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Yvonne Kreis. Systemic Risk in a Structural Model of Bank Default Linkages
1.
Eesti Pank –
August 2016 © 2016 Kreis Systemic Risk in a Structural Model of Bank Default Linkages Yvonne Kreis Gutenberg University Mainz Dietmar Leisen Gutenberg University Mainz
2.
Eesti Pank –
August 2016 © 2016 Kreis 2 This Paper • Structural model of bank default in an asset- based approach • Focus on the impact of asset correlations • Systemic risk measure: Conditional Expected Default Frequency • Empirical analysis for the U.S. banking sector: • Macro-prudential regulation required; SIFI capital supplement too “small”
3.
Eesti Pank –
August 2016 © 2016 Kreis 3 Agenda Motivation Model Correlation Implications & Regulation Conclusion
4.
Eesti Pank –
August 2016 © 2016 Kreis Motivation I: Level of Interconnectedness • Banks are interconnected on several layers. – Direct connection (asset investments, loans) – Indirect connection via common (systemic) factors (e.g. market risk perception) • Severe systemic events affect all banks through direct and / or indirect connections. (e.g. exposure, risk perception, trust in and between banks) • Current literature often focuses on modeling direct connections. 4
5.
Eesti Pank –
August 2016 © 2016 Kreis Motivation II: Impact of Systemic Risk • Severe systemic events affect all banks. • Only relevant factor during a financial crises • Single Factor Approach to Systemic Risk • Foundation: Vasicek (1987) 5
6.
Eesti Pank –
August 2016 © 2016 Kreis Motivation III: Default • Default results from the balance sheet. • Regulation focuses on assets. • Asset Based Approach to Systemic Risk • Foundation: Structural Model by Merton (1974) 6
7.
Eesti Pank –
August 2016 © 2016 Kreis 7 Agenda Motivation Model Correlation Implications & Regulation Conclusion
8.
Eesti Pank –
August 2016 © 2016 Kreis Structural Model of Default • Individual bank defaults iff assets < debt < • Introduce default correlation through asset correlation V = + • Study a banking system with N individual banks 8
9.
Eesti Pank –
August 2016 © 2016 Kreis Normal Periods vs. Crisis Periods • Normal periods encompasses fundamental factors, e.g. KMV. • Crisis periods encompasses only the systemic shock. 9 = , + , , = , + , ,
10.
Eesti Pank –
August 2016 © 2016 Kreis Default Frequency • Individual default probability • Indicator variable for default of bank i: Xi • Default frequency: = • Conditional default probability • Conditional distribution of default frequency 10
11.
Eesti Pank –
August 2016 © 2016 Kreis Density of Default Frequency MN 11 parameters: p=1%; N=1,000
12.
Eesti Pank –
August 2016 © 2016 Kreis 12 Agenda Motivation Model Correlation Implications & Regulation Conclusion
13.
Eesti Pank –
August 2016 © 2016 Kreis Data • Analyses for the U.S. banking sector 1980 – 2015 • Selection of “core” sector, i.e. 15 large banks • Daily stock price returns as approximation of asset returns • Application of a principal component analysis – over a rolling 3-month window – mean (median) factor loadings of the first principal component 13
14.
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August 2016 © 2016 Kreis Time Series of Average Correlation 14
15.
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August 2016 © 2016 Kreis Time Series of Average Correlation 15
16.
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August 2016 © 2016 Kreis Asset Correlations • Asset correlations between banks have strongly increased over time! • They have become very high in the past decade! • This strongly influences the bank default linkages and thus systemic risk! • How to adequately introduce to risk management? 16
17.
Eesti Pank –
August 2016 © 2016 Kreis 17 Agenda Motivation Model Correlation Implications & Regulation Conclusion
18.
Eesti Pank –
August 2016 © 2016 Kreis Risk Measures • For correlation=0, Law of Large Numbers implies – suggests that default frequency is close to individual default probability (micro-prudential regulation) • Actual numbers are far too small to capture “infinity”. • Need to capture departure from p – Study Conditional Expected Default Frequency: = [ | ] – foundation for macro-prudential regulation 18
19.
Eesti Pank –
August 2016 © 2016 Kreis Conditional Expected Default Frequency 19
20.
Eesti Pank –
August 2016 © 2016 Kreis U.S. Sample: Temporal Evolution of CEDF 20
21.
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August 2016 © 2016 Kreis Outlook: Relative Systemic Capital Supplement on Correlation 21
22.
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August 2016 © 2016 Kreis 22 Agenda Motivation Model Correlation Implications & Regulation Conclusion
23.
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August 2016 © 2016 Kreis Conclusion • Approach to systemic risk based on well-known structural model to credit risk • Asset correlations have a strong impact (shape of the density of default frequencies, risk measure, and thus capital requirements) • “Large” correlation levels imply that stronger macro-prudential regulation is required • Next steps: stress testing & systemic capital
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