multimarket trading and corporate bond liquidity

Journal of Banking & Finance 36 (2012) 2110–2121

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Journal of Banking & Finance

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Multimarket trading and corporate bond liquidity

Lubomir Petrasek ⇑Smeal College of Business, Pennsylvania State University, University Park, PA 16802, USA

a r t i c l e i n f o a b s t r a c t

Article history:Received 8 September 2011Accepted 15 March 2012Available online 23 March 2012

JEL classification:G15G12F36

Keywords:Corporate bondsLiquidityInternational financial markets

0378-4266/$ - see front matter � 2012 Elsevier B.V. Ahttp://dx.doi.org/10.1016/j.jbankfin.2012.03.015

⇑ Tel.: +1 814 865 0581.E-mail address: [email protected]

Global bonds are international securities traded and settled efficiently in multiple markets. This paperexamines global bonds to evaluate the effects of multimarket trading on corporate bond liquidity andpricing. The results show that global bonds are significantly more liquid than similar-sized domesticbonds of the same issuers, and their liquidity advantage is reflected in higher market valuations. Thesefindings support microstructure models that predict a positive relation between the number of potentialinvestors and liquidity in over-the-counter markets, and help explain the increasing use of global bondsby corporate issuers.

� 2012 Elsevier B.V. All rights reserved.

1. Introduction bond liquidity and pricing. It examines global bond liquidity and

Rather than issuing bonds in domestic markets, many of theworld’s largest corporations have recently started to issue globalbonds. Global bonds are offered simultaneously to investors inthe two major markets for dollar-denominated debt, namely theUS bond market and the overseas market known as the Eurobondmarket. Unlike domestic bonds, global bonds are designed for mul-timarket trading. These bonds include features that facilitate theirtrading, clearing, and settlement in the US bond market, the Euro-bond market, as well as between markets. Global bonds have be-come the debt instrument of choice for large corporate issuers inrecent years, and corporate global bond issuance accounted formore than 80% of the total US-dollar denominated corporate bondissuance in 2009 (see Fig. 1).

Despite the increasing importance of global bonds, the effects ofmultimarket trading on corporate bond liquidity and pricing arenot well understood. Miller and Puthenpurackal (2005) study glo-bal bond offerings from the issuer’s perspective, and find that firmscan lower their cost of debt by issuing global rather than domesticbonds. However, the benefits of global bonds from the investor’sperspective have not been previously documented. Not much isknown about the trading, liquidity, and pricing of global bonds insecondary markets, and the effects of their multimarket tradingon liquidity. The present paper provides new evidence from sec-ondary markets on the effects of multimarket trading on corporate

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transaction prices in secondary markets, and compares them withthe liquidity and prices of bonds issued by the same corporationsin the US domestic market.

Global bonds have key similarities when compared with USdomestic bonds. They are registered with the SEC, have similarindentures to US bonds, and pay interest semiannually. The dis-tinctive property of global bonds is their multimarket trading. Theyare designed to trade simultaneously in the US bond market andthe Eurobond market, and have features that minimize cross-mar-ket transaction costs. Multimarket trading could be a source of va-lue to bondholders because it improves corporate bond liquidity.Specifically, by virtue of trading in several markets, global bondshave the potential to reach a wider international investor baseand have a greater number of dealers. Therefore, global bonds be-come more liquid than similar domestic bonds. Since prior re-search shows that liquidity has a large positive effect oncorporate bond prices,1 multimarket trading could affect corporatebond valuations.

This paper examines the effects of multimarket trading oncorporate bond liquidity and pricing using a sample of 930 globaland domestic bonds. To explore these effects, I compare secondarymarket yields of global and domestic bonds issued by the sameobligor. Transactions prices in secondary markets for both US andglobal bonds are obtained from TRACE.2 Next, I supplement the

1 See, e.g. Longstaff et al. (2005), Chen et al. (2007), and Bao et al. (2011).2 TRACE is the Trade Reporting and Compliance Engine, sponsored by the US

Financial Industry Regulatory Authority (FINRA).

http://dx.doi.org/10.1016/j.jbankfin.2012.03.015

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http://dx.doi.org/10.1016/j.jbankfin.2012.03.015

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98 99 00 01 02 03 04 05 06 07 08 09

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enta

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Global bonds U.S. domestic bonds

Fig. 1. Corporate issuance of global and US bonds (% of debt issued). The figure plotsthe proportions of global and domestic issuance of US dollar-denominatedcorporate debt from 1998 to 2009. Global bonds are designed for trading in theUS bond market and in the international market known as the Eurobond market,whereas US bonds are designed for trading only in the US domestic bond market.The figure includes all public issues of straight corporate debt denominated in USdollars and registered in the US The source of the data is SDC.

4 FINRA is the US Financial Industry Regulatory Authority, formerly the NationaAssociation of Securities Dealers (NASD).

L. Petrasek / Journal of Banking & Finance 36 (2012) 2110–2121 2111

TRACE data with information on trading activity in the Eurobondmarket from TRAX,3 compute multiple trade-based measures ofcorporate bond liquidity, and test whether global bonds are more li-quid than comparable domestic bonds. Finally, I examine whetherliquidity can explain the yield spreads between global and domesticbonds.

The methodology also represents an improvement over previ-ous studies of corporate bonds. Global bonds are typically issuedby large corporations that have multiple debt issues outstandingin the domestic market as well as the global market. This allowsme to examine a matched sample of global and domestic bonds is-sued by the same companies, and fully control for the issuer creditrisk when analyzing corporate bond liquidity and prices.

The results support the hypothesis that multimarket tradingimproves corporate bond liquidity. Compared to the outstandingdomestic bonds of the same issuers, global bonds are significantlymore liquid. Even after controlling for well-known determinants ofcorporate bond liquidity, such as bond age and issue size, globalbonds exhibit greater trading volumes in the US bond marketand in the Eurobond market, trade more frequently, and theirprices are less volatile and less strongly affected by large trades.Several measures of transaction costs, including the measure ofprice impact proposed by Amihud (2002), and the measure of pricereversals suggested by Roll (1984) and Bao et al. (2011), are signif-icantly smaller for global bonds than for domestic bonds. Further-more, the liquidity advantage of global bonds is priced. When twobonds of the same issuer, one global and one domestic, trade on thesame day, the yield on the global bond is on average about 20 basispoints lower. The yield spread between global and domestic bondsis greater for speculative grade bonds than for investment gradebonds, and it increases during liquidity crises. Finally, I find thatthe trade-based liquidity measures can explain a large part of theyield difference between global and domestic bonds, and up to16% of the cross-sectional variation in yield spreads between dif-ferent bonds of the same company.

Overall, the empirical findings in this paper show a strong rela-tion between multimarket trading and corporate bond liquidity.Bonds that can be traded and settled efficiently in multiple marketsexhibit a significant liquidity advantage over domestic bonds is-sued by the same firms. These findings are consistent with micro-

3 TRAX is the trade matching and regulatory system for the Eurobond marketsponsored by the International Capital Markets Association (ICMA).

5 ICMA is the International Capital Market Association, formerly the Association oInternational Bond Dealers (AIBD).

6 The Tax Equity and Fiscal Responsibility Act of 1982 imposes tax sanctions onboth the issuers and the holders of anonymous bearer instruments.

,

structure models that predict a positive relation between the num-ber of potential investors and liquidity in over-the-counter mar-kets (e.g. Duffie et al., 2005, 2007). Furthermore, the liquidityadvantage of global bonds is priced, and can explain the tendencyof large corporations to issue global rather than domestic bonds.

The remainder of the paper is organized as follows. Section 2provides a brief description global bonds and their multimarkettrading. Section 3 develops testable hypothesis about the relationbetween multimarket trading and corporate bond liquidity. Sec-tion 4 describes the data. Section 5 shows the empirical results,including the analysis of transaction prices and liquidity. Section6 provides concluding remarks.

2. Global bonds and multimarket trading

The market for publicly traded US dollar-denominated corpo-rate bonds has traditionally been divided between two financialcenters: the US bond market and the Eurobond market. Tradingin both markets takes place primarily over-the-counter betweenbond dealers and institutional investors. However, several legaland institutional differences between the two markets preventtheir full integration.

Most of the trading activity in the US corporate bond market in-volves a relatively small number of dealers (Schultz, 2001). All USbond dealers are required to be members of FINRA,4 and must re-port trades to the Trade Reporting and Compliance Engine (TRACE)sponsored by FINRA. Trading is concentrated in New York tradinghours. Trades are settled through the Depository Trust Company(DTC). In general, the bonds traded in this market must be registeredwith the Securities and Exchange Commission (SEC) under the Secu-rities Act of 1933. The bonds are also in registered form, meaningthat bondholders’ names are entered in a register kept by the issuer.US domestic bonds are structured to meet US regulatory require-ments and appeal primarily to US investors.

