48 research outputs found
Replication Data for The Rise of Finance Companies and FinTech Lenders in Small Business Lending
No full textStata code and non-proprietary data to replicate results in Gopal and Schnabl (2022
Computer science : an overview / J. Glenn Brookshear and Dennis Brylow ; global edition contributions by Manasa S.
No full textPrevious edition 2012.Includes bibliographical references and index.640 pages :This classic book provides an overview to the field of computing, with new material on networking, C#, XML, and Java, making it the most current book available. The seventh edition has been thoroughly updated to discuss important trends in such areas as networking and the Internet, software engineering, public-key encryption, and artificial intelligence. The discussions of the ethical and legal issues revolving around computing have been expanded in this edition. This book is for those who are interested in taking a tour of the field of computer science, as well as those taking an introductory course on these topics
Market-based Eurobonds Without Cross-Subsidisation
Get PDFMost current Eurobond proposals imply substantial cross-subsidisation since some countries partially pay the risk premia for others, thus creating moral hazard and disincentives for fiscal discipline. We suggest, instead, to use standard technologies of financial intermediation like pooling and collateralizing risks. The proposed Eurobond system decreases the costs for all participating nations which is Pareto improving. Since collateral requirements are calculated on individual risk, we eliminate cross-subsidisation. It is essential for the model that a significant fraction of governmental bonds is still issued individually since the model utilizes the risk perception abilities and disciplinating functions of the private capital market. We also discuss institutional issues of possible implementations
Essays on Household Finance, FinTech, and Entrepreneurship
No full textThis dissertation consists of five essays that examine the intersection of household finance, FinTech, and entrepreneurship, leveraging comprehensive credit bureau data and novel empirical strategies. The first essay investigates the impact of banks' cloud technology adoption on credit card management and borrower outcomes, highlighting differential effects across credit segments. The second essay compares the long-term borrowing capacities and outcomes of marketplace lending (MPL) borrowers to those of traditional bank borrowers, emphasizing the limitations of data-driven lending models in mitigating information frictions. The third essay documents significant gender-based sorting across credit card products and its implications for gender gaps in borrowing capacities and consumption smoothing. The fourth essay studies the impact of the federal student loan forbearance program on distressed borrowers' debt accumulation and delinquency patterns, suggesting that extended forbearance may accelerate financial distress. The final essay examines the negative long-term consequences of entrepreneurship on entrepreneurs' personal credit, highlighting the role of increased personal borrowing and the potential costs of business-friendly policies.Ph.D
Essays on Fintech, AI, and Innovation in Finance
No full textThe dissertation consists of five essays on FinTech, AI and innovation in finance. These essays center around how innovation and capital market influence each other, and how to use cutting-edge technologies like machine learning and AI to address the economic questions that would otherwise remain unanswered. In the first essay, I investigate the redeployability channel of trademarks' collateral value. Using a novel court decision that exogenously weakens trademark redeployability, I find a 3.4 percentage point reduction in affected firms’ book leverage, equivalent to a 16.9\% decrease in their average book leverage. By using firm-level trademark portfolio data and employing natural language processing (NLP) techniques, including ChatGPT, I show that firms with more licensed trademarks (i.e., those more exposed to the court ruling), experience a stronger negative impact. Additionally, affected firms are less likely to pledge their registered trademarks as collateral afterward. When they do pledge, they pledge a greater number of trademarks, as well as more valuable ones. Affected firms also register fewer new trademarks in the future. In sum, my results highlight the value of trademark collateral in enhancing firms' debt capacity through its redeployability channel.
In the second essay, we develop a text-based measure of firm-level inflation exposure from earnings calls. Our deep learning model identifies sentences discussing price changes, while distinguishing price increases from decreases and inputs from outputs. Our aggregate inflation exposure measure strongly correlates with official inflation measures. Firms with higher inflation exposure experience negative stock price reactions to earnings calls. The price reaction is attenuated when a firm has pricing power. Further, firms with higher inflation exposure have higher future costs of goods sold and lower operating cash flows. They perform worse on Consumer Price Index (CPI) release days when CPI exceeds the consensus forecast.
