquired throughout their academic experience. |
| Keywords: | Educational technology evaluation, Blockchain, Smart contracts, Competencies, Student wallet. |
| JEL: | I21 I23 |
| Date: | 2020–07–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:101518&r=all |
| By: | Yongge Wang |
| Abstract: | This paper compares mathematical models for automated market makers including logarithmic market scoring rule (LMSR), liquidity sensitive LMSR (LS-LMSR), constant product/mean/sum, and others. It is shown that though LMSR may not be a good model for Decentralized Finance (DeFi) applications, LS-LMSR has several advantages over constant product/mean based automated market makers. However, LS-LMSR requires complicated computation (i.e., logarithm and exponentiation) and the cost function curve is concave. In certain DeFi applications, it is preferred to have computationally efficient cost functions with convex curves to conform with the principle of supply and demand. This paper proposes and analyzes constant circle/ellipse based cost functions for automated market makers. It is shown that the proposed cost functions are computationally efficient (only requires multiplication and square root calculation) and have several advantages over widely deployed constant product cost functions. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.01676&r=all |
| By: | Jorrat, Diego |
| Abstract: | The aim of many experiments is to estimate the effect of different interventions on subjects' decision making. However, obtaining large samples and internal validity is challenging. This paper presents an alternative device at almost no cost that can easily provide a very large number of participants (700 in 5 hours). We asked 14 students to invite their WhatsApp contacts to participate in an online experiment. The students created a total of 80 diffusion groups with 25 contacts each. Using the diffusion groups as clusters, we ran a cluster randomization procedure in order to assign subjects to a framing experiment (treatment + control). We obtained the same level of attrition, duplicates and uninvited subjects across the treatment and control groups. Moreover, the experiment yielded consistent results in line with the framing literature. |
| Keywords: | Recruiting, Online Experiments, Prisoner's Dilemma, Randomization |
| JEL: | C8 C9 C99 D70 |
| Date: | 2020–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:101467&r=all |
| By: | Alabi Reuben Adeolu; Oshobugie Ojor Adams (Universität Bremen,Germany) |
| URL: | http://d.repec.org/n?u=RePEc:aer:wpaper:390&r=all |
| By: | Minzhi Wu (Department of Economics, Universitat Jaume I, Castellón, Spain); Emili Tortosa-Ausina (IVIE, Valencia and Department of Economics, Universitat Jaume I, Castellón, Spain) |
| Abstract: | Bank diversification and focus strategies are becoming crucial issues for commercial banks’ future viability, due to their links with the emergence of new products, services and competitors. We investigate the effects of such strategies for Chinese banks during 2007–2018, a particularly turbulent period for both macroeconomic reasons (the impact of the 2007/08 international financial crisis) as well as others related to innovation in the industry—such as the rise of FinTech. For this, we construct measures of diversification from both the two main perspectives taken into account so far by the literature, namely, incomebased indicators and asset-based indicators. In the case of income-based indicators, we consider further categories—non-interest income ratio, the Herfindahl-Hirschman index, and the entropy index. We evaluate the impact of the different indicators considered on measures of risk and profitability, and whether this impact varies depending on the type of bank—state-owned banks, national shareholding commercial banks, and city commercial banks. We argue that the links can be too intricate to be captured by linear models and, complementing the previous literature, evaluate them considering semiparametric specifications. Overall results indicate that Chinese banks do not benefit to a great deal in terms of profitability and risk by following neither income nor asset diversification strategies, although the former are higher than the latter. |
| Keywords: | bank, China, diversification, focus, semiparametric regression |
| JEL: | G21 G28 C14 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:jau:wpaper:2020/21&r=all |
| By: | Alla Petukhina; Simon Trimborn; Wolfgang Karl H\"ardle; Hermann Elendner |
| Abstract: | Cryptocurrencies (CCs) have risen rapidly in market capitalization over the last years. Despite striking price volatility, their high average returns have drawn attention to CCs as alternative investment assets for portfolio and risk management. We investigate the utility gains for different types of investors when they consider cryptocurrencies as an addition to their portfolio of traditional assets. We consider risk-averse, return-seeking as well as diversificationpreferring investors who trade along different allocation frequencies, namely daily, weekly or monthly. Out-of-sample performance and diversification benefits are studied for the most popular portfolio-construction rules, including mean-variance optimization, risk-parity, and maximum-diversification strategies, as well as combined strategies. To account for low liquidity in CC markets, we incorporate liquidity constraints via the LIBRO method. Our results show that CCs can improve the risk-return profile of portfolios. In particular, a maximum-diversification strategy (maximizing the Portfolio Diversification Index, PDI) draws appreciably on CCs, and spanning tests clearly indicate that CC returns are non-redundant additions to the investment universe. Though our analysis also shows that illiquidity of CCs potentially reverses the results. |
| Date: | 2020–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2009.04461&r=all |