The microstructure of the european sovereign bond market. Loriana Pellizzon. May, 9 2013

The microstructure of the european sovereign bond market.A study of the Euro-zone crisis

SYstemic Risk TOmography:Signals, Measurements, Transmission Channels, and Policy Interventions

Loriana Pelizzon, Goethe UniversityMarti Subrahmanyam, NYU SternDavide Tomio, Copenhagen Business SchoolJun Uno, Waseda University

NY-FED seminar. MAY 9, 2013.

THE MOTIVATION

I The European sovereign debt crisis, peaked in the summer of 2011, with bondyields in Italy and Spain hitting 7%.

I Subsequently, there is growing awareness of the connection between liquidityand credit risk.

I We investigate this linkage through an analysis of market-maker behaviorduring times of crisis:

I How is liquidity affected by a shock to credit risk?

I How do market-makers react to an unprecedented level of the CDS spread?

I How effective are ECB interventions in calming down the fears of dealers,particularly market-makers?

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THE MOTIVATION

OECD Countries by Total Central Government Debt (in B$, OECD 2010):

Japan $9465 Poland $237United States $9035 Portugal $203Italy $2256 Sweden $172United Kingdom $2068 Israel $162France $1755 Australia $125Germany $1483 Ireland $125Spain $734 Denmark $123Canada $584 Switzerland $118Belgium $456 Norway $111Greece $455 Finland $100Netherlands $410 Hungary $96Korea $329 Czech Republic $72Turkey $307 New Zealand $41Mexico $291 Slovak Republic $34Austria $250 Chile $19

I Italy has the largest sovereign bond market in the Euro-zone and the thirdlargest in the world.

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THE MICROSTRUCTURE OF THE EUROPEAN SOVEREIGN BONDMARKET

A STUDY OF THE EURO-ZONE CRISIS

Loriana PelizzonVenice University & MIT

Marti SubrahmanyamNYU

Davide TomioCopenhagen Business School

Jun UnoWaseda University

THE MOTIVATION

I The European sovereign debt crisis, peaked in the summer of 2011, with bondyields in Italy and Spain hitting 7%.

I Subsequently, there is growing awareness of the connection between liquidityand credit risk.

I We investigate this linkage through an analysis of market-maker behaviorduring times of crisis:

I How is liquidity affected by a shock to credit risk?

I How do market-makers react to an unprecedented level of the CDS spread?

I How effective are ECB interventions in calming down the fears of dealers,particularly market-makers?

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THE MOTIVATION




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THE MOTIVATION




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ITALIAN 2- AND 10-YEAR BOND YIELD

Time-series of the Italian bond yield for 2- and 10-year maturities.3/38

ITALIAN AND GERMAN 10-YEAR BOND YIELD AND SPREAD

Time-series of the Italian and German bond yields spread for 10-year maturity,CDS and BTP-10Y. Our analysis period covers the two highest spikes in the CDSspread and BTP-Bund spread pattern.

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EVOLUTION OF THE BID-ASK AND CDS SPREAD

Time-series of market-wide bid-ask spread and CDS spread. Spikes in the quoted(green) and effective (red) bid-ask spread overlap with spikes in the CDS spread.

Back to Time Series

THE CONTRIBUTION

Focus:I Major European Government Debt: ItalyI Period of financial turmoil

Findings:I Non-linear relationship between Credit risk (CDS spread) and market-wide

liquidity (bid-ask spread and quoted quantity). When credit risk rises,illiquidity increases at a much faster pace.

I Market-makers stop making markets at least temporarily, when the CDSspread widens, both in less-stressful and extreme cases. In particular, primarydealers in the sovereign bond market are more risk averse than CDS marketparticipants.

I ECB interventions successfully calmed the fear of solvency risk, and hence,improved liquidity as well.

I Case studies show that big spikes in the bid-ask spread and the drop ofmarket maker participation happen only on the event day, if it was a surprise.It occurs one day before in the case of anticipated events.

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LITERATURE: ON AMERICAN TREASURY BOND MARKET

On the government bond market:I Fleming, Remolona JF ’99: Show the effect of public information releases on

the market for US Treasury bonds.

I Fleming ’03: Analyzes liquidity measures, both trade- and quote-based, andtheir correlation. The quoted bid-ask spread turns out to be the most efficientmeasure.

I Engle, Fleming, Ghysels, and Nguyen ’12: Propose a new class of dynamicorder book models. They show that liquidity decreases with price volatility,but increases with liquidity volatility.

I Goyenko, Subrahmanyam, and Ukhov JFQA’11: Study the determinants ofbond liquidity. The illiquidity difference between on- and off-the-run bondswidens during a recession, in a flight-to-liquidity.

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LITERATURE: ON THE CRISIS

I Dick-Nielsen, Feldhuetter, and Lando JFE’12: Analyze the effect of illiquidityon corporate bond yield spreads. During the crisis, the contribution ofilliquidity grows, especially for speculative-grade bonds. They show aflight-to-liquidity in the early stages of the crisis.

