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SOVEREIGN CREDIT RISK,
LIQUIDITY, AND
THE ECB INTERVENTION:
DEUS EX MACHINA?
SYstemic Risk TOmography:
Signals, Measurements, Transmission Channels, and
Policy Interventions
Loriana Pelizzon, Goethe University
Marti Subrahmanyam, NYU Stern
Davide Tomio, Copenhagen Business School
Jun Uno, Waseda University
THE MOTIVATION
The European sovereign debt crisis, peaked in the summer of 2011, with bond
yields and CDS spreads in Italy and Spain hitting 7%.
Substantial reduction in market liquidity for sovereign bonds of countries in
the Euro-zone periphery.
The two variable were shown to inuence the bond yields, can we say
anything about their comovement? Is there a spillover between one variable
and the other?
1/24
ITALIAN AND GERMAN 10-YEAR BOND YIELD AND SPREAD
Time-series of the Italian and German bond yields spread for 10-year maturity,
the Italian CDS spread and BTP-10Y yield. Our analysis period covers the two
highest spikes in the CDS spread and BTP-Bund spread pattern.
2/24
EVOLUTION OF THE BID-ASK AND CDS SPREAD
Spikes in the quoted bid-ask spread (blue) overlap with spikes in the CDS spread
(Red).
3/24
EVOLUTION OF THE BID-ASK AND CDS SPREAD
Spikes in the quoted bid-ask spread (blue) overlap with spikes in the CDS spread
(Red).
3/24
THE CONTRIBUTION
Focus:
Major European Government Debt: Italy
Sample June 1, 2011 to December 31, 2012: Includes the period of high
nancial turmoil
Hypotheses investigated:
H1: Changes in credit risk have an important bearing on changes in liquidity.
H2: The relationship between credit risk and liquidity risk is altered when
credit risk is high, in particular when the CDS spread on the obligor crosses a
threshold.
H3: Monetary policy interventions by the central bank aect the relationship
between credit risk and market liquidity.
H4: Market liquidity is driven by both global market nd funding liquidity risk
factors.
H5: The funding costs of the primary dealers (market makers) adversely
aects market liquidity.
H6: Over time, the change in credit risk leads changes in market liquidity and
vice-versa.
4/24
THE CONTRIBUTION
Our ndings:
H1: A strong and dynamic relationship between changes in Italian sovereign
credit risk and market liquidity in the (secondary) sovereign bond market.
H2: The relationship is stronger when the CDS spread is above 500 bp
H3: The strength of the relationship diminishes after the announcement of
the LTRO by the ECB on December 8, 2011.
H4: Other global market and funding liquidity risk factors aect market
liquidity.
H5: Funding costs specic of the primary dealers adversely aects market
liquidity
H6: The change in credit risk leads changes in market liquidity, not vice-versa.
5/24
PREVIOUS LITERATURE: OVERVIEW
CONTRIBUTION
We investigate the eect of credit risk on the market liquidity of government
bonds.
Theoretical Background: Inventory models, Amihud and Mendelson (1980),
Ho and Stoll (1980); Funding liquidity: Brunnermeier and Pedersen (2009).
Papers on the market liquidity of the US Treasury bond market: Fleming,
Remolona '99, Fleming '03, Goyenko, Subrahmanyam, and Ukhov '11
Paper on the liquidity of the corporate bond market: Friewald, Jankowitsch,
Subrahmanyam '12, Dick-Nielsen, Feldhuetter, and Lando '12
Papers on Euro-zone sovereign bonds: Beber, Brandt, Kavajecz '08, Cheung,
de Jong, Rindi '05
6/24
THE MARKET STRUCTURE
MTS, Mercato dei Titoli di Stato, is an Electronic, Inter-Dealer market.
In 2000, MTS executed 65% Volume of secondary market for IT-debt
In 2003, MTS executed 74% Volume of secondary market for EU-debt
In 2005, the largest market for EU government bonds (with public daily
turnover 25Be).
The MTS is a system of markets.
The European Market: European Bond Market (EBM).
Domestic Markets: Several, for larger countries.
Dealer to Retail client. Not covered.
There are two kinds of participants in the market:
Primary Dealers: Market-makers
Dealers: Price takers
7/24
THE DATA: A UNIQUE DATASET IN A UNIQUE PERIOD
From June 2011:
Trade-by-Trade data.
Order-by-Order data, uniquely linked to the trades.
Every quote, every update, un-netted.
Until June 2011:
Trade-by-Trade data.
Best 3 quotes prices and quantities, cumulative.
We calculate a series of liquidity measures.
Quoted Spread: Best ask-Best bid per 100e of face value.
Quoted Quantity: Quantity quoted at any level of the bid and ask, in Million e.
Lambda: How much a trader would move the best bid (ask) if she were to trade
e 15 million
Eective Bid-Ask Spread: 2*|Share-weighted average price - relevant best price|.
8/24
THE DATA
BONDS COMPOSITION AND MARKET VOLUME
Our data covers 152 Italian sovereign bonds traded on the MTS between June
2011 and December 2012 (=406 days).
Variable Mean 5th Pct Median 95th Pct
Bonds 90 87 90 93
Trades 265 116 249 449
Volume(be) 2.0 0.8 1.9 3.8
Quoted Spread (e/100e) 0.18 0.42 1.24
Eective Spread (e/100e) 0.06 0.18 0.33
Quoted Quantity (MMe) 96.2 122.5 153.2
Lambda (e/100e) 0.006 0.01 0.05
Italian CDS (bps) 194 421 552
Median market daily volume is 2 billion e.
US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US
securitized xed income (structured product) market and US corporate bond
market.
We conducted the analysis with all these measures. This presentation reports
Quoted Spread.
CDS spread increased nearly threefold in the sample.
9/24
THE DATA
BONDS COMPOSITION AND MARKET VOLUME
Our data covers 152 Italian sovereign bonds traded on the MTS between June
2011 and December 2012 (=406 days).
