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on Payment Systems and Financial Technology |
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Issue of 2019‒06‒24
29 papers chosen by |
| By: | Jillian Grennan (Duke University - Fuqua School of Business; Duke Innovation & Entrepreneurship Initiative); Roni Michaely (University of Geneva - Geneva Finance Research Institute (GFRI); Swiss Finance Institute) |
| Abstract: | Market intelligence FinTechs aggregate many data sources, including nontraditional ones, and synthesize such data using artificial intelligence to make investment recommendations. Using data from a market intelligence FinTech, we evaluate the relationship between the FinTech data coverage and market efficiency. We find an increase in price informativeness for stocks with higher FinTech coverage and that traditional sources of information have less impact on prices for those stocks. Consistent with FinTechs changing investors' behavior, we show a substitution between traditional information sources and FinTechs using internet click data. Overall, our results suggest the rise in FinTechs for investment recommendations benefits investors. |
| Keywords: | Fintech, FinTechs (financial technology firms), Market intelligence, Artificial intelligence, Aggregators, Social media, Financial blogs, Information and market efficiency, Big data, Machine learning, Datamining, Data signal providers |
| JEL: | D14 G11 G14 G23 |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp1910&r=all |
| By: | Serge Ky (LAPE - Laboratoire d'Analyse et de Prospective Economique - IR SHS UNILIM - Institut Sciences de l'Homme et de la Société - UNILIM - Université de Limoges); Clovis Rugemintwari (LAPE - Laboratoire d'Analyse et de Prospective Economique - IR SHS UNILIM - Institut Sciences de l'Homme et de la Société - UNILIM - Université de Limoges); Alain Sauviat (LAPE - Laboratoire d'Analyse et de Prospective Economique - IR SHS UNILIM - Institut Sciences de l'Homme et de la Société - UNILIM - Université de Limoges) |
| Abstract: | Mobile money, a technology-driven innovation in financial services, has profoundly penetrated the financial landscape in Sub-Saharan Africa, including banks. Yet, besides anecdotal evidence, little is known about whether mobile money adoption enhances or worsens bank performance. Combining hand-collected data with balance sheet data from Bankscope for a panel of 170 financial institutions over the period 2009-2015, we find a strong positive and significant relationship between the time elapsed since banks' adoption of mobile money and their performance considering an array of proxies of bank profitability, efficiency and stability. In further investigations, we show how bank specialization and size alter such an association. Our results are robust to using instrumental variables, controlling for bank and macro level confounding factors, bank fixed effects and considering alternative measures of bank performance and mobile money adoption. Furthermore, we show that enhanced income diversification and broadened access to deposits are possible channels through which banks involved in mobile money improve their performance. Overall, our findings highlight the bright side of cooperation between banks and mobile network operators in the provision of mobile money. |
| Keywords: | Fintech,Mobile money,Innovation,Bank performance,East African Community |
| Date: | 2019–06–13 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-02155077&r=all |
| By: | Wendy C.Y. LI; NIREI Makoto; YAMANA Kazufumi |
| Abstract: | The Facebook-Cambridge Analytica data scandal demonstrates that there is no such thing as a free lunch in the digital world. Online platform companies exchange "free" digital goods and services for consumer data, reaping potentially significant economic benefits by monetizing data. The proliferation of "free" digital goods and services pose challenges not only to policymakers who generally rely on prices to indicate a good's value but also to corporate managers and investors who need to know how to value data, a key input of digital goods and services. In this research, we first examine the data activities for seven major types of online platforms based on the underlying business models. We show how online platform companies take steps to create the value of data, and present the data value chain to show the value-added activities involved in each step. We find that online platform companies can vary in the degree of vertical integration in the data value chain, and the variation can determine how they monetize their data and how much economic benefit they can capture. Unlike R&D that may depreciate due to obsolescence, data can produce new values through data fusion, a unique feature that creates unprecedented challenges in measurements. Our initial estimates indicate that data can have enormous value. Online platform companies can capture the most benefit from the data because they create the value of the data and because consumers lack knowledge regarding the value of their own data. As trends such as 5G and the Internet of Things are accelerating the accumulation speed of data types and volume, the valuation of data will have important policy implications for investment, trade, and growth. |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:19022&r=all |
| By: | Li, Yiting; Wang, Chien-Chiang |
