Default Cascades in Scale-free Networks Assessing the role of - PowerPoint PPT Presentation

Default Cascades in Scale-free Networks Assessing the role of topology in the emergence of systemic risk Tarik Roukny 1 , 3 Stefano Battiston 2 Hugues Bersini 1 Hugues Pirotte 3 1 IRIDIA, Université Libre de Bruxelles 2 Chair of System Design, ETH Zurich 3 Centre Emile Bernheim, Université Libre de Bruxelles September 11, 2012 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 1 / 33

Outline Introduction 1 The Model 2 Contagion Dynamics Market’s structure Experiments and Results 3 Validating the model Out-degree distribution Liquidity level Conclusion 4 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 2 / 33

Introduction "The Economic Crisis is a Crisis for Economic Theory" “[...] systematic warnings over more than a century [...] have been ignored and we have persisted with models which are both unsound theoretically and incompatible with data . It is suggested that we drop the unrealistic individual basis for aggregate behavior and the even more unreasonable assumption that the aggregate behaves like such a rational individual . We should rather analyse the economy as a complex adaptive system , and take the network structure that governs interaction into account.” Kirman, 2010 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 3 / 33

Introduction Complex Systems and Networks in Complex Systems The inner structure can have an influence on the system’s stability Epidemics The Internet Power Grids Albert, Albert, Albert, Jeong, Nakarado Barabasi, Pastor-Satorras, Vespignani, 2004 2000 2000 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 4 / 33

Introduction Our Question In Financial Systems What influence can the network’s structure have on default contagion and systemic risk? Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 5 / 33

Introduction Background Litterature Review Empirical studies and stress-test analysis 1 Italy: (Mistrulli 2005), (Iori et al. , 2007) Austria: (Boss et al. , 2004) USA: (Furfine et al. , 2003) Belgium: (Degryse & Nguyen, 2007) Brazil: (Cont et al. , 2011), (Cajueiro& Tabak, 2008) Germany: (Upper & Worms, 2002) etc. Default contagion dynamic models 2 From models of social influence: (Granovetter, 1978), (Watts, 2002) (Eisenberg & Noe, 2001): fictitious default sequence (Gai & Kapadia, 2010), (Battiston et al. , 2012), (Cont et al. , 2011) Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 6 / 33

Introduction In this work Overview of the Model Agent-based model Agents: financial institutions Interactions: credit ties Network: market’s structure From the analytical model introduced in (Battiston et al ., 2012) a Default cascades in credit networks (e.g. interbank market) 2 channels of contagion: Direct 1 Illiquidity and Panic 2 Analysis on the impact of risk diversification a Battiston, S., Gatti, D. D., Gallegati, M., Greenwald, B., and Stiglitz, J. E. (2012). Default cascades: When does risk diversification increase stability? Journal of Financial Stability 8, 3, 138-149 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 7 / 33

Introduction Take home message Contribution to the debate on the optimal architecture of the financial system w.r.t. systemic risk and default contagion No single topology is always optimal regardless of the market conditions Several factors matter: Asset market liquidity 1 Correlation between core-capital and connectivity degree 2 Correlation in-degree and out-degree 3 Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 8 / 33

The Model A E B F H C G D Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 10 / 33

The Model Financial robustness index ∼ equity ratio � A N η i = ( A i − L i ) / ij j Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 11 / 33

The Model Contagion Channels - First type Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 12 / 33

The Model Contagion Channels - First type Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 13 / 33

The Model Contagion Channels - First type η i ( t ) = η i ( 0 ) − k fi ( t ) k i Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 14 / 33

The Model Contagion Channels Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 15 / 33

The Model Contagion Channels - Second type Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 16 / 33

The Model Contagion Channels - Second type η i ( t ) = η i ( 0 ) − k fi ( t ) − b , if η i ( 0 ) < γ k fi ( t ) k i Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 19 / 33

The Model Market Financial robustness distribution p ( η ( t = 0 )) ∼ Gauss ( m , σ ) Out-degree distributions Erdos-Renyi Homogenous Scale-Free � n − 1 � p k ( 1 − p ) n − 1 − k k i = k ck − α k Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 21 / 33

The Model In this work What is explored Cascade size for different classes of topology Under different conditions: Level of liquidity Level of connectedness Level of capital structure Under different scenarios Connectivity - robustness correlations Lending - borrowing correlations Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 22 / 33

Experiments Validating the Model Frontier of large cascades change for Homogenous Random networks (Battiston et al. , 2012) Scenario Random individual financial robustness Result Diversification has an ambiguous role Roukny, Battiston, Bersini, Pirotte (ULB) Default Cascades in Scale-free Networks September 11, 2012 24 / 33

Default Cascades in Scale-free Networks Assessing the role of - PowerPoint PPT Presentation

Default Cascades in Scale-free Networks Assessing the role of topology in the emergence of systemic risk Tarik Roukny 1 , 3 Stefano Battiston 2 Hugues Bersini 1 Hugues Pirotte 3 1 IRIDIA, Universit Libre de Bruxelles 2 Chair of System Design, ETH

Scale-Free Networks Original model Introduction Model details Complex Networks, Course 303A,

Outline Scale-Free Networks Networks Scale-Free Networks Original model Original model

Information Cascades in Human Networks Milo Trujillo Professor Gao Information Cascades

The contact process on evolving scale-free networks Peter M orters Bath joint work with

Liberating the API Economy with Scale-Free Networks Mike Amundsen CA Technologies @mamund I

Synchronous Batching: From Cascades to Free Routes Roger Dingledine The Free Haven Project

Cascades Social and Technological Networks Rik Sarkar University of Edinburgh, 2019. Network

Constructing Error- -Correction Codes Correction Codes Constructing Error from Scale- -Free

All scale-free networks are sparse Charo I. Del Genio Max Planck Institute for the Physics of

Probabilistic Methods in Complex Networks Lecture 3: Small worlds, scale-free networks, generating

Metastability for the contact process on evolving scale-free networks Peter M orters K oln

Uncovering disassortativity in large scale-free networks Nelly Litvak University of Twente,

The Contact Process on Evolving Scale-free Networks Motivation and results Amitai Linker

Albert-Lszl Barabsi with Emma K. Towlson, Michael M. Danziger, Sebastian Ruf and Louis

Study of Geo-Social Networks, Social Cascades and Applications Cecilia Mascolo Computer

Bio-inspired computation: Clock-free, grid-free, scale-free, and symbol-free (FA2386-12-1-4050)

compsci 514: algorithms for data science Cameron Musco University of Massachusetts Amherst. Fall

Recursively Enumerable and Recursive Languages 1 L Definition: Let be a recursively

Review of Model Existence Theorem MAT309, Fall 2019 Completeness Theorem. If | = , then

= 2( u + ) 1. v = 2 t 1, pro ving the inductiv e step.

A majority of Britons believe immigration has had a bad impact on the NHS but are split when it

What Roles Might We Play? Alex R Gulotta, Executive Director Legal Aid Justice Center 1000

Rome Seminar Next Challenges Leonard Waverman DeGroote School of Business McMaster University,

Sustainable financing of welfare states BRNO, NEUJOBS 27th May, 2013 Professor Bent Greve, RUC,