MarketAxess (MKTX) UBS Financial Services Conference 2026 summary
Event summary combining transcript, slides, and related documents.
UBS Financial Services Conference 2026 summary
9 Feb, 2026Growth initiatives and strategic focus
Three-year targets set for 8%-9% annual revenue growth and margin expansion, with new initiatives focused on scaling globally across high-grade, high-yield, EM, and EU markets.
Key protocols include X-Pro front end, blocks protocol (notably Targeted RFQ), portfolio trading (PT), and dealer-initiated solutions like Mid-X.
Blocks protocol saw strong ADV growth: 24% overall, 18% in the U.S., 27% in EM, and 66% in Eurobonds, with further U.S. rollout planned.
Portfolio trading share in the U.S. reached 19%, with high-yield PT share up to 15% in October; protocol enhancements continue.
Dealer-initiated Mid-X solution launched in the U.S., ramping up to daily sessions and receiving positive dealer feedback.
Market structure and competitive positioning
Market structure in fixed income has shifted: client-initiated trades now 58%, PT 11%, dealer 31%, reflecting a more diverse trading landscape.
Maintains leading liquidity in RFQ and all-to-all, with volumes and differentiated data supporting competitive strength.
Electronification has driven a 65% increase in credit market volume, with significant TAM remaining.
Non-U.S. businesses, especially EM and Eurobonds, are major growth drivers, with EM blocks ADV up 27% and PT up 172%.
Eurobonds benefit from protocol fit and are often used as a testbed for new technology rollouts.
Technology, automation, and AI
Automation via Auto-X protocol is growing, with sticky adoption and increasing use for larger trades.
Pragma acquisition enhances next-gen automation through advanced algos, with integration into X-Pro underway.
AI initiatives split between commercial (e.g., CP+ pricing, AI Select for block trading) and corporate efficiency projects.
CP+ leverages proprietary data for unique pricing outputs; AI Select aims to optimize dealer selection for clients.
Internal AI projects focus on workflow streamlining and coding, with a strategy of "AI everywhere."
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