| Abstract: | We study cryptocurrency in a monetary economy with imperfect information. The network imperfection provides traders opportunities to engage in double spending fraud, but the trackability of transaction messages allows us to impose proof-of-work (PoW), proof-of-stake (PoS), and currency exclusion to mitigate fraud incentives. However, PoW consumes energy, and PoS requires extra cryptocurrency to be held as deposits, so deterring fraud may not be optimal. We find that forks can serve as signals to detect double spending fraud and to trigger punishments. If the probability is high that forks appear under double spending, imposing PoW and PoS to deter fraud is optimal; otherwise, it is optimal to save the cost but allow for double spending. Finally, by endogenizing the incentives to double spend and the size of PoW and PoS, we show that cryptocurrency economy can achieve efficient allocation as the imperfectness of the internet is sufficiently low. |
| Keywords: | cryptocurrency, money, search, imperfect information, fraud |
| JEL: | D80 E40 G10 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94309&r=all |
| By: | Anna T. Falentina; Budy P. Resosudarmo; Danang Darmawan; Eny Sulistyaningrum |
| Abstract: | The world is going digital. Little is known about how this digitalization affects the performance of micro and small enterprises, one of the major foundations of the economy in developing countries but with relatively low productivity. This paper examines the causal impact of internet utilization, as a part of digitalization, on enterprise performance. We conducted a field survey among micro and small enterprises in Yogyakarta, the densest micro and small enterprise population province in Indonesia. The identification strategy exploits the fact that the differences in geographic topography produce conceivably exogenous variations in the strength of cellular signal that micro and small enterprises in various areas can receive to connect to the internet. We find that internet utilization has enabled micro and small enterprises to engage in the digital economy and has improved labor productivity and exports. |
| Keywords: | digital technology, internet, micro and small enterprises, productivity, exports |
| JEL: | H54 L53 L96 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:pas:papers:2019-08&r=all |
| By: | Estrin, Saul; Gozman, Daniel; Khavul, Susanna |
| Abstract: | Equity crowdfunding (ECF) offers entrepreneurs an online social media marketplace where they can access numerous potential investors who, in exchange for an ownership stake, may supply them with finance. In this paper, we describe the evolution of this market in the UK. Using an inductive qualitative longitudinal research design, we analyse the emerging views of entrepreneurs and investors towards ECF. Our interviewees include large and small-scale investors, as well as market participants who have chosen not to invest or raise funds via ECF. We find that the large financial flows to entrepreneurs in the UK via the ECF platforms, nearly half a billion GBP since 2011, have probably been largely incremental to traditional sources of early stage entrepreneurial finance. Moreover, our research indicates that for the most part, investors appear to understand and appropriately evaluate the risks that they are bearing; ECF investments are perceived as a high risk, high return component within individuals’ portfolios. Investors also use their communication with peers and entrepreneurs via the ECF platform as a learning tool. On the entrepreneurs’ side, ECF allows them to test their products, to develop their brand, to build a loyal customer base and to turn customers into investors. We conclude that policymakers, with the support of a locally appropriate regulatory framework, could support equity crowdfunding as one of the market choices available for entrepreneurs looking to start or grow their ventures |
| Keywords: | Entrepreneurship Equity crowdfunding Early stage entrepreneurial finance Regulation Investor choices |
| JEL: | G21 G3 M21 |
| Date: | 2018–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:87351&r=all |
| By: | Stéphane Blémus (UP1 - Université Panthéon-Sorbonne, Labex ReFi - UP1 - Université Panthéon-Sorbonne, Kalexius law firm, ChainTech); Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS - Centre National de la Recherche Scientifique - UP1 - Université Panthéon-Sorbonne, UP1 - Université Panthéon-Sorbonne, Labex ReFi - UP1 - Université Panthéon-Sorbonne, University of Ca’ Foscari [Venice, Italy], IPAG Business School) |
| Abstract: | This paper discusses the potential impacts of the so-called "initial coin offerings", and of several developments based on distributed ledger technology ("DLT"), on corporate governance. While many academic papers focus mainly on the legal qualification of DLT and crypto-assets, and most notably in relation to the potential definition of the latter as securities/financial instruments, the authors analyze some of the use cases based on DLT technology and their potential for significant changes of the corporate governance analyses. This article studies the consequences due to the emergence of new kinds of firm stakeholders, i.e. the crypto-assets holders, on the governance of small and medium-sized enterprises ("SMEs") as well as of publicly traded companies. Since early 2016, a new way of raising funds has rapidly emerged as a major issue for FinTech founders and financial regulators. Frequently referred to as initial coin offerings, Initial Token Offerings ("ITO"), Token Generation Events ("TGE") or simply "token sales", we use in our paper the terminology Initial Crypto-asset Offerings ("ICO"), as it describes more effectively than "initial coin offerings" the vast diversity of assets that could be created and which goes far beyond the payment instrument issue. |