Variable Mean 5th Pct Median 95th Pct
Bonds 90 87 90 93
Trades 265 116 249 449
Volume(be) 2.0 0.8 1.9 3.8
Quoted Spread (e/100e) 0.18 0.42 1.24
Eective Spread (e/100e) 0.06 0.18 0.33
Quoted Quantity (MMe) 96.2 122.5 153.2
Lambda (e/100e) 0.006 0.01 0.05
Italian CDS (bps) 194 421 552
Median market daily volume is 2 billion e.
US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US
securitized xed income (structured product) market and US corporate bond
market.
We conducted the analysis with all these measures. This presentation reports
Quoted Spread.
CDS spread increased nearly threefold in the sample.
9/24
THE DATA
BONDS COMPOSITION AND MARKET VOLUME
Our data covers 152 Italian sovereign bonds traded on the MTS between June
2011 and December 2012 (=406 days).
Variable Mean 5th Pct Median 95th Pct
Bonds 90 87 90 93
Trades 265 116 249 449
Volume(be) 2.0 0.8 1.9 3.8
Quoted Spread (e/100e) 0.18 0.42 1.24
Eective Spread (e/100e) 0.06 0.18 0.33
Quoted Quantity (MMe) 96.2 122.5 153.2
Lambda (e/100e) 0.006 0.01 0.05
Italian CDS (bps) 194 421 552
Median market daily volume is 2 billion e.
US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US
securitized xed income (structured product) market and US corporate bond
market.
We conducted the analysis with all these measures. This presentation reports
Quoted Spread.
CDS spread increased nearly threefold in the sample.
9/24
THE DATA
BONDS COMPOSITION AND MARKET VOLUME
Our data covers 152 Italian sovereign bonds traded on the MTS between June
2011 and December 2012 (=406 days).
Variable Mean 5th Pct Median 95th Pct
Bonds 90 87 90 93
Trades 265 116 249 449
Volume(be) 2.0 0.8 1.9 3.8
Quoted Spread (e/100e) 0.18 0.42 1.24
Eective Spread (e/100e) 0.06 0.18 0.33
Quoted Quantity (MMe) 96.2 122.5 153.2
Lambda (e/100e) 0.006 0.01 0.05
Italian CDS (bps) 194 421 552
Median market daily volume is 2 billion e.
US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US
securitized xed income (structured product) market and US corporate bond
market.
We conducted the analysis with all these measures. This presentation reports
Quoted Spread.
CDS spread increased nearly threefold in the sample.
9/24
H1: CHANGES IN CREDIT RISK AFFECT CHANGES
IN LIQUIDITY
Credit risk to aect liquidity through two channels:
Microstructure: The higher the risk of an asset, the greater its illiquidity
Asymmetry of information
Inventory models
VaR: Internal and external risk control constraints
∆BASpreadt = α0 +
M
i=1
αi ∆BASpreadt−i +
N
j=0
βj ∆CDSt−j + t
We consider log-changes of the variables.
Variable 1 2 3 4 5
Intercept −0.001 −0.001 0. −0.002 −0.001
∆BAt−1 . −0.291 *** −0.352 *** −0.339 *** −0.329 ***
∆CDSt 1.172 *** 1.149 *** . 0.909 ** 0.870 **
∆CDSt−1 . . 1.261 *** 1.042 *** 1.133 ***
∆CDSt−2 . . . . −0.411
Adj R2
0.051 0.134 0.141 0.170 0.174
10/24
H1: CHANGES IN CREDIT RISK AFFECT CHANGES
IN LIQUIDITY
Credit risk to aect liquidity through two channels:
Microstructure: The higher the risk of an asset, the greater its illiquidity
Asymmetry of information
Inventory models
VaR: Internal and external risk control constraints
∆BASpreadt = α0 +
M
i=1
αi ∆BASpreadt−i +
N
j=0
βj ∆CDSt−j + t
We consider log-changes of the variables.
Variable 1 2 3 4 5
Intercept −0.001 −0.001 0. −0.002 −0.001
∆BAt−1 . −0.291 *** −0.352 *** −0.339 *** −0.329 ***
∆CDSt 1.172 *** 1.149 *** . 0.909 ** 0.870 **
∆CDSt−1 . . 1.261 *** 1.042 *** 1.133 ***
∆CDSt−2 . . . . −0.411
Adj R2
0.051 0.134 0.141 0.170 0.174
10/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
We expect a structural shift in the relation between credit risk and liquidity:
Margins in the REPO market depend on credit quality
Dierent credit rating means dierent investors
Similar to grouping corporate bonds by credit rating
We estimate the threshold ˆγ0 that minimizes the sum of squared residual of the
following regression:
∆BASpreadt =α0 + α1∆BASpreadt−1 + β0∆CDSt + β1∆CDSt−1
+I [CDS ≤ γ0] (˜α0 + ˜α1∆BASpreadt−1 + ˜β0∆CDSt + ˜β1∆CDSt−1) + t
The test HT(γ, ˆγ0) developed by Hansen (2001) has a pivotal non-standard
distribution which allows us to calculate condence intervals for ˆγ0. We estimate
ˆγ0 and calculate HT(γ, ˆγ0), for the null H0 : γ = ˆγ0, which is drawn in the next
slide as a function of γ.
11/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
Hansen Test: Modication of the Likelihood Ratio Test
Presence of a threshold at 500bp in the CDS spread:
Statistical (see Hansen 2001): 487-504bp is the 5% condence interval
Investment Grade: 500bp is the CDS level for junk-bonds also for CCP's
Margins: LCH.Clearnet documents cite 500 bps.
Market participants' comments
12/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
Hansen Test: Modication of the Likelihood Ratio Test
Presence of a threshold at 500bp in the CDS spread:
Statistical (see Hansen 2001): 487-504bp is the 5% condence interval
Investment Grade: 500bp is the CDS level for junk-bonds also for CCP's
Margins: LCH.Clearnet documents cite 500 bps.
