The Wiley Series in Modeling and Simulation provides an interdisciplinary and global approach to the numerous real-world applications of modeling and simulation (M&S) that are vital to business professionals, researchers, policymakers, program managers, and academics alike. Written by recognized international experts in the field, the books present the best practices in the applications of M&S as well as bridge the gap between innovative and scientifically sound approaches to solving real-world problems and the underlying technical language of M&S research. The series successfully expands the way readers view and approach problem solving in addition to the design, implementation, and evaluation of interventions to change behavior. Featuring broad coverage of theory, concepts, and approaches along with clear, intuitive, and insightful illustrations of the applications, the Series contains books within five main topical areas: Public and Population Health; Training and Education; Operations Research, Logistics, Supply Chains, and Transportation; Homeland Security, Emergency Management, and Risk Analysis; and Interoperability, Composability, and Formalism.
Founding Series Editors:
Joshua G. Behr, Old Dominion University
Rafael Diaz, MIT Global Scale
Advisory Editors:
Homeland Security, Emergency Management, and Risk Analysis
Interoperability, Composability, and Formalism
Saikou Y. Diallo, Old Dominion University
Mikel Petty, University of Alabama
Operations Research, Logistics, Supply Chains, and Transportation
Loo Hay Lee, National University of Singapore
Public and Population Health
Peter S. Hovmand, Washington University in St. Louis
Bruce Y. Lee, University of Pittsburgh
Training and Education
Thiago Brito, University of Sao Paolo
Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology
By S.M. Niaz Arifin, Gregory R. Madey, Frank H. Collins
The Digital Patient: Advancing Healthcare, Research, and Education
By C.D. Combs (Editor), John A. Sokolowski (Editor), Catherine M. Banks (Editor)
This edition first published 2017
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The book “BANKING SYSTEMS SIMULATION” intuitively presents essentials tools for integrating risks in banks and bank systems that are essential for risk professionals and regulators.
Prof. Harald Scheule,
University of Technology Sydney, Australia
Stefano Zedda succeeds in illustrating a wide array of state of the art techniques to set up effective models of bank management, risks and contagion. Real life applications show how the book's key concepts can be used to overcome data limitations and develop parsimonious, yet accurate representations of how outside shocks and policy changes affect lenders.
Prof. Andrea Resti,
Università Bocconi, Italy
The book offers a comprehensive analysis of bank and banking system risks by adopting a simulation framework and an integrated approach between the micro and macro dimension of risk management. The analysis provides important insights for academics, regulators and practitioners.
Prof. Francesco Vallascas,
University of Leeds, UK
Why write (or read) another book about models of banking? It sometimes seems that banking is passé — that the real financial action lies elsewhere. A recent survey (R. Greenwood and D. Scharfstein, “The Growth of Finance,” J. of Econ. Perspectives, 2013) documents the explosive growth in non-bank financial products and services. Securities markets more than quadrupled in size, from 0.4 to 1.7 percent of GDP between 1980 and 2007, on the eve of the crisis. Surely this is where we should focus — the busy secondary markets for bonds, equities, securitized products, and over-the-counter derivatives.
Yet, reports of the demise of traditional banking have been greatly exaggerated. Credit intermediation, which includes traditional deposit-taking and lending alongside banks' transactional services such as credit-card accounts and ATM activity, have also grown. Starting from a much larger share, Greenwood and Scharfstein (2013) calculate that credit intermediation grew from 2.6 to 3.4 percent of GDP over the 1980–2007 period. When the dust has settled on a quarter century of remarkable growth, banking is still roughly twice the size of securities markets.
One key reason that banking has been able to keep pace with the booming secondary markets is that banking is a key player in them. Banks provide custodial services for investors and asset managers, prime brokerage services for hedge funds, and much of the loan origination at the front end of asset securitization pipelines. Banks also still dominate the wholesale funding markets that manage much of the financial sector's liquidity provision every day.
Perhaps most importantly, banks provide the crucial cornerstone of financial capital upon which much of the edifice of credit expansion is built. The ability to leverage capital to extend liquidity (by expanding lending) during an economic expansion is critical to the functioning of the system. But the possibility of overleveraging and aggregate liquidity shocks are critical dangers. The crisis of 2007–09 demonstrated that these are not idle fantasies. The challenges of defining “adequate” capital and liquidity levels and ensuring that banks meet this standard are the driving forces behind the often highly technical conversations around the new Basel III, supervisory stress testing, and orderly resolution protocols.
In short, the management and regulation of banks and banking remain important, challenging, and timely topics, worthy of our attention.
Why is simulation a useful approach for addressing these topics? Simulation has two key features that make it an appropriate methodology in this context. First, the financial sector in general, and banking in particular, are evolving rapidly. In addition to the growing volumes of activity, there are significant innovations in both institutions and practice. For example, an entrepreneurial wave of fintech innovation is working to disrupt retail payments and traditional lending channels; supervisors are forging ahead with major new efforts in stress testing and data-driven regulation; and post-crisis institutional reforms are forcing the clearing and settlement of many over-the-counter transactions onto central counterparties. The upshot of these changes is that past is not prologue for many important questions. Moreover, the pace of innovation is such that market participants and regulators alike continue to wrestle with yet new counterfactual proposals. When simple historical patterns cease to be reliable, a higher-order model is vital. Second, many of these issues, especially at the system level, involve intricate interactions and nonlinear feedback effects that pose insurmountable tractability challenges for more traditional theoretical models.
Simulations can be implemented poorly, of course, but when done well, they have the potential to provide us guidance on this turbulent voyage. Books like the one you are reading help move us toward this better practice.
Mark D. Flood
Washington, D.C.
February 2017
Simulation methods have recently received great attention, and many studies based on this approach have been developed in the last decade for assessing banking systems stability, determinants, and possible consequences.
Different approaches have been developed to address the main problems, but no single paper aimed at analyzing some specific aspect gives a complete picture or an orderly presentation of the topic.
The aim of this book is to present in an orderly manner the main steps, information sources, and methodologies developed for modeling and simulating banking systems stability and its applications.
The recent financial crises have led to the realization of the importance of simulations, as on one hand systemic risks are really important, and on the other hand it is not possible to make all analyses based on actual data, as the available data are limited by case number, early intervention of supervisors, and the framework evolution.
The modeling and simulation approach, which has been particularly described and developed in this book, is based on a theoretical representation of the fundamental mechanisms of risk managing of banks, and it aims at simulating the possible outcome of the banking sector as a consequence of important shocks, or for having some clue about what the consequences can be in case of regulation changes, modifications in the system structure, introduction or modification of the safety net, and other possible interventions or policies.
This book also includes the main references for banking systems risk simulation, including the models used for representing and quantifying the main banking risk sources, the banking network linkages representation and estimation, correlation and contagion mechanisms, simulation models and methods, and the most important applications for evaluating and testing the effects of possible interventions and regulation changes, and contributes to a better understanding of the banking systems risks and stability.