| Keywords: | ICO,Crypto-asset,Blockchain,Governance,Tokens |
| Date: | 2019–02 |
| URL: | http://d.repec.org/n?u=RePEc:hal:cesptp:halshs-02079171&r=all |
| By: | Zeling Zhong (MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School, LITEM - Laboratoire en Innovation, Technologies, Economie et Management - UEVE - Université d'Évry-Val-d'Essonne - IMT-BS - Institut Mines-Télécom Business School); Christine Balagué (MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School, LITEM - Laboratoire en Innovation, Technologies, Economie et Management - UEVE - Université d'Évry-Val-d'Essonne - IMT-BS - Institut Mines-Télécom Business School) |
| Abstract: | The Consumer Internet of Things (CIoT), which has attracted increasing attention in recent years, is beginning to offer advantageous new services based on advances in IoT technologies, changing our daily lives. Nevertheless, previous literature has provided little insight into smart connected objects (SCO) consumers' appropriation measure and impact. The current research examines this appropriation through an empirical investigation of 505 SCO users by combining marketing and IS perspectives. The results show that CIoT appropriation is a higher order formative construct having knowledge, consciousness, self-adaptation, control, creation, psychological ownership as its first order reflective subdimensions. Furthermore, the study reveals a positive impact of CIoT appropriation on extra role behaviors, perceived value of SCO and satisfaction of life, as well as the mediating role of extra role behavior on the relationship between appropriation and perceived value of SCO. |
| Keywords: | Extra role behavior,Consumer Internet of Things,Appropriation |
| Date: | 2019–05–28 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-02145551&r=all |
| By: | André Binette; Karyne B. Charbonneau; Nicholas Curtis; Gabriela Galassi; Scott Counts; Justin Cranshaw |
| Abstract: | Labour markets in Canada and around the world are evolving rapidly with the digital economy. Traditional data are adapting gradually but are not yet able to provide timely information on this evolution. |
| Keywords: | Central bank research; Labour markets; Monetary Policy |
| JEL: | C80 E24 J21 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:bca:bocsan:19-18&r=all |
| By: | Robert Bartlett; Adair Morse; Richard Stanton; Nancy Wallace |
| Abstract: | Discrimination in lending can occur either in face-to-face decisions or in algorithmic scoring. We provide a workable interpretation of the courts’ legitimate-business-necessity defense of statistical discrimination. We then estimate the extent of racial/ethnic discrimination in the largest consumer-lending market using an identification afforded by the pricing of mortgage credit risk by Fannie Mae and Freddie Mac. We find that lenders charge Latinx/African-American borrowers 7.9 and 3.6 basis points more for purchase and refinance mortgages respectively, costing them $765M in aggregate per year in extra interest. FinTech algorithms also discriminate, but 40% less than face-to-face lenders. These results are consistent with both FinTech and non-FinTech lenders extracting monopoly rents in weaker competitive environments or profiling borrowers on low-shopping behavior. Such strategic pricing is not illegal per se, but under the law, it cannot result in discrimination. The lower levels of price discrimination by algorithms suggests that removing face-to-face interactions can reduce discrimination. Further silver linings emerge in the FinTech era: (1) Discrimination is declining; algorithmic lending may have increased competition or encouraged more shopping with the ease of platform applications. (2) We find that 0.74-1.3 million minority applications were rejected between 2009 and 2015 due to discrimination; however, FinTechs do not discriminate in loan approval. |
| JEL: | G21 G28 J15 K22 K23 R31 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:25943&r=all |
| By: | Brettschneider, Jörg |
| Abstract: | The German law to combat VAT fraud and other tax regulations went into force recently. The German legislator aims to enforce German VAT law via a liability of platform operators (like Amazon and eBay). The consequences of this regulatory approach are a) that platform operators enforce the law more strictly in relation to the ecommerce sellers than required by the law, b) that legal uncertainty occurs and c) that the legal protection of ecommerce sellers is not clear. Background of the more strict enforcement is that platform operators want to avoid liability risks. The situation from the ecommerce sellers’ perspective is described and discussed. |
| Keywords: | VAT,VAT fraud,Umsatzsteuer,ecommerce,online-Handel,Amazon,ebay,Steuerbetrug,Mehrwertsteuer,Gesetz zur Vermeidung von Umsatzsteuerausfällen beim Handel mit Waren im Internet,China,Germany,Haftung,Liability,UStG,Umsatzsteuergesetz,Finanzamt Neukölln,legal enforcement,electronic marketplace,Fulfillment by Amazon,Value Added Tax,Fulfillment,e-commerce,Marktplatzhaftung |
