Systemic Risk Tomography

Systemic Risk Tomography

Signals, Measurement and Transmission Channels

1st Edition - November 22, 2016

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  • Authors: Monica Billio, Loriana Pelizzon, Savona Roberto
  • Hardcover ISBN: 9781785480850
  • eBook ISBN: 9780081011768

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In April 2010 Europe was shocked by the Greek financial turmoil. At that time, the global financial crisis, which started in the summer of 2007 and reached systemic dimensions in September 2008 with the Lehman Brothers’ crash, took a new course. An adverse feedback loop between sovereign and bank risks reflected into bubble-like spreads, as if financial markets had received a wake-up call concerning the disregarded structural vulnerability of economies at risk.These events inspired the SYRTO project to “think and rethink” the economic and financial system and to conceive it as an “ensemble” of Sovereigns and Banks with other Financial Intermediaries and Corporations. Systemic Risk Tomography: Signals, Measurement and Transmission Channels proposes a novel way to explore the financial system by sectioning each part of it and analyzing all relevant inter-relationships. The financial system is inspected as a biological entity to identify the main risk signals and to provide the correct measures of prevention and intervention.

Key Features

  • Explores the economic and financial system of Sovereigns, Banks, other Financial Intermediaries, and Corporations
  • Presents the financial system as a biological entity to be explored in order to identify the main risk signals and provide the right measures of prevention and interventions
  • Offers a new, systemic-based approach to construct a hierarchical, internally coherent framework to be used in developing an effective early warning system


Universities (graduate and phd students), academic researchers, policy institutions (national central banks, IMF, ECB, BIS, OECD, EC)

Table of Contents

    • Introduction: Systemic Risk: Measures and Warnings
      • I.1 Introduction
      • I.2 The new systemic risk context
      • I.3 Systemic risk objectives
      • I.4 Some lessons we learned in studying systemic risks: the book content
      • I.5 Conclusion
    • Part 1: Risk Connections and Systemic Risk Indicators
      • 1: Systemic Risk via Dynamic Correlations
        • Abstract
        • 1.1 Introduction
        • 1.2 The problem
        • 1.3 Review
        • 1.4 The model of Dellaportas et al.
        • 1.5 Estimation with nested Laplace approximations
        • 1.6 Empirical studies
        • 1.7 Conclusion
      • 2: Systemic Risk and Financial Interconnectedness: Network Measures and the Impact of the Indirect Effect
        • Abstract
        • 2.1 Introduction
        • 2.2 Methodology
        • 2.3 The data
        • 2.4 Empirical analysis
        • 2.5 Conclusion
        • 2.6 Acknowledgments
      • 3: Are Critical Slowing Down Indicators Useful to Detect Financial Crises?
        • Abstract
        • 3.1 Introduction
        • 3.2 Theory
        • 3.3 Data and empirical application
        • 3.4 Conclusion
      • 4: Onset of Financial Instability Studied via Agent-based Models
        • Abstract
        • 4.1 Introduction
        • 4.2 Experimental approach
        • 4.3 Simulation approach
        • 4.4 Experimental results
        • 4.5 Simulation results
        • 4.6 Conclusion
        • 4.7 Acknowledgments
    • Part 2: Early Warning System for Systemic Risk(s)
      • 5: Score-driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads
        • Abstract
        • 5.1 Introduction
        • 5.2 Score-driven systemic risk models
        • 5.3 Data
        • 5.4 Empirical results
        • 5.5 Conclusion
      • 6: Model-based Business Cycle and Financial Cycle Decomposition for Europe and the United States
        • Abstract
        • 6.1 Introduction
        • 6.2 Data
        • 6.3 Multivariate unobserved components model
        • 6.4 Results of empirical study
        • 6.5 Conclusion
      • 7: Danger Zones for the Financial System
        • Abstract
        • 7.1 Introduction
        • 7.2 Risk stratification: from regression trees to ensemble learning
        • 7.3 Implementing an early warning system
        • 7.4 Conclusion
      • 8: Risk Monitoring Systems in Real-time Based on Dynamic Factor Models
        • Abstract
        • 8.1 Introduction
        • 8.2 Systemic risks: definitions and measurement
        • 8.3 The model
        • 8.4 Estimation and forecasting
        • 8.5 Identification and stress testing
        • 8.6 Implementation
        • 8.7 Conclusion
        • 8.8 Appendix A: tables and figures
        • 8.9 Appendix B: list of variables
    • Part 3: Policy Implications
      • 9: Policy Lessons from Systemic Risk Modeling and Measurement
        • Abstract
        • 9.1 Introduction
        • 9.2 Prevention
        • 9.3 Mitigation
        • 9.4 Stabilization
        • 9.5 Conclusion
    • List of Authors
    • Index

Product details

  • No. of pages: 300
  • Language: English
  • Copyright: © ISTE Press - Elsevier 2016
  • Published: November 22, 2016
  • Imprint: ISTE Press - Elsevier
  • Hardcover ISBN: 9781785480850
  • eBook ISBN: 9780081011768

About the Authors

Monica Billio

Monica Billio is Full Professor of Econometrics at Ca’ Foscari University of Venice, Italy. She is participating in many research projects financed by the European Commission, Eurostat and the Italian Ministry of Research. She was scientific co-coordinator of the SYRTO project.

Affiliations and Expertise

Professor of Econometrics, Department of Economics, University Ca’Foscari of Venice

Loriana Pelizzon

Loriana Pelizzon is Full Professor of Economics at Ca’ Foscari University of Venice, Italy. She is also the program director of the Systemic Risk Lab and Chair of Law and Finance at Research Centre SAFE at Goethe University in Frankfurt, Germany.

Affiliations and Expertise

Program Director, Systemic Risk Lab and Chair, Law and Finance, Research Centre SAFE, Goethe University Frankfurt

Savona Roberto

Roberto Savona is Professor of Financial Markets and Institutions at the University of Brescia, Italy. He served as a Member of the Steering Committee of the Macro‐prudential Research Network – ECB. He was primary and scientific coordinator of the SYRTO project.

Affiliations and Expertise

Associate Professor, Financial Markets and Institutions, University of Brescia

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