July 8, 2025
ICE’s Liquidity Metrics provide a deeper understanding of tradability across fixed income segments and can be used to inform index design
For fixed income market participants, liquidity can be an elusive concept: hard to assess and difficult to quantify. Yet the ease with which a bond can be traded is frequently a critical factor in capital allocation, portfolio composition and trading strategy. Traditional approaches to assessing liquidity - such as analyzing TRACE data for average daily volume (ADV) and turnover - typically demand significant data processing, normalization and supplementation. Even when metrics are available, many market participants know that the liquidity available for specific trades frequently differs from historical metrics.
In response, ICE is introducing four liquidity measures across its global bond indices and their constituents. These new Liquidity Metrics are based on ICE’s established Liquidity Indicators™ service, which provides an independent, near-term view of relative liquidity to support risk management, investment decision making and regulatory obligations.
The new measures allow users to choose from metrics that capture a bond’s recent trading history, or a modelled approach that applies additional inputs to assess the likelihood it can be traded, and in what size. The latter approach is important where a bond may not have traded in the past three months - so has no recent ADV data - yet may have other characteristics relevant to its liquidity like size, issuer level trading activity, or related quote activity.
The four Liquidity Metrics include:
The charts above illustrate the projected difference in liquidity for an index and a bond based on recent trading history (time-weighted ADV) versus a modelled projection (projected trade capacity).
From a research perspective, the integration of these liquidity measures offers rich opportunity. ICE’s fixed income index Liquidity Metrics provide a deeper, more uniform understanding of liquidity variation across asset segments and market conditions. As a result, researchers can better quantify the relationship between bid-offer spreads and volume-based liquidity metrics, as well as potentially provide ETF issuers and investors with clearer visibility into premium/discount behaviors. Risk assessment in fixed income markets could also be refined through granular liquidity analysis. Both asset managers and issuers could apply these insights to inform index design and methodology, incorporating elements demonstrated to support liquidity. For these use cases, the ICE Custom Index Tool provides a web-based platform for analyzing the liquidity impact of user decisions on custom indices representing alternative investment strategies. And at a higher level, ICE Data Indices' extensive coverage universe and standardized index constituent data allow users to compare liquidity metrics across diverse bond market segments around the world.
ICE's Liquidity Metrics for fixed income indices incorporate four years of historical data and are accessible through the ICE Index Platform. The underlying data has established credibility through years of use for regulatory and reporting purposes as part of ICE's Liquidity Indicators™. As data and technology in bond trading continue to evolve, these metrics represent the first phase of ICE's broader efforts to integrate liquidity-based concepts with its industry-leading fixed income indices.
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Varun Pawar, ICE Fixed Income & Data Services’ Chief Product Officer, spoke with The DESK about the latest trends in funds management, the use of AI, and how index providers are keeping pace with growing demand for customisation.
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