| JEL: | K34 H25 H26 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:197795&r=all |
| By: | David, Alexandra; Terstriep, Judith; Sospiro, Paolo; Scibè, Elisa |
| Abstract: | * From a macro-perspective, digital transformation regarded as a continuous process not only impacts our daily lives but also influences social phenomena such as migration processes. * Rather than a luxury item, for refugees' smartphones appear to open a "new window" to the outside world, which influence social behaviour. * Digital, real-time knowledge and information exchange help refugees to find orientation on their escape routes and within the receiving country and thus, are likely to affect migration processes. * Digital apps and social media in particular are important information and communication channels, which accelerate the circulation of information. However, they might also contribute to the creation of positive and negative myths about destination countries. |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iatfor:062019&r=all |
| By: | Dhillon, Amrita (King’s College London); Kotsialou, Grammateia (King’s College London); McBurney, Peter (King’s College London); Riley, Luke (King’s College London) |
| Abstract: | This work discusses the potential of a blockchain based infrastructure for a decentralised online voting platform. When compared to paper based voting, online voting can vastly increase the speed that votes can be counted, expand the overall accessibility of the election system and decrease the cost of turnout. Yet despite these advantages, online voting for political office is subject to fraud at various levels due to its centralised nature. In this paper, we describe a general architecture of a centralised online voting system and detail which areas of such a system are vulnerable to electoral fraud. We then proceed to introduce the key ideas underlying blockchain technology as a decentralised mechanism that can address these problems. We discuss the advantages and weaknesses of the blockchain technology, the protocols the technology uses and what criteria a good blockchain protocol should satisfy (depending on the voting application). We argue that the decentralisation inherent in the blockchain technology could increase the public’s trust in national elections, as well as eliminate voter impersonation and double voting. We conclude with a discussion regarding how economists and social scientists can collaborate with the blockchain community in a research agenda on the design of efficient blockchain protocols and new voting systems such as liquid democracy. |
| Keywords: | JEL Classification: |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:cge:wacage:416&r=all |
| By: | Heiko Karle; Martin Peitz; Markus Reisinger |
| Abstract: | For many products, platforms enable sellers to transact with buyers. We show that the competitive conditions among sellers shape the market structure in plat form industries. If product market competition is tough, sellers avoid competitors by joining different platforms. This allows platforms to sustain high fees and ex plains why, for example, in some online markets, several homogeneous platforms segment the market. Instead, if product market competition is soft, agglomeration on a single platform emerges, and platforms fight for the dominant position. These insights give rise to novel predictions. For instance, market concentration and fees are negatively correlated in platform industries, which inverts the standard logic of competition. |
| Keywords: | intermediation, two-sided markets, market structure, price competition, endogenous segmentation |
| JEL: | L13 D43 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2019_101&r=all |
| By: | Paul Belleflamme; Martin Peitz |
| Abstract: | We consider two-sided platforms with the feature that some users on one or both sides of the market lack information about the price charged to participants on the other side of the market. With positive cross-group external effects, such lack of price information makes demand less elastic. A monopoly platform does not benefit from opaqueness and optimally reveals price information. By contrast, in a two-sided singlehoming duopoly, platforms benefit from opaqueness and, thus, do not have an incentive to disclose price information. In competitive bottleneck markets, results are more nuanced: if one side is fully informed (for exogenous reasons), platforms may decide to inform users on the other side either fully, partially or not at all, depending on the strength of cross-group external effects and the degree of horizontal differentiation. |
| Keywords: | price transparency, two-sided markets, competitive bottleneck, platform competition, price information, strategic disclosure |
| JEL: | D43 L12 L13 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2019_99&r=all |
| By: | Thomas I. Palley |
