Spatial Dependence and Data-Driven Networks of International Banks


Book Description

This paper computes data-driven correlation networks based on the stock returns of international banks and conducts a comprehensive analysis of their topological properties. We first apply spatial-dependence methods to filter the effects of strong common factors and a thresholding procedure to select the significant bilateral correlations. The analysis of topological characteristics of the resulting correlation networks shows many common features that have been documented in the recent literature but were obtained with private information on banks' exposures, including rich and hierarchical structures, based on but not limited to geographical proximity, small world features, regional homophily, and a core-periphery structure.







Global Financial Stability Report, April 2015


Book Description

The current report finds that, despite an improvement in economic prospects in some key advanced economies, new challenges to global financial stability have arisen. The global financial system is being buffeted by a series of changes, including lower oil prices and, in some cases, diverging growth patterns and monetary policies. Expectations for rising U.S. policy rates sparked a significant appreciation of the U.S. dollar, while long term bond yields in many advanced economies have decreased—and have turned negative for almost a third of euro area sovereign bonds—on disinflation concerns and the prospect of continued monetary accommodation. Emerging markets are caught in these global cross currents, with some oil exporters and other facing new stability challenges, while others have gained more policy space as a result of lower fuel prices and reduced inflationary pressures. The report also examines changes in international banking since the global financial crisis and finds that these changes are likely to promote more stable bank lending in host countries. Finally, the report finds that the asset management industry needs to strengthen its oversight framework to address financial stability risks from incentive problems between end-investors and portfolio managers and the risk of runs due to liquidity mismatches.




IMF Research Bulletin, December 2016


Book Description

The Research Summaries in this issue of the IMF Research Bulletin cover “Tax Capacity and Growth” (by Vitor Gaspar, Laura Jaramillo, and Philippe Wingender), and “U.S. Shale Revolution and Its Spillover Effects on the Global Economy” (Ravi Balakrishnan, Keiko Honjo, Akito Matsumoto, and Andrea Pescatori). The Q&A coauthored by Amadou Sy and Mariama Sow covers “Seven Questions about the Relationship between Country Finance and Governance.” A listing of recent IMF Working Papers, Staff Discussion Notes, and Recommended Readings from IMF Publications is included in the IMF Research Bulletin. Readers can also find news on free-to-view articles from IMF Economic Review and a call for conference papers in this issue of the Bulletin.




The Econometrics of Networks


Book Description

Showcasing fresh methodological and empirical research on the econometrics of networks, and comprising both theoretical, empirical and policy papers, the authors in this volume bring together a wide range of perspectives to facilitate a dialogue between academics and practitioners for better understanding this groundbreaking field.




Handbook of Applied Economic Statistics


Book Description

This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.




Data Analytics for Management, Banking and Finance


Book Description

This book is a practical guide on the use of various data analytics and visualization techniques and tools in the banking and financial sectors. It focuses on how combining expertise from interdisciplinary areas, such as machine learning and business analytics, can bring forward a shared vision on the benefits of data science from the research point of view to the evaluation of policies. It highlights how data science is reshaping the business sector. It includes examples of novel big data sources and some successful applications on the use of advanced machine learning, natural language processing, networks analysis, and time series analysis and forecasting, among others, in the banking and finance. It includes several case studies where innovative data science models is used to analyse, test or model some crucial phenomena in banking and finance. At the same time, the book is making an appeal for a further adoption of these novel applications in the field of economics and finance so that they can reach their full potential and support policy-makers and the related stakeholders in the transformational recovery of our societies. The book is for stakeholders involved in research and innovation in the banking and financial sectors, but also those in the fields of computing, IT and managerial information systems, helping through this new theory to better specify the new opportunities and challenges. The many real cases addressed in this book also provide a detailed guide allowing the reader to realize the latest methodological discoveries and the use of the different Machine Learning approaches (supervised, unsupervised, reinforcement, deep, etc.) and to learn how to use and evaluate performance of new data science tools and frameworks




AI 2023: Advances in Artificial Intelligence


Book Description

This two-volume set LNAI 14471-14472 constitutes the refereed proceedings of the 36th Australasian Joint Conference on Artificial Intelligence, AI 2023, held in Brisbane, QLD, Australia during November 28 – December 1, 2023. The 23 full papers presented together with 59 short papers were carefully reviewed and selected from 213 submissions. They are organized in the following topics: computer vision; deep learning; machine learning and data mining; optimization; medical AI; knowledge representation and NLP; explainable AI; reinforcement learning; and genetic algorithm.




Community Based Water Management and Social Capital


Book Description

Community Based Water Management and Social Capitalprovides scientific understanding of community based water management and how to secure responsible management to satisfy quality and quantity requirements. It shows how community based water management can be synchronized with public water service, by introducing the most recent field experiments and theoretical studies in economics, social science, engineering, and regional planning which include game theory, microeconomics, econometric, statistics, social network analysis, social choice, and micro finance. Community Based Water Management and Social Capital presents field experiments and theoretical studies in economics, social science, engineering, and regional planning to investigate important questions: what motivates people involve in voluntary water management what is the effect of participatory approach in water management how does social capital work in the voluntary actions what are key factors for effective governance for water management with diverse actors - local people, enterprise, and government; what is necessary for proper water allocation; vi) how to synchronize public water service with community based water management. The book provides students, researchers, practitioners and governments with a comprehensive account of the current situation and perspectives on voluntary water management. It delivers a new scientific understanding on sustainable water management schemes and appropriate institutional social structures to secure inalienable rights to access to water. Author: Kiyoshi Kobayashi, Kyoto University, Japan, Ibnu Syabri Institute of Technology Bandung, Indonesia, Ismu Rini Dwi Ari, Brawijaya University, East Java, Hayeong Jeong, Isabel C Escobar, Andrea Schaefer.




Spatial Econometrics


Book Description

Advances in Econometrics 37 highlights key research in econometrics in a user friendly way for economists who are not econometricians.