Market participants' comments
12/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
CDSt Below 500bp
Intercept −0.001 −0.002 0. 0. 0.
∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 ***
∆CDSt 0.72 ** 0.671 ** . 0.427 0.404
∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 ***
∆CDSt−2 . . . . −0.315
Adj R2
0.023 0.092 0.157 0.163 0.165
CDSt Above 500bp
Intercept −0.024 −0.02 0.003 −0.014 −0.007
∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 ***
∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 ***
∆CDSt−1 . . 0.932 −0.743 −0.447
∆CDSt−2 . . . . −0.861
Adj R2
0.216 0.339 0.104 0.338 0.341
Relationships between changes in the CDS spread and liquidity are dierent below and
above 500bp:
Larger economic impact: a 10% increase in CDS→ Five-fold increase
Below 500bp: 7% increase in Quoted Spread
Above 500bp: 36% increase in Quoted Spread
Dierent dynamics
Below 500bp: Lagged reaction
Above 500bp: Contemporaneous reaction
13/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
CDSt Below 500bp
Intercept −0.001 −0.002 0. 0. 0.
∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 ***
∆CDSt 0.72 ** 0.671 ** . 0.427 0.404
∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 ***
∆CDSt−2 . . . . −0.315
Adj R2
0.023 0.092 0.157 0.163 0.165
CDSt Above 500bp
Intercept −0.024 −0.02 0.003 −0.014 −0.007
∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 ***
∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 ***
∆CDSt−1 . . 0.932 −0.743 −0.447
∆CDSt−2 . . . . −0.861
Adj R2
0.216 0.339 0.104 0.338 0.341
Relationships between changes in the CDS spread and liquidity are dierent below and
above 500bp:
Larger economic impact: a 10% increase in CDS→ Five-fold increase
Below 500bp: 7% increase in Quoted Spread
Above 500bp: 36% increase in Quoted Spread
Dierent dynamics
Below 500bp: Lagged reaction
Above 500bp: Contemporaneous reaction
13/24
H2: THE RELATIONSHIP CHANGES WHEN
CREDIT RISK IS HIGH
CDSt Below 500bp
Intercept −0.001 −0.002 0. 0. 0.
∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 ***
∆CDSt 0.72 ** 0.671 ** . 0.427 0.404
∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 ***
∆CDSt−2 . . . . −0.315
Adj R2
0.023 0.092 0.157 0.163 0.165
CDSt Above 500bp
Intercept −0.024 −0.02 0.003 −0.014 −0.007
∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 ***
∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 ***
∆CDSt−1 . . 0.932 −0.743 −0.447
∆CDSt−2 . . . . −0.861
Adj R2
0.216 0.339 0.104 0.338 0.341
Relationships between changes in the CDS spread and liquidity are dierent below and
above 500bp:
Larger economic impact: a 10% increase in CDS→ Five-fold increase
Below 500bp: 7% increase in Quoted Spread
Above 500bp: 36% increase in Quoted Spread
Dierent dynamics
Below 500bp: Lagged reaction
Above 500bp: Contemporaneous reaction
13/24
H3: CENTRAL BANK INTERVENTIONS AFFECT THE
CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP
Euro-zone nancial regulators took actions which we expect to aect the
credit-liquidity relationship
EU bail-outs.
ECB Monetary interventions: SMP, LTRO, OMT.
Draghi's The ECB is ready to do whatever it takes to preserve the Euro and,
believe me, it will be enough.
The ECB can aect market liquidity through 3 channels:
Purchase of bonds on the market
Provide liquidity to the banks
Moral Suasion
14/24
H3: CENTRAL BANK INTERVENTIONS AFFECT THE
CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP
Structural break for:
∆BAt = ∆CDSt
∆BAt = ∆CDSt−1
Evidence of structural break
on December 8, 2011
Statistical (Chow (1960)
test)
Announcement date of
LTRO I
Sample split
15/24
H3: CENTRAL BANK INTERVENTIONS AFFECT THE
CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP
Estimating the same equation for the three subsamples:
Before 8/12/2011 Before 8/12/2011 After 8/12/2011
Variable CDS500bp CDS500bp
Intercept 0.003 0.0 -0.007
∆BAt−1 -0.318** -0.088 -0.378***
∆CDSt 0.702 5.844*** 0.313
∆CDSt−1 1.754*** -2.658** 0.553**
Adj R2
0.207 0.452 0.147
Dierent economic impact: a 10% increase in CDS→
Below 500: 18% increase in Quoted Spread
Above 500: 58% increase in Quoted Spread
In 2012: 5% increase in Quoted Spread
16/24
H3: CENTRAL BANK INTERVENTIONS AFFECT THE
CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP
Estimating the same equation for the three subsamples:
Before 8/12/2011 Before 8/12/2011 After 8/12/2011
Variable CDS500bp CDS500bp
Intercept 0.003 0.0 -0.007
∆BAt−1 -0.318** -0.088 -0.378***
∆CDSt 0.702 5.844*** 0.313
∆CDSt−1 1.754*** -2.658** 0.553**
Adj R2
0.207 0.452 0.147
Dierent economic impact: a 10% increase in CDS→
Below 500: 18% increase in Quoted Spread
Above 500: 58% increase in Quoted Spread
In 2012: 5% increase in Quoted Spread
16/24
H3: CENTRAL BANK INTERVENTIONS AFFECT THE
CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP
Estimating the same equation for the three subsamples:
Before 8/12/2011 Before 8/12/2011 After 8/12/2011
Variable CDS500bp CDS500bp
Intercept 0.003 0.0 -0.007
∆BAt−1 -0.318** -0.088 -0.378***
∆CDSt 0.702 5.844*** 0.313
∆CDSt−1 1.754*** -2.658** 0.553**
Adj R2
0.207 0.452 0.147
Dierent economic impact: a 10% increase in CDS→
Below 500: 18% increase in Quoted Spread
Above 500: 58% increase in Quoted Spread
In 2012: 5% increase in Quoted Spread
16/24
H4: MARKET LIQUIDITY IS DRIVEN BY MARKET AND FUNDING RISK
FACTORS.