I Friewald, Jankowitsch, Subrahmanyam JFE ’12: Show that liquidity effectsare more pronounced in periods of financial crises. In a large sample ofcorporate bonds, they employ a range of liquidity measures, including trade-and quote-based measures, to show that liquidity is priced in bond yieldspreads.

I Cheung, de Jong, Rindi ’05: Study the impact of trading intensity on (trade)prices, narrowing down the sample, and response to large trades.

I Beber, Brandt, Kavajecz RFS ’08: Disentangle flight-to-liquidity andflight-to-quality focusing on EU debt in 03-04. Investors demand (and pay)for both liquidity and lower credit risk. Both are priced, especially forlow-credit countries and in distressed periods.

I Darbha and Dufour ’12: Analyze the liquidity component of Euro-areasovereign bond yield spreads, using a range of liquidity proxies.

I Brunnermeier and Pedersen RFS’09: Shows theoretically that a reduction incapital reduces market liquidity, especially if the capital is already low (anonlinear effect).

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THE MARKET STRUCTURE

MTS, Mercato dei Titoli di Stato, is an Electronic, Inter-Dealer market.

I In 2000, MTS executed 65% Volume of secondary market for IT-debtI In 2003, MTS executed 74% Volume of secondary market for EU-debtI In 2005, the largest market for EU government bonds (with public daily

turnover 25Be).I Traders confirm similar conditions apply to today’s market share, although

detailed market share data are not publicly available.I MTS’s (NASDAQ:MTSC) majority shareholder is the LSE. Other

shareholders: JP Morgan, Deutsche Bank, BNP Paribas, Citigroup, GoldmanSachs.

The MTS is a system of markets.I The European Market: European Bond Market (EBM).I Domestic Markets: Several, for larger countries.I Dealer to Retail client. Not covered.

Updates of the best five prices on each side and the corresponding aggregatedquantity are available on screens to traders, to ensure a linkage between theEuropean and domestic markets.

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THE TRADERS AND THE MARKET MAKERS

There are two kinds of participants in the market:I Primary Dealers: Market-makersI Dealers: Price takers

The way traders interact is as follow:I Market-Makers submit bid- and ask-prices and the quantity they are willing

to trade (Proposals).I Their quotes (proposals) are iceberg orders.I Both other primary dealers and primary dealers can hit/lift a primary

dealers’ bid- and ask- quotes (proposals).I Price takers can only submit market orders.I However, 90% of the trades are initiated by market-makers.

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THE DATA: A UNIQUE DATASET IN A UNIQUE PERIOD

From June 2011:I Trade-by-Trade data.I Order-by-Order data, uniquely linked to the trades.I Every quote, every update, un-netted.

Until June 2011:I Trade-by-Trade data.I Best 3 quotes prices and quantities, cumulative.

New data allow us to:Un-netted quotes: Measure liquidity, when not at the market.Proposal ID: Follow the same quote throughout the day, observe its every change.Drip Quantities: Know the quantity the dealers are actually willing to trade

(iceberg orders).

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(iceberg orders).

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(iceberg orders).

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THE MEASURESTHE LEFT-HAND SIDE VARIABLES

We calculate a series of liquidity measures.Bid-Ask Spread: Best ask-Best bid per 100eof face value.Effective Bid-Ask Spread: 2*|Share-weighted average price - relevant best price|.Revision per Single Proposal: Average number of revisions per single proposal

(Proposal ID).Single Proposal 5 min: Number of standing single proposals, sampled at a

5-minute frequency.Quantity at Best: Quantity quoted at the best bid and ask, in Million e.Total Quoted Quantity: Quantity quoted at any level of the bid and ask, in

Million e.Log Var: Logarithm of the variance of mid-quote returns.Amihud Measure: Ratio of volume exchanged to mid-quote return.Roll Measure: Square root of the negative of the covariance of adjacent

transaction price changes.

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EVOLUTION OF THE SINGLE PROPOSALS 5MIN

Daily time-series average of number of single proposals per bond, sampled at a 5-minfrequency.

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THE EXPLANATORY VARIABLESTHE RIGHT-HAND SIDE VARIABLES

We explain them using the followingMaturity: Time from issuance to maturity date, rounded, in years.Time-to-maturity (Age): Time between quotation day and maturity(issuance), in years.Coupon Type: Coupon-bearing vs. Non-Coupon Bonds, dummy.Amount Issued: Size of the issuance, in Million e.Coupon Rate: In percentage points.

We control for trading activitiesDaily Trades: In the cross-sectional analysis, average number of trades perday, per bond.Total Quantity: In the time-series analysis, total quantity traded on themarket.

We control for the change in Italian Government creditworthinessCDS level: Level of the CDS spread on the 5-year US dollar-denominatedCDS on the Italian Sovereign, from Thomson-Reuters-Datastream.

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THE DATA

Our data covers 148 Italian sovereign bonds traded on the MTS between June2011 and December 2012 (=404 days).

