AI And The Municipal Bond Market: Solving The Pricing Problem

For a brief time, I worked for a pricing service, then Thomson Reuters, now LSEG. I took the job for two reasons. First, a colleague I liked worked there, so it would be fun. Second, after joining the chorus of grumblers about how bad municipal bond pricing was, I was curious for a look behind the curtains.

It Pucks

Ask nearly anyone in the muni market about pricing and they usually respond with words that rhyme with “it pucks”. One rationale is the market has what is genteelly referred to as a ‘structural problem’. In broad terms, the problem is that of the $4 trillion par value outstanding bonds with over 1 million unique identifiers, just 0.33 percent of those traded. That was in 2023—a record trading year. Of bonds that do trade, the market is essentially bifurcated between institutional block sizes ($1 million or larger) or retail odd-lots ($100,000 or smaller).

Institutional block trades drive valuations, with trades generally in big new issue underwritings and on the ‘long end’ of the curve: 20 year and 30 year maturities. In most cases, bonds from new issues trade for a few months, then get laid to rest in a mutual fund or SMA portfolio. It’s what market participants call “going to bond heaven”.

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