Do global factors have an eect on the liquidity of the Italian bond market? Global
systemic factors impact liquidity through risk-aversion and inventory concerns:
Cost and availability of funding liquidity (Euribor-Eonia, Eonia-DeTBill,
CCBSS)
Appetite for risk (USVIX)
Funding Liquidity: DiEuribor:
FLrt,τ =
M
i=1 ri,t,τ
M
− ˆrt,τ
17/24
H5: FUNDING COST OF THE MARKET
MAKERS ADVERSELY AFFECTS MARKET LIQUIDITY.
Can we disentangle market-wide liquidity concerns and market-maker specic
liquidity concerns?
Brunnermeier and Pedersen (2009) show how funding liquidity aects market
liquidity. Higher margins will have market-wide eect on market liquidity.
18/24
H5: FUNDING COST OF THE MARKET
MAKERS ADVERSELY AFFECTS MARKET LIQUIDITY.
To test the funding liquidity hypothesis, we replicate the previous regression,
including a cohort of macro variables and proceed in a general-to-specic fashion.
Variable Below 500, 2011 Above 500, 2011 2012
Intercept 0.004 -0.030 -0.007
∆BAt−1 -0.306 *** 0.061 -0.496 ***
∆BAt−2 -0.070 -0.095 -0.307 ***
∆BAt−3 -0.122 -0.345 *** -0.188 ***
∆CDSt 0.058 5.047 *** -0.050
∆CDSt−1 1.702 *** -2.533 ** 0.566 **
∆Euribor-Eoniat . 1.924 ** .
∆CCBSSt 0.695 ** . 0.836 ***
∆DiEuribort 0.043 ** . .
Adj R2
0.258 0.62 0.233
19/24
H6: THE CHANGE IN CREDIT RISK LEADS
CHANGES IN MARKET LIQUIDITY, NOT VICE VERSA.
The market perception of credit risk could depend on market liquidity. So far, we
have investigated one direction, although the causality might run both ways.
20/24
H6: THE CHANGE IN CREDIT RISK LEADS CHANGES
IN MARKET LIQUIDITY, NOT VICE VERSA.
In order to establish whether the liquidity on the secondary market may drive the
CDS market, or whether the eect is unidirectional, as suggested by the previous
slides, we perform a Granger causality analysis on the Quoted Spread and the
CDS spread time-series:
∆QSt
∆CDSt
=
KQS
KCDS
+
a111
a121
a211
a221
∆QSt−1
∆CDSt−1
+
a112
a122
a212
a222
∆QSt−2
∆CDSt−2
(1)
+
a113
a123
a213
a223
∆QSt−3
∆CDSt−3
+ · · · +
a11P
a12P
a21P
a22P
∆QSt−P
∆CDSt−P
+








b11 b12
b21 b22
.
.
.
.
.
.
bq1 bq2














∆X1t
∆X2t
.
.
.
∆Xqt






+ QSt
CDSt
We control for exogenous variables by including them rst, then by using the
orthogonalized CDS spread ∆CDS⊥
t
21/24
H6: THE CHANGE IN CREDIT RISK LEADS CHANGES
IN MARKET LIQUIDITY, NOT VICE VERSA.
Variable ∆BAt ∆CDSt
Intercept -0.002 0.001
∆BAt−1 -0.369*** -0.008
∆CDSt−1 1.264*** 0.266***
∆BAt−2 -0.131* 0.013
∆CDSt−2 -0.296 -0.113*
∆BAt−3 -0.166*** -0.006
∆CDSt−3 0.056 0.003
Granger Causality Tests
BA
GC
−−→ CDS . 1.012
CDS
GC
−−→ BA 5.189*** .
Strong support for one-directional relationship.
22/24
H6: THE CHANGE IN CREDIT RISK LEADS CHANGES
IN MARKET LIQUIDITY, NOT VICE VERSA.
Variable ∆BAt ∆CDSt
Intercept -0.002 0.001
∆BAt−1 -0.369*** -0.008
∆CDSt−1 1.264*** 0.266***
∆BAt−2 -0.131* 0.013
∆CDSt−2 -0.296 -0.113*
∆BAt−3 -0.166*** -0.006
∆CDSt−3 0.056 0.003
Granger Causality Tests
BA
GC
−−→ CDS . 1.012
CDS
GC
−−→ BA 5.189*** .
Strong support for one-directional relationship.
22/24
THE CONCLUSIONS
Strong negative eect of credit risk on market liquidity (with no
feedback eect).
CDS-Liquidity linkage is stronger and faster when the CDS level
rises above 500 bp.
The relationship is weaker after the Central Bank intervention.
23/24
THE CONCLUSIONS
Policy implications:
Euro-zone national treasuries: to understand the dynamic nature of the
relationship between credit risk, global risk factors and market liquidity,
which has strong consequences for the pricing of their issues in the auctions as
well as in secondary markets.
ECB: to understand the impact of the unconventional instruments of new
monetary policy and focus on the market's perceptions of sovereign credit
risk. The introduction of the LTRO program, providing short-term liquidity
to banks, shows that the channel from bank bailout to sovereign risk could be
reversed: oering liquidity to banks may improve the market liquidity of
sovereign bonds and also indirectly reduce sovereign risk!
Market regulators (the national central banks or European market regulators
such as ESMA): to identify the main factors that aect sovereign bonds'
market liquidity in the Euro area.
Bank regulators: to improve their tools for monitoring both bank capital
adequacy and liquidity risk. Changes in bank regulation impact market
liquidity, close coordination between regulators may prevent strong negative
externalities.
24/24
Thank you for your attention!
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.