Maturity Group # Bonds Coupon Rate Avg- Maturity0.25 9 0 0.270.50 24 0 0.511.00 32 0 1.012.00 11 0 2.023.00 10 3.20 2.995.00 13 3.87 5.036.00 13 Floating 6.7010.00 19 4.44 10.4115.00 7 4.57 15.7130.00 10 5.88 30.88

I Coupon-Bearing BondsI Non-Coupon-Bearing Bonds

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THE DATA




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THE DATA




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STYLIZED FACTSFOR THE CROSS-SECTION

Variable 5th Percentile Median 95th PercentileAmount Issued (Be) 4 12 26

Daily Trades 0.8 2.8 12.2Daily Quantity (Me) 4 26 85Daily Revisions (m) 10 28 77

Total Single Proposals 23 27 144Single Proposals 5min 14 17 20

Revisions per Single Proposal 395 1,076 2.682Total Quoted Quantity (Me) 77 123 169

Best Quantity 7 12 25Bid-Ask Spread 0.02 0.25 1.26

I Number of trades per bond similar to TRACE. In line with the prior MTSliterature.

I On average, 2.2 revisions per single proposal per minute. Per bond, a revisionevery second.

I About 10% of the quoted quantity is at the best price.

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STYLIZED FACTSFOR THE TIME-SERIES

Variable 5th Percentile Median 95th PercentileTraded Quantity (Be) 1 2 4

Daily Trades 114 260 494Single Proposals 5min 13 18 20

Revisions per SP 834 1332 2304Bid-Ask Spread 0.18 0.43 1.3CDS spread 179 427 550

∆CDS -24.3 0.3 25.7I Median market daily volume is 2 billion e.I US treasury market: 500$Billion. US muni: 15$Billion. Similar for US

securitized fixed income (structured product) market.

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STYLIZED FACTSFOR THE TIME-SERIES

Variable 5th Percentile Median 95th PercentileTraded Quantity (Be) 1 2 4

Daily Trades 114 260 494Single Proposals 5min 13 18 20

Revisions per SP 834 1332 2304Bid-Ask Spread 0.18 0.43 1.3CDS spread 179 427 550

∆CDS -24.3 0.3 25.7I Median market daily volume is 2 billion e.I US treasury market: 500$Billion. US muni: 15$Billion. Similar for US

securitized fixed income (structured product) market.

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THE CROSS-SECTIONAL ANALYSISTHE REGRESSION

We estimate the following cross-section regression, using time-series averages:

Coupon: LMi =β1 + β2AmountIssuedi + β3Daily Tradesi +

+ β4CouponRatei + β5−8MaturityDummiesi + +

+ β9Time to Maturity

Maturity i+ β10

(Time to Maturity

Maturity i

)2+ εi

I Investigate whether our Liquidity Measures can be explained by (and howthey vary across) product characteristics and trading activity variables

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THE CROSS-SECTIONAL ANALYSISTHE RESULTS FOR THE SPREADS

Variable Quoted Spread Effective SpreadAmountIssued −0.009*** −0.004**Daily Trades −0.03*** −0.008***CouponRate 0.009 0.009Maturity3 0.351*** 0.1**Maturity5 0.41*** 0.13***Maturity10 0.537*** 0.18***Maturity15 0.728*** 0.235***Maturity30 1.13*** 0.426***

TTM/Maturity 0.842*** 0.315***TTM/Maturity2 −0.601** −0.241***

R2(N=58) 0.985 0.985

I Significant non-linear effect of Time-to-Maturity (or, conversely, Age).On-the-run and close-to-maturity bonds have the lowest bid/ask spread.

I Bid-ask spread grows from issuance, peaks at one-fourth of total maturity,and then decreases until maturity. Reversed U-Shape

I Larger issues have a smaller bid-ask spread.I Longer Maturities have significantly larger spreads.I Endogeneity of the trading decision.

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R2(N=58) 0.985 0.985




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R2(N=58) 0.985 0.985




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R2(N=58) 0.985 0.985




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THE CROSS-SECTIONAL ANALYSISTHE RESULTS FOR THE QUOTE-BASED MEASURES

Variable Revisions Single Prop Qty at TotalPer SP 5 min Best Quantity

AmountIssued −22.25** −0.03 0.411 1.221Daily Trades −80.225*** 0.174*** −0.095 −0.946*CouponRate 36.01 0.089 0.75 1.732Maturity3 1280.97*** 15.298*** 15.445*** 153.89***Maturity5 1274.88*** 15.82*** 13.248*** 150.411***Maturity10 1893.15*** 16.444*** 10.611* 140.065***Maturity15 2205.129*** 16.282*** 10.199* 126.97***Maturity30 2748.806*** 15.509*** 8.153 102.754***

TTM/Maturity 36.958 7.272*** −45.511* −174.291**TTM/Maturity2 961.61 −4.482** 36.689* 137.371**

R2(N=58) 0.978 0.999 0.901 0.987I Quote-based measures are U-shaped in maturity. Revision per SP is an

exception.I Quote-based measures show the negative relationship between liquidity and

maturity. Single Prop 5 min is an exception.I Bid-ask Spread increases while Quoted Quantity decreases → Unequivocally

lower liquidity.I Revision per Single Proposal positively depends on maturity.

