Extreme and Systemic Risk Analysis: A Loss Distribution Approach (Integrated Disaster Risk Management)

✍ Scribed by Stefan Hochrainer-Stigler

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 166
• Category: Library

✦ Synopsis

This book is about how extreme and systemic risk can be analyzed in an integrated way. Risk analysis is understood to include measurement, assessment as well as management aspects. Integration is understood as being able to perform risk analysis for extreme and systemic events simultaneously. The presented approach is based on Sklar's theorem, which states that a multivariate distribution can be separated into two parts – one describing the marginal distributions and the other describing the dependency between the distributions using a so-called copula. It is suggested to reinterpret Sklar's theorem from a system or network perspective, treating copulas as a network property and individual, including extreme, risk as elements within the network. In that way, extreme and systemic risk can be analyzed independently as well as jointly across several scales. The book is intended for a large audience, and all techniques presented are guided with examples and applications with a special focus on natural disaster events. Furthermore, an extensive literature and discussion of it are given in each chapter for the interested reader.

✦ Table of Contents

Foreword to the IDRiM Book Series
Contents
List of Figures
List of Tables
1 Introduction
1.1 Risk Analysis of Extremes: Loss Distributions
1.2 Systemic Risk Analysis: Dependencies and Copulas
1.3 Extreme and Systemic Risk Analysis: Sklar's Theorem
1.4 The Way Forward: Structure of Book and Related Literature
References
2 Individual Risk and Extremes
2.1 The Loss Distribution
2.2 Extreme Value Theory and Statistics
2.2.1 Distributions of Maxima
2.2.2 Distribution of Exceedances
2.2.3 Point Process Characterization of Extremes
2.2.4 Modeling the K Largest Order Statistics
2.2.5 Temporal Dependence and Non-stationarity Issues
2.3 Risk Management Using Loss Distributions
References
3 Systemic Risk and Dependencies
3.1 Dependence Measures
3.2 Multivariate Dependence Modeling with Copulas
3.3 A Joint Framework Using Sklar's Theorem: Copulas as a Network Property
3.4 Resilience, Risk Layering, and Multiplex Networks
References
4 Applications
4.1 Modeling Applications
4.1.1 Hierarchical Coupling: Flood Risks on the Regional Level
4.1.2 Minimax and Structural Coupling: Pan-European Flooding
4.1.3 Vine Coupling: Large-Scale Drought Risk
4.2 Measuring and Managing Individual and Systemic Risk
4.2.1 Risk Layering on the Regional and Country Level
4.2.2 An Application to the EU Solidarity Fund
4.2.3 Multi-hazard and Global Risk Analysis
4.3 Loss Distributions and ABM Modeling
References
5 Conclusion
References