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Sovereign credit risk, liquidity, and the ecb intervention: deus ex machina? - Loriana Pelizzon, Marti Subrahmanyam, Davide Tomio, Jun Uno. June, 5 2014

  • 1. SOVEREIGN CREDIT RISK, LIQUIDITY, AND THE ECB INTERVENTION: DEUS EX MACHINA? SYstemic Risk TOmography: Signals, Measurements, Transmission Channels, and Policy Interventions Loriana Pelizzon, Goethe University Marti Subrahmanyam, NYU Stern Davide Tomio, Copenhagen Business School Jun Uno, Waseda University
  • 2. THE MOTIVATION The European sovereign debt crisis, peaked in the summer of 2011, with bond yields and CDS spreads in Italy and Spain hitting 7%. Substantial reduction in market liquidity for sovereign bonds of countries in the Euro-zone periphery. The two variable were shown to inuence the bond yields, can we say anything about their comovement? Is there a spillover between one variable and the other? 1/24
  • 3. ITALIAN AND GERMAN 10-YEAR BOND YIELD AND SPREAD Time-series of the Italian and German bond yields spread for 10-year maturity, the Italian CDS spread and BTP-10Y yield. Our analysis period covers the two highest spikes in the CDS spread and BTP-Bund spread pattern. 2/24
  • 4. EVOLUTION OF THE BID-ASK AND CDS SPREAD Spikes in the quoted bid-ask spread (blue) overlap with spikes in the CDS spread (Red). 3/24
  • 5. EVOLUTION OF THE BID-ASK AND CDS SPREAD Spikes in the quoted bid-ask spread (blue) overlap with spikes in the CDS spread (Red). 3/24
  • 6. THE CONTRIBUTION Focus: Major European Government Debt: Italy Sample June 1, 2011 to December 31, 2012: Includes the period of high nancial turmoil Hypotheses investigated: H1: Changes in credit risk have an important bearing on changes in liquidity. H2: The relationship between credit risk and liquidity risk is altered when credit risk is high, in particular when the CDS spread on the obligor crosses a threshold. H3: Monetary policy interventions by the central bank aect the relationship between credit risk and market liquidity. H4: Market liquidity is driven by both global market nd funding liquidity risk factors. H5: The funding costs of the primary dealers (market makers) adversely aects market liquidity. H6: Over time, the change in credit risk leads changes in market liquidity and vice-versa. 4/24
  • 7. THE CONTRIBUTION Our ndings: H1: A strong and dynamic relationship between changes in Italian sovereign credit risk and market liquidity in the (secondary) sovereign bond market. H2: The relationship is stronger when the CDS spread is above 500 bp H3: The strength of the relationship diminishes after the announcement of the LTRO by the ECB on December 8, 2011. H4: Other global market and funding liquidity risk factors aect market liquidity. H5: Funding costs specic of the primary dealers adversely aects market liquidity H6: The change in credit risk leads changes in market liquidity, not vice-versa. 5/24
  • 8. PREVIOUS LITERATURE: OVERVIEW CONTRIBUTION We investigate the eect of credit risk on the market liquidity of government bonds. Theoretical Background: Inventory models, Amihud and Mendelson (1980), Ho and Stoll (1980); Funding liquidity: Brunnermeier and Pedersen (2009). Papers on the market liquidity of the US Treasury bond market: Fleming, Remolona '99, Fleming '03, Goyenko, Subrahmanyam, and Ukhov '11 Paper on the liquidity of the corporate bond market: Friewald, Jankowitsch, Subrahmanyam '12, Dick-Nielsen, Feldhuetter, and Lando '12 Papers on Euro-zone sovereign bonds: Beber, Brandt, Kavajecz '08, Cheung, de Jong, Rindi '05 6/24
  • 9. THE MARKET STRUCTURE MTS, Mercato dei Titoli di Stato, is an Electronic, Inter-Dealer market. In 2000, MTS executed 65% Volume of secondary market for IT-debt In 2003, MTS executed 74% Volume of secondary market for EU-debt In 2005, the largest market for EU government bonds (with public daily turnover 25Be). The MTS is a system of markets. The European Market: European Bond Market (EBM). Domestic Markets: Several, for larger countries. Dealer to Retail client. Not covered. There are two kinds of participants in the market: Primary Dealers: Market-makers Dealers: Price takers 7/24
  • 10. THE DATA: A UNIQUE DATASET IN A UNIQUE PERIOD From June 2011: Trade-by-Trade data. Order-by-Order data, uniquely linked to the trades. Every quote, every update, un-netted. Until June 2011: Trade-by-Trade data. Best 3 quotes prices and quantities, cumulative. We calculate a series of liquidity measures. Quoted Spread: Best ask-Best bid per 100e of face value. Quoted Quantity: Quantity quoted at any level of the bid and ask, in Million e. Lambda: How much a trader would move the best bid (ask) if she were to trade e 15 million Eective Bid-Ask Spread: 2*|Share-weighted average price - relevant best price|. 8/24
