Econophysics of systemic risk and network dynamics

edited by Frédéric Abergel, Bikas K. Chakrabarti, Anirban Chakraborti, Asim Ghosh

The primary goal of the book is to present the ideas and research findings of active researchers such as physicists, economists, mathematicians and financial engineers working in the field of "Econophysics, who have undertaken the task of modeling and analyzing systemic risk, network dynamics and other topics.Of primary interest in these studies is the aspect of systemic risk, which has long been identified as a potential scenario in which financial institutions trigger a dangerous contagion mechanism, spreading from the financial economy to the real economy.This type of risk, long confined to the monetary market, has spread considerably in the recent past, culminating in the subprime crisis of 2008. As such, understanding and controlling systemic risk has become an extremely important societal and economic challenge. The Econophys-Kolkata VI conference proceedings are dedicated to addressing a number of key issues involved. Several leading researchers in these fields report on their recent work and also review contemporary literature on the subject.

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Year of publication:	2013
Authors:	Abergel, Frédéric
Other Persons:	Chakrabarti, Bikas K. (contributor) ; Chakraborti, Anirban (contributor) ; Ghosh, Asim K. (contributor)
Publisher:	Milano : Springer
Subject:	Finanzmarkt \| Financial market \| Systemrisiko \| Systemic risk \| Komplexe Systeme \| Complex systems \| Ökonophysik \| Econophysics
Description of contents:	Description [zbmath.org]

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Extent:	Online-Ressource digital
Series:	New Economic Windows
Type of publication:	Book / Working Paper
Language:	English
Notes:	Description based upon print version of record Econophysics of Systemic Risk and Network Dynamics; Preface; Contents; Part I: Systemic Risk, Network Dynamics and Other Empirical Studies; Chapter 1: Diffusion of Defaults Among Financial Institutions; 1.1 Introduction; 1.2 The Framework; 1.2.1 Contagion Process; The Pure Network Model; Macroeconomic Risk; Ampliﬁcation Effects; 1.2.2 Characterization of the Defaulting Set; 1.3 Measuring Losses and Externalities; 1.3.1 Some Measures; Loss and Externality Conditional on a Bank's Default (Bottom Up); Top Down Ex Ante Evaluation; 1.3.2 Some Properties of the Conditional Loss Some Concluding RemarksReferences; Chapter 2: Systemic Risk and Complex Systems: A Graph-Theory Analysis; 2.1 Introduction; 2.2 Data; 2.3 The Graph Theory: From Full Connected Graphs to Minimum Spanning Trees (MST); 2.3.1 Synchronous Correlation Coefﬁcients of Prices Returns; 2.3.2 From Correlations to Distances; 2.3.3 From Fully Connected Graphs to Minimum Spanning Trees; 2.4 The Topology of the Trees; 2.4.1 The Emerging Taxonomy in the Three Dimensions; 2.4.2 The Evolution of the MSTs Topology Through Time, in the Maturity Dimension; 2.4.3 Allometric Properties of the MST 2.5 Dynamical Analysis2.5.1 The Nodes Strength in the Fully Connected Graphs; 2.5.2 The Length of the Minimum Spanning Trees; 2.5.3 Survival Ratios, the Stability of the Prices System and the Interconnections Between Markets; 2.6 Conclusions; References; Chapter 3: Omori Law After Exogenous Shocks on Supplier-Customer Network; 3.1 Introduction; 3.2 Aftershocks as Chained Failures; 3.2.1 Supplier-Customer Network; 3.2.2 Aftershocks as Chained Failures; 3.3 Omori-Law for Aftershocks on Supplier-Customer Network; 3.4 Discussion; 3.5 Summary; References Chapter 4: Aftershock Prediction for High-Frequency Financial Markets' Dynamics4.1 Introduction; 4.2 Model Calibration; 4.3 Aftershock Prediction; 4.4 Comparison of the Model Predictions with the Statistics of Aftershocks; 4.5 Conclusions; References; Chapter 5: How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations; 5.1 Introduction; 5.2 The Network of Financial Intermediaries; 5.3 Topological Properties; 5.4 Dynamics of Failure Propagation; References; Chapter 6: Study of Statistical Correlations in Intraday and Daily Financial Return Time Series 6.1 Introduction6.2 Some Data Speciﬁcations, Notations, and Deﬁnitions; 6.2.1 Cross-sectional "Dispersion" of the Binned Data; 6.2.2 Correlation Matrix with Tick-by-Tick Data; Hayashi-Yoshida (HY) Estimator; 6.2.3 Pearson Correlation Coefﬁcient and Correlation Matrix with Daily Returns; 6.2.4 Distance Matrix; 6.2.5 Multidimensional Scaling (MDS); 6.3 Results; 6.3.1 U-Effect in Volatility; 6.3.2 The Eigenvalues of the Correlation Matrix and Average Correlations; 6.3.3 MDS Using Intraday Data; 6.3.3.1 Averaged (over Days) Coordinates in Different Bins 6.3.3.2 Averaged (over Days) Correlations in Different Bins
ISBN:	978-88-470-2553-0 ; 978-88-470-2552-3
Other identifiers:	10.1007/978-88-470-2553-0 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014275466