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

1. 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 University Marti Subrahmanyam, NYU Stern Davide Tomio, Copenhagen Business School Jun Uno, Waseda University NY-FED seminar. MAY 9, 2013.

2. THE MOTIVATION The European sovereign debt crisis, peaked in the summer of 2011, with bond yields in Italy and Spain hitting 7%. Subsequently, there is growing awareness of the connection between liquidity and credit risk. We investigate this linkage through an analysis of market-maker behavior during times of crisis: How is liquidity aﬀected by a shock to credit risk? How do market-makers react to an unprecedented level of the CDS spread? How eﬀective are ECB interventions in calming down the fears of dealers, particularly market-makers? 1/38

3. THE MOTIVATION OECD Countries by Total Central Government Debt (in B$, OECD 2010): Japan $9465 Poland $237 United States $9035 Portugal $203 Italy $2256 Sweden $172 United Kingdom $2068 Israel $162 France $1755 Australia $125 Germany $1483 Ireland $125 Spain $734 Denmark $123 Canada $584 Switzerland $118 Belgium $456 Norway $111 Greece $455 Finland $100 Netherlands $410 Hungary $96 Korea $329 Czech Republic $72 Turkey $307 New Zealand $41 Mexico $291 Slovak Republic $34 Austria $250 Chile $19 Italy has the largest sovereign bond market in the Euro-zone and the third largest in the world. 2/38

4. THE MICROSTRUCTURE OF THE EUROPEAN SOVEREIGN BOND MARKET A STUDY OF THE EURO-ZONE CRISIS Loriana Pelizzon Venice University & MIT Marti Subrahmanyam NYU Davide Tomio Copenhagen Business School Jun Uno Waseda University

5. THE MOTIVATION The European sovereign debt crisis, peaked in the summer of 2011, with bond yields in Italy and Spain hitting 7%. Subsequently, there is growing awareness of the connection between liquidity and credit risk. We investigate this linkage through an analysis of market-maker behavior during times of crisis: How is liquidity aﬀected by a shock to credit risk? How do market-makers react to an unprecedented level of the CDS spread? How eﬀective are ECB interventions in calming down the fears of dealers, particularly market-makers? 1/38

8. ITALIAN 2- AND 10-YEAR BOND YIELD Time-series of the Italian bond yield for 2- and 10-year maturities. 3/38

9. 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 CDS spread and BTP-Bund spread pattern. 4/38

10. 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

11. THE CONTRIBUTION Focus: Major European Government Debt: Italy Period of ﬁnancial turmoil Findings: 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. Market-makers stop making markets at least temporarily, when the CDS spread widens, both in less-stressful and extreme cases. In particular, primary dealers in the sovereign bond market are more risk averse than CDS market participants. ECB interventions successfully calmed the fear of solvency risk, and hence, improved liquidity as well. Case studies show that big spikes in the bid-ask spread and the drop of market maker participation happen only on the event day, if it was a surprise. It occurs one day before in the case of anticipated events. 6/38

12. LITERATURE: ON AMERICAN TREASURY BOND MARKET On the government bond market: Fleming, Remolona JF ’99: Show the effect of public information releases on the market for US Treasury bonds. Fleming ’03: Analyzes liquidity measures, both trade- and quote-based, and their correlation. The quoted bid-ask spread turns out to be the most efficient measure. Engle, Fleming, Ghysels, and Nguyen ’12: Propose a new class of dynamic order book models. They show that liquidity decreases with price volatility, but increases with liquidity volatility. Goyenko, Subrahmanyam, and Ukhov JFQA’11: Study the determinants of bond liquidity. The illiquidity difference between on- and off-the-run bonds widens during a recession, in a flight-to-liquidity. 7/38