  • 11. THE DATA BONDS COMPOSITION AND MARKET VOLUME Our data covers 152 Italian sovereign bonds traded on the MTS between June 2011 and December 2012 (=406 days). Variable Mean 5th Pct Median 95th Pct Bonds 90 87 90 93 Trades 265 116 249 449 Volume(be) 2.0 0.8 1.9 3.8 Quoted Spread (e/100e) 0.18 0.42 1.24 Eective Spread (e/100e) 0.06 0.18 0.33 Quoted Quantity (MMe) 96.2 122.5 153.2 Lambda (e/100e) 0.006 0.01 0.05 Italian CDS (bps) 194 421 552 Median market daily volume is 2 billion e. US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US securitized xed income (structured product) market and US corporate bond market. We conducted the analysis with all these measures. This presentation reports Quoted Spread. CDS spread increased nearly threefold in the sample. 9/24
  • 12. THE DATA BONDS COMPOSITION AND MARKET VOLUME Our data covers 152 Italian sovereign bonds traded on the MTS between June 2011 and December 2012 (=406 days). Variable Mean 5th Pct Median 95th Pct Bonds 90 87 90 93 Trades 265 116 249 449 Volume(be) 2.0 0.8 1.9 3.8 Quoted Spread (e/100e) 0.18 0.42 1.24 Eective Spread (e/100e) 0.06 0.18 0.33 Quoted Quantity (MMe) 96.2 122.5 153.2 Lambda (e/100e) 0.006 0.01 0.05 Italian CDS (bps) 194 421 552 Median market daily volume is 2 billion e. US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US securitized xed income (structured product) market and US corporate bond market. We conducted the analysis with all these measures. This presentation reports Quoted Spread. CDS spread increased nearly threefold in the sample. 9/24
  • 13. THE DATA BONDS COMPOSITION AND MARKET VOLUME Our data covers 152 Italian sovereign bonds traded on the MTS between June 2011 and December 2012 (=406 days). Variable Mean 5th Pct Median 95th Pct Bonds 90 87 90 93 Trades 265 116 249 449 Volume(be) 2.0 0.8 1.9 3.8 Quoted Spread (e/100e) 0.18 0.42 1.24 Eective Spread (e/100e) 0.06 0.18 0.33 Quoted Quantity (MMe) 96.2 122.5 153.2 Lambda (e/100e) 0.006 0.01 0.05 Italian CDS (bps) 194 421 552 Median market daily volume is 2 billion e. US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US securitized xed income (structured product) market and US corporate bond market. We conducted the analysis with all these measures. This presentation reports Quoted Spread. CDS spread increased nearly threefold in the sample. 9/24
  • 14. THE DATA BONDS COMPOSITION AND MARKET VOLUME Our data covers 152 Italian sovereign bonds traded on the MTS between June 2011 and December 2012 (=406 days). Variable Mean 5th Pct Median 95th Pct Bonds 90 87 90 93 Trades 265 116 249 449 Volume(be) 2.0 0.8 1.9 3.8 Quoted Spread (e/100e) 0.18 0.42 1.24 Eective Spread (e/100e) 0.06 0.18 0.33 Quoted Quantity (MMe) 96.2 122.5 153.2 Lambda (e/100e) 0.006 0.01 0.05 Italian CDS (bps) 194 421 552 Median market daily volume is 2 billion e. US treasury market: 500 Billion$. US muni: 15 Billion$. Similar for US securitized xed income (structured product) market and US corporate bond market. We conducted the analysis with all these measures. This presentation reports Quoted Spread. CDS spread increased nearly threefold in the sample. 9/24
  • 15. H1: CHANGES IN CREDIT RISK AFFECT CHANGES IN LIQUIDITY Credit risk to aect liquidity through two channels: Microstructure: The higher the risk of an asset, the greater its illiquidity Asymmetry of information Inventory models VaR: Internal and external risk control constraints ∆BASpreadt = α0 + M i=1 αi ∆BASpreadt−i + N j=0 βj ∆CDSt−j + t We consider log-changes of the variables. Variable 1 2 3 4 5 Intercept −0.001 −0.001 0. −0.002 −0.001 ∆BAt−1 . −0.291 *** −0.352 *** −0.339 *** −0.329 *** ∆CDSt 1.172 *** 1.149 *** . 0.909 ** 0.870 ** ∆CDSt−1 . . 1.261 *** 1.042 *** 1.133 *** ∆CDSt−2 . . . . −0.411 Adj R2 0.051 0.134 0.141 0.170 0.174 10/24
  • 16. H1: CHANGES IN CREDIT RISK AFFECT CHANGES IN LIQUIDITY Credit risk to aect liquidity through two channels: Microstructure: The higher the risk of an asset, the greater its illiquidity Asymmetry of information Inventory models VaR: Internal and external risk control constraints ∆BASpreadt = α0 + M i=1 αi ∆BASpreadt−i + N j=0 βj ∆CDSt−j + t We consider log-changes of the variables. Variable 1 2 3 4 5 Intercept −0.001 −0.001 0. −0.002 −0.001 ∆BAt−1 . −0.291 *** −0.352 *** −0.339 *** −0.329 *** ∆CDSt 1.172 *** 1.149 *** . 0.909 ** 0.870 ** ∆CDSt−1 . . 1.261 *** 1.042 *** 1.133 *** ∆CDSt−2 . . . . −0.411 Adj R2 0.051 0.134 0.141 0.170 0.174 10/24
  • 17. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH We expect a structural shift in the relation between credit risk and liquidity: Margins in the REPO market depend on credit quality Dierent credit rating means dierent investors Similar to grouping corporate bonds by credit rating We estimate the threshold ˆγ0 that minimizes the sum of squared residual of the following regression: ∆BASpreadt =α0 + α1∆BASpreadt−1 + β0∆CDSt + β1∆CDSt−1 +I [CDS ≤ γ0] (˜α0 + ˜α1∆BASpreadt−1 + ˜β0∆CDSt + ˜β1∆CDSt−1) + t The test HT(γ, ˆγ0) developed by Hansen (2001) has a pivotal non-standard distribution which allows us to calculate condence intervals for ˆγ0. We estimate ˆγ0 and calculate HT(γ, ˆγ0), for the null H0 : γ = ˆγ0, which is drawn in the next slide as a function of γ. 11/24
  • 18. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH Hansen Test: Modication of the Likelihood Ratio Test Presence of a threshold at 500bp in the CDS spread: Statistical (see Hansen 2001): 487-504bp is the 5% condence interval Investment Grade: 500bp is the CDS level for junk-bonds also for CCP's Margins: LCH.Clearnet documents cite 500 bps. Market participants' comments 12/24