The Eurobond market is an international bond market for med-ium and long-term debt. Most Eurobond dealers are members ofICMA,5 a self-regulatory organization for the Eurobond market. Trad-ing is concentrated in London trading hours. Trades are settledthrough Clearstream or Euroclear. In contrast to US bonds, Eurobondsare not registered with the SEC or other national regulatory authori-ties. In addition, Eurobonds are anonymous bearer securities. How-ever, US tax law penalizes the holders of bearer securities such asEurobonds,6 which makes them unattractive to US investors. To sat-isfy US regulatory requirements, Eurobonds are not offered to USinvestors in the primary market, and they are ‘‘locked up’’ for 40 daysafter issuance to be sold exclusively to non-US investors (see, e.g.Wood, 2008). Therefore, Eurobonds are rarely held by US investors,who prefer global bonds to gain exposure to the Eurobond market.

Global bonds are designed for trading in both the US and Euro-bond markets. The first global bonds were issued by the WorldBank in 1989. The World Bank observed yield disparities on its dol-lar-denominated debt outstanding in the Eurobond market and inthe US market, and issued the first global bonds to take advantageof these disparities. By virtue of trading in both markets, globalbonds were expected to overcome market segmentation and be-come more liquid (Kapur et al., 1997).

Global bonds share many characteristics with US domesticbonds, such as being registered with the SEC and paying semi-an-nual coupon. Their tax treatment is also similar to US domestic

l

f

Table 1Characteristics of global and domestic bond issuers. The table compares thecharacteristics of 219 global bond issuers with the characteristics of 523 firms thatissue bonds only in the US domestic market. Presented are the averages across globaland domestic issuers, and the differences between the characteristics of global anddomestic issuers. The data are obtained from COMPUSTAT. Total assets and marketcapitalization are measured at the end of each fiscal year. Leverage is measured asshort-term and long-term debt divided by end-of-year total assets. Book-to-market iscalculated as the book value of equity divided by market capitalization at the end ofeach fiscal year. Foreign issuers are firms incorporated outside the United States,financial firms have SIC codes in the 6000s, and utilities in the 4900s.

Globalissuers

Domesticissuers

Difference

Total assets ($B) 127.92 29.97 97.95**

Market capitalization ($B) 41.26 10.08 31.18**

Leverage 0.30 0.33 �0.04**

Book-to-market ratio 0.55 0.67 �0.12**

Percentage of foreign issuers (%) 22 20 2Percentage of financial firms (%) 26 25 1

2112 L. Petrasek / Journal of Banking & Finance 36 (2012) 2110–2121

bonds and neither US nor foreign investors can gain a tax advan-tage by investing in global bonds.7 However, global bonds are soldto investors in multiple markets and their features allow both US andEurobond investors to trade these bonds as if they were local secu-rities. Global bonds are structured to clear through several clearingsystems, including DTC and Clearstream or (and) Euroclear. Conse-quently, US investors settle global bond transactions through DTCas they would settle domestic bond transactions, and overseas inves-tors settle global bond transactions through Clearstream or Euroclearas they would settle Eurobond transactions. Cross-market trades inglobal bonds are efficiently settled between the depositories. Thus,non-US investors are more likely to trade global bonds than USdomestic bonds, and global bonds have a larger investor base.

Although the first global bonds were issued by the World Bank,global bonds have recently become the debt instrument of choicefor many large corporate issuers. Fig. 1 compares the proportionsof global and domestic issuance of US dollar-denominated corpo-rate bonds from 1998 to 2009. Included are all public issues ofstraight corporate debt denominated in US dollars and registeredfor public trading in the US. The figure reveals a large increase inthe issuance of global bonds compared to US domestic bonds overtime. Whereas global bonds accounted for less than 10% of the totalproceeds from publicly traded, US-dollar denominated corporatebond issuance in 1998, they accounted for more than 80% in 2009.

3. Multimarket trading and liquidity

The most important channel through which multimarket trad-ing can increase corporate bond value is liquidity. Global bondscould be more liquid because they have a greater number of deal-ers and a wider investor base. For one thing, both the dealers in theUS market and the dealers in the Eurobond market stand ready tobuy and sell global bonds. The microstructure models of Demsetz(1968) and Ho and Stoll (1983), among others, predict a positiverelation between the number of dealers making the market in a gi-ven security and its liquidity. A greater number of dealers leads tomore competitive dealer markets (Demsetz, 1968), and facilitatesinventory risk management through inter-dealer trading (Ho andStoll, 1983; Reiss and Werner, 1998). Lower inventory risk andmore intense competition among market makers, in turn, reducetransaction costs.

Liquidity may also be greater for bonds with a wider investorbase. Since global bonds can be marketed to investors in both theUS market and the Eurobond market, their pool of potential inves-tors is larger. Duffie et al. (2005, 2007) develop a model in whichtransactions costs and liquidity in over-the-counter markets, suchas the corporate bond market, depend on the number of potentialinvestors. Their model predicts that illiquidity discounts are smal-ler if investors have access to multiple market makers, and thenumber of qualified investors is larger. Thus, global bonds thathave an international investor base and a large network of dealersshould be more liquid than domestic issues.

In addition, global bonds are often placed with investors in mul-tiple markets, allowing them to have a greater issue size. However,prior research on the relation between bond issue size and itsliquidity is inconclusive. On the one hand, Longstaff et al. (2005),Edwards et al. (2007), and Mahanti et al. (2008) find a positive rela-tion between issue size and liquidity. On the other hand, Crabbeand Turner (1995) contend that large and small bonds issued bythe same borrowers are close substitutes. Chen et al. (2007) findlittle evidence of the importance of the outstanding principal

7 Global and domestic bonds held by US residents are taxed equally. Foreigninvestors in either global or domestic bonds issued after 1984 are exempt from the USwithholding tax (see IRS Publication 515 (2011), Withholding of Tax on NonresidentAliens and Foreign Entities).

amount in explaining corporate bond liquidity. I contribute to thisdebate and distinguish between the effects of issue size and multi-market trading in the analysis of global bond liquidity and pricing.

Several recent papers find a positive relation between corporatebond prices and their liquidity (e.g. Longstaff et al., 2005; Chen etal., 2007; Bao et al., 2011). For instance, Bao et al. (2011) argue thatilliquidity is as least as important in explaining cross-sectional dif-ferences in corporate bond yield spreads as credit risk. In times ofcrisis, the contribution of illiquidity to yield spreads can over-shadow credit risk. These findings imply that global bonds maycommand a liquidity premium relative to domestic bonds, in par-ticular during liquidity crises.

4. Data

The data for this study come from several sources. The SDCdatabase provides information on new issues, including bond type,issue size, and domestic and foreign issuance proceeds. I obtaininformation on all corporate bond issues that are offered by publiccorporations, denominated in US dollars, and publicly traded in theUS bond market, the Eurobond market, or both markets (globalbonds). In addition, I keep only bonds that are straight, senior,non-convertible, non-asset backed, and without credit enhance-ments. Sample bonds are issued between January 1998 andDecember 2008, and have a maturity of 5 years or more at the timeof issuance. Short-term notes are excluded because they are notcomparable with longer-term bonds.

Table 1 compares the sample of 219 global bond issuers with523 firms that issue bonds only in the US domestic market duringthe sample period 1998–2009. Global bond issuers have, on aver-age, total assets that are four times larger than those of domesticissuers ($128 billion vs. $30 billion). The average market capitaliza-tion of global bond issuers is also four times greater ($41 billion vs.$10 billion), and global bond issuers have lower leverage and lowerbook-to-market ratios. These characteristics suggest that the creditrisk and liquidity of bonds of global and domestic issuers are notcomparable. Therefore, I confine the analysis to bonds of globalissuers. Global bond issuers tend to be well-known corporationswith multinational operations and a global reputation. AppendixA provides the names of the 45 most important issuers of globalbonds. The list is comprised of large financial firms such as MorganStanley, utilities such as Dominion Resources Inc., and globalindustrial companies such as Ford Motor Company or Caterpillar

Percentage of utility firms (%) 21 21 0

No. of issuers 219 523

** Differences marked with are significant at the 5% levels.

Table 2Summary statistics for the global and domestic bond sample. The table reports summary statistics for the sample of global and domestic bonds of global bond issuers. Informationon new bond issues, including bond type, total principal issued, and bond placements, is from the SDC data base. Total principal is the principal amount placed in all markets.Foreign principal as % of total principal shows the percentage of the total principal issued that is initially placed with non-US investors. Bond characteristics and bond ratinghistory are from the FISD database. Trading yields and yield spreads are derived from secondary market transaction prices reported on TRACE. The numbers reported in the tableare the means (medians) of individual bond averages.