13. LITERATURE: ON THE CRISIS Dick-Nielsen, Feldhuetter, and Lando JFE’12: Analyze the effect of illiquidity on corporate bond yield spreads. During the crisis, the contribution of illiquidity grows, especially for speculative-grade bonds. They show a flight-to-liquidity in the early stages of the crisis. Friewald, Jankowitsch, Subrahmanyam JFE ’12: Show that liquidity effects are more pronounced in periods of financial crises. In a large sample of corporate bonds, they employ a range of liquidity measures, including trade- and quote-based measures, to show that liquidity is priced in bond yield spreads. Cheung, de Jong, Rindi ’05: Study the impact of trading intensity on (trade) prices, narrowing down the sample, and response to large trades. Beber, Brandt, Kavajecz RFS ’08: Disentangle flight-to-liquidity and flight-to-quality focusing on EU debt in 03-04. Investors demand (and pay) for both liquidity and lower credit risk. Both are priced, especially for low-credit countries and in distressed periods. Darbha and Dufour ’12: Analyze the liquidity component of Euro-area sovereign bond yield spreads, using a range of liquidity proxies. Brunnermeier and Pedersen RFS’09: Shows theoretically that a reduction in capital reduces market liquidity, especially if the capital is already low (a nonlinear effect). 8/38

14. 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). Traders conﬁrm similar conditions apply to today’s market share, although detailed market share data are not publicly available. MTS’s (NASDAQ:MTSC) majority shareholder is the LSE. Other shareholders: JP Morgan, Deutsche Bank, BNP Paribas, Citigroup, Goldman Sachs. 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. Updates of the best ﬁve prices on each side and the corresponding aggregated quantity are available on screens to traders, to ensure a linkage between the European and domestic markets. 9/38

15. THE TRADERS AND THE MARKET MAKERS There are two kinds of participants in the market: Primary Dealers: Market-makers Dealers: Price takers The way traders interact is as follow: Market-Makers submit bid- and ask-prices and the quantity they are willing to trade (Proposals). Their quotes (proposals) are iceberg orders. Both other primary dealers and primary dealers can hit/lift a primary dealers’ bid- and ask- quotes (proposals). Price takers can only submit market orders. However, 90% of the trades are initiated by market-makers. 10/38

16. 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. 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). 11/38

19. THE MEASURES THE 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. 12/38

20. EVOLUTION OF THE SINGLE PROPOSALS 5MIN Daily time-series average of number of single proposals per bond, sampled at a 5-min frequency. 13/38

23. THE EXPLANATORY VARIABLES THE RIGHT-HAND SIDE VARIABLES We explain them using the following Maturity: 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 activities Daily Trades: In the cross-sectional analysis, average number of trades per day, per bond. Total Quantity: In the time-series analysis, total quantity traded on the market. We control for the change in Italian Government creditworthiness CDS level: Level of the CDS spread on the 5-year US dollar-denominated CDS on the Italian Sovereign, from Thomson-Reuters-Datastream. 14/38

24. THE DATA Our data covers 148 Italian sovereign bonds traded on the MTS between June 2011 and December 2012 (=404 days). Maturity Group # Bonds Coupon Rate Avg- Maturity 0.25 9 0 0.27 0.50 24 0 0.51 1.00 32 0 1.01 2.00 11 0 2.02 3.00 10 3.20 2.99 5.00 13 3.87 5.03 6.00 13 Floating 6.70 10.00 19 4.44 10.41 15.00 7 4.57 15.71 30.00 10 5.88 30.88 Coupon-Bearing Bonds Non-Coupon-Bearing Bonds 15/38

27. STYLIZED FACTS FOR THE CROSS-SECTION Variable 5th Percentile Median 95th Percentile Amount Issued (Be) 4 12 26 Daily Trades 0.8 2.8 12.2 Daily Quantity (Me) 4 26 85 Daily Revisions (m) 10 28 77 Total Single Proposals 23 27 144 Single Proposals 5min 14 17 20 Revisions per Single Proposal 395 1,076 2.682 Total Quoted Quantity (Me) 77 123 169 Best Quantity 7 12 25 Bid-Ask Spread 0.02 0.25 1.26 Number of trades per bond similar to TRACE. In line with the prior MTS literature. On average, 2.2 revisions per single proposal per minute. Per bond, a revision every second. About 10% of the quoted quantity is at the best price. 16/38

