With this additional volume in smaller trades, market participants have been seeking to analyze the impact of size on pricing. For years, a relative pricing disadvantage had been a concern for firms transacting in smaller sized fixed income trades. The general acceptance of smaller size transactions has broadened the need for insightful data to make informed decisions.

The price adjustments for size to what has traditionally been an institutional (or round lot) market in fixed income has largely been a qualitative exercise by the trader, applying knowledge gained during their career. With relatively low volumes, long transaction times and an investor base that was less likely to “shop” around, the system limped along. Traders, from the sell side, viewed these smaller size trades not worth their effort - or just wanted to avoid getting stuck with an odd lot or micro lot on the books. Today by contrast, an explosion of fixed income ETFs (as shown in Figure 3), increased adoption of separately managed accounts, and higher interest rate backdrop have combined to help transform fixed income trading.

The create/redeem process for ETFs brought new participants into the fixed income market, while existing institutional trading desks also continue to play a role. The create/redeem process often deals with smaller trade sizes (i.e., <1mm in USD par notional per issue), even though the number of issues transacted during any one process may total in the dozens or hundreds. The result is a changing market dynamic, which challenges historic assumptions.

Recent trade data reflects the impact of these ongoing changes. Our analysis of the data generated by these new dynamics has led us to conclude that the fixed income market is undergoing an evolutionary change. In our view, this evolution has created increased access and transparency to fixed income markets and has provided benefits to all investors.

As the trading market evolved, the need for better pricing led to greater demand for intra-day fixed income pricing. The next natural step is to acknowledge the need for a more quantitative approach to account for trade size. This is the void that ICE Size-Adjusted Pricing can help to fill.

ICE uses a well-established methodology to evaluate fixed income instruments globally. The process to calculate the SAP for an instrument starts with a process that combines and pairs the relevant ICE evaluation with the statistical analysis generated by the ICE BestEx service (as further described in the ICE Best Ex Methodology document). The ICE evaluation is the reference price used in the Best Ex service to build the trade price distributions. When creating distributions by comparing ICE’s evaluations to trade prices, we are able to identify consistent patterns. These patterns become more obvious when breaking the distributions into different trading buckets based on asset class, tenor, trade direction and trade size. We extrapolate this price distribution based on side and size across a wide range of fixed income assets (see Figure 4). The dealer buy side of the distribution is the “bid” side of the size adjusted price. The dealer sell side of the distribution is the “ask” side of the size-adjusted price. The size-adjusted price is an estimate of what a holder may receive in an orderly transaction based on the inputs provided by the user.

Figure 5 represents price differences for a few different asset types including US Investment Grade Corporates, US High Yield Corporates, US Tax-Exempt Revenue Investment Grade Municipals and MBS FIX Specified Pools. These prices differences are referred to as trade buckets and as they are presented here it helps to appreciate the generally widening pattern as you move from larger size trade activity to smaller size trade activity.

Over the years there has been no shortage of questions about the pricing of smaller trades. At ICE, we defined evaluated prices as market-based measurements that are processed through a rules-based pricing application and represent our good faith determination as to what the holder may receive in an orderly transaction for an institutional round lot position (typically 1MM or greater current face USD or local currency equivalent) under current market conditions. In reality, a baseline institutional size trade may be defined differently based on each individual fixed income asset class. For example, for U.S. Treasuries and Mortgage TBAs, one might consider an institutional round lot trade to be much higher, but for global corporate bonds and municipal bonds it is reasonable to consider a one million par notional trade size as the threshold for what constitutes an institutional round lot size trade. For this reason, one million USD or greater in par notional continues to be a widely, almost unanimously, agreed amount when thinking about institutional round lot trading. There are two reasons ICE continues to view 1mm+ as a reasonable threshold to define institutional size:(i) trading in 1mm+ lot sizes most often happen between institutional market participants; and (ii) under normal market conditions trading in larger sizes typically takes place in a more tight, well defined pricing context.

Since 2016, ICE has been able to identify and quantify the distance between “round lot - institutional trading” compared to smaller trade size activity. Figure 6 below is an overall view of how the size-adjusted bid/ask has evolved. The chart provides context on the core 10yr. U.S. Corporate bond trade size trading buckets. The analysis below examines various sizes through the lens of bid/ask in percentage of par, dollar price terms and is presented as TCA or a transaction cost analysis.

Figure 7 presents four charts which examine a specific moment in time and calculate what the market implied size-adjusted bid/ask price is at the 50th percentile (i.e., a Best Ex score of 50). This view is used to illustrate how the various size-adjusted percentiles vary by trade size. As a result, we infer a market implied transaction cost analysis (TCA). The charts represent the 10yr. U.S. Investment Grade (top) and 5yr. High Yield (bottom) Corporate bond market implied size adjusted expected TCA in dollar price across a variety of best execution percentiles (scores). In this example we calculate half of the market implied size-adjusted bid/ask as a way to illustrate the compression we have seen on trade activity across various trade sizes. We use these examples to focus on two main themes:

As previously stated, the amount of smaller fixed income transactions has increased dramatically in recent years while during the same period, institutional size transactions (on count) have remained steady or even declined slightly. The greater trade flow in smaller sizes brought about by the evolving market has resulted in transaction price compression. The compression is within the variance between round lot trading and odd lot / micro lot trading as seen in Figure 8. The compression also existing within the bid/ask spread, or the “markup”, associated with round lot trading compared to odd and micro lot trading.

We see similar behavior when we look at U.S. Municipal trading in Figure 8 - the difference between micro lot trading to round lot trading continue to compress, having a direct impact on overall TCA:

Micro Lot = <100k, Odd Lot = 100k-500k, Round Lot = >500k.

Seeing these results in a table (Figure 10) helps illustrate the dramatic evolution we have seen in Municipal Bond TCA. The market implied cost to trade over the past seven years has been virtually cut in half for trading of micro lot transactions (see Figure 9). ICE’s Size-Adjusted Price is a quantification of that compression.

Figure 9: Source: ICE Data Services TCA using half the market implied bid/ask spread at BestEx percentiles ranging from 1-100.

Decades of pricing experience makes SAP a natural extension of an evaluation which is a core competency ICE offers. To be clear the methodology to derive the traditional ICE evaluations are separate and distinct to how ICE derives SAP. However, we feel SAP offers a differentiated dataset that may serve as a great source of information for firms dealing with an ever changing fixed income market dynamic.

Although the magnitude of differentials has consolidated over time, we still see value in tracking and using SAP to help provide greater transparency in the market. Although the trend toward smaller size adjustments have been good overall for investors there are “white space” gaps between the “inside market” on larger trades compared to the “inside market” on smaller trades.

In a fast-changing landscape and unprecedented access to fixed income markets it is critical to have access to data that better reflects what one may expect when entering odd lot or micro lot transactions. This content represents yet another set of data and analytics that can help provide more transparency. Combining public trade data with proprietary data from ICE helps to quantify size adjustments related to pricing - something for years market participants had to manually. ICE SAP can finally help fill the void that has long existed in the market for odd lot or micro lot pricing.