Comparing Corporate Bond Liquidity Across Regions


By Grant Lowensohn and Hidde Verholt.


  • The US corporate bond market offers a significantly greater number of ISINs with high daily trade counts than other developed markets.
  • The most liquid ISINs in the US market typically see more daily trades than the most liquid ISINs in European markets.
  • Depth of liquidity increases more rapidly as Relative Liquidity Score (RLS) increases for US IG bonds than for US HY bonds.

Depth of liquidity

The rise of automation has led to increased market interest in highly liquid bonds that change hands frequently. A metric that can be used to assess liquidity from this perspective is the depth of liquidity, which we define as the total number of secondary market trades an ISIN sees in a day. During FY 2021, we find that, on average, 1,316 US IG ISINs have a depth of liquidity greater or equal to 10 on a given day, compared to 52 in EUR IG (Figure 1).1 This disparity in depth of liquidity is not limited to absolute ISIN count terms, but persists as a share of daily ISINs traded, since around 18% of US IG and HY ISINs traded on a given day had a depth of liquidity of at least 10, compared to 3% in EUR IG Corps, and 1% in GBP IG Corps. We thus see a substantially steeper drop-off in depth of liquidity in European markets than in US markets. This is particularly evident when comparing the US HY and EUR IG universe, which are comparable in terms of average number of unique ISINs traded per day (2,325 vs 1,948), but the US HY market has a substantially greater number of ISINs with strong depth of liquidity (414 vs 53).

Cumulative distribution of average % of daily ISINs traded and average ISIN counts by depth of liquidity and market (FY 2021)

Fig 1: Cumulative distribution of average % of daily ISINs traded and average ISIN counts by depth of liquidity and market (FY 2021).

Depth of liquidity by relative liquidity score (RLS)

When comparing depth of liquidity across markets by RLS, we see the pattern of superior liquidity in US markets persist. Bonds in the most liquid portion (RLS = 10) of the EUR IG bond universe typically trade 3.21 times per day, compared to an average of 15.08 and 6.63 in US IG and US HY (Figure 2). Within the US market, as RLS increases, the depth of liquidity for US IG bonds increases rapidly, whereas we see a more moderate increase in US HY. For example, an RLS increase from 6 to 10 yields an expected depth of liquidity growth of 305% for US IG (3.72 à 15.08), compared to only a 33% expected increase in depth of liquidity for US HY (4.98 à 6.63). This large relative spike in depth of liquidity for US IG bonds with high RLS coincides with a spike in ETF constituency. For example, on average 83% of US IG ISINs with an RLS of 10 are constituents of the actively traded iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD), compared to 27% of bonds with an RLS of 6. For the US HY universe, this ETF relationship appears less pronounced, as the percentage of ISINs included in the iShares iBoxx $ High Yield Corporate Bond ETF (HYG) remains fairly constant around 60% for ISINs with RLS between 6 and 10.

Average daily trade count by Relative Liquidity Score and market (FY 2021)

Fig 2: ​​​​Average daily trade count by Relative Liquidity Score and market (FY 2021).

Relative Liquidity Score (RLS) Methodology

The proprietary MarketAxess Relative Liquidity Score provides a consolidated measure of the current liquidity of an individual bond, using factors such as trading activity, MarketAxess platform inquiry activity and platform dealer activity. The methodology covers approximately 33,000 bonds daily. Scores range from one to ten, where ten indicates the highest level of liquidity and one the lowest.

1 It should be noted that figures for US markets are based on TRACE volumes, whereas European market insights are based on TraX®volumes. Centralized reporting of European market data is not mandated and thus TraX® is estimated to cover 75% of European market activity, compared to 100% US market coverage by TRACE.
For questions or follow-up, email our data scientists at