31. STYLIZED FACTS FOR THE TIME-SERIES Variable 5th Percentile Median 95th Percentile Traded Quantity (Be) 1 2 4 Daily Trades 114 260 494 Single Proposals 5min 13 18 20 Revisions per SP 834 1332 2304 Bid-Ask Spread 0.18 0.43 1.3 CDS spread 179 427 550 ∆CDS -24.3 0.3 25.7 Median market daily volume is 2 billion e. US treasury market: 500$Billion. US muni: 15$Billion. Similar for US securitized ﬁxed income (structured product) market. 17/38

32. STYLIZED FACTS FOR THE TIME-SERIES Variable 5th Percentile Median 95th Percentile Traded Quantity (Be) 1 2 4 Daily Trades 114 260 494 Single Proposals 5min 13 18 20 Revisions per SP 834 1332 2304 Bid-Ask Spread 0.18 0.43 1.3 CDS spread 179 427 550 ∆CDS -24.3 0.3 25.7 Median market daily volume is 2 billion e. US treasury market: 500$Billion. US muni: 15$Billion. Similar for US securitized ﬁxed income (structured product) market. 17/38

33. THE CROSS-SECTIONAL ANALYSIS THE REGRESSION We estimate the following cross-section regression, using time-series averages: Coupon: LMi =β1 + β2AmountIssuedi + β3Daily Tradesi + + β4CouponRatei + β5−8MaturityDummiesi + + + β9 Time to Maturity Maturity i + β10 Time to Maturity Maturity i 2 + i Investigate whether our Liquidity Measures can be explained by (and how they vary across) product characteristics and trading activity variables 18/38

34. THE CROSS-SECTIONAL ANALYSIS THE RESULTS FOR THE SPREADS Variable Quoted Spread Effective Spread AmountIssued −0.009*** −0.004** Daily Trades −0.03*** −0.008*** CouponRate 0.009 0.009 Maturity3 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 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. Bid-ask spread grows from issuance, peaks at one-fourth of total maturity, and then decreases until maturity. Reversed U-Shape Larger issues have a smaller bid-ask spread. Longer Maturities have significantly larger spreads. Endogeneity of the trading decision. 19/38

38. THE CROSS-SECTIONAL ANALYSIS THE RESULTS FOR THE QUOTE-BASED MEASURES Variable Revisions Single Prop Qty at Total Per SP 5 min Best Quantity AmountIssued −22.25** −0.03 0.411 1.221 Daily Trades −80.225*** 0.174*** −0.095 −0.946* CouponRate 36.01 0.089 0.75 1.732 Maturity3 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 0.987 Quote-based measures are U-shaped in maturity. Revision per SP is an exception. Quote-based measures show the negative relationship between liquidity and maturity. Single Prop 5 min is an exception. Bid-ask Spread increases while Quoted Quantity decreases → Unequivocally lower liquidity. Revision per Single Proposal positively depends on maturity. 20/38

43. THE TIME-SERIES ANALYSIS THE REGRESSION We estimate the following time-series regression, using “across-bonds” averages: ∆LMt = β0 + β1∆CDSt + β2 (∆CDSt )2 + β3TradedQuantityt + t Investigate how overall-market liquidity measures change, when the CDS spread changes. Back to the CDS graph Brunnermeier and Pedersen’s (BP) model implies that the effect of speculative capital on market liquidity is highly nonlinear: a marginal change in capital has a small effect, when speculators are far from their constraints, but a large effect when they are close to their constraints. In our study, the CDS spread is used to assess both credit and funding constraints faced by primary dealers BP assume that speculators provide market liquidity in keeping the ratio of illiquidity to margin constant across assets. They optimally invest in securities that have the greatest expected profit per capital used. Not a valid assumption for MTS: Market-makers are assigned bonds exogenously. 21/38

