Systemic Risk Tomography: Signals, Measurement and Transmission Channels

Description

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. Front Cover Systemic Risk Tomography: Signals, Measurement and Transmission Channels Copyright 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 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 1.8. Bibliography 2 Systemic Risk and Financial Interconnectedness: Network Measures and the Impact of the Indirect Effect 2.1. Introduction 2.2. Methodology 2.3. The data 2.4. Empirical analysis 2.5. Conclusion 2.6. Acknowledgments 2.7. Bibliography 3 Are Critical Slowing Down Indicators Useful to Detect Financial Crises? 3.1. Introduction 3.2. Theory 3.3. Data and empirical application 3.4. Conclusion 3.5. Bibliography PART 2 Early Warning System for Systemic Risk(s) 5 Score-driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads 5.1. Introduction 5.2. Score-driven systemic risk models 5.3. Data 5.4. Empirical results 5.5. Conclusion 5.6. Bibliography 6 Model-based Business Cycle and Financial Cycle Decomposition for Europe and the United States 6.1. Introduction 6.2. Data 6.3. Multivariate unobserved components model 6.4. Results of empirical study 6.5. Conclusion 6.6. Bibliography 7 Danger Zones for the Financial System 7.1. Introduction 7.2. Risk stratification: from regression trees to ensemble learning 7.3. Implementing an early warning system 7.4. Conclusion 7.5. Bibliography 8 Risk Monitoring Systems in Real-time Based on Dynamic Factor Models 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 8.10. Bibliography PART 3 Policy Implications 9 Policy Lessons from Systemic Risk Modeling and Measurement 9.1. Introduction 9.2. Prevention 9.3. Mitigation 9.4. Stabilization 9.5. Conclusion 9.6. Bibliography List of Authors Index Back Cover