Sample mean Sample median

Global Domestic Difference Global Domestic Difference

Total principal ($M) 1652.42 712.08 940.34** 1197.25 462.05 735.20**

Foreign principal as % of total principal 32.37 10.54 21.83** 39.44 0.00 39.44**

Trading yield (%) 5.95 6.10 �0.16* 5.79 5.93 �0.14*

Trading yield spread (%) 2.28 2.43 �0.15* 1.87 2.05 �0.18**

Time to maturity (yrs when traded) 10.51 10.58 �0.07 7.82 7.05 0.77Age (yrs when traded) 1.37 3.23 �1.86** 0.86 2.66 �1.80**

Coupon (%) 5.72 5.85 �0.13* 5.73 5.77 0.04Percentage of callable bonds (%) 63 68 �4 100 100 0Percentage of inv. grade bonds (% when traded) 85 84 1 100 100 0

No. of sample trades per bond 736 456 280** 296 99 197**

No. of bonds (930) 480 450 – 480 450 –No. of issuers (135) 135 135 – 135 135 –

* Differences marked with are significant at the 10% levels.** Differences marked with are significant at the 5% levels.

9 Observations that are more than three standard deviations away from aneighborhood of the 30 nearest valid observations are considered to be outliersThe tests are not sensitive to the inclusion of these observations.

10


Inc. Overall, 2175 global and US bonds were issued by 219 globalbond issuers between January 1998 and December 2008.

The final sample is comprised of a subset of bonds that are ac-tively traded in US secondary markets. The source of secondarymarket prices for global and US bonds is the Trade Reporting andCompliance Engine, commonly referred to as TRACE. Since June2002, all broker-dealers active in the US market have an obligationto report transactions in publicly registered corporate bonds toTRACE. Since global bonds are like US public bonds registered withthe SEC, they are subject to TRACE reporting and dissemination.Eurobonds, in contrast, are not subject to TRACE reporting, andtherefore are not included in the sample. The information dissem-inated by TRACE includes bond CUSIP, transaction price, date, time,and volume. I complement this data with bond descriptive infor-mation and bond ratings from the Fixed Income Securities Data-base (FISD).

The sample of secondary market transactions starts in 2003, thefirst full year of TRACE reporting. It is comprised of a subset of ac-tively traded bonds. Specifically, the analysis requires data on bothglobal and domestic bond transactions from the same day. There-fore, a global (domestic) bond is required to trade on the sameday as another domestic (global) bond of the same issuer to enterthe sample. Further, sample bonds are required to have at least5 years to maturity at the time of trading. There are 930 such bondsissued by 135 issuers; 480 are global bonds and 450 are US domes-tic bonds.

Several filters are applied to the sample trades. First, global(domestic) bond trades must be matched by issuer and tradingday with domestic (global) bond trades to be included in the sam-ple. Further, only institutional-sized trades of 100,000 dollars orlarger are examined. Retail-sized trades are discarded becausetheir transaction costs account for a non-negligible percentage ofthe traded price (Edwards et al., 2007). Nevertheless, all tradesare considered when calculating measures of corporate bondliquidity. In addition, the data are purged of trade reports that weresubject to cancellations or corrections, are missing key informa-tion, include commission in the price, or were entered by multipledealers.8 Next, I remove 3321 trades that appear to be outliers. Theoutliers are identified on the basis of their relative distance from a

8 Dick-Nielsen (2009) argues that transactions with zero returns for consecutivetrades are the result of double reporting in interdealer trading. Failing to removethese duplicates could bias the liquidity measures. Following Dick-Nielsen (2009),remove all reports with zero returns for consecutive trades.

The daily yield curve for constant maturities of 2, 5, 10, and 30 years is obtainedfrom the US Department of Treasury. Linear interpolation is used for each monthwithin the intermediate maturities, and the yield curve is assumed to be flat beyond30 years.

11 The averages are first calculated for each bond across all sample trades and then
I
neighborhood of the nearest valid observations.9 The final sampleconsists of 558,362 trades that take place between January 2003and March 2009.

Table 2 provides summary statistics for the sample bonds. Allthe sample bonds are large issues, but the average global bond is-sue of $1652 million is more than two times larger than the aver-age domestic bond issue of $712 million. This marked difference inissue size is consistent with the finding of Miller and Puthenpurac-kal (2005) that the decision to issue globally is an increasing func-tion of issue size. Foreign placements amount to 32.4% of the totalproceeds for the average global bond, and 10.5% for the averagedomestic bond. The foreign placements for domestic bonds are pri-vate placements. Whereas the median domestic bond involves noforeign placements, 39.4% of the proceeds from the median globalbond come from non-US investors.

Bond prices are transformed into spreads over US Treasuryyields. Specifically, trade prices are first adjusted for accrued inter-est and converted into yields to maturity. The yield spreads arethen calculated by subtracting the nearest corresponding constantmaturity Treasury rates from the yields.10 Table 2 reports the bond-weighted averages of trading yields and yield spreads.11 Tradingyields are 5.95% for the average global bond and 6.10% for the aver-age domestic bond. Trading yield spreads average 2.28% for globalbonds and 2.43% for domestic bonds, but they change greatly overthe sample period. The spreads range from just above 1% in January2003 to more than 6% in September 2008. The summary statisticssuggest that yield spreads tend to be lower for global bonds thanfor domestic bonds, but a simple comparison of yield spreads with-out controlling for issuer and time effects could be misleading.

The summary statistics also indicate that global and US bondsare comparable with respect to their maturity, embedded call op-tions, and ratings. A large part of the sample bonds are callable,and the call option feature must be taken into account in the anal-ysis. It is also important to control for differences in bond age. Glo-

across bonds.

.

Table 3Yield spreads between global and domestic bonds: paired t-tests. The table reports the differences in trading yields between matched pairs of global and domestic bonds. Allbonds are non-callable and matched by issuer. In addition, the bonds in Panel A mature within 2 years from one another. The bonds in Panel B have an issue size within 10% fromone another. The bonds in Panel C are matched by both maturity and size. The yield difference for each bond pair is calculated from all transactions that occur on the same days.Shown is the number of matched pairs, the mean difference in trading yield spreads between global and domestic bonds across the matched pairs, the t-statistic for the meandifference, the median difference in trading yield spreads, and the percentage of bond pairs for which the difference is negative.

No. of matched bond pairs Mean difference T-statistic Median difference Negative difference (% of pairs)

Panel A: Matched by issuer and maturityAll bonds 137 �0.22** �5.31 �0.09** 73Investment grade 132 �0.21** �5.19 �0.09** 75Speculative grade 25 �0.61* �1.82 �0.24* 64

Panel B: Matched by issuer and sizeAll bonds 139 �0.13** �3.43 �0.07** 62Investment grade 136 �0.10** �3.15 �0.07** 63Speculative grade 26 �0.92** �2.17 �0.86** 62

Panel C: Matched by issuer, maturity and sizeAll bonds 59 �0.20** �3.44 �0.08** 69Investment grade 56 �0.18** �3.47 �0.08** 73Speculative grade 13 �1.02 �1.63 �0.86 62

* Mean (median) differences marked with are significant at the 10% levels according to the t-test (Wilcoxon signed rank test).** Mean (median) differences marked with are significant at the 5% levels according to the t-test (Wilcoxon signed rank test).


bal bonds tend to have a lower age (1.37 years) than domesticbonds (3.23 years) because firms are less likely to offer domesticbonds after issuing global bonds (see Fig. 1).

2 One global (domestic) bond can match with two or more domestic (global) bonds.3 Most speculative bonds are issued as investment grade bonds and enter theeculative sample later due to downgrades so the same bond can be in both groups

at different times.

5. Empirical analysis

5.1. Global and domestic bond yields

Prior research shows that global bond offerings are associatedwith lower yields and borrowing costs than comparable domesticofferings (Miller and Puthenpurackal, 2005). However, different of-fer yields of global and domestic bonds do not necessarily implythat secondary market prices also differ. The prices of new corpo-rate bond issues could also be affected by transitory factors such asunderpricing (Cai et al., 2007) or issuance price pressure (Newmanand Rierson, 2004).

To examine whether investors place higher valuations on globalbonds, this section compares the yields to maturity of global anddomestic bonds in secondary markets. When global and domesticbonds of one issuer trade on the same day, their trading yields re-flect the same credit risk. However, the bonds may differ in theirsize, maturity, or embedded call options. I use two methods to con-trol for these characteristics. First, I create a matched sample ofbond pairs that have no call options and are similar in terms ofissue size and maturity. I conduct paired t-tests and Wilcoxonsigned rank tests to examine if these bonds trade at the sameyields. The second method is to estimate panel regressions that re-late yield differentials to differences in bond characteristics.