44. THE TIME-SERIES ANALYSIS THE RESULTS FOR THE SPREADS Variable Quoted BA Eﬀective Spread 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 Positive convex relationship between ∆CDS and Quoted BA Spread. Similar result for the Eﬀective Spread. 22/38

45. THE TIME-SERIES ANALYSIS THE RESULTS FOR THE SPREADS Variable Quoted BA Eﬀective Spread 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 Positive convex relationship between ∆CDS and Quoted BA Spread. Similar result for the Eﬀective Spread. 22/38

46. THE TIME-SERIES ANALYSIS THE RESULTS FOR THE QUOTE-BASED MEASURES Variable Revision SingleProp Qty Total per 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 −0.9816 R2(N=404) 0.0435 0.0648 0.0239 0.0676 Negative convex relationship between ∆CDS and Single Prop 5min: When credit risk is high, the number of market makers diminishes. Similar result for the Total Quoted Quantity BP predicts that when funding liquidity is tight, traders become reluctant to take on positions. Revision per Single Proposal depends solely on the Traded Quantity When trading interest is high, market-makers update quotes more often. 23/38

50. THE TIME-SERIES ANALYSIS SUBSAMPLE: 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 Variable Quoted Spread Effective Spread 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 when splitting the sample between On-the-Run and Off-the-Run bonds. 24/38

51. THE TIME-SERIES ANALYSIS SUBSAMPLE: SUB-PERIODS Until December 2011 Variable Quoted Spread Eﬀective Spread Intercept −0.0588 * −0.0124 * ∆CDS 0.0039 ** 0.0008 ** ∆CDS2 0.0001 ** 0.00003** ∆TradedQuantity −0.0494 ** −0.0155 *** R2 0.1563 0.1815 N 151 151 From January 2012 Variable Quoted Spread Eﬀective Spread Intercept −0.0131 *** −0.0050 * ∆CDS 0.001 ** 0.0006 ** ∆CDS2 0.00005*** 0.00002* ∆TradedQuantity 0.0061 −0.0024 R2 0.07786 0.08069 N 253 253 Results hold when splitting the sample between pre- and post-ECB intervention periods. 25/38

52. THE CASE STUDY THE SETTING We calculate the Abnormal Liquidity Measure for bond i on day t around event d. ALMdit = LMdit − CLMdi CLMdi The event days are those when the top 1% and bottom 1% CDS changes (in our sample) took place (8 days). For a 8-day window around each event, we calculate the ALMdit for bond i. CLMdi is the Comparison Liquidity Measure, which we deﬁne as the median of LMd−9,i , LMd−10,i ,...LMd−19,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 26/38

53. THE CASE STUDY THE HYPOTHESES When credit risk jumps, market liquidity suddenly dries up: Market makers increase the quoted and eﬀective spread, while continuing to provide liquidity. Market makers stop making markets and wait until uncertainty is reduced. Once uncertainty is eliminated, they resume market making. Each market maker reduces his position as a liquidity provider but remains “at market” to provide liquidity (panel analysis). To the Event Days 27/38

54. THE CASE STUDY QUOTED AND EFFECTIVE SPREAD Quoted Bid-ask Spread. 7 out of 8 positive and signiﬁcant tests. 130% increase in the quoted bid-ask spread. Increase lasts up to day +1. Eﬀective Spread. Same results as for the quoted spread. Higher quoted spread translates into higher transaction costs for liquidity demanders. 28/38

55. THE CASE STUDY AVERAGE REVISION AND SINGLE PROPOSALS Average Revisions per Single Proposal. Consistently higher in the post-event window. Single Proposal 5min. Market makers withdraw from the market on day 0. Their presence is restored on day +2. 29/38