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THE TIME-SERIES ANALYSISTHE REGRESSION

We estimate the following time-series regression, using “across-bonds” averages:

∆LMt = β0 + β1∆CDSt + β2 (∆CDSt )2 + β3TradedQuantityt + εt

I Investigate how overall-market liquidity measures change, when the CDSspread changes. Back to the CDS graph

I Brunnermeier and Pedersen’s (BP) model implies that the effect ofspeculative capital on market liquidity is highly nonlinear: a marginal changein capital has a small effect, when speculators are far from their constraints,but a large effect when they are close to their constraints.

I In our study, the CDS spread is used to assess both credit and fundingconstraints faced by primary dealers

I BP assume that speculators provide market liquidity in keeping the ratio ofilliquidity to margin constant across assets. They optimally invest insecurities that have the greatest expected profit per capital used. Not a validassumption for MTS: Market-makers are assigned bonds exogenously.

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THE TIME-SERIES ANALYSISTHE RESULTS FOR THE SPREADS

Variable Quoted BA EffectiveSpread Spread

Intercept −0.0359*** −0.00810**∆CDS 0.0029** 0.0007**∆CDS2 0.0001** 0.00002***

∆TradedQuantity −0.0198** −0.0082***R2(N=404) 0.1266 0.1439

I Positive convex relationship between ∆CDS and Quoted BA Spread.I Similar result for the Effective Spread.

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THE TIME-SERIES ANALYSISTHE RESULTS FOR THE SPREADS


Intercept −0.0359*** −0.00810**∆CDS 0.0029** 0.0007**∆CDS2 0.0001** 0.00002***

∆TradedQuantity −0.0198** −0.0082***R2(N=404) 0.1266 0.1439

I Positive convex relationship between ∆CDS and Quoted BA Spread.I Similar result for the Effective Spread.

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THE TIME-SERIES ANALYSISTHE RESULTS FOR THE QUOTE-BASED MEASURES

Variable Revision SingleProp Qty Totalper SP 5 Min at Best Quoted Qty

Intercept −0.5648 0.1565 0.0988 1.014∆CDS −0.7672 −0.0136** −0.0045 −0.198***∆CDS2 0.0097 −0.0006*** −0.0004*** −0.0043***

∆TradedQuantity 55.1763*** −0.1249 −0.045 −0.9816R2(N=404) 0.0435 0.0648 0.0239 0.0676

I Negative convex relationship between ∆CDS and Single Prop 5min:I When credit risk is high, the number of market makers diminishes.

I Similar result for the Total Quoted QuantityI BP predicts that when funding liquidity is tight, traders become reluctant to

take on positions.

I Revision per Single Proposal depends solely on the Traded QuantityI When trading interest is high, market-makers update quotes more often.

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take on positions.


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take on positions.


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take on positions.


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THE TIME-SERIES ANALYSISSUBSAMPLE: ON-THE-RUN VS. OFF-THE-RUN

On The Run

Variable Quoted Spread Effective Spread

Intercept -0.0334** -0.0043∆CDS 0.0028** 0.0008**∆CDS2 0.0001** 0.00001

∆TradedQuantity -0.543*** -0.0354***

R2 0.1147 0.0907

Off The Run


Intercept -0.0364*** -0.0105***∆CDS 0.0029** 0.0006**∆CDS2 0.0001** 0.00003***

∆TradedQuantity -0.0269** -0.0130 ***

R2 0.1276 0.1425

Results hold whensplitting the samplebetween On-the-Runand Off-the-Runbonds.

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THE TIME-SERIES ANALYSISSUBSAMPLE: SUB-PERIODS

Until December 2011


Intercept −0.0588 * −0.0124 *∆CDS 0.0039 ** 0.0008 **∆CDS2 0.0001 ** 0.00003**

∆TradedQuantity −0.0494 ** −0.0155 ***

R2 0.1563 0.1815N 151 151

From January 2012


Intercept −0.0131 *** −0.0050 *∆CDS 0.001 ** 0.0006 **∆CDS2 0.00005*** 0.00002*

∆TradedQuantity 0.0061 −0.0024

R2 0.07786 0.08069N 253 253

Results hold whensplitting the samplebetween pre- andpost-ECB interventionperiods.

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THE CASE STUDYTHE SETTING

We calculate the Abnormal Liquidity Measure for bond i on day t around event d .

ALMdit =LMdit − CLMdi

CLMdi

I The event days are those when the top 1% and bottom 1% CDS changes (inour sample) took place (8 days).