  • 19. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH Hansen Test: Modication of the Likelihood Ratio Test Presence of a threshold at 500bp in the CDS spread: Statistical (see Hansen 2001): 487-504bp is the 5% condence interval Investment Grade: 500bp is the CDS level for junk-bonds also for CCP's Margins: LCH.Clearnet documents cite 500 bps. Market participants' comments 12/24
  • 20. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH CDSt Below 500bp Intercept −0.001 −0.002 0. 0. 0. ∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 *** ∆CDSt 0.72 ** 0.671 ** . 0.427 0.404 ∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 *** ∆CDSt−2 . . . . −0.315 Adj R2 0.023 0.092 0.157 0.163 0.165 CDSt Above 500bp Intercept −0.024 −0.02 0.003 −0.014 −0.007 ∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 *** ∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 *** ∆CDSt−1 . . 0.932 −0.743 −0.447 ∆CDSt−2 . . . . −0.861 Adj R2 0.216 0.339 0.104 0.338 0.341 Relationships between changes in the CDS spread and liquidity are dierent below and above 500bp: Larger economic impact: a 10% increase in CDS→ Five-fold increase Below 500bp: 7% increase in Quoted Spread Above 500bp: 36% increase in Quoted Spread Dierent dynamics Below 500bp: Lagged reaction Above 500bp: Contemporaneous reaction 13/24
  • 21. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH CDSt Below 500bp Intercept −0.001 −0.002 0. 0. 0. ∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 *** ∆CDSt 0.72 ** 0.671 ** . 0.427 0.404 ∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 *** ∆CDSt−2 . . . . −0.315 Adj R2 0.023 0.092 0.157 0.163 0.165 CDSt Above 500bp Intercept −0.024 −0.02 0.003 −0.014 −0.007 ∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 *** ∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 *** ∆CDSt−1 . . 0.932 −0.743 −0.447 ∆CDSt−2 . . . . −0.861 Adj R2 0.216 0.339 0.104 0.338 0.341 Relationships between changes in the CDS spread and liquidity are dierent below and above 500bp: Larger economic impact: a 10% increase in CDS→ Five-fold increase Below 500bp: 7% increase in Quoted Spread Above 500bp: 36% increase in Quoted Spread Dierent dynamics Below 500bp: Lagged reaction Above 500bp: Contemporaneous reaction 13/24
  • 22. H2: THE RELATIONSHIP CHANGES WHEN CREDIT RISK IS HIGH CDSt Below 500bp Intercept −0.001 −0.002 0. 0. 0. ∆BAt−1 . −0.264 *** −0.318 *** −0.311 *** −0.297 *** ∆CDSt 0.72 ** 0.671 ** . 0.427 0.404 ∆CDSt−1 . . 1.334 *** 1.248 *** 1.313 *** ∆CDSt−2 . . . . −0.315 Adj R2 0.023 0.092 0.157 0.163 0.165 CDSt Above 500bp Intercept −0.024 −0.02 0.003 −0.014 −0.007 ∆BAt−1 . −0.371 *** −0.404 *** −0.326 *** −0.353 *** ∆CDSt 3.64 *** 3.78 *** . 4.03 *** 3.822 *** ∆CDSt−1 . . 0.932 −0.743 −0.447 ∆CDSt−2 . . . . −0.861 Adj R2 0.216 0.339 0.104 0.338 0.341 Relationships between changes in the CDS spread and liquidity are dierent below and above 500bp: Larger economic impact: a 10% increase in CDS→ Five-fold increase Below 500bp: 7% increase in Quoted Spread Above 500bp: 36% increase in Quoted Spread Dierent dynamics Below 500bp: Lagged reaction Above 500bp: Contemporaneous reaction 13/24
  • 23. H3: CENTRAL BANK INTERVENTIONS AFFECT THE CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP Euro-zone nancial regulators took actions which we expect to aect the credit-liquidity relationship EU bail-outs. ECB Monetary interventions: SMP, LTRO, OMT. Draghi's The ECB is ready to do whatever it takes to preserve the Euro and, believe me, it will be enough. The ECB can aect market liquidity through 3 channels: Purchase of bonds on the market Provide liquidity to the banks Moral Suasion 14/24
  • 24. H3: CENTRAL BANK INTERVENTIONS AFFECT THE CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP Structural break for: ∆BAt = ∆CDSt ∆BAt = ∆CDSt−1 Evidence of structural break on December 8, 2011 Statistical (Chow (1960) test) Announcement date of LTRO I Sample split 15/24
  • 25. H3: CENTRAL BANK INTERVENTIONS AFFECT THE CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP Estimating the same equation for the three subsamples: Before 8/12/2011 Before 8/12/2011 After 8/12/2011 Variable CDS500bp CDS500bp Intercept 0.003 0.0 -0.007 ∆BAt−1 -0.318** -0.088 -0.378*** ∆CDSt 0.702 5.844*** 0.313 ∆CDSt−1 1.754*** -2.658** 0.553** Adj R2 0.207 0.452 0.147 Dierent economic impact: a 10% increase in CDS→ Below 500: 18% increase in Quoted Spread Above 500: 58% increase in Quoted Spread In 2012: 5% increase in Quoted Spread 16/24
  • 26. H3: CENTRAL BANK INTERVENTIONS AFFECT THE CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP Estimating the same equation for the three subsamples: Before 8/12/2011 Before 8/12/2011 After 8/12/2011 Variable CDS500bp CDS500bp Intercept 0.003 0.0 -0.007 ∆BAt−1 -0.318** -0.088 -0.378*** ∆CDSt 0.702 5.844*** 0.313 ∆CDSt−1 1.754*** -2.658** 0.553** Adj R2 0.207 0.452 0.147 Dierent economic impact: a 10% increase in CDS→ Below 500: 18% increase in Quoted Spread Above 500: 58% increase in Quoted Spread In 2012: 5% increase in Quoted Spread 16/24