56. THE GRANGER CAUSALITY In order to establish: whether the ECB intervention had an effect on the effect of the CDS market on the liquidity supply, 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 CDS spread time-series: ∆LMt ∆CDSt = KLM KCDS + a111 a121 a211 a221 ∆LMt−1 ∆CDSt−1 + a112 a122 a212 a222 ∆LMt−2 ∆CDSt−2 + a113 a123 a213 a223 ∆LMt−3 ∆CDSt−3 + · · · + a11P a12P a21P a22P ∆LMt−P ∆CDSt−P + LMt CDSt And we verify the previous statement by testing for: a12p = 0 before and after December 2011. a21p = 0 before and after December 2011. 30/38

57. THE GRANGER CAUSALITY Brunnermeier and Pedersen shows that, when funding liquidity is tight, traders become reluctant to take on positions. ECB interventions should ease funding liquidity: they affect the primary dealers’ appetite for liquidity provision. Sample Caused Causing Significance All CDS Bid-Ask Spread * All Bid-Ask Spread CDS *** Up to November 2011 CDS Quoted Spread Up to November 2011 Quoted Spread CDS *** From January 2012 CDS Quoted Spread From January 2012 Quoted Spread CDS All CDS Quantity at Best All Quantity at Best CDS ** Up to November 2011 CDS Quantity at Best Up to November 2011 Quantity at Best CDS ** From January 2012 CDS Quantity at Best From January 2012 Quantity at Best CDS Quoted spread (quantity at best) is Granger-caused by CDS. Relationship holds only until November 2011. From January 2012, the relationship is not significant. 31/38

61. THE PANEL ANALYSIS THE EQUATION We estimate the following panel regression: ∆LMit =β1∆LMit−1 + β2 Time to Maturity Maturity it + β3DummyTradeit +β...Below500t · MaturityDummyi · ∆CDSt +β...Above500t · MaturityDummyi · ∆CDSt + ci + it where ∆LMit is the change in the liquidity measure for bond i on day t. ∆CDSt is the change in CDS from day t − 1 to day t. DummyTradeit equals 1, if bond i traded on day t. 32/38

62. THE PANEL ANALYSIS THE RESULTS FOR THE SPREAD Variable Quoted BA Effective Spread 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 Yes R2 0.20 0.19 N 21127 21083 Changes in CDS have a different effects on liquidity, conditional on the level of the CDS spread. The larger the increase in CDS, the larger the increase in illiquidity. The relative sensitivity of the 5- and 10-year bond Quoted Spread is smaller than for the other maturities. 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. Similar results for the Effective Spread, i.e., conditional on trading. 33/38

67. THE PANEL ANALYSIS THE RESULTS FOR THE QUOTE-BASED MEASURES Variable Revision SingleProp Qty Total per SP 5 Min at Best Quoted Qty ∆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 Yes R2 0.2043 0.0570 0.1558 0.1132 N 21127 21127 21127 21127 Primary Dealers update 30- and 15-year bond quotes less frequently Primary Dealers update 5-year bond quotes more frequently. Selling interest from investors Single Proposals 5min steadily decreases for all maturities, more so for high CDS levels. 34/38

71. THE PANEL ANALYSIS THE RESULTS FOR THE SPREAD: UNTIL DECEMBER 2011 Variable Quoted BA Eﬀective Spread Spread ∆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 7668 R2 0.245 0.063 35/38

72. THE PANEL ANALYSIS THE RESULTS FOR THE SPREAD: FROM JANUARY 2012 Variable Quoted BA Eﬀective Spread Spread ∆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 13415 R2 0.163 0.0546 36/38

