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C.Drago

First International NPR Workshop Catholic University of the Sacred Heart Milan - 16-17 September 2009. Liaisons Dangereuses : Increasing Connectivity, Risk Sharing, and Systemic Risk by Battiston, Delli Gatti, Gallegati, Greenwald and Stiglitz. Discussion: Carlo Drago.

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C.Drago

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  1. First International NPR Workshop Catholic University of the Sacred Heart Milan -16-17 September 2009 Liaisons Dangereuses: Increasing Connectivity, Risk Sharing, and Systemic Risk by Battiston, Delli Gatti, Gallegati, Greenwald and Stiglitz Discussion: Carlo Drago C.Drago 1 1

  2. Outline • Paper contents and topic relevance • Paper main conclusions • Analysing Credit Networks and sources of contagion • Credit Network metrics and financial distress • Network structure, robustness and Bankruptcy Cascades • Modelling contagion: issues • Modelling contagion prevention: failures • Bibliography C.Drago 2

  3. Liaisons Dangereuses on Credit Networks • Credit Networks: the General Model • Contagion channels: definition (types of propagation of financial distress)‏ • Interdependence and Trend Reinforcements • Bankruptcy Cascades • Paper conclusions I: ”…We show that when only risk sharing and distress propagation are present, the shock is absorbed and goes to zero as connectivity increases…” • ”….In other words, as expected, distress propagation per se, therefore, does not offset the benign effect of risk sharing…” (Battiston, Delli Gatti, Gallegati, Greenwald and Stiglitz 2009)‏ C.Drago 3

  4. Liaisons Dangereuses on Credit Networks • Paper Conclusion II: “…Adding trend reinforcement to the picture modifies radically the conclusion. In this case the relationship between the probability of failure and connectivity is U-shaped. The stabilizing role of risk diversification prevails only when connectivity is low. If connectivity is already high, a further increase may have the perverse effect of amplifying the shock due to distress propagation and trend reinforcement…” • …”The situation is even more complicated if one takes into account also the bankruptcy cascade effect. In this case, the relationship between systemic risk and connectivity may present multiple local maxima and minima…”(Battiston, Delli Gatti, Gallegati, Greenwald and Stiglitz 2009)‏ C.Drago 4

  5. Analysing the Credit Networks and Sources of Contagion • Network models seem a natural way to describe the relationships between individuals (Wassermann Faust 1994, in epidemiological context Lloyd Valeika 2005)‏ • ….“Many markets for credit can be conceived of as credit networks in which nodes represent agents and links represent credit relationships…” (Battiston, Delli Gatti, Gallegati, Greenwald, Stiglitz 2009) • Network structure seems to be important to determinate the final effects of external shocks. • Useful in this case decompose the credit network. C.Drago 5

  6. Credit Networks Metrics and Financial Distress • Structure can be useful to understand the dynamics of the contagion (distress propagation). • Interaction among key actors: egocentric networks (analysing connections of each bank for example). Different egocentric structure (which could be differently measured) tend to respond differently to shocks. • Size of the network (distance between nodes, diameter and average path length)‏ • High-risk individuals in the network (higher contagion channels). The network centre seems to be more exposed than the periphery . • Network clusters and subgroups (higher contagion channels)‏ • Network components (higher contagion risk for reachable nodes) C.Drago 6

  7. Networks Structure, Robustness and Bankruptcy Cascades • Structure can be useful to analyse the robustness of the system to the contagion • …Effects of the network structure on the spreading of the crisis (density of the linkages and “system core”)‏ • …Network robustness and bankruptcy cascades (resistance to the network to the nodes elimination)‏ • …What if there is more than one node simultaneous elimination…? • …Effects over the time and trend reinforcement (new links destruction\creation)‏ • …Dynamical structural network changes and effects on the spreading of the contagion C.Drago 7

  8. Modelling Contagion: Issues • The tentative to model network patterns of contagion dynamics can be useful to identify… • …The risk of infection for each actor in the financial network • …The time to infection for each actor in the financial network • Predicting effects of changes in networks over the time (in dynamic network contexts)‏ • …Are the contagion effects related to some spatial patterns (geographical distribution of the crisis)? • ..Are there relationships between credit networks and other networks? • …Are there signals that can be understood in advance (contagion prevention failures…)? C.Drago 8

  9. Modelling Contagion Prevention: Failures • Signalling I: predicting the collapse of a single agent and the contagion (see above)‏ • Signalling II: interlocking directorships networks (are the dynamical reduction centrality measures in the network a signal of danger?)‏ • Signalling III: corporate governance failures (would it be possible to estimate the risk in a specific credit network?)‏ • Signalling IV: are there diagnostic mechanisms to prevent financial contagion (at a general level)? • Signalling V: are there diagnostic mechanisms to prevent financial contagion by considering individual financial fragility situations related to specific network subgroups or clusters? C.Drago 9

  10. Bibliography (I)‏ • Battiston, Delli Gatti, Gallegati, Greenwald, Stiglitz (2009). “Liaisons Dangereuses: Increasing Connectivity, Risk Sharing, and Systemic Risk “ Working paper • Carley, (2003) “Dynamic Network Analysis” in Dynamic Social Network Modeling and Analysis: Workshop Summary and Papers, Ronald Breiger, Kathleen Carley, and Philippa Pattison, (Eds.) Committee on Human Factors, National Research Council, National Research Council. Pp. 133–145, Washington, DC. • Lloyd, Valeika (2005) “Network Models in Epidemiology: an Overview” Working Paper • Newman (2007) “The Mathematics of Networks” Working Paper C.Drago 10

  11. Bibliography (II)‏ • Santella, Drago, Polo (2007). “The Italian Chamber of Lords Sits on Listed Company Boards: An Empirical Analysis of Italian Listed Company Boards from 1998 to 2006”. Available at SSRN: http://ssrn.com/abstract=1027947 • Snijders, , Van de Bunt, Steglich (2009) “Introduction to actor-based models for network dynamics” Social Networks, in press. http://stat.gamma.rug.nl/ • Wassermann Faust (1994) “Social Network Analysis: Methods and Applications” Cambridge University Press C.Drago 11

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