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

New institutional set-up in the euro area EU ECB European Systemic Risk Board (ESRB) Monetary Policy Price Stability Macro-prudential policy Financial stability Systemic dimension Micro-prudential Soundness of individual banks Institution dimension European Financial Authorities (EBA, ESMA, EIOPA) It is useful to establish a broad taxonomy of the interaction of monetary policy and supervision, both with respect to micro and macro-prudential supervision. We have borrowed the framework established by Schoenmaker and Wierts (2011). The interaction of monetary policy and supervision differs with respect its micro prudential tasks. Macro-prudential and micro-prudential supervision of very different nature: Mapru: designed to identify and mitigate risks to financial system as a whole; given this systemic dimension, mapru is on the same level as monetary policy which also affects entire economy; Mipru: concerned with safety and soundness of each individual institution. Therefore one my think of a hierarchy in objectives by which system wide price and financial stability are aimed at system wide macro stability, whereas the objective of microprudential supervision is more concerned with the soundness and stability of individual institutions. Naturally, institution stability is related and can impact macro-stability, but the seminar abstracts for those interactions. Throughout presentation treat the interaction with MP for each of these policy domains separately. Since topic of seminar is on interactions of SSM with MP, presentation focuses on interactions A and B (rather than C, which governs the interactions within the supervision domain).

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. 3

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 dealers’leverage: 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? 4

Early warning signal models “Global” credit gap and optimal early warning threshold (Q1 1979 – Q4 2012; percentages) —— De-trended private credit-to-GDP ratio (GDP-weighted average across countries) ––––– “Optimal” signal threshold 5

Largest increase in leverage in OFIs 6

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

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

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 sector’s 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. 9

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