Financial Flows Centrality PDF Download

Author: Rogelio V. Mercado (Jr.)
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: SAINAN HUANG
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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This paper investigates the relationship between financial centrality and capital flow waves from a network perspective. Using the BIS CBS dataset on bilateral banking flows from 2000 Q1 through 2021 Q4, we construct several financial centrality measures. Then we discover that financial network centralities play an important role in reducing the occurrence of extreme capital flow movements in the aftermath of the global financial crisis of 2007-2009 (GFC). Therefore, financial network plays a role in explaining why the large global “waves” in international capital flow have more recently become “ripples”

Author: Fuad Aleskerov
Publisher: CRC Press
ISBN: 1000536106
Category : Technology & Engineering
Languages : en
Pages : 114

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Over the last number of years there has been a growing interest in the analysis of complex networks which describe a wide range of real-world systems in nature and society. Identification of the central elements in such networks is one of the key research areas. Solutions to this problem are important for making strategic decisions and studying the behavior of dynamic processes, e.g. epidemic spread. The importance of nodes has been studied using various centrality measures. Generally, it should be considered that most real systems are not homogeneous: nodes may have individual attributes and influence each other in groups while connections between nodes may describe different types of relations. Thus, critical nodes detection is not a straightforward process. New Centrality Measures in Networks presents a class of new centrality measures which take into account individual attributes of nodes, the possibility of group influence and long-range interactions and discusses all their new features. The book provides a wide range of applications of network analysis in several fields – financial networks, international migration, global trade, global food network, arms transfers, networks of terrorist groups, and networks of international journals in economics. Real-world studies of networks indicate that the proposed centrality measures can identify important nodes in different applications. Starting from the basic ideas, the development of the indices and their advantages compared to existing centrality measures are presented. Features Built around real-world case studies in a variety of different areas (finance, migration, trade, etc.) Suitable for students and professional researchers with an interest in complex network analysis Paired with a software package for readers who wish to apply the proposed models of centrality (in Python) available at https://github.com/SergSHV/slric.

Author: Ms.Sheri M. Markose
Publisher: International Monetary Fund
ISBN: 1475577508
Category : Business & Economics
Languages : en
Pages : 58

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Financial network analysis is used to provide firm level bottom-up holistic visualizations of interconnections of financial obligations in global OTC derivatives markets. This helps to identify Systemically Important Financial Intermediaries (SIFIs), analyse the nature of contagion propagation, and also monitor and design ways of increasing robustness in the network. Based on 2009 FDIC and individually collected firm level data covering gross notional, gross positive (negative) fair value and the netted derivatives assets and liabilities for 202 financial firms which includes 20 SIFIs, the bilateral flows are empirically calibrated to reflect data-based constraints. This produces a tiered network with a distinct highly clustered central core of 12 SIFIs that account for 78 percent of all bilateral exposures and a large number of financial intermediaries (FIs) on the periphery. The topology of the network results in the “Too- Interconnected-To-Fail” (TITF) phenomenon in that the failure of any member of the central tier will bring down other members with the contagion coming to an abrupt end when the ‘super-spreaders’ have demised. As these SIFIs account for the bulk of capital in the system, ipso facto no bank among the top tier can be allowed to fail, highlighting the untenable implicit socialized guarantees needed for these markets to operate at their current levels. Systemic risk costs of highly connected SIFIs nodes are not priced into their holding of capital or collateral. An eigenvector centrality based ‘super-spreader’ tax has been designed and tested for its capacity to reduce the potential socialized losses from failure of SIFIs.

Author: Ying Xu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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This paper uses a new approach to measuring financial openness, highlighting interconnectedness in a network of financial flows. Applying an adapted version of eigenvector centrality, often used in network analysis, the new measure captures multidimensional and high-degree financial relations among countries. It provides a nuanced picture of financial integration and interconnectedness in the global and regional financial networks. The United Kingdom and the United States remain the 'core' in the global banking network, with all other countries scattered in the 'periphery'. The application of the new measure of financial integration to the empirical analysis reveals the nonlinear relationship between financial integration and output volatility.

Author: Ying Xu
Publisher:
ISBN:
Category :
Languages : en
Pages : 34

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While deeper financial integration is often considered conducive to the efficient allocation of resources and risk sharing, an increasingly important policy concern is whether it brings greater vulnerability to shocks. To address the latter concern, this paper uses a different approach to measuring financial integration, highlighting interconnectedness in a network of financial flows. Applying an adapted version of eigenvector centrality, often used in network analysis, the new measure provides a nuanced picture of financial integration and interconnectedness in the global and regional financial networks. The United States and the United Kingdom remain the 'core' in the global banking network, with all other countries scattered in the 'periphery'. With China rapidly integrating with the region, the Asian banking network increasingly resembles the structure of the global network. This is the beginning of essential work to discover whether such network structures pose an added threat of shock transmission around the region.

Author: Ying Xu
Publisher:
ISBN:
Category : Banks and banking, International
Languages : en
Pages : 39

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Book Description
This paper uses a new approach to measuring financial openness, highlighting interconnectedness in a network of financial flows. Applying an adapted version of eigenvector centrality, often used in network analysis, the new measure captures multidimensional and high-degree financial relations among countries. It provides a nuanced picture of financial integration and interconnectedness in the global and regional financial networks. The United Kingdom and the United States remain the "core' in the global banking network, with all other countries scattered in the "periphery'. The application of the new measure of financial integration to the empirical analysis reveals the nonlinear relationship between financial integration and output volatility.

Author: Sergio Consoli
Publisher: Springer Nature
ISBN: 3030668916
Category : Application software
Languages : en
Pages : 357

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Book Description
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Author: Daryna Grechyna
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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This paper explores the impact of international trade and financial networks on the current account balances. The network centrality measures are computed based on the structure and volume of trade and financial flows among the countries. A more central position in the international trade network improves the current account balance in developed countries but has no impact on the current account in developing countries. A more central position in the international financial network improves the current account balance in developed and developing countries. Besides, the impact of the international financial network on the current account has become stronger over time.

Author: Nan Zhang
Publisher: Springer Nature
ISBN: 9819710294
Category :
Languages : en
Pages : 311

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