73. THE CONCLUSIONS Non-linear relationship between credit risk and market-wide liquidity is confirmed in our empirical examination. When credit risk rises, illiquidity spreads at a much faster pace. This results in a jump in bond yields. Effects of CDS spread changes to illiquidity are more prevalent and persistent among bond maturities when the CDS level rises above 500 bp. Primary dealers stop making markets, at least temporarily, when the CDS spread widens, both in less stressful and in extreme cases. Case studies shows that the big spike in the bid-ask spread, and the consequent drop in market-maker participation, happens only on the event day. It occurs one day before, in the case of anticipated events. Coverage by market makers does not vary on maturity group, yet their “attention” does. Quotes for bonds with maturities of less than five years are updated more frequently. Market-makers pay highest attention to the 5-10 year bonds at the crisis. It indicates that an increasing fear for default of government bonds pushes segments of buy-and-hold investors. This requires further investigation in subsequent research. Overall, these findings are consistent with big spikes in yield observed during the Euro-zone financial crisis. 37/38

74. UPCOMING PROJECTS Further Research: Investigate credit risk further by separating illiquidity eﬀects in the CDS price. Separate Eurozone credit risk from Italian sovereign credit risk. Model and characterize market maker behavior. Examine the impact of news on liquidity during the ﬁnancial crisis. Investigate the relationship between government debt issuance (auctions) and secondary market liquidity. 38/38

75. Thank you for your attention!

76. APPENDIX GRAPHS TS Volume TTM-Spread Proposals Case Study Intraday Quantity Intraday Quantity at Best Intraday Spread Intraday Volume Time-Series Quantity Time-Series Amihud and Roll Quadratic Delta Quotes Updates An Event Example TABLES TS Logvar CS Logvar Panel Logvar Event Days Panel with different Threshold Regression LM on LM NOTES

77. EVOLUTION OF THE VOLUME Time-series daily number of trades (RHS axis) and traded quantity (LHS axis, in Be)

78. TIME-TO-MATURITY/SPREAD RELATION Bid-ask spread*Time-to-Maturity (time-series averages, 0=Maturity Date, coupon-bearing bonds) Back to Regression

79. PROPOSALS DURING THE CASE STUDY Single Proposals 5min and Quoted Quantity Around Berlusconi’s Resignation

80. INTRADAY QUOTED QUANTITY EVOLUTION Intraday evolution of Quoted Quantity and Single Proposal

81. INTRADAY EVOLUTION OF QUANTITY AT THE BEST PRICE Intraday evolution of Quantity at the Best Bid and Ask

82. INTRADAY EVOLUTION OF QUOTED SPREAD Intraday Evolution of the Quoted Bid-Ask Spread, averaged through days and bonds

83. INTRADAY EVOLUTION OF TRADED QUANTITY AND TRADES Intraday evolution of traded quantity and trades.

84. TIME-SERIES EVOLUTION OF QUOTED QUANTITY Time-series evolution of total quoted bid- and ask-quantity.

85. TIME-SERIES EVOLUTION OF THE AMIHUD AND ROLL MEASURES Time series evolution of the Amihud and Roll measures.

86. QUADRATIC DELTA Graphic rendition of time-series parameters for the bid-ask spread and normalized distribution of delta.

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

88. QUADRATIC DELTA Empirical distribution of Delta

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

90. A FLAVOR... MARKET CHARACTERISTICS AROUND BERLUSCONI’S RESIGNATION Market-wide bid-ask spread and the level of CDS spread (right axis) around Berlusconi’s resignation.

91. THE TIME-SERIES ANALYSIS THE RESULTS FOR THE MEASURES Variable Log Amihud Roll Var 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 Log var grows in the square of the change of the CDS, thus, regardless of the sign

92. THE TIME-SERIES ANALYSIS THE RESULTS FOR THE MEASURES Variable Log Amihud Roll Var 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 Log var grows in the square of the change of the CDS, thus, regardless of the sign

93. THE CROSS-SECTIONAL ANALYSIS THE RESULTS FOR THE MEASURES Variable Log Amihud Roll Var Measure Measure Intercept −15.25*** −0.61 0.0449 AmountIssued 0.05*** 0.09* −0.0018 Daily Trades −0.13*** −0.33*** −0.0031*** CouponRate 0.15 −0.24 −0.0017 Maturity5 −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 The Amihud and Roll measures show similar results to those for the bid-ask spread They are poor measures (Log) Variance of mid-quotes shows few signiﬁcant regressand.