Matched sample estimation has been widely used to test for dif-ferences in bond prices and transaction costs. I apply the matchedsample approach to test for differences in yields to maturity andliquidity between global and domestic bonds. Specifically, globaland domestic bonds that are non-callable and issued by the samefirms are matched into pairs by term to maturity and/or issue size.For each pair, I calculate the average difference in trading yieldsbetween the global and the domestic bond using only trades thatoccur on the same days. I then compute the mean and median dif-ference across all bond pairs and perform t-tests for the signifi-cance of the mean difference. I also test for differences betweenthe matched pairs using the non-parametric Wilcoxon signed ranktest.

Panel A of Table 3 presents the test results for bonds matchedby issuer and term to maturity. Specifically, the pairs are madeup of one global bond and one domestic bond that mature within

2 years from one another. There are 137 such bond pairs, made upof 139 different bonds12 issued by 23 firms. As Panel A of Table 3shows, global bonds trade on average at yields 22 basis points belowthe yields on domestic bonds of the same issuers with similar matu-rities. The average difference in yields between all pairs of global anddomestic bonds is negative and statistically significant at the 5% le-vel using a paired t-test. The median yield difference of �9 basispoints is also statistically significant using a Wilcoxon signed ranktest. The differences are negative for 73% of the bond pairs.

When the yields of investment grade bonds (132 pairs) andspeculative grade bonds (25 pairs)13 are examined separately, thedifference is greater for speculative grade bonds than for investmentgrade bonds. The average difference between global and domesticbonds is �21 basis points for investment grade bonds compared to�61 basis points for speculative grade bonds. Prior studies show thatilliquidity has a larger impact on the yields of speculative gradebonds than on investment grade bonds (see, e.g. Longstaff et al.,2005; Chen et al., 2007; Mahanti et al., 2008). Therefore, the findingof larger yield differences for speculative grade bonds is consistentwith the liquidity explanation of the spread between global anddomestic bonds.

Panel B of Table 3 reports the results if bonds are matched byissuer and issue size. The bond pairs are selected to have an issuesize within 10% from one another. There are 139 such pairs, madeup of 121 bonds issued by 17 firms. The average yield spread be-tween the global and domestic bonds is �13 basis points, statisti-cally significant at the 5% level using a paired t-test or a Wilcoxonsigned rank test. The spread is larger for speculative grade bondsthan for investment grade bonds. Finally, in Panel C of Table 3,bonds of the same issuers are matched by both time to maturityand issue size. There are 59 possible bond pairs, made up of 78 dif-ferent bonds issued by 16 firms. The mean yield spread betweenglobal and domestic bonds is �20 basis points, and the medianspread is �8 basis points. The mean and median yield spread be-tween global and domestic bonds is negative and significant atthe 5% level.

Bond traders tend to regard the Treasury zero curve as the risk-free zero curve and measure a corporate bond yield spread as thespread of the corporate bond yield over the yield on a similar gov-

1

1

sp

Table 4Yield spreads between global and domestic bonds: panel regressions with issuer/dayfixed effects. The table presents estimates from regressions of trading yield spreads onan indicator variable that equals one for global bonds, the interaction of the globalbond dummy with the speculative grade indicator variable, and several controlvariables. Maturity is the time to maturity and Age is the bond age, both measured inyears at the time of trading. Principal is the natural logarithm of the outstanding bondprincipal. Call option is an indicator variable equal to one if the bond is callable.Liquidity crisis is a dummy variable that equals one if the spread between the 3-month LIBOR and the 3-month Treasury bill rate exceeds 2%. The regressions areestimated using panel data transformed by subtracting issuer/day fixed effects.Robust t-statistics adjusted for clustering by bond are in parentheses.

(1) (2) (3)

Global bond �0.233** �0.109** �0.088**

(�4.42) (�4.08) (�3.05)Speculative � global �0.487** �0.458**

(�2.81) (�2.65)Maturity 0.104** 0.094** 0.094**

(5.59) (6.07) (6.15)Maturity squared �0.002** �0.002** �0.002**

(�4.56) (�4.97) (�5.04)Age 0.029** 0.036** 0.034**

(2.95) (3.81) (3.66)Principal �0.037 �0.041 �0.040

(�0.70) (�0.77) (�0.78)Call option 0.211** 0.173* 0.177**

(2.30) (1.93) (2.07)Liquidity crisis � global �0.378**

(�3.36)

Adj. R2 0.18 0.20 0.21No. of trades 558,362 558,362 558,362No. of bonds 930 930 930No. of issuers 135 135 135

* Coefficients marked with are significant at the 10% levels.** Coefficients marked with are significant at the 5% levels.


ernment bond (Hull et al., 2004). Therefore, Constant MaturityTreasury yields are used as the benchmark rate for corporate bondsthroughout the paper. However, the tests in which bonds arematched by term to maturity (Panel A and Panel C in Table 3) donot require a specification of the benchmark rate. To examinewhether the results are sensitive to the benchmark rate assump-tion, I perform the t-tests in Panel A and Panel C of Table 3 usingbond yields rather than yield spreads. I find that the results usingbond yields (not shown) are virtually identical to those using yieldspreads shown in Table 3 if bonds are matched by term tomaturity.

Paired t-tests provide a simple method to test for differences inyields, but restrict the sample to a small number of non-callablebonds with similar maturities and issue sizes. Next, I estimate pa-nel regressions to examine the full sample of 930 global anddomestic bonds and control for additional bond characteristics.The regression model is as follows:

Spgreadijd ¼ b0 þ b1Glgobalijd þ b02Congtrolsijd þ eijd; ð1Þ

where Spreadijd is the yield spread on the ith issue of firm j traded onday d. Globalijd is a dummy variable set equal to one for globalbonds. Controlsijd is a vector of issue-specific control variables,including the time to maturity measured in years, the square ofthe time to maturity, bond age in years, the natural logarithm ofthe bond principal, and an indicator variable set equal to one ifthe bond is callable.

The set of independent variables includes the time to maturityto control for the term structure of credit risk. The contingent claimapproach to valuing corporate debt pioneered by Merton (1974)predicts that credit risk premiums for investment grade debt areincreasing with term to maturity, but the relation is non-linear.Therefore, the squared term to maturity is also included in theregression. Age and principal are proxies for corporate bond liquid-ity that are not directly related to global bond issuance. Alexanderet al. (2000) and Edwards et al. (2007) show that trading volume ofcorporate bonds declines as they become older and settle intoinstitutional portfolios. Chen et al. (2007), and Bao et al. (2011),among others, show that bond age is positively related to corporateyield spreads. Therefore, I control for bond age at the time of trad-ing. Bond principal has been widely used to proxy for corporatebond liquidity because larger issues tend to trade more frequentlyand have a higher trading volume. The regressions are estimatedon panel data transformed by subtracting issuer/day fixed effects.Specifically, each observation on the ith issue of firm j is trans-formed by subtracting the panel mean for all bonds of firm j tradedon day d. The transformation removes the firm-specific effect thatmay be correlated with the error terms.

Table 4 presents the regression estimates of yield spreads be-tween global and domestic bonds and the robust t-statistics ad-justed for clustering by bond. The main result is presented incolumn (1). The coefficient estimate on the global dummy variablein is �23 basis points, significant at the 5% level, showing that glo-bal bonds trade at lower yields than comparable domestic bondsissued by the same firms. The magnitude of the regression estimateis similar to that from paired t-tests. The specification in column(2) allows for different coefficient estimates for investment andspeculative grade bonds. Consistent with the results from t-tests,the effect of global trading is smaller in absolute value for invest-ment grade bonds (�11 basis points) than for speculative gradebonds (�60 basis points). The difference in coefficient estimatesbetween speculative and investment grade bonds is significant atthe 5% level.

All the control variables have the expected sign. In line withMerton’s (1974) model of the maturity structure of credit risk, timeto maturity has a positive non-linear effect on credit spreads. Bond

age also has a significant positive effect on yields. On average, oneadditional year since issuance increases the required yield by threebasis points. This estimate is consistent with the findings of Chenet al. (2007) and Bao et al. (2011) regarding the effect of age on cor-porate bond yields. Issue size is not significantly related to yieldsafter controlling for other bond characteristics. The contributionof the call option feature to yield spreads is 17–21 basis points.Overall, the regression model explains 18–21% of the differencesin yields between different bonds of the same issuers, and the con-tribution of the global dummy to the R-squared is around 2%.

To better understand the factors that explain the yield spreadbetween global and domestic bonds, I estimate Eq. (1) with yeardummies and an indicator variable for liquidity crises. None ofthe year dummy variables (not reported) is statistically significantwhen interacted with the global bond indicator variable. Column(3) in Table 4 reports the regression results including the indicatorof liquidity crises interacted with the global dummy variable. Aliquidity crisis is said to occur when the spread between the 3-month LIBOR and the 3-month Treasury bill rate (the TED spread)exceeds 2%. This definition of crises corresponds to roughly 5% ofthe sample days, mostly during the second half of 2008 and in2009. The yield spread between global and domestic bonds remainson average negative and statistically significant after accounting forliquidity crises. The average spread is �9 basis points for invest-ment grade bonds and �55 basis points for high yield bonds. How-ever, the spread widens by 38 basis points during crises, and theincrease is statistically significant at the 1% level. These findingssuggest that the price difference between global and domesticbonds is related to liquidity.