| Abstract: | Recently, there has been a burst of interest in modern money theory (MMT). The essential claim of MMT is sovereign currency issuing governments do not need taxes or bonds to finance government spending and are financially unconstrained. MMT rests on a triad of arguments concerning: (i) the macroeconomics of money financed budget deficits, (ii) the employer of last resort or job guarantee program, and (iii) the history of money. This primer analyzes that triad and shows each element involves suspect economic arguments. That leads MMT to underestimate the economic costs and exaggerate the capabilities of money financed fiscal policy. MMT's analytic shortcomings render it poor economics. However, its simplistic printing press economics is proving a popular political polemic, countering the equally simplistic and wrong-headed household economics of neoliberal austerity polemic. |
| Keywords: | Modern money theory (MMT), budget deficits, job guarantee program |
| JEL: | E00 E12 E40 E58 E60 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:imk:fmmpap:44-2019&r=all |
| By: | Michael Bailey; Drew Johnston; Theresa Kuchler; Johannes Stroebel; Arlene Wong |
| Abstract: | We study the nature of peer effects in the market for new cell phones. Our analysis builds on de-identified data from Facebook that combine information on social networks with information on users’ cell phone models. To identify peer effects, we use variation in friends’ new phone acquisitions resulting from random phone losses and carrier-specific contract terms. A new phone purchase by a friend has a substantial positive and long-term effect on an individual’s own demand for phones of the same brand, most of which is concentrated on the particular model purchased by the friend. We provide evidence that social learning contributes substantially to the observed peer effects. While peer effects increase the overall demand for cell phones, a friend’s purchase of a new phone of a particular brand can reduce individuals’ own demand for phones from competing brands—in particular those running on a different operating system. We discuss the implications of these findings for the nature of firm competition. We also find that stronger peer effects are exerted by more price-sensitive individuals. This positive correlation suggests that the elasticity of aggregate demand is substantially larger than the elasticity of individual demand. Through this channel, peer effects reduce firms’ markups and, in many models, contribute to higher consumer surplus and more efficient resource allocation. |
| Keywords: | peer effects, demand spillovers, social learning |
| JEL: | L10 L20 M30 D40 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7685&r=all |
| By: | Antonio Lebeo Guzmán Raya |
| Keywords: | dinero; valor-trabajo; precio; circulación simple; institución monetaria; Money; labor value; price; simple circulation; monetary institution |
| Date: | 2018–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:col:000418:017303&r=all |
| By: | Gary B. Gorton |
| Abstract: | Financial crises are bank runs. At root the problem is short-term debt (private money), which while an essential feature of market economies, is inherently vulnerable to runs in all its forms (not just demand deposits). Bank regulation aims at preventing bank runs. History shows two approaches to bank regulation: the use of high quality collateral to back banks’ short-term debt and government insurance for the short-term debt. Also, explicit or implicit limitations on entry into banking can create charter value (an intangible asset) that is lost if the bank fails. This can create an incentive for the bank to abide by the regulations and not take too much risk. |
| JEL: | G2 G21 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:25891&r=all |
| By: | Chandan K. Jha (Madden School of Business, New York, USA); Oasis Kodila-Tedika (University of Kinshasa, The DRC) |
| Abstract: | This study explores the relationship between social media and democracy in a cross- section of over 125 countries around the world. We find the evidence of a strong, positive correlation between Facebook penetration (a proxy for social media) and democracy. We further show that the correlation between social media and democracy is stronger for low-income countries than high-income countries. Our lowest point estimates indicate that a one-standard deviation (about 18 percentage point) increase in Facebook penetration is associated with about 8-point (on a scale of 0–100) increase for the world sample and over 11 points improvement for low-income countries. |
| Keywords: | Democracy; Information; Facebook; Internet; Social Media |
| JEL: | D72 D83 O1 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:agd:wpaper:19/031&r=all |
| By: | Donald E. Bowen III (Virginia Tech - Department of Finance, Insurance, and Business Law); Laurent Frésard (Universita della Svizzera italiana (USI Lugano); Swiss Finance Institute); Gerard Hoberg (University of Southern California - Marshall School of Business - Finance and Business Economics Department) |
| Abstract: | We show that the recent decline in IPOs on U.S. markets is related to changes in the technological disruptiveness of startups, which we measure using textual analysis of patents from 1930 to 2010. We focus on VC-backed startups and show that those with ex-ante disruptive technologies are more likely to exit via IPO and less likely to exit via sell-out. This is consistent with IPOs being favored by firms with the potential to carve out independent market positions with strong defenses against rivals. We document an economy-wide trend of declining technological disruptiveness since World War II that accelerated since the late 1990s. This trend predicts fewer IPOs and more sell-outs, and we find that roughly 20% of the recent dearth of IPOs, and 49% of the surge in sell-outs, can be attributed to changes in firms' technological characteristics. |
