1. Dynamic macro prudential stress testing using network science
Dror Y. Kenett1,2
1 Department of Physics, Boston University
2 U.S. Department of the Treasury, Office of Financial Research
15 December 2014

2. Prof. Sary Levy-Carciente
Team
Prof. H. Eugene Stanley
Prof. Sary Levy-Carciente
Prof. Shlomo Havlin
Adam Avakian

3. What is the challenge? Approach
Design a framework of prudential financial supervision in such a way of considering both the actors of the system (financial institutions) and the vulnerabilities that emerge from their connections and interdependence. Uncover the systemic structure of a banking system, analyze its sensitivity to external shocks and to evaluate the presence of contagious underlying features of the system.
Approach
Use network science to develop a bi-partite network model to dynamically stress test a banking system, uncover hidden global systemic risks, and introduce intervention strategies

4. Bipartite Network Model
Banks are interconnected in many ways, i.e. interbank loans. We only consider the liquidity risk. Which means, when a bank can’t meet its liability and fails, it needs to sell its assets to meet the liability. If the market can’t absorb the sale, then the value of this asset will decrease for a period.
Simulate the model with real data.
X. Huang, I. Vodenska, S. Havlin, H.E. Staenly (2013), Cascading Failures in Bi-partite Graphs: Model for Systemic Risk Propagation, Scientific Reports 3, 1219.

5. Summary of model parameters

6. Data
Monthly Venezuelan bank balance sheet data for the period

7. Network representation

8. Surviving banks, shock level and contagion effect

9. Surviving banks, shock level and contagion effect

10. as a function of time for different asset classes

11. Asset size, diversification

12. Non-surviving banks versus solvency index

13. Intervention strategies
Protect one bank from failing, and compare the number of surviving banks at the end of a failure cascade
Protect a pair of banks
Cost of bailout, change inapt value, time effects

14. Summary
Dynamic bi-partite network model for banks and assets (DBNM-BA)
Critical parameters:
Comparison of macro variables ( ) to asset ( , HHI) and bank (solvency) micro variables
Future work
Intervention strategies
Multi-market model
Bankruptcy rules

15. Thank You. Questions? Paper: http://ssrn.com/abstract=2482742