In untabulated results, I estimate the yield spread regression inTable 4 on different subsamples. First, all callable bonds are ex-cluded from the analysis. Another test excludes bonds for a periodof 6 months after issuance because new issues are known to bemore liquid than older bonds (see, e.g. Alexander et al., 2000; Chen


et al., 2007; Edwards et al., 2007; Bao et al., 2011). Finally, I excludebonds issued by financial firms and utilities. In all cases, I find thatthe subsample results are not substantively different from thoseusing the entire sample.

5.2. Measures of corporate bond liquidity

A major argument in favor of global bond issuance is greaterliquidity. Liquidity has multiple dimensions, and many alternativemeasures of corporate bond liquidity have been proposed in theliterature.14 I measure liquidity in several ways, including tradingvolume, trading frequency, zero volume days, price volatility, theprice impact of trades, and the autocovariance of daily returns.

The liquidity measures use data from TRACE for the US bondmarket, complemented with additional information from TRAXfor the Eurobond market. The monthly trading volume in the USbond market is computed using all trades on TRACE over a periodof 20 preceding trading days. For confidentiality reasons, TRACEdoes not disseminate the exact trading volume for transactions lar-ger than the cap value of $5 million ($1 million for high yieldbonds). The actual transaction volume is therefore assumed to beequal to the cap value. The monthly trading volume for the Euro-bond market is obtained by multiplying the average daily volumefor the previous month provided by TRAX by 20. In contrast toreporting to TRACE, which is mandatory for all broker-dealers reg-istered in the US, only ICMA members have an obligation to reporttheir trades to TRAX. However, most Eurobond dealers are mem-bers of the ICMA. There is also very little overlap between ICMAmember firms and US bond dealers.15 Therefore, TRAX volume isa reasonable proxy for trading activity in the Eurobond market.

I compute three measures of trading frequency from TRACE: themonthly number of trades, the monthly number of large trades,and the monthly number of zero-volume days counting the dayson which no large trades occur. Large trades are defined as trans-actions of 100,000 dollars or greater. Smaller, retail-sized tradesmay not be indicative of greater liquidity (see, e.g. Edwards et al.,2007). All the measures of trading frequency are counted overthe last 20 trading days preceding each observation.

Price volatility is related to liquidity through dealer inventoryrisk (see, e.g. Stoll, 1978). I compute two volatility measures: themonthly price range as a percentage of the average price, and thecoefficient of variation of the transaction price. The coefficient ofvariation is the monthly standard deviation scaled by the averageprice. Both measures are computed from intraday price changesover the period of 20 trading days preceding an observation, andonly large trades are used in their calculation.

Further, I consider two return-based liquidity measures derivedfrom daily closing prices: the Amihud ratio and the Gamma mea-sure (c). Let Pt denote the closing price on day t, adjusted for theinterest accrued since the last coupon date. Closing prices are ob-tained from the last large transaction on each day. For bonds trad-ing on two consecutive business days, I calculate the dailypercentage return as rt = 100 � (lnPt � lnPt�1). Both the Amihudilliquidity and c are computed only for the subset of bonds with15 or more daily return observations over a 20-day period. Thereare 528 such bonds with 355,357 transactions, and the analysisof return-based liquidity measures is conducted on this subsample.

Liquidity can be defined as the ability to buy or sell an asset inlarge quantity quickly and without affecting the market price. Tomeasure illiquidity as the price impact of trading, I calculate the ra-tio proposed by Amihud (2002):

14 See, e.g., Houweling et al. (2005), Chen et al. (2007), and Bao et al. (2011).15 The ICMA currently has about 400 members in 50 countries, and its TRAX system

covers the greater part of the Eurobond market. Only three ICMA member firms aredomiciled in the United States.

Amihud ¼ AbsðrtÞVt

; ð2Þ

where Vt is the daily trading volume measured in millions of dollars.The Amihud ratio is calculated for each non-zero return day, andaveraged over the period of 20 business days.

Finally, I construct a liquidity measure from the autocovariancein daily returns. Roll (1984) first considered a similar measure as aproxy for the bid-ask spread, but Bao et al. (2011) argue that themeasure can capture additional aspects of liquidity such as marketdepth and resilience. Furthermore, Bao et al. (2011) show that themeasure explains individual bond yield spreads with large eco-nomic significance. Following Bao et al. (2011), I define the mea-sure of illiquidity c as:

c20 ¼ �Covðrt; rt�1Þ: ð3Þ

Table 5 summarizes the trade-based liquidity measures for globaland domestic bonds. The average monthly trading volume in eitherthe US market or in the Eurobond market located overseas is almostthree times larger for global bonds than for domestic bonds ($95million vs. $33 million in the US market, and $29 million vs. $13million in the overseas market). The median differences are evengreater, in particular in the overseas market. The median globalbond has a trading volume of 12 million dollars in the Eurobondmarket, compared to less than 1 million dollars for the mediandomestic bond. In the US market, the average global bond trades186 times per month, of which 59 trades are large (of $100,000 ormore). In contrast, the average domestic bond trades only 80 timesper month, of which merely 22 trades are large. Considering onlylarge trades, the average US bond has 14 zero volume days permonth, compared to 8 zero volume days for the average globalbond. Thus, although global bonds are significantly more liquid thandomestic bonds, they still do not trade on one out of every threebusiness days if only large trades are considered. This result reflectsthe well-known fact that trading is less frequent in the corporatebond market than in the stock market.

Table 5 further reveals that the prices of global bonds are lessvolatile than the prices of domestic bonds. Global bonds have a sig-nificantly smaller price range and coefficient of variation. Also, theAmihud measure indicates that global bond prices are less ad-versely impacted by large trades than domestic bond prices. Theestimated price impact of trading one million dollars is 67 basispoints for the average global bond, and 87 basis points for the aver-age domestic bond. Finally, global bonds exhibit significantly lessilliquidity as measured by c. The average global bond in the samplehas a c coefficient of 0.26, whereas the average domestic bond hasa c of 0.66. Overall, the estimates of c are in the same range asthose obtained by Bao et al. (2011) using only large trades.

5.3. Global and domestic bond liquidity

The summary statistics indicate that global bonds are consider-ably more liquid than domestic bonds. However, it is not clearwhether the liquidity advantage of global bonds is related to theirmultimarket trading, or if it merely reflects their larger issue sizeand other characteristics. Therefore, the tests in this section exam-ine whether global bonds are more liquid than domestic bonds ofthe same issuers with comparable characteristics such as issuesize, bond age, maturity, and embedded call options. Similar tothe analysis of trading yields, I use two methods to test for differ-ences in liquidity between global and domestic bonds: matchedsample analysis and fixed effects regressions.

First, I conduct paired t-tests and Wilcoxon signed rank tests ona matched sample of global and domestic bonds that were issuedby the same firm and have a similar issue size. Table 6 reportsthe paired t-tests for liquidity differences between global and

Table 5Summary statistics for liquidity measures. The table presents summary statistics for several transaction-based measures of corporate bond liquidity. Trading volume is themonthly trading volume, reported separately for the US market and the overseas (Eurobond) market. Other liquidity measures are based on data from the US bond market. Largetrades are transactions of at least 100,000 dollars. Price range is scaled by the average price. Coefficient of variation is the standard deviation of prices scaled by the average price.Amihud illiquidity is defined as the absolute value of daily returns divided by volume in millions of dollars. Gamma is the negative of the autocovariance in daily returns. Onlylarge trades are used to compute the number of zero volume days, price range, coefficient of variation, Amihud illiquidity, and Gamma. Gamma and Amihud illiquidity areavailable for a subsample of 528 bonds.

Sample mean Sample median

Global Domestic Difference Global Domestic Difference

US trading volume ($M) 94.85 32.92 61.93** 60.37 13.45 46.92**

Overseas trading volume ($M) 29.45 13.28 16.17** 11.78 0.63 11.15**

Monthly # of trades 186.23 79.93 106.30** 104.36 29.76 74.60**

Monthly # of large trades 59.07 21.92 37.15** 40.23 10.05 30.18**

Monthly # of zero volume days 8.11 13.63 �5.52** 7.57 15.00 �7.43**

Price range (%) 6.59 9.64 �3.05** 4.93 6.02 �1.09**

Coefficient of variation (%) 1.80 2.88 �1.08** 1.34 1.92 �0.58**

No. of bonds (930) 480 450 480 450Amihud illiquidity (%) 0.67 0.87 �0.20** 0.59 0.74 �0.15**

Gamma (%) 0.26 0.66 �0.40** 0.09 0.29 �0.20**

No. of bonds (528) 374 154 374 154

� Differences marked with are significant at the 10% levels.** Differences marked with are significant at the 5% levels.