I For a 8-day window around each event, we calculate the ALMdit for bond i.I CLMdi is the Comparison Liquidity Measure, which we define as the median

of LMd−9,i , LMd−10,i ,...LMd−19,i .I ALMt are graphed in the following slides. D(=8) t-test are calculated across

the I bonds for each event and each liquidity measure.To the Event Days

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THE CASE STUDYTHE HYPOTHESES

When credit risk jumps, market liquidity suddenly dries up:I Market makers increase the quoted and effective spread, while continuing to

provide liquidity.

I Market makers stop making markets and wait until uncertainty is reduced.Once uncertainty is eliminated, they resume market making.

I Each market maker reduces his position as a liquidity provider but remains“at market” to provide liquidity (panel analysis).

To the Event Days

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THE CASE STUDYQUOTED AND EFFECTIVE SPREAD

I Quoted Bid-ask Spread.I 7 out of 8 positive and

significant tests.I 130% increase in the

quoted bid-ask spread.I Increase lasts up to day

+1.

I Effective Spread.I Same results as for the

quoted spread.I Higher quoted spread

translates into highertransaction costs forliquidity demanders.

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THE CASE STUDYAVERAGE REVISION AND SINGLE PROPOSALS

I Average Revisions perSingle Proposal.

I Consistently higher in thepost-event window.

I Single Proposal 5min.I Market makers withdraw

from the market on day 0.I Their presence is restored

on day +2.

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THE GRANGER CAUSALITY

In order to establish:I whether the ECB intervention had an effect on the effect of the CDS market

on the liquidity supply,I whether an enhanced liquidity on the secondary market may benefit the CDS

market,we perform a Granger causality analysis on our liquidity measures and the CDSspread time-series:(

∆LMt∆CDSt

)=

(KLM

KCDS

)+

(a111

a121a211

a221

)(∆LMt−1

∆CDSt−1

)+

(a112

a122a212

a222

)(∆LMt−2

∆CDSt−2

)

+

(a113

a123a213

a223

)(∆LMt−3

∆CDSt−3

)+ · · · +

(a11P

a12Pa21P

a22P

)(∆LMt−P

∆CDSt−P

)+

(εLMtεCDSt

)And we verify the previous statement by testing for:

I a12p = 0 before and after December 2011.I a21p = 0 before and after December 2011.

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Brunnermeier and Pedersen shows that, when funding liquidity is tight,traders become reluctant to take on positions. ECB interventions should easefunding liquidity: they affect the primary dealers’ appetite for liquidity provision.

Sample Caused Causing SignificanceAll CDS Bid-Ask Spread *All Bid-Ask Spread CDS ***

Up to November 2011 CDS Quoted SpreadUp to November 2011 Quoted Spread CDS ***From January 2012 CDS Quoted SpreadFrom January 2012 Quoted Spread CDS

All CDS Quantity at BestAll Quantity at Best CDS **

Up to November 2011 CDS Quantity at BestUp to November 2011 Quantity at Best CDS **From January 2012 CDS Quantity at BestFrom January 2012 Quantity at Best CDS

I Quoted spread (quantity at best) is Granger-caused by CDS.I Relationship holds only until November 2011.I From January 2012, the relationship is not significant.

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THE PANEL ANALYSISTHE EQUATION

We estimate the following panel regression:

∆LMit =β1∆LMit−1 + β2Time to Maturity

Maturity it+ β3DummyTradeit

+β...Below500t ·MaturityDummyi ·∆CDSt

+β...Above500t ·MaturityDummyi ·∆CDSt + ci + εit

where ∆LMit is the change in the liquidity measure for bond i on day t . ∆CDSt isthe change in CDS from day t − 1 to day t . DummyTradeit equals 1, if bond itraded on day t .

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THE PANEL ANALYSISTHE RESULTS FOR THE SPREAD


∆LMit−1 −0.3536*** −0.2257***TTM/Maturity 0.0203** 0.0072***DumTrades −0.0487*** −

<500*∆CDS*M3 0.0002 0.0002<500*∆CDS*M5 0.0004*** 0.0004***<500*∆CDS*M10 −0.0006** -0.0002<500*∆CDS*M15 −0.0003 0.0003*<500*∆CDS*M30 −0.0009* −0.0004

>500*∆CDS*M3 0.0066*** 0.0014***>500*∆CDS*M5 0.0058*** 0.0016***>500*∆CDS*M10 0.0079*** 0.0012***>500*∆CDS*M15 0.0175*** 0.0023***>500*∆CDS*M30 0.0314*** −0.0008

Bond-FE Yes YesR2 0.20 0.19N 21127 21083

I Changes in CDS have a different effects on liquidity, conditional on the level of the CDSspread.

I The larger the increase in CDS, the larger the increase in illiquidity.I The relative sensitivity of the 5- and 10-year bond Quoted Spread is smaller than for the

other maturities.I Quoted Spread is not affected by changes in the CDS level, when the latter is below 500

bp. One exception: 10-year bonds, the benchmark.I Similar results for the Effective Spread, i.e., conditional on trading.

