Contagion! Systemic Risk in Financial Networks PDF Download

Author: T. R. Hurd
Publisher: Springer
ISBN: 3319339303
Category : Mathematics
Languages : en
Pages : 146

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Book Description
This volume presents a unified mathematical framework for the transmission channels for damaging shocks that can lead to instability in financial systems. As the title suggests, financial contagion is analogous to the spread of disease, and damaging financial crises may be better understood by bringing to bear ideas from studying other complex systems in our world. After considering how people have viewed financial crises and systemic risk in the past, it delves into the mechanics of the interactions between banking counterparties. It finds a common mathematical structure for types of crises that proceed through cascade mappings that approach a cascade equilibrium. Later chapters follow this theme, starting from the underlying random skeleton graph, developing into the theory of bootstrap percolation, ultimately leading to techniques that can determine the large scale nature of contagious financial cascades.

Author: Anna Nagurney
Publisher: Springer Science & Business Media
ISBN: 3642590667
Category : Business & Economics
Languages : en
Pages : 499

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Book Description
Financial analysis is concerned with the study of capital flows over time and space. This book presents a new theory of multi-sector, multi-instrument financial systems based on the visualization of such systems as networks. The framework is both qualitative and computational and depends crucially on the methodologies of finite-dimensional variational inequality theory for the study of statics and equilibrium states and on projected dynamical systems for the study of dynamics and disequilibrium behavior. Moreover, it adds a graphical dimension to the fundamental economic structure of financial systems and their evolution through time.

Author: Sandra Navidi
Publisher: Nicholas Brealey
ISBN: 1857889797
Category : Business & Economics
Languages : en
Pages : 387

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Book Description
An international bestseller, SUPERHUBS offers a startling new perspective on how the world's elite make the decisions that impact all our lives. A BLOOMBERG Best Book of the Year Winner, Silver Medal, Axiom Business Book Awards 2018 FOREWORD BY NOURIEL ROUBINI $UPERHUBS is a rare, behind-the-scenes look at how the world's most powerful titans, the "superhubs," pull the levers of our global financial system. Combining insider's knowledge with principles of network science, Sandra Navidi offers a startling new perspective on how superhubs build their powerful networks and how their decisions impact all our lives. $UPERHUBS reveals what happens at the exclusive, invitation-only platforms - The World Economic Forum in Davos, the meetings of the International Monetary Fund, think-tank gatherings and exclusive galas. This is the most vivid portrait to date of the global elite: the bank CEOs, fund managers, billionaire financiers and politicians who, through their interlocking relationships and collective influence are transforming our increasingly fragile financial system, economy and society.

Author: Dimitris N Chorafas
Publisher: Springer
ISBN: 134909479X
Category : Computers
Languages : en
Pages : 253

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Book Description
The objective of this book is to provide banks and the financial industry at large with an analysis of what is and what is not a network at their service. The background to the book is electronic banking, and the foreground brings into perspective what has been done by forward-looking financial industries and the benefits they have achieved. While banking is today an industry, it cannot be satisfactorily compared to other industries as it operates too much by its own rules. Examples in the text have therefore been restricted to banking only and, more precisely, to the four generations of online financial networks which have evolved over the past twenty years in Japan. This book is a study addressed to the management of financial institutions. Computers and communications technologists will also gain from it both insight and foresight.

Author: Kimmo Soramäki
Publisher:
ISBN: 9781782724322
Category : Financial risk
Languages : en
Pages : 0

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Book Description
With new innovations in the field, this new edition of Network Theory and Financial Risk has been fully updated and expanded. A hands-on guide to analysing and modelling financial networks, authors Kimmo Soramäki and Samantha Cook provide an in-depth introduction to network theory and examine the general tools for network analysis. [Resumen de editor]

Author: Jimmy Shadbolt
Publisher: Springer Science & Business Media
ISBN: 1447101510
Category : Computers
Languages : en
Pages : 266

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Book Description
This volume looks at financial prediction from a broad range of perspectives. It covers: - the economic arguments - the practicalities of the markets - how predictions are used - how predictions are made - how predictions are turned into something usable (asset locations) It combines a discussion of standard theory with state-of-the-art material on a wide range of information processing techniques as applied to cutting-edge financial problems. All the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract information from very noisy, sparse data sets. Aimed primarily at researchers in financial prediction, time series analysis and information processing, this book will also be of interest to quantitative fund managers and other professionals involved in financial prediction.

Author: Joseph S. Zirilli
Publisher:
ISBN:
Category : Business & Economics
Languages : en
Pages : 168

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Book Description
Focusing on approaches to performing trend analysis through the use of neural nets, this book comparess the results of experiments on various types of markets, and includes a review of current work in the area. It appeals to students in both neural computing and finance as well as to financial analysts and academic and professional researchers in the field of neural network applications.

Author: Anindya S. Chakrabarti
Publisher: Springer Nature
ISBN: 9811383197
Category : Business & Economics
Languages : en
Pages : 454

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Book Description
This book presents the latest findings on network theory and agent-based modeling of economic and financial phenomena. In this context, the economy is depicted as a complex system consisting of heterogeneous agents that interact through evolving networks; the aggregate behavior of the economy arises out of billions of small-scale interactions that take place via countless economic agents. The book focuses on analytical modeling, and on the econometric and statistical analysis of the properties emerging from microscopic interactions. In particular, it highlights the latest empirical and theoretical advances, helping readers understand economic and financial networks, as well as new work on modeling behavior using rich, agent-based frameworks. Innovatively, the book combines observational and theoretical insights in the form of networks and agent-based models, both of which have proved to be extremely valuable in understanding non-linear and evolving complex systems. Given its scope, the book will capture the interest of graduate students and researchers from various disciplines (e.g. economics, computer science, physics, and applied mathematics) whose work involves the domain of complexity theory.

Author: Francis X. Diebold
Publisher: Oxford University Press
ISBN: 0199338329
Category : Business & Economics
Languages : en
Pages : 285

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Book Description
Connections among different assets, asset classes, portfolios, and the stocks of individual institutions are critical in examining financial markets. Interest in financial markets implies interest in underlying macroeconomic fundamentals. In Financial and Macroeconomic Connectedness, Frank Diebold and Kamil Yilmaz propose a simple framework for defining, measuring, and monitoring connectedness, which is central to finance and macroeconomics. These measures of connectedness are theoretically rigorous yet empirically relevant. The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses.

Author: Antonios K. Alexandridis
Publisher: John Wiley & Sons
ISBN: 1118596293
Category : Mathematics
Languages : en
Pages : 262

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Book Description
A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.