Table 6Liquidity differences between global and domestic bonds: paired t-tests. The table reports the differences in liquidity between matched pairs of global and domestic bonds. Allbonds are non-callable, matched by issuer, and have an issue size within 10% from one another. The liquidity differences for each pair are calculated from all transactions thatoccur on the same days. Shown is the number of matched bond pairs, the liquidity of the global and domestic bonds, the mean difference in liquidity between global and domesticbonds across the matched pairs, and the t-statistic for the difference.

Liquidity measure No. of matched bond pairs Global bond liquidity Domestic bondliquidity

Mean difference in liquidity T-statistic fordifference

Matched by issuer and sizeUS trading volume ($M) 139 78.53 58.88 19.65** 2.63Overseas trading volume ($M) 139 29.63 15.64 13.99** 3.56Number of trades 139 165.19 137.94 27.25** 2.31Number of large trades 139 52.71 42.68 10.03** 2.92Number of zero volume days 139 7.63 9.47 �1.84** �5.09Price range (%) 139 5.30 6.06 �0.76* �1.82Coefficient of variation (%) 139 1.44 1.82 �0.38** �2.99Amihud illiquidity (%) 91 0.64 0.78 �0.14** �2.57Gamma (%) 91 0.29 0.46 �0.18* �1.92

Issue size ($M) 139 1011.30 1008.35 2.95 0.91



domestic bonds matched by issuer and issue size. All sample bondsare non-callable, matched by issuer, and have an issue size within10% from one another. The sample is the same as that used in theanalysis of yields spreads in Panel B of Table 3. Although matchingby issue size typically reduces the liquidity differences betweenglobal and domestic bonds (compare with Table 5), the differencesremain large and statistically significant. For example, the monthlytrading volume of domestic bonds in the US bond market increasesto 59 million dollars after matching domestic bonds by size withglobal bonds, but remains significantly below that of global bondsof 79 million dollars. Similarly, the number of zero volume days fordomestic bonds decreases to 9.5 after matching, which is signifi-cantly more than the 7.6 zero volume days for global bonds. Themeasures of price volatility and the return-based liquidity mea-sures also indicate that global bonds are significantly more liquidin the matched sample analysis.

Alexander et al. (2000) and Edwards et al. (2007), among oth-ers, show that trading in corporate bonds is abnormally high inthe first few months after issuance. Recently issued bonds couldtherefore appear more liquid than seasoned bond issues. To ad-dress this concern, I exclude from the matched sample comparisonall newly issued bonds for 6 months after issuance. Table 7 reportsthe results. Compared to Table 6, all bonds in Table 7 are less li-quid, regardless of whether they are global or domestic bonds.

However, the differences in liquidity between seasoned globaland domestic bonds generally remain statistically and economi-cally significant. Trading volume in the US (overseas) market, forinstance, declines to 61 million dollars (23 million dollars) forglobal bonds, but remains significantly higher than the 44 milliondollars (7 million dollars) for domestic bonds. Other liquidity mea-sures, except for the price range, also indicate that global bondshave a liquidity advantage.

Finally, I estimate panel regressions with issuer/day fixed ef-fects for each liquidity measure. Panel data estimation makes itpossible to include all the bonds in the analysis and control for anumber of bond characteristics such as age, maturity, and embed-ded call options. Table 8 contains the estimates. The dependentvariables in these regressions are the log-transformed (except forthe number of zero-volume days) liquidity measures. The firsttwo columns show that trading volume is larger for global bondsthan for domestic bonds, even after taking into account their largerissue size and other characteristics. In addition to global issuance,trading volume is significantly related to bond age and issue size.The coefficient on bond age is negative, confirming that volume de-clines as bonds age and settle in investors’ portfolios. The totalnumber of trades from TRACE is not significantly related to globalissuance. It is greater for larger issues and bonds with embeddedcall options. However, the total number of trades may not be a

Table 7Liquidity differences between seasoned global and domestic bonds: paired t-tests. The table reports the differences in liquidity between matched pairs of seasoned global anddomestic bonds. The sample includes bonds seasoned for more than 6 months after issuance. All bonds are non-callable, matched by issuer, and have an issue size within 10%from one another. The liquidity differences for each pair are calculated from all transactions that occur on the same days. Shown is the number of matched bond pairs, theliquidity of the global and domestic bonds, the mean difference in liquidity between global and domestic bonds across the matched pairs, and the t-statistic for the difference.

Liquidity measure No. of matched bond Pairs Global bond liquidity Domestic bondliquidity

Mean difference in liquidity T-statistic fordifference

Matched by issuer and sizeUS trading volume ($M) 125 61.36 44.46 16.90** 2.86Overseas trading volume ($M) 125 22.54 7.45 15.08** 6.97Number of trades 125 122.74 93.30 29.44** 4.54Number of large trades 125 46.23 33.98 12.25** 4.21Number of zero volume days 125 8.51 10.42 �1.91** �4.91Price range (%) 125 7.25 8.02 �0.78 �1.32Coefficient of variation (%) 125 2.01 2.35 �0.34* �1.87Amihud illiquidity (%) 63 0.77 1.06 �0.29** �3.26Gamma (%) 63 0.36 0.55 �0.19* �1.89

Issue size ($M) 125 990.37 985.20 5.16 0.99


Table 8Liquidity differences between global and domestic bonds: panel regressions with issuer/day fixed effects. The table presents estimates from regressions of several measures ofcorporate bond liquidity on a dummy variable that equals one if the bond is global, and the interaction of the global bond dummy with the speculative grade indicator variable.Also included are control variables for bond age, principal, time to maturity, and embedded call options. The dependent variables are the log-transformed (except for zero-volumedays) liquidity measures. The regressions are estimated on panel data transformed by subtracting issuer/day fixed effects. Robust t-statistics adjusted for clustering by bond are inparentheses.

Dependent variable

US tradingvolume

Overseas tradingvolume

No. oftrades

No. of largetrades

Zero volumedays

Pricerange

Coeff. ofvariation

Amihudilliquidity

Gamma

Global bond 0.187** 0.502** 0.070 0.112** �1.224** �0.003** �0.020** �0.071** �0.044**

(2.92) (2.49) (1.39) (2.46) (�6.01) (�3.60) (�3.55) (�2.31) (�5.22)Speculative � global 0.23 0.62 �0.20 0.04 0.13 �0.01 �0.02** �0.28** �0.12**

(1.29) (1.28) (�1.07) (0.21) (0.29) (�0.40) (�5.54) (�5.54) (�6.97)Age �0.138** �0.369** �0.021 �0.080** 0.192** �0.037** 0.011** 0.039** 0.008**

(�8.56) (�7.46) (�1.27) (�5.76) (3.18) (�8.24) (3.17) (5.26) (3.91)Principal 0.616** 1.468** 0.455** 0.486** �1.979** �0.002* �0.037** �0.115** �0.004

(10.06) (8.29) (8.60) (9.31) (�9.74) (�1.72) (�8.24) (�4.59) (�0.61)Maturity 0.013 �0.013 �0.029 �0.012 0.140** 0.005** 0.055** 0.029** 0.009**

(0.40) (�0.14) (�1.49) (�0.53) (2.66) (11.56) (20.34) (2.29) (2.70)Maturity squared 0.001 0.001 0.001 0.001 �0.003* �0.001** �0.001** �0.001** �0.001**

(0.28) (0.19) (1.24) (0.94) (�1.97) (�9.48) (�14.95) (�2.42) (�2.25)Callable bond 0.098 0.198 0.246** 0.155* �0.400 0.005** 0.031 0.045* 0.015*

(1.02) (0.73) (2.79) (1.91) (�1.46) (2.55) (1.43) (1.69) (1.87)

Adj. R2 0.27 0.20 0.16 0.31 0.19 0.18 0.31 0.23 0.20No. of trades 558,362 558,362 558,362 558,362 558,362 558,362 558,362 355,357 355,357No. of bonds 930 930 930 930 930 930 930 528 528No. of issuers 135 135 135 135 135 135 135 98 98



good proxy for bond liquidity since the majority of trades are re-tail-sized. The number of large trades, which likely better measuresliquidity, is positively related to global issuance. Additionally, thenumber of zero volume days is significantly smaller for globalbonds than for domestic bonds.

The return-based liquidity measures in Table 8 also indicatethat global securities are more liquid. Measures of price volatility,the price range and the coefficient of variation, are lower for globalbonds. The Amihud illiquidity, which is a proxy for the price im-pact of trading, is significantly lower for global bonds, in particularif they are rated below investment grade. The measure of pricereversals (c) is strongly negatively related to the global bond dum-my variable, and the effect is larger for speculative grade bonds. Byalmost all measures, corporate bonds become less liquid as theyage and settle in investors’ portfolios, and larger issues are more li-quid than smaller ones. However, differences in bond characteris-tics such as issue size, age, or maturity do not subsume thesignificance of global issuance for corporate bond liquidity.