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Bond-FE Yes YesR2 0.20 0.19N 21127 21083





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Bond-FE Yes YesR2 0.20 0.19N 21127 21083





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Bond-FE Yes YesR2 0.20 0.19N 21127 21083





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Bond-FE Yes YesR2 0.20 0.19N 21127 21083





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THE PANEL ANALYSISTHE RESULTS FOR THE QUOTE-BASED MEASURES


∆LMit−1 −0.3887 *** −0.2963 *** −0.3113 *** −0.327 ***TTM/Maturity 84.8674 *** 0.2082 *** 0.0302 −0.0672 **DumTrades −51.5177 *** −0.0278 −0.5528 *** −0.0297

<500*∆CDS*M3 0.3013 −0.0034 ** 0.0061 0.0017<500*∆CDS*M5 0.9466 *** −0.0033 * −0.0038 −0.0015<500*∆CDS*M10 −0.4817 −0.0005 −0.0034 −0.0012<500*∆CDS*M15 −1.5964 −0.0022 −0.0006 0.0008 ***<500*∆CDS*M30 −3.3733 *** −0.0026 *** −0.0025 ** 0.0004 ***

>500*∆CDS*M3 −2.1851 * −0.0364 *** −0.0166 −0.0018>500*∆CDS*M5 −2.2076 *** −0.0359 *** −0.0076 ** 0.0005>500*∆CDS*M10 −0.8226 −0.0372 *** −0.0089 0.0029 ***>500*∆CDS*M15 −4.8253 *** −0.0357 *** −0.0014 0.0023 ***>500*∆CDS*M30 −7.2577 *** −0.0334 *** 0.0016 0.0006 ***

Bond-FE Yes Yes Yes YesR2 0.2043 0.0570 0.1558 0.1132N 21127 21127 21127 21127

I Primary Dealers update 30- and 15-year bond quotes less frequentlyI Primary Dealers update 5-year bond quotes more frequently. Selling interest

from investorsI Single Proposals 5min steadily decreases for all maturities, more so for high

CDS levels.

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CDS levels.

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CDS levels.

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CDS levels.

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THE PANEL ANALYSISTHE RESULTS FOR THE SPREAD: UNTIL DECEMBER 2011


∆LMit−1 −0.3511 *** −0.2238 ***TTM/Maturity 0.7469 *** 0.091 ***DumTrades −0.1169 *** 0.007 ***

<500*∆CDS*M3 0.0001 0.0004<500*∆CDS*M5 0.0007 *** 0.0005 **<500*∆CDS*M10 −0.0013 ** −0.0003<500*∆CDS*M15 −0.0003 0.0004<500*∆CDS*M30 0.0026 *** 0.0005

>500*∆CDS*M3 0.01 *** 0.0021 ***>500*∆CDS*M5 0.0086 *** 0.0024 ***>500*∆CDS*M10 0.0111 *** 0.0021 ***>500*∆CDS*M15 0.0252 *** 0.0033 ***>500*∆CDS*M30 0.0461 *** 0.0012

N 7712 7668R2 0.245 0.063

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THE PANEL ANALYSISTHE RESULTS FOR THE SPREAD: FROM JANUARY 2012


∆LMit−1 −0.3932 *** −0.2298 ***TTM/Maturity −0.1012 *** −0.0239 ***DumTrades −0.0081 ** −0.0031 ***

<500*∆CDS*M3 0.0001 0.0001<500*∆CDS*M5 0.0001 0.0002<500*∆CDS*M10 0.000006 −0.0002<500*∆CDS*M15 −0.0003 0.0002<500*∆CDS*M30 −0.0006 *** 0.0001

>500*∆CDS*M3 0.0009 ** 0.0003>500*∆CDS*M5 0.001 *** 0.0002>500*∆CDS*M10 0.0016 *** −0.0005>500*∆CDS*M15 0.0022 *** 0.0004>500*∆CDS*M30 0.0018 *** −0.0002

N 13415 13415R2 0.163 0.0546

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THE CONCLUSIONS

I Non-linear relationship between credit risk and market-wide liquidity isconfirmed in our empirical examination. When credit risk rises, illiquidityspreads at a much faster pace. This results in a jump in bond yields.

I Effects of CDS spread changes to illiquidity are more prevalent and persistentamong bond maturities when the CDS level rises above 500 bp.

I Primary dealers stop making markets, at least temporarily, when the CDSspread widens, both in less stressful and in extreme cases.

I Case studies shows that the big spike in the bid-ask spread, and theconsequent drop in market-maker participation, happens only on the eventday. It occurs one day before, in the case of anticipated events.

I Coverage by market makers does not vary on maturity group, yet their“attention” does. Quotes for bonds with maturities of less than five years areupdated more frequently. Market-makers pay highest attention to the 5-10year bonds at the crisis. It indicates that an increasing fear for default ofgovernment bonds pushes segments of buy-and-hold investors. This requiresfurther investigation in subsequent research.

Overall, these findings are consistent with big spikes in yield observed during theEuro-zone financial crisis.

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UPCOMING PROJECTS

Further Research:

I Investigate credit risk further by separating illiquidity effects in the CDSprice.

