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1 1 1 Frank Smets Directorate General - Research Macro Financial Modeling Group Conference, Chicago 2-3 May 2013 Panel discussion on Policy Perspectives.

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Presentation on theme: "1 1 1 Frank Smets Directorate General - Research Macro Financial Modeling Group Conference, Chicago 2-3 May 2013 Panel discussion on Policy Perspectives."— Presentation transcript:

1 1 1 1 Frank Smets Directorate General - Research Macro Financial Modeling Group Conference, Chicago 2-3 May 2013 Panel discussion on Policy Perspectives on Systemic Risk Measurement

2 Rubric Systemic dimension Institution dimension Micro-prudential Soundness of individual banks Monetary Policy Price Stability Macro-prudential policy Financial stability New institutional set-up in the euro area 2 European Systemic Risk Board (ESRB) European Financial Authorities (EBA, ESMA, EIOPA) ECB EU

3 3 3 Two perspectives Time-series perspective: Smoothen the financial cycle Finance is pro-cyclical: Why? Endogenous credit constraints and liquidity creation? Incentives? Expectations? How to manage the financial cycle? Need tools to analyse and interpret the build-up and unravelling of financial imbalances. Cross-section perspective: Improve the resilience of the financial system Finance is inherently fragile: Why? Leverage, liquidity/maturity/risk transformation, interconnectedness, complexity. How to make the financial system more resilient? Need tools to understand/predict spill-overs, contagion, negative feedback loops.

4 4 4 Quantity versus price-based indicators Quantity-based indicators have performed better in signalling the building up of financial imbalances E.g. Credit-to-GDP ratio: Borio, Alessi-Detken, Schularick and Taylor; Non-core liabilities as fraction of M2, broker dealersleverage: Adrian & Shin. More useful for ex-ante leaning against the financial cycle? Prices sent the wrong signals ex ante, partly due to what has been called the volatility paradox, but are better at capturing the unravelling of the imbalances: E.g. Marginal Expected Shortfall, CoVar, Bank Stability Index; Network analysis; etc More useful for ex-post interventions?

5 5 5 Early warning signal models Global credit gap and optimal early warning threshold De-trended private credit-to-GDP ratio (GDP-weighted average across countries) ––––– Optimal signal threshold (Q – Q4 2012; percentages)

6 6 6 Largest increase in leverage in OFIs

7 7 7 ECB Systemic Risk Indicator Probability of two or more banks defaulting simultaneously within next 2 years Source: ECB Lucas, A., Schwaab, B., and X. Zhang (2012), ECB WP

8 8 8 Exemplified by: Strong correlation between bank CDS and sovereign CDS in the euro area Sovereign and bank CDS premia United StatesEuro area Sources: Thomson Reuters and ECB calculations. In: ECB (2013): Report on Financial Integration in Europe. Negative feedback loop between banks and sovereigns

9 9 9 Challenge Link time-series and cross-section perspectives: Why and in what circumstances do credit booms go hand in hand with greater leverage, liquidity mismatch, interconnectedness and complexity? Why and in what circumstances are credit booms associated with more risk-taking on the financial sectors asset side? Need better time series data and measurement of leverage, liquidity mismatch, interconnectedness and complexity Need dynamic macro models that incorporate the building up of systemic risk and the non-linear feedback mechanisms that kick in in crises.

10 10 MaRs: ESCB research network Three work streams: 1.Macro-financial models linking financial stability and the performance of the economy 2.Early warning systems and systemic risk indicators 3.Assessing contagion risks Interim report available on the ECBs website.


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