5.4. Corporate bond prices and liquidity

Multiple liquidity measures indicate that global bonds have aliquidity advantage over domestic bonds. I investigate nextwhether the liquidity measures are priced, and whether they canexplain why investors require lower yields on global bonds. Toexamine these questions, I re-estimate the yield spread regressions(Eq. (1)) with liquidity measures among the explanatory variables.The regression estimates are reported in Table 9. The sample in Ta-ble 9 is not the full sample because return-based liquidity mea-sures are only available for a subset of 528 bonds. However, thesubsample yields very similar coefficient estimates as the full sam-ple without controlling for liquidity (compare column (1) in Table9 with column (2) in Table 4).

Column (2) of Table 9 provides the estimation results with sev-eral liquidity measures among the explanatory variables, includingthe total trading volume, number of trades, number of zero volumedays, price range, and coefficient of variation. Trading volume is

Table 9Liquidity and the spreads between global and domestic bonds: Panel regressions withissuer/day fixed effects. The table presents estimates from regressions of trading yieldspreads on a dummy variable that takes a value of one for global bonds, theinteraction of the global bond dummy with the speculative grade indicator variable,and various measures of corporate bond liquidity. Trading volume is the sum of thetrading volume in the US bond market and in the Eurobond market. All liquiditymeasures, except for the number of zero-volume days, are log-transformed. Alsoincluded are control variables for bond age, principal, time to maturity, andembedded call options. The regressions are estimated using panel data transformedby subtracting issuer/day fixed effects. Robust t-statistics adjusted for clustering bybond are in parentheses.

(1) (2) (3)

Global bond �0.135** �0.087** �0.045(�3.04) (�2.16) (�1.25)

Speculative⁄global �0.488** �0.399** �0.229(�2.49) (�2.60) (�1.55)

Maturity 0.106** 0.025 0.010(5.26) (0.97) (0.44)

Maturity squared �0.003** �0.001 �0.001(�4.18) (�1.20) (�0.72)

Age 0.053** 0.037** 0.030**

(3.76) (3.09) (3.02)Principal �0.075 �0.026 0.001

(�1.01) (�0.37) (0.02)Call option 0.199* 0.137 0.123

(1.87) (1.55) (1.45)Trading volume �0.160** �0.064

(�3.25) (�1.29)No. of trades 0.428** 0.405**

(6.18) (5.73)Zero volume days 0.044** 0.042**

(6.16) (5.69)Price range 1.569 1.702

(1.06) (1.11)Coefficient of variation 1.168** 1.028**

(4.12) (3.73)Amihud illiquidity 0.755**

(7.29)Gamma 0.891**

(4.09)Adj. R2 0.24 0.35 0.40No. of trades 355,357 355,357 355,357No. of bonds 528 528 528No. of issuers 98 98 98


Table 10The effect of taxes on the yield spreads between global and domestic bonds: Panelregressions with issuer/day fixed effects. The table presents estimates from regres-sions of trading yield spreads on an indicator variable that equals one for globalbonds, the interaction of the global bond dummy with the speculative grade indicatorvariable, and several control variables including the coupon rate to account for theeffect of taxes. Maturity is the time to maturity and Age is the bond age, bothmeasured in years at the time of trading. Principal is the natural logarithm of theoutstanding bond principal. Call option is an indicator variable equal to one if thebond is callable. Coupon is the coupon rate of the bond. Liquidity crisis is a dummyvariable that equals one if the spread between the 3-month LIBOR and the 3-monthTreasury bill rate exceeds 2%. The regressions are estimated using panel datatransformed by subtracting issuer/day fixed effects. Robust t-statistics adjusted forclustering by bond are in parentheses.

(1) (2) (3)

Global bond �0.224** �0.102** �0.081**

(�4.30) (�4.05) (�2.95)Speculative � global �0.482** �0.452**

(�2.79) (�2.62)Maturity 0.109** 0.091** 0.091**

(5.51) (5.95) (6.04)Maturity squared �0.002** �0.002** �0.002**

(�4.56) (�4.97) (�5.04)Age 0.027** 0.035** 0.032**

(2.94) (3.83) (3.68)Principal �0.045 �0.048 �0.047

(�0.85) (�0.92) (�0.94)Call option 0.212** 0.175* 0.178**

(2.29) (1.94) (2.08)Coupon 0.080** 0.077** 0.078**

(3.80) (3.59) (3.78)Liquidity crisis � global �0.382**

(�3.40)

Adj. R2 0.19 0.21 0.22No. of trades 558,362 558,362 558,362No. of bonds 930 930 930No. of issuers 135 135 135



measured as the sum of the trading volume in the US bond marketand in the Eurobond market. All liquidity measures, except for thenumber of zero-volume days, are log-transformed. The yieldspread between global and domestic bonds narrows after control-ling for the liquidity measures, but remains statistically significant.The estimated spread is �9 basis points for investment gradebonds and �49 basis points for speculative grade bonds. Further,several liquidity measures in column (2) are significantly relatedto corporate bond yields. A greater trading volume, smaller num-ber of zero volume days, and smaller price volatility as measuredby the coefficient of variation are associated with lower yieldspreads. In accordance with the findings of Bao et al. (2011), theterm to maturity is no longer statistically significant after control-ling for liquidity, and the number of trades enters the regressionwith a positive sign. However, the coefficient on bond age remainspositive and statistically significant. The R-squared increases from0.24 to 0.35 after controlling for the liquidity measures.

The last column in Table 9 shows the regression results with allthe liquidity measures among the independent variables, includingAmihud illiquidity and the measure of price reversals (c).16 The

16 Multicollinearity does not appear to be a major concern with the model. Includingall the liquidity measures, the average variance inflation factor is 3.17 (with amaximum of 6.03) and the condition number is 5.76, which is not unusually high.

yield spread between global and domestic bonds narrows furtherafter controlling for the return-based liquidity measures, and be-comes statistically insignificant for investment grade bonds. Thecombined coefficient estimate for speculative grade bonds of �27basis points remains marginally significant at the 10% level (the F-statistic is 3.27). The two return-based liquidity measures, Amihudilliquidity and c, have a significant positive effect on corporate yieldspreads. Overall, liquidity measures explain 16% of the cross-sec-tional variation in yield spreads between different bonds issued bythe same firms, and account for a major part of the yield spread be-tween global and domestic bonds.

5.5. Alternative hypotheses

Besides liquidity differences, the yield spread between globaland domestic bonds could also be consistent with the existenceof distinct investor clienteles. One type of clientele that has beendocumented in the corporate bond market is induced by heteroge-neous tax treatments of different groups of investors. For example,Liu et al. (2007) argue that individual investors have an incentiveto invest in low coupon corporate bonds because of the asymmet-ric tax treatment of coupon income and premium or discountamortization. Institutional investors are taxed symmetrically butcannot fully eliminate the price effect due to the substantial trans-actions costs and the low liquidity of corporate bonds. Consistentwith the tax-induced clientele hypothesis, Liu et al. (2007) findthat corporate bonds with higher coupon rates trade at lowerprices compared to corporate bonds with lower coupon rates.

The tax treatment of global bonds in the US does not differ sig-nificantly from US domestic bonds (see footnote 7). However, tax-


induced clienteles may still exist if global bonds tend to be issuedwith a lower coupon than domestic bonds. To control for the taxeffect found by Liu et al. (2007), I estimate Eq. (1) with the couponrate among the explanatory variables. As Table 10 reports, the cou-pon rate is positively and significantly related to yields, suggestingthat taxes induce price differentials among corporate bonds. Nev-ertheless, the magnitude of the yield spread between global anddomestic bonds and its statistical significance are little affectedby controlling for the tax effect (compare Table 10 with Table 4).

Yet another explanation of the spread between global anddomestic bonds is international bond market segmentation. Pricedisparities between global and US bonds could reflect an incom-plete integration of the US and the international bond market.However, it is unlikely that the markets remain segmented giventhat global bonds have reduced the costs of cross-market tradingand settlement. Thus, only the low liquidity of corporate bondscan hamper the ability of traders to arbitrage across different typesof bonds.

Table A1The top 45 issuers of sample bonds.