  • 27. H3: CENTRAL BANK INTERVENTIONS AFFECT THE CREDIT RISK - MARKET LIQUIDITY RELATIONSHIP Estimating the same equation for the three subsamples: Before 8/12/2011 Before 8/12/2011 After 8/12/2011 Variable CDS500bp CDS500bp Intercept 0.003 0.0 -0.007 ∆BAt−1 -0.318** -0.088 -0.378*** ∆CDSt 0.702 5.844*** 0.313 ∆CDSt−1 1.754*** -2.658** 0.553** Adj R2 0.207 0.452 0.147 Dierent economic impact: a 10% increase in CDS→ Below 500: 18% increase in Quoted Spread Above 500: 58% increase in Quoted Spread In 2012: 5% increase in Quoted Spread 16/24
  • 28. H4: MARKET LIQUIDITY IS DRIVEN BY MARKET AND FUNDING RISK FACTORS. Do global factors have an eect on the liquidity of the Italian bond market? Global systemic factors impact liquidity through risk-aversion and inventory concerns: Cost and availability of funding liquidity (Euribor-Eonia, Eonia-DeTBill, CCBSS) Appetite for risk (USVIX) Funding Liquidity: DiEuribor: FLrt,τ = M i=1 ri,t,τ M − ˆrt,τ 17/24
  • 29. H5: FUNDING COST OF THE MARKET MAKERS ADVERSELY AFFECTS MARKET LIQUIDITY. Can we disentangle market-wide liquidity concerns and market-maker specic liquidity concerns? Brunnermeier and Pedersen (2009) show how funding liquidity aects market liquidity. Higher margins will have market-wide eect on market liquidity. 18/24
  • 30. H5: FUNDING COST OF THE MARKET MAKERS ADVERSELY AFFECTS MARKET LIQUIDITY. To test the funding liquidity hypothesis, we replicate the previous regression, including a cohort of macro variables and proceed in a general-to-specic fashion. Variable Below 500, 2011 Above 500, 2011 2012 Intercept 0.004 -0.030 -0.007 ∆BAt−1 -0.306 *** 0.061 -0.496 *** ∆BAt−2 -0.070 -0.095 -0.307 *** ∆BAt−3 -0.122 -0.345 *** -0.188 *** ∆CDSt 0.058 5.047 *** -0.050 ∆CDSt−1 1.702 *** -2.533 ** 0.566 ** ∆Euribor-Eoniat . 1.924 ** . ∆CCBSSt 0.695 ** . 0.836 *** ∆DiEuribort 0.043 ** . . Adj R2 0.258 0.62 0.233 19/24
  • 31. H6: THE CHANGE IN CREDIT RISK LEADS CHANGES IN MARKET LIQUIDITY, NOT VICE VERSA. The market perception of credit risk could depend on market liquidity. So far, we have investigated one direction, although the causality might run both ways. 20/24
  • 32. H6: THE CHANGE IN CREDIT RISK LEADS CHANGES IN MARKET LIQUIDITY, NOT VICE VERSA. In order to establish whether the liquidity on the secondary market may drive the CDS market, or whether the eect is unidirectional, as suggested by the previous slides, we perform a Granger causality analysis on the Quoted Spread and the CDS spread time-series: ∆QSt ∆CDSt = KQS KCDS + a111 a121 a211 a221 ∆QSt−1 ∆CDSt−1 + a112 a122 a212 a222 ∆QSt−2 ∆CDSt−2 (1) + a113 a123 a213 a223 ∆QSt−3 ∆CDSt−3 + · · · + a11P a12P a21P a22P ∆QSt−P ∆CDSt−P +         b11 b12 b21 b22 . . . . . . bq1 bq2               ∆X1t ∆X2t . . . ∆Xqt       + QSt CDSt We control for exogenous variables by including them rst, then by using the orthogonalized CDS spread ∆CDS⊥ t 21/24
  • 33. H6: THE CHANGE IN CREDIT RISK LEADS CHANGES IN MARKET LIQUIDITY, NOT VICE VERSA. Variable ∆BAt ∆CDSt Intercept -0.002 0.001 ∆BAt−1 -0.369*** -0.008 ∆CDSt−1 1.264*** 0.266*** ∆BAt−2 -0.131* 0.013 ∆CDSt−2 -0.296 -0.113* ∆BAt−3 -0.166*** -0.006 ∆CDSt−3 0.056 0.003 Granger Causality Tests BA GC −−→ CDS . 1.012 CDS GC −−→ BA 5.189*** . Strong support for one-directional relationship. 22/24
  • 34. H6: THE CHANGE IN CREDIT RISK LEADS CHANGES IN MARKET LIQUIDITY, NOT VICE VERSA. Variable ∆BAt ∆CDSt Intercept -0.002 0.001 ∆BAt−1 -0.369*** -0.008 ∆CDSt−1 1.264*** 0.266*** ∆BAt−2 -0.131* 0.013 ∆CDSt−2 -0.296 -0.113* ∆BAt−3 -0.166*** -0.006 ∆CDSt−3 0.056 0.003 Granger Causality Tests BA GC −−→ CDS . 1.012 CDS GC −−→ BA 5.189*** . Strong support for one-directional relationship. 22/24
  • 35. THE CONCLUSIONS Strong negative eect of credit risk on market liquidity (with no feedback eect). CDS-Liquidity linkage is stronger and faster when the CDS level rises above 500 bp. The relationship is weaker after the Central Bank intervention. 23/24
  • 36. THE CONCLUSIONS Policy implications: Euro-zone national treasuries: to understand the dynamic nature of the relationship between credit risk, global risk factors and market liquidity, which has strong consequences for the pricing of their issues in the auctions as well as in secondary markets. ECB: to understand the impact of the unconventional instruments of new monetary policy and focus on the market's perceptions of sovereign credit risk. The introduction of the LTRO program, providing short-term liquidity to banks, shows that the channel from bank bailout to sovereign risk could be reversed: oering liquidity to banks may improve the market liquidity of sovereign bonds and also indirectly reduce sovereign risk! Market regulators (the national central banks or European market regulators such as ESMA): to identify the main factors that aect sovereign bonds' market liquidity in the Euro area. Bank regulators: to improve their tools for monitoring both bank capital adequacy and liquidity risk. Changes in bank regulation impact market liquidity, close coordination between regulators may prevent strong negative externalities. 24/24
  • 37. Thank you for your attention!
  • 38. 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.