| Keywords: | Initial Public Offerings (IPOs), Acquisitions, Sell-Outs, Technology, Disruptiveness, Venture Capital |
| JEL: | G32 G34 G24 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp1922&r=all |
| By: | Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Konstantinos Gkillas (Department of Business Administration, University of Patras − University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa) |
| Abstract: | In this paper, we use daily data from October 2011 to May 2019 to estimate the monthly realized correlation between stock returns of the United States (US) and Bitcoin returns. Then, we relate the realized correlation with a news-based measure of the growth of trade uncertainty for the US. Our results show that the realized correlation is negatively impacted by increases in trade uncertainty, suggesting that Bitcoin can act as a hedge relative to the US stock market in the wake of heightened trade policy-related uncertainties, and can provide diversification benefits for investors. |
| Keywords: | US stock market, Bitcoin, realized correlation, trade uncertainty |
| JEL: | C22 G10 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:201948&r=all |
| By: | Ojo, Marianne |
| Abstract: | With ever expanding possibilities for innovative advances and technological breakthroughs, the need for facilitating techniques to ensure that economic and environmental sustainability measures can match or rather keep up with such pace of development, is becoming more evident. Artificial Intelligence (AI), vertical integration and block chain systems and technologies will have increasing roles to play, particularly in respect of areas which relate to global climate change, trade and energy, in facilitating transitional processes, complex transactions and changes which are consequential of such developments. The Seychelles “Debt Conversion for Marine Conservation and Climate Program” illustrates the complexity of transactions involved in the program – as well as the need for future and flexible provisional arrangements and technologies which will facilitate the achievement of the goals and objectives of the programs – in addition to the intended roles and engagements of stakeholders involved. Challenges presented with Artificial Intelligence and Block Chain Systems incorporate the need for greater certainty and tested (and proven) procedures with controls and governance in respect of bionic collaborations between humans and technology. In their publication “Harnessing Innovation to Lead the Bionic Lending Revolution (© 2019 PwC)”, Pollini, Hernandez, Prescher and Shipley highlight the following in respect of the “Bionic Revolution”: “With the onset of the fourth industrial revolution (4IR), consumer lending organizations are facing altogether new questions about the future. The lending environment has already experienced vast change; yet, we are quickly seeing a transition into a marketplace of end-to-end home ownership offerings and financial health ecosystems that are likely to trigger a revolution rather than the next stage of evolution.” As well as illustrating and addressing certain questions and challenges which Artificial Intelligence and Block chain technologies face, possible steps forward, and why Blockchain technology, particularly, still has quite a way to go, this paper highlights how such technologies can play vital roles in sustainable development – and with particular reference to complex lending and financing arrangements which embody such programs as those relating to the “Debt Conversion for Marine Conservation and Climate Program”. What possibilities also exist for wild life programs – particularly those aimed at preserving endangered species in environments not heavily affected by air or water pollution? Moreover, how can leading economies engage in programs more effectively to mitigate jurisdictional differences, facilitate disclosure and transparency in their collaborations – whilst also according appropriate considerations to increasingly topical matters as trade, climate change and sustainable development? |
| Keywords: | Artificial Intelligence; Vertical Integration; Block chain systems; Sustainable Development; energy; climate, environment; Fourth Industrial Revolution; The Bionic Revolution; patents; intellectual property; trade relationships; transparency; information disclosure |
| JEL: | D8 G2 G28 G3 K2 Q2 Q5 Q56 |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:94210&r=all |
| By: | Gill Newton (University of Cambridge) |
| Abstract: | Part I of this paper describes a new 'Big Data' resource for historical mortality, the Family History Society burials dataset. This comprises 8.9 million individual records harmonised from Family History Society transcriptions of burial records in 4,200 English places with varying coverage dates spanning from about 1500 to 2000, and concentrated in the period 1600 to 1850. Adult and child burials have been separately identified using family relationship information, and post-1812 more precise age information is stated. Part II presents an exploratory analysis of burial seasonality and age at death using the Family History Society burials dataset. The seasonality of birth and baptism, which impacts on infant burial seasonality, is also considered using a subsample of four English counties (Suffolk, Cambridgeshire, Nottinghamshire and Lancashire). This research forms part of a Wellcome Trust funded research project led by Richard Smith at CAMPOP entitled ‘Migration, Mortality and Medicalisation: investigating the long-run epidemiological consequences of urbanisation 1600-1945’. |