Parent CUSIP Corporate parent Sampletrades

Samplebonds

Creditrating

617446 Morgan Stanley 4055 25 Inv25746U Dominion Resources Inc 3891 23 Inv842587 Southern Co 1095 21 Inv025537 American Electric Power Inc 602 19 Inv060505 Bank of America Corp 32,974 19 Inv524908 Lehman Brothers Holdings Inc 14,585 19 Inv/Spec209115 Consolidated Edison Inc 2087 17 Inv345370 Ford Motor Co 61,734 17 Inv/Spec149123 Caterpillar Inc 6894 16 Inv264399 Duke Energy Corp 3544 16 Inv590188 Merrill Lynch & Co Inc 24,042 16 Inv87612E Target Corp 15,516 16 Inv026874 AIG 9148 15 Inv00206R AT&T Inc 2127 15 Inv370442 General Motors Corp 127,326 15 Inv/Spec46625H JPMorgan Chase & Co 12,529 14 Inv580135 McDonald’s Corp 4002 14 Inv78442P SLM Corp 12,767 13 Inv035229 Anheuser-Busch Cos Inc 2040 12 Inv125581 CIT Group Inc 10,871 12 Inv/Spec225401 Credit Suisse Group 13,273 12 Inv892331 Toyota Motor Corp 2237 12 Inv92343V Verizon Communications Inc 11,215 12 Inv949746 Wells Fargo, San Francisco, CA 3923 12 Inv126408 CSX Corp 1712 11 Inv438516 Honeywell International Inc 2108 11 Inv98385X XTO Energy Inc 3280 11 Inv02209S Altria Group Inc 17,015 10 Inv404280 HSBC 8013 10 Inv494550 Kinder Morgan Energy Partners 2477 10 Inv12189T Burlington Northern Santa Fe 1923 9 Inv244199 Deere & Co 3643 9 Inv319963 First Data Corp 4653 9 Inv441815 Household International Inc 646 9 Inv45031U iStar Financial Inc 1615 9 Inv/Spec49811T AIG Life Holdings (US) Inc 3941 8 Inv079860 BellSouth Corp 11,483 8 Inv136375 Canadian National Railway Co 331 8 Inv172967 Citigroup Inc 538 8 Inv40414L HCP Inc 647 8 Inv/Spec929903 Wachovia Corp, Charlotte, NC 3034 8 Inv002824 Abbott Laboratories 8217 7 Inv136385 Canadian Natural Resources Ltd 658 7 Inv263534 DuPont 8393 7 Inv

6. Conclusion

Large multinational corporations increasingly raise funds byissuing global bonds. Global bonds resemble US domestic bonds,but their distinctive features allow global bonds to be traded inmultiple markets. They are placed simultaneously with US andoverseas investors, and can be traded in the US bond market andthe Eurobond market, as well as between markets. However, theeffects of multimarket trading on corporate bond value are not wellunderstood. This paper examines how multimarket trading affectscorporate bond liquidity and prices in secondary markets.

The results confirm the hypothesis that multimarket tradingimproves corporate bond liquidity. Compared to domestic bondsissued by the same firms, global bonds are more liquid. They exhi-bit greater trading volumes in the US bond market and in the Euro-bond market, trade more frequently, and their prices are lessvolatile. Furthermore, the price impact of large trades is signifi-cantly reduced for global bonds, and transitory price movementsthat lead to serially correlated price changes are smaller. Theliquidity advantage of global bonds persists even after controllingfor their greater issue size and other characteristics, and it appearsto be related to their multimarket trading.

These findings are consistent with microstructure models thatpredict a positive relation between the number of potential inves-tors and liquidity in over-the-counter markets. Duffie et al. (2005,2007) develop a model in which transactions costs and liquidity inover-the-counter markets, such as the corporate bond market, de-pend on the number of potential investors. Their model predictsthat illiquidity discounts are smaller if the number of qualifiedinvestors is greater, and investors have access to multiple dealers.Global bond offerings increase the pool of potential bondholders toinclude investors overseas. In addition, liquidity in global bonds isprovided by both US bond dealers and Eurobond dealers. Thus, glo-bal bonds that are traded in multiple markets are more liquid thanUS domestic bonds.

Another important finding is that the liquidity advantage of glo-bal bonds is priced. If two bonds of the same issuer, one global andone domestic, trade on the same day, the yield on the global bondis on average about 20 basis points lower. The yield difference isgreater for speculative grade bonds than for investment gradebonds, and it increases during liquidity crises. In accordance withthe liquidity hypothesis, the spread between global and domesticbonds is closely related to the differences in liquidity. In particular,several trade-based liquidity measures explain a large part of theyield difference between global and domestic bonds, and up to

16% of the cross-sectional variation in yield spreads between dif-ferent bonds issued by the same firms.

Overall, the results show that investors value global bonds fortheir greater liquidity. The liquidity advantage of global bondscan account for the increasing popularity of global bonds in recentyears. The findings also contribute to our understanding of the fac-tors affecting corporate bond liquidity, and help explain prior evi-dence that global bond issues reduce the cost of debt.

Acknowledgements

I thank Charles Cao, Jaewon Choi, Stefano Corradin, Laura Field,Pascal Francois, David Haushalter, Jean Helwege, Nancy R. Mahon,Marco Rossi, and an anonymous referee for valuable comments. Igratefully acknowledge financial support from the Lamfalussy Re-search Fellowship of the European Central Bank. This research wasalso supported in part by a Doctoral Research Award from theSmeal College of Business.

Appendix A

See Table A1.


References

Alexander, G., Edwards, A., Ferri, M., 2000. The determinants of trading volume ofhigh-yield corporate bonds. Journal of Financial Markets 3, 177–204.

Amihud, Y., 2002. Illiquidity and stock returns: cross-section and time-serieseffects. Journal of Financial Markets 5, 31–56.

Bao, J., Pan, J., Wang, J., 2011. The illiquidity of corporate bonds. Journal of Finance66, 911–946.

Cai, N., Helwege, J., Warga, A., 2007. Underpricing in the corporate bond market.Review of Financial Studies 20, 2021–2046.

Chen, L., Lesmond, D.A., Wei, J., 2007. Corporate yield spreads and bond liquidity.Journal of Finance 62, 119–149.

Crabbe, L.E., Turner, C.M., 1995. Does the liquidity of a debt issue increase with itssize? Evidence from the corporate bond and medium-term note markets.Journal of Finance 50, 1719–1734.

Demsetz, H., 1968. The cost of transacting. Quarterly Journal of Economics 82, 33–53.Dick-Nielsen, J., 2009. Liquidity biases in TRACE. Journal of Fixed Income 19, 43–55.Duffie, D., Garleanu, N., Pedersen, L.H., 2005. Over-the-counter markets.

Econometrica 73, 1815–1835.Duffie, D., Garleanu, N., Pedersen, L.H., 2007. Valuation in over-the-counter markets.

Review of Financial Studies 20, 1865–1900.Edwards, A.K., Harris, L.E., Piwowar, M.S., 2007. Corporate bond market transaction

costs and transparency. Journal of Finance 62, 1421–1450.Ho, T., Stoll, H.R., 1983. The dynamics of dealer markets under competition. Journal

of Finance 38, 1053–1074.Houweling, P., Metnik, A., Vorst, T., 2005. Comparing possible proxies of corporate

bond liquidity. Journal of Banking and Finance 29, 1331–1356.Hull, J., Predescu, M., White, A., 2004. The relationship between credit default swap

spreads, bond yields, and credit rating announcements. Journal of Banking andFinance 28, 2789–2811.

Kapur, D., Lewis, J.P., Webb, R., 1997. The World Bank: Its First Half Century.Brookings Institution Press, New York.

Liu, S., Shi, J., Wang, J., Wu, C., 2007. How much of the corporate bond spread is dueto personal taxes? Journal of Financial Economics 85, 599–636.

Longstaff, F.A., Mithal, S., Neis, E., 2005. Corporate yield spreads: default risk orliquidity? New evidence from the credit default swap market. Journal of Finance60, 2213–2253.

Mahanti, S., Nashikkar, A., Subrahmanyam, M., Chacko, G., Mallik, G., 2008. Latentliquidity: a new measure of liquidity, with an application to corporate bonds.Journal of Financial Economics 88, 273–298.

Merton, R., 1974. On the pricing of corporate debt: the risk structure of interestrates. Journal of Finance 29, 449–470.

Miller, D.P., Puthenpurackal, J.J., 2005. Security fungibility and the cost of capital:evidence from global bonds. Journal of Financial and Quantitative Analysis 40,849–872.

Newman, Y.S., Rierson, M.A., 2004. Illiquidity Spillovers: Theory and Evidence fromEuropean Telecom Bond Issuance. Working Paper, Stanford University.

Reiss, P.C., Werner, I.M., 1998. Does risk sharing motivate interdealer trading?Journal of Finance 53, 1657–1703.

Roll, R., 1984. A simple implicit measure of the effective bid-ask spread in anefficient market. Journal of Finance 39, 1127–1139.

Schultz, P., 2001. Corporate bond trading costs: a peek behind the curtain. Journal ofFinance 56, 677–698.

Stoll, H.R., 1978. The pricing of security dealer services: an empirical study ofNASDAQ stocks. Journal of Finance 33, 1153–1172.

Wood, P., 2008. Law and Practice of International Finance. Thomson Retuters Ltd.,London.

multimarket trading and corporate bond liquidity

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