In the third essay, we explore the area of emerging technologies which can potentially transform business and society but are difficult to identify and prone to hype and uncertainty. We construct a dictionary of emerging technology phrases from earnings calls using deep learning techniques and document an immediate positive stock market reaction to firms’ discussions of emerging technologies. We find that the positive reaction is more pronounced when firms discuss emerging technologies early in their life cycle. Firms with lower ex-ante credibility, such as a prior history of earnings management, innovate less ex-post and experience poorer long-term returns. Overall, our results highlight when firms' discussions of emerging technologies convey credible information to investors.
The fourth essay examines whether managers walk the talk on the environmental and social discussion. We train a deep-learning model on various corporate sustainability frameworks to construct a comprehensive Environmental and Social (E\&S) dictionary. Using this dictionary, we find that the discussion of environmental topics in the earnings conference calls of U.S. public firms is associated with higher pollution abatement and more future green patents. Similarly, the discussion of social topics is positively associated with improved employee ratings. The association with E\&S performance is weaker for firms that give more non-answers and when the topic is immaterial to the industry. Overall, our results provide some evidence that firms do walk their talk on E\&S issues.
In the final essay, we address the limitations of generic training schemes in the realm of financial language models. We propose a novel domain specific Financial LANGuage model (FLANG) which uses financial keywords and phrases for better masking. We further extend it to include span boundary objective and in-filing objective, utilizing the fact that many financial terminologies are phrases. Additionally, the evaluation benchmarks in the field have been limited. To this end, we contribute the Financial Language Understanding Evaluation (FLUE), an open-source comprehensive suite of benchmarks for the financial domain. These include new benchmarks across 5 NLP tasks in financial domain as well as common benchmarks used in the previous research. Experiments on these benchmarks suggest that our model outperforms those in prior literature on a variety of NLP tasks.Ph.D
Magneto-transport in an interacting single molecular transistor using Anderson-Holstein model
No full textIMS in 5G: Analysis of IMS based communication services in the 5G network
No full textThe thesis focuses on investigating the role of IP Multimedia Subsystem (IMS) in 5G networks. IMS already plays a very important role in enabling a wide range of real-time multimedia communication services such as basic phone calls and messaging in the LTE network. Addition of application servers on top of the IMS core can provide enhanced functionalities like presence, advanced messaging and SIP trunking. IMS guarantees quality, security and reliability of multimedia services when serving users without the installation of any application as well as flexibility over access. This sets IMS apart from other third party applications found on the internet. IMS was created with the idea of being adaptable to the evolving technology. With the implementation of the 5G network underway, a study of the impact of this new architecture on the IMS services is imminent. The thesis focuses on the study of different network elements participating in an IMS service as well as investigating IMS voice and video calls over the 5G network.The thesis consists of two parts: The first part involves exploring the role of IMS in 5G networks. A brief overview of the evolution of mobile networks will help understand the differences between 1G/2G/3G/4G. Following this, IMS and its role in enabling multimedia services in the LTE network is explored. Next, the 5G System Architecture is explained along with components and their functions.Next, a comparison between the elements in 4G and 5G provides a clear understanding of the technological evolution and the procedure involved. The next steps would include understanding the IMS call flow in LTE networks. This would provide a good foundation to understand how the IMS services will be provided over the 5G network. The second part of the thesis includes testing the voice and video services over Ericsson’s 5G network at their Rijen office. As a starting step, the voice and video services are tested using WebRTC. Upon succeeding in the peer-to-peer test, the next step is establishing connectivity to Ericsson’s IMS network at Kista, Sweden. This will allow the testing of IMS voice and video services over the 5G network. The results are recorded and analysed. These are in agreement with the theoretical expectations.Electrical Engineering | Telecommunications and Sensing System
Characterization of Polyhydroxyalkanoates Producing Bacillus species
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Potentiation of Endosulfan Induced Oxidative Stress by Thiram
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Enzyme Assisted Extraction of Ginger Oleoresin.
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