94. THE RESULTS FOR OTHER MEASURES THE RESULTS FOR THE MEASURES Variable Log Amihud Roll Var Measure Measure ∆LMit−1 −0.4293*** −0.4371*** −0.07*** TTM/Maturity 0.1645*** 0.4924 0 DumTrades 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 Yes R2 0.20 0.22 0.01 N 19369 6366 6374 Reduction in sample size for Amihud and Roll Measure Log Var indicates that prices change more often when CDS levels are high. The change is negatively proportional to maturity.

97. TIME-TO-MATURITY/SPREAD RELATION Date ∆CDSt CDSt August 08, 2011 -49.47 336.21 September 20, 2011 53.90 502.22 September 27, 2011 -51.77 445.77 October 27, 2011 -51.04 402.40 November 01, 2011 77.53 517.06 November 09, 2011 50.33 564.64 December 08, 2011 52.58 524.44 June 29, 2012 -49.26 480.99 Back to the Analysis

98. PANEL WITH DIFFERENT THRESHOLD Variable Spread Sig AvgRev Sig Lag∆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

99. CROSS-SECTIONAL REGRESSION OF LIQUIDITY MEASURE ON LIQUIDITY MEASURE Dependent Eff. Avg SP Qty Tot Log Amihud Roll Spread 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 *** 1 SP5m -1 *** -1 *** -1 1 1 QtyBest 1 *** -1 -1 -1 TotQty -1 -1 * -1 LogVar 1 *** 1 Amihud 1 The table reports the signs of the coefficients of the regressions: LMi (Dependent)=LMi (Column)+MDummiesi . I.e. When AvgRev is regressed on Total Quantity, the sign of the TotQty coefficient is negative and significant at a 1% level.

100. PRIMARY DEALERS QUOTING OBLIGATIONS The Treasure does not directly set specific quoting obligations for the Specialists (i.e. Primary Dealers) on the market. Indeed, according to the current Italian framework, the Treasure must evaluate the Specialists on quote-driven regulated markets. The banks must therefore fulfill the quoting obligations set up by companies managing the market (MTS). The Treasure evaluation is performed on certain parameters such as quotation quality index (QQI), depth contribution index (DCI), etc. Each instrument is quoted by a number of Market Makers adequate to ensure competition Each Market Maker is assigned 31 financial instruments, including four index linked BTPs, so that each Market Maker shall quote a basket representing the full yield curve and balanced in terms of liquidity Each financial instrument is allocated to at least three Market Makers. Bonds issued during the current month shall be automatically considered as allocated to all Market Makers.

101. PRIMARY DEALERS QUOTING OBLIGATIONS Valuation of Market Makers is based on high-frequency book snapshots, for each bond, for each dealer. Only proposals for more than 5Me(visible) are considered. Relative specialists ranking are calculated daily. The ranking for the quotes are weighted by their distance from the best bid- and ask-price. Dealer continuously quoting the best bid- or ask-price receives the highest score. The absence of a market maker from an order book is reflected in the Quotation Quality Index. However, short suspension following trades are allowed. Market Makers have also privileges: 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 the offered amount. Exclusive access for selection as lead managers of syndicated issuances, as dealers of US dollar benchmark program, as counter-parties for bilateral buy-back transactions. Preference for selection as counter-party in other issuances in foreign currency and for derivatives transactions. Candidate Specialists considered capable of significantly improving distribution may be called to participate in syndicated transactions. It is, however, necessary that the performance of these same Candidate Specialists be in line with the expectations of the Treasury

102. 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

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

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