Systemic risk from global financial derivatives : a network analysis of contagion and its mitigation with super-spreader tax

Sheri M. Markose

Financial network analysis is used to provide firm level bottom-up holistic visualizations of interconnections of financial obligations in global OTC derivatives markets. This helps to identify Systemically Important Financial Intermediaries (SIFIs), analyse the nature of contagion propagation, and also monitor and design ways of increasing robustness in the network. Based on 2009 FDIC and individually collected firm level data covering gross notional, gross positive (negative) fair value and the netted derivatives assets and liabilities for 202 financial firms which includes 20 SIFIs, the bil

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Year of publication:	2012
Authors:	Markose, Sheri M.
Publisher:	Washington, DC : Internat. Monetary Fund
Subject:	Derivat \| Derivative \| OTC-Handel \| OTC market \| Systemrisiko \| Systemic risk \| Finanzintermediation \| Financial intermediation \| Ansteckungseffekt \| Contagion effect

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Extent:	Online-Ressource graph. Darst.
Series:	IMF working papers. - Washington, DC : IMF, ZDB-ID 2108494-4. - Vol. 12/282 IMF Working Papers
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Arbeitspapier ; Working Paper ; Graue Literatur ; Non-commercial literature
Language:	English
Notes:	Includes bibliographical references Systemvoraussetzungen: Acrobat Reader Cover; Abstract; Contents; I. Introduction; Figures; 1. Gross Notional of Financial Derivatives; 2. Gross Market Values OTC Derivatives; II. Systemic Risk in OTC Derivatives: Modeling Challenges; A. SIFIs in Derivatives Markets and Market Concentration; 3. Affiliation Graph of Global SIFIs and United States (U.S.) FDIC FIs as Participants in the Five Financial Derivatives Markets; Tables; 1. Value and Market Share of Financial Derivatives for 202 FIs; B. Market Data Based Systemic Risk Measures and Financial Network Perspective; III. Financial Network Analysis A. Adjacency Matrix and Gross Flow Matrix for DerivativesB. Bilaterally Netted Matrix of Payables and Receivables; C. Topology of Financial Networks Complete, Random, Core-periphery, Clustered, and Small World; 2. Networks Statistics: Diagonal Elements Characterize Small World; D. Economics Literature on Financial Networks; E. Eigenvalue Perspective of Network Stability; IV. Contagion and Stability Analysis; A. Furfine (2003) Methodology: Cascades from Failure of a Trigger Bank; B. Financial Network Stability Analysis; C. Mitigation and Management of Financial Contagion: Super-spreader Tax V. Empirical Results: Network Analysis of the Calibrated Aggregated Global Derivatives MarketA. Empirical (Small World) Core-Periphery Network Algorithm; 4. Empirically Constructed Global Derivatives Network (Bilaterally) Aggregated over all Derivatives Products for FIs and Outside Entities: Empirical Small World Network in Tiered Layout; B. Global Derivatives Network Statistics (2009:Q4); 3. Network Statistics for Degree Distribution for Derivatives Network 2009 Q4; C. Eigenvector Centrality and Furfine Stress Test Results; 4. Rich Club Statistics 5. 2009:Q4 Derivatives Network Eigenvector Centrality and Furfine First Round Contagion Results for Top 20 FIs5. Furfine Contagion Stress test on Empirical Calibrated Derivatives; D. Quantification and Evaluation of the Super-spreader Tax (2009 Q4); 6. Maximum Eigenvalue (λ(sup[#])(sub[max]) ,Y-Axis) Using Different Values of α> 0(Equation; 7. Individual FI Tax Rates Obtained by Multiplying Right Eigenvector Centrality by or Different Values of Alpha α>0; VI. Conclusion; 6. Super-Spreader Tax Raised from Top 20 SIFIs; Appendix Tables; A.1 Financial Derivatives for the Top 22 Banks; References Electronic reproduction; Available via World Wide Web
ISBN:	978-1-4755-3186-2 ; 978-1-4755-7750-1 ; 978-1-4755-7750-1
Source:	ECONIS - Online Catalogue of the ZBW

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