I Separate Eurozone credit risk from Italian sovereign credit risk.

I Model and characterize market maker behavior.

I Examine the impact of news on liquidity during the financial crisis.

I Investigate the relationship between government debt issuance (auctions) andsecondary market liquidity.

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Thank you for your attention!

APPENDIX

GRAPHSTS VolumeTTM-SpreadProposals Case StudyIntraday QuantityIntraday Quantity at BestIntraday SpreadIntraday VolumeTime-Series QuantityTime-Series Amihud and RollQuadratic DeltaQuotes UpdatesAn Event Example

TABLESTS LogvarCS LogvarPanel LogvarEvent DaysPanel with different ThresholdRegression LM on LM

NOTES

EVOLUTION OF THE VOLUME

Time-series daily number of trades (RHS axis) and traded quantity (LHS axis, inBe)

TIME-TO-MATURITY/SPREAD RELATION

Bid-ask spread*Time-to-Maturity (time-series averages, 0=Maturity Date,coupon-bearing bonds) Back to Regression

PROPOSALS DURING THE CASE STUDY

Single Proposals 5min and Quoted Quantity Around Berlusconi’s Resignation

INTRADAY QUOTED QUANTITY EVOLUTION

Intraday evolution of Quoted Quantity and Single Proposal

INTRADAY EVOLUTION OF QUANTITY AT THE BEST PRICE

Intraday evolution of Quantity at the Best Bid and Ask

INTRADAY EVOLUTION OF QUOTED SPREAD

Intraday Evolution of the Quoted Bid-Ask Spread, averaged through days andbonds

INTRADAY EVOLUTION OF TRADED QUANTITY AND TRADES

Intraday evolution of traded quantity and trades.

TIME-SERIES EVOLUTION OF QUOTED QUANTITY

Time-series evolution of total quoted bid- and ask-quantity.

TIME-SERIES EVOLUTION OF THE AMIHUD AND ROLL MEASURES

Time series evolution of the Amihud and Roll measures.

QUADRATIC DELTA

Graphic rendition of time-series parameters for the bid-ask spread and normalizeddistribution of delta.

QUADRATIC DELTA

Graphic rendition of time-series parameters for the bid-ask, linear specification,and normalized distribution of delta.

QUADRATIC DELTA

Empirical distribution of Delta

BID ASK SPREAD

Intraday quotes evolution for a 33.3 years-long French bond on June 7,11. A tradetook place at 16:50. Ask quotes are in blue, bid quotes in red.

A FLAVOR...MARKET CHARACTERISTICS AROUND BERLUSCONI’S RESIGNATION

Market-wide bid-ask spread and the level of CDS spread (right axis) aroundBerlusconi’s resignation.

THE TIME-SERIES ANALYSISTHE RESULTS FOR THE MEASURES

Variable Log Amihud RollVar Measure Measure

Intercept −0.1080 −0.2767 0∆CDS 0.0045 0.0362* 0∆CDS2 0.0004*** 0.0009 0

∆TradedQuantity 0.1296** 0.0668 0.0016***R2 0.0463 0.0444 0.0197

I Log var grows in the square of the change of the CDS, thus, regardless of thesign

THE TIME-SERIES ANALYSISTHE RESULTS FOR THE MEASURES


Intercept −0.1080 −0.2767 0∆CDS 0.0045 0.0362* 0∆CDS2 0.0004*** 0.0009 0

∆TradedQuantity 0.1296** 0.0668 0.0016***R2 0.0463 0.0444 0.0197

I Log var grows in the square of the change of the CDS, thus, regardless of thesign

THE CROSS-SECTIONAL ANALYSISTHE RESULTS FOR THE MEASURES


Intercept −15.25*** −0.61 0.0449AmountIssued 0.05*** 0.09* −0.0018Daily Trades −0.13*** −0.33*** −0.0031***CouponRate 0.15 −0.24 −0.0017Maturity5 −0.45 0.51* 0.0110*Maturity10 −0.72** 1.49*** 0.0377***Maturity15 0.08 4.59*** 0.0570***Maturity30 0.21 11.17*** 0.0763***

TTM/Maturity −0.14 7.15*** 0.1275**TTM/Maturity2 1.38 −1.93 −0.0978*

R2 0.59 0.96 0.66

I The Amihud and Roll measures show similar results to those for the bid-askspread

I They are poor measuresI (Log) Variance of mid-quotes shows few significant regressand.

