Discussion of “Systemic and Systematic risk” by Billio et al. and “CDS based indicators for systemic risk of Euro area sovereigns and for Euro area financial firms” by Lucas et al.

SYstemic Risk TOmography:

Signals, Measurements, Transmission Channels, and Policy Interventions

Carsten Detken Head of Financial Stability Surveillance Division Directorate General Macroprudential Policy and Financial Stability SYRTO Code Workshop Workshop on Systemic Risk Policy Issues for SYRTO July, 2 2014 - Frankfurt (Bundesbank-ECB-ESRB)

Carsten DetkenHead of Financial Stability Surveillance Division

Directorate General Macroprudential Policy and Financial Stability

Discussion of“Systemic and Systematic risk” by Billio et al.

and

“CDS based indicators for systemic risk of Euro area sovereigns

and for Euro area financial firms” by Lucas et al.

2 July 2014 SYRTO workshop

RubricPapers by A. Lucas and co-authors

Empirical implications of the models consistent with economic intuition:

• Strong dependencies between European sovereigns

• In 2011 IE and PT perceived to be more affected by a possible Greek default than

others

Concerns mostly about countries which are already fiscally weaker

• EFSF/SMP and OMT announcements decreased joint sovereign default risk but

not conditional risk/dependence (contagion)

Arguably, this is what they were intended to: eliminate break-up risk

• Joint tail risks for EA banks peak in summer 2012

• OMT announcement decreased joint bank default risk but not conditional

risk/dependence (contagion)

Owing to absence of full banking union

Praise

Rubric

Marginal value added?

Papers by A. Lucas and co-authors

Important for policy-making?

Criticism

Source: Lucas et al., JBES 2014

10-year sovereign bond yields for selected EA countries

Source: Reuters

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• One potential use of the approach– Obtaining long time series of “systemic stress” e.g. for dating banking crises or

use in early warning models. Those measures would have to be based on bond yields and/or equity prices which cover longer time spans (than CDS spreads).

• Conditional probabilities of default– Segoviano and Goodhart (2009): “conditional probabilities do not imply

causation”. But what to learn from those measures? Disentangling the drivers!

– Page 280 JBES: “During 2011 Ireland and Portugal are perceived by credit market participants to be more affected by a possible Greek credit event”. However, P(A) was the highest for PT and IE (after GR) at that time.

RubricPapers by A. Lucas and co-authors

Proposal

Real-time

Out-of-sample

A policy-maker's wish list:

General comments

• What is the meaning of now-casting in a model featuring daily data?

• Spatial dependence vs. spillover vs. financial (de)fragmentation?

Source: Blasques et al., 2014

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• Is spatial dependence necessarily bad?

• Given the separation in the EA (stressed vs. non-stressed countries) is it sufficient

to describe spatial dependence with a single parameter?

• Is the time-varying rho capturing/approximating a possibly higher order spatial dependence process?

• What is the economic intuition for choosing h(ft)=tanh-1 as monotonic transformation (equ. 4, p. 5 and p.17 eq. 17)?

• Why not normalise the exposure matrix W by GDP? Economically a time-varying matrix seems more reasonable. Good fit is not everything. Would be interesting to understand better why Wcat (p.21) performs best compared to others (p. 25). Is it because the other regressors already pick up lots of volatility so that a time-varying matrix at lower frequency doesn’t help much?

• See also comparisons of results with different W-matrices. Would be nice to see the associated rho-measures.

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• It appears that the most important improvement comes from assuming t-distributed errors instead for Gaussian. The improvement from using the GAS-model instead of the static model is much smaller (Table 4, Appendix).

• P. 23: “Our results suggest that the sovereign CDS market had already acknowledged the message earlier, resulting in an overall decrease of spatial dependence”. What does this exactly mean in terms of timing? The Draghi speech in London was the major trigger for reducing redenomination risk…

• P. 23. Next sentence on regulatory treatment. This is a smooth process, so unlikely that it is the final recap implementation in mid-April would trigger a downshift in spatial dependence. This is a bit of loose story telling.

• Marginal contribution of this approach against simple spread measures (e.g. EURBOR-OIS) or the CISS (see Arsov et al. 2013)?

RubricBillio et al. (2014)

1. Can we separate systematic from systemic risk?2. Does systemic risk kill diversification benefits?

Definition of both terms is crucial for answering the proposed question(s).

– “Systematic risk” is a well established concept.• It refers to the risk an investor of a well-diversified portfolio is exposed to, which stems

from the dependence of returns to common factors.

• No market failure, no policy intervention necessary to prevent the problem.

– There is still no consensus on the definition of the term “Systemic risk”.• ECB (FSR 6/2010): “[…] financial instability becomes so widespread that it

impairs the functioning of a financial system to the point where economic growth

and welfare suffer materially.”

• Systemic risk is associated with market failure.

• Volatility is not and bank failure not necessarily systemic,

Difference systemic – systematic risk

RubricBillio et al. (2014) cont’d

• Nice idea to link network analysis with time series/panel models.

However:

• According to Acharya and Yorulmazer (2002), Nier et al. (2007) and De

Bandt et al. (2010) systemic risk materialises through (1) “pure” contagion,

(2) exposure to common factors, (3) herding behaviour causing informational

contagion, and (4) feedback effects from endogenous fire sales. Hartmann

(2002) argues systemic risk stems from either build-up imbalances,

contagion or large shocks. This paper equates systemic risk with

contagion risk, which is too narrow. Final impact on real economy is key

defining element of systemic risk.

• Also need exposure based network analysis to conduct macro-pru policies.

But analysis can help investors (and supervisors) to evaluate level of risk

diversification in the presence of systemic risk.

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What are we concerned with now.....

• Prevention => When to use macro-pru instruments?• Need models identifying vulnerable states to inform judgement• - Lead times• - Evaluation methods• - Suite of models => Meta EWS?• - Lack of Events• - Thresholds from pooled analysis or country specific?• - How to implement in policy process (intuition, performance,

visualisation)

This project has received funding from the European Union’s

Seventh Framework Programme for research, technological

development and demonstration under grant agreement n° 320270

www.syrtoproject.eu

This document reflects only the author’s views.

The European Union is not liable for any use that may be made of the information contained therein.