| Keywords: | seasonality, mortality, burials, baptisms, big data |
| JEL: | N33 |
| Date: | 2019–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:cmh:wpaper:34&r=all |
| By: | Simon Schn\"urch; Andreas Wagner |
| Abstract: | This paper employs machine learning algorithms to forecast German electricity spot market prices. The forecasts utilize in particular bid and ask order book data from the spot market but also fundamental market data like renewable infeed and expected demand. Appropriate feature extraction for the order book data is developed. Using cross-validation to optimise hyperparameters, neural networks and random forests are proposed and compared to statistical reference models. The machine learning models outperform traditional approaches. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.06248&r=all |
| By: | Giovanni Barone-Adesi (University of Lugano; Swiss Finance Institute); Antonietta Mira (Università della Svizzera italiana - InterDisciplinary Institute of Data Science); Matteo Pisati (Universita' della Svizzera Italiana) |
| Abstract: | The problem of market predictability can be decomposed into two parts: predictive models and predictors. At first, we show how the joint employment of model selection and machine learning models can dramatically increase our capability to forecast the equity premium out-of-sample. Secondly, we introduce batteries of powerful predictors which brings the monthly S&P500 R-square to a high level of 24%. Finally, we prove how predictability is a generalized characteristic of U.S. equity markets. For each of the three parts, we consider potential and challenges posed by the new approaches in the asset pricing field. |
| Keywords: | Markets Predictability, Machine Learning, Model Selection |
| Date: | 2019–03 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp1915&r=all |
| By: | Suyong Song; Stephen S. Baek |
| Abstract: | We study the association between physical appearance and family income using a novel data which has 3-dimensional body scans to mitigate the issue of reporting errors and measurement errors observed in most previous studies. We apply machine learning to obtain intrinsic features consisting of human body and take into account a possible issue of endogenous body shapes. The estimation results show that there is a significant relationship between physical appearance and family income and the associations are different across the gender. This supports the hypothesis on the physical attractiveness premium and its heterogeneity across the gender. |
| Date: | 2019–06 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1906.06747&r=all |
| By: | Michael Allan Ribers; Hannes Ullrich |
| Abstract: | Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict diagnostic test outcomes for urinary tract infections. Based on predictions, we develop policies to improve prescribing in primary care, highlighting the relevance of physician expertise and policy implementation when patient distributions vary over time. The proposed policies delay antibiotic prescriptions for some patients until test results are known and give them instantly to others. We find that machine learning can reduce antibiotic use by 7.42 percent without reducing the number of treated bacterial infections. As Denmark is one of the most conservative countries in terms of antibiotic use, this result is likely to be a lower bound of what can be achieved elsewhere. |
| Keywords: | antibiotic prescribing, prediction policy, machine learning, expert decision-making |
| JEL: | C10 I11 I18 L38 O38 Q28 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7654&r=all |
| By: | Rishab Guha; Serena Ng |
| Abstract: | This paper analyzes weekly scanner data collected for 108 groups at the county level between 2006 and 2014. The data display multi-dimensional weekly seasonal effects that are not exactly periodic but are cross-sectionally dependent. Existing univariate procedures are imperfect and yield adjusted series that continue to display strong seasonality upon aggregation. We suggest augmenting the univariate adjustments with a panel data step that pools information across counties. Machine learning tools are then used to remove the within-year seasonal variations. A demand analysis of the adjusted budget shares finds three factors: one that is trending, and two cyclical ones that are well aligned with the level and change in consumer confidence. The effects of the Great Recession vary across locations and product groups, with consumers substituting towards home cooking away from non-essential goods. The adjusted data also reveal changes in spending to unanticipated shocks at the local level. The data are thus informative about both local and aggregate economic conditions once the seasonal effects are removed. The two-step methodology can be adapted to remove other types of nuisance variations provided that these variations are cross-sectionally dependent. |
| JEL: | E21 E32 |
| Date: | 2019–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:25899&r=all |