THE RESULTS FOR OTHER MEASURESTHE RESULTS FOR THE MEASURES


∆LMit−1 −0.4293*** −0.4371*** −0.07***TTM/Maturity 0.1645*** 0.4924 0DumTrades 0.1659*** − −0.0220**

<500*∆CDS*M30 −0.0027*** −0.0565 0.0001<500*∆CDS*M15 −0.0008 0.0379 0<500*∆CDS*M10 0.0016** 0.0177 0<500*∆CDS*M5 0.0063*** 0.0047 0<500*∆CDS*M3 0.0025 0.0081** 0

>500*∆CDS*M30 0.0069*** −0.2123 0.0002>500*∆CDS*M15 0.0148*** 0.1824 0>500*∆CDS*M10 0.0119*** −0.0068 0>500*∆CDS*M5 0.0139*** 0.0155** 0>500*∆CDS*M3 0.0165*** 0.0210 0

Bond-FE Yes Yes YesR2 0.20 0.22 0.01N 19369 6366 6374

I Reduction in sample size for Amihud and Roll MeasureI Log Var indicates that prices change more often when CDS levels are high.

The change is negatively proportional to maturity.

















TIME-TO-MATURITY/SPREAD RELATION

Date ∆CDSt CDStAugust 08, 2011 -49.47 336.21

September 20, 2011 53.90 502.22September 27, 2011 -51.77 445.77October 27, 2011 -51.04 402.40November 01, 2011 77.53 517.06November 09, 2011 50.33 564.64December 08, 2011 52.58 524.44

June 29, 2012 -49.26 480.99Back to the Analysis

PANEL WITH DIFFERENT THRESHOLD

Variable Spread Sig AvgRev SigLag∆LM -0.3560 *** -0.4078 ***

TTM/Maturity 0.0613 *** 70.1522 ***DummyQuantity -0.0607 *** -64.0242 ***

<400*∆CDS*M30 0.0006 2.7679 **<400*∆CDS*M15 -0.0029 * -0.2307<400*∆CDS*M10 -0.0030 *** -0.8719<400*∆CDS*M5 -0.0000 1.7134 ***<400*∆CDS*M3 -0.0003 -0.1102

>400*∆CDS*M30 0.0145 *** -6.2487 ***>400*∆CDS*M15 0.0085 *** -3.1915 **>400*∆CDS*M10 0.0036 *** 0.0079>400*∆CDS*M5 0.0027 *** 0.2061>400*∆CDS*M3 0.0033 *** -0.0280

CROSS-SECTIONAL REGRESSION OF LIQUIDITY MEASURE ON LIQUIDITYMEASURE

Dependent Eff. Avg SP Qty Tot Log Amihud RollSpread Rev 5min Best Qty Var M M

Spread 1 *** 1 * -1 -1 *** -1 *** 1 *** 1 *** 1 ***EffSpread 1 * -1 -1 *** -1 *** 1 *** 1 *** 1 ***AvgRev 1 ** -1 *** -1 *** 1 ** 1 *** 1SP5m -1 *** -1 *** -1 1 1

QtyBest 1 *** -1 -1 -1TotQty -1 -1 * -1LogVar 1 *** 1Amihud 1

The table reports the signs of the coefficients of the regressions:LMi (Dependent)=LMi (Column)+MDummiesi . I.e. When AvgRev is regressed onTotal Quantity, the sign of the TotQty coefficient is negative and significant at a1% level.

PRIMARY DEALERS QUOTING OBLIGATIONS

I The Treasure does not directly set specific quoting obligations for theSpecialists (i.e. Primary Dealers) on the market. Indeed, according to thecurrent Italian framework, the Treasure must evaluate the Specialists onquote-driven regulated markets. The banks must therefore fulfill the quotingobligations set up by companies managing the market (MTS). The Treasureevaluation is performed on certain parameters such as quotation quality index(QQI), depth contribution index (DCI), etc.

I Each instrument is quoted by a number of Market Makers adequate to ensurecompetition

I Each Market Maker is assigned 31 financial instruments, including four indexlinked BTPs, so that each Market Maker shall quote a basket representing thefull yield curve and balanced in terms of liquidity

I Each financial instrument is allocated to at least three Market Makers. Bondsissued during the current month shall be automatically considered asallocated to all Market Makers.

PRIMARY DEALERS QUOTING OBLIGATIONS

I Valuation of Market Makers is based on high-frequency book snapshots, foreach bond, for each dealer. Only proposals for more than 5Me(visible) areconsidered.

I Relative specialists ranking are calculated daily. The ranking for the quotesare weighted by their distance from the best bid- and ask-price. Dealercontinuously quoting the best bid- or ask-price receives the highest score.

I The absence of a market maker from an order book is reflected in theQuotation Quality Index. However, short suspension following trades areallowed.

Market Makers have also privileges:I Exclusive access to re-openings following auctions of medium-long-term bonds

and 6/12-months BOTs for an amount of 10% (25$ for first tranches) of theoffered amount.

I Exclusive access for selection as lead managers of syndicated issuances, asdealers of US dollar benchmark program, as counter-parties for bilateralbuy-back transactions.

I Preference for selection as counter-party in other issuances in foreign currencyand for derivatives transactions.

I Candidate Specialists considered capable of significantly improvingdistribution may be called to participate in syndicated transactions. It is,however, necessary that the performance of these same Candidate Specialistsbe in line with the expectations of the Treasury

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

Economy & Finance

The microstructure of the european sovereign bond market. Loriana Pellizzon. May, 9 2013