← back to rankingTW · Tradeweb Markets Inc.
Financial - Capital Markets · mkt cap $20.9B · calls: Q1 FY2026 vs Q4 FY2025
52.0 conviction · conf-adj 52
conf 3/10 partial
enthusiasm:27.0 · trend:8 · quantifies:0 · impact:0 · under_radar:0 · credibility:0 · business_impact:8 · disruption:0 · commitment:6 · confirmation:3
Enthusiasm latest 9 / prev 7 (rising)
The AI thesis is that Tradeweb's proprietary market data can power client-facing workflow automation, generative insight tools, and predictive price discovery, while AIX already shows measurable ETF adoption. Enthusiasm is rising because Q1 FY2026 added concrete product launches, Terra and AI Price 2.0, versus Q4 FY2025's broader framing. Credibility is moderate to high on adoption metrics, but management has not quantified direct AI revenue, margin, cost, or productivity contribution.
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $2.1B · net income $0.8B · net margin 39.6% · diluted EPS 3.78
These are next-fiscal-year annual uplift estimates, not next-quarter numbers.
Aggregate next-FY est. rev uplift: % · next-FY EPS uplift: % · vs analysts: inline · priced in: high · confidence: 3/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
AIX ETF avg daily trades +70% YoY (Q1'26)
engagement · soft | over 70% YoY | Trade-COUNT growth on the ETF/equities sub-segment, not revenue. ETF/equities is a minor share of $2,052.4M total and no ETF AIX revenue, trade-count base, or fee/take-rate is disclosed in any claim, so 70% trade growth cannot be mapped to a revenue $ (AIX automates small tickets; trades != $). No base obtainable -> unsizeable. | | |
AIX ETF avg daily trades +70% YoY (Q4'25)
engagement · soft | over 70% YoY | Same metric, prior quarter — duplicate of the Q1'26 print. Confirms a durable trend but adds no new disclosed base; no ETF revenue/fee anchor against $2.052B revenue / $812.8M NI. | | |
US ETF AIX avg daily trades +28% QoQ
engagement · soft | up 28% QoQ | Narrower US-ETF sub-segment trade-count growth off a small early-adoption base. No US ETF revenue, fee, or take-rate disclosed; QoQ trade growth not convertible to a revenue/EPS figure against $2.052B revenue / $812.8M NI. | | |
$600B AI infrastructure spend -> more rates trading
other · soft | $600B macro capex | Economy-wide AI capex narrative — an adopter macro-tailwind, NOT Tradeweb selling AI capacity. $600B is external spend, not TW revenue, and management gives no conversion to incremental rates volume, market share, or fee capture, so $600B/$2.052B is not a valid TW uplift. | | |
Assumptions: Default incremental net margin = current 39.6% and tax rate 21% would apply IF any claim were sizeable, but none are: all four are growth RATES on undisclosed sub-segment bases (AIX ETF/equities) or an unquantified external macro capex number. ETF/equities is a small slice of $2,052.4M total and no ETF revenue base appears in any claim, so the disclosed-base rule does not rescue them. No phasing/bookings conversion assumed because no dollar anchor exists. EPS sized against consensus adjusted basis (FY25 $3.44, FY26 $4.05).
Top line: AIX is a genuine, deepening differentiator — ETF automated trades +70% YoY (group) and US ETF +28% QoQ — but every claim is a trade-COUNT growth rate on the ETF/equities sub-segment, a minor slice of the $2,052.4M base, with no disclosed ETF revenue or fee capture to anchor it. Trades != revenue (AIX automates small tickets). The $600B AI-capex line is a macro tailwind to rates trading, not a Tradeweb dollar figure. Net: directionally supportive of continued volume-led growth, but not separately sizeable as a revenue uplift.
Bottom line: No EPS uplift can be computed: with zero sizeable revenue anchor there is no incremental net income to flow through against $812.8M current NI. AIX automation is plausibly margin-accretive (it scales execution without proportional headcount), but management gave no cost or savings figure, so any EPS effect is subsumed in the volume-growth consensus models — not separable.
[impact n/m (all claims soft/unanchored)] Consensus already bakes in ~14.6% FY26 revenue growth ($2,052.4M -> ~$2,353.8M) and +17.5% adjusted EPS growth ($3.44 -> $4.05), with further growth into FY27 — a volume-and-automation-driven trajectory. The AIX 70%/28% trade-growth and the $600B capex narrative are exactly the kind of volume tailwind that path assumes; none points to revenue ABOVE consensus by a quantifiable margin, so there is no arithmetic basis to call estimates too low. The AI story supports, rather than exceeds, the priced-in trajectory.
MODEL CONSENSUS (impact)
partial
Full agreement on all four soft/null claims and adopter framing; differences only on verdict fields, resolved conservatively.
Conflicts reconciled
- priced_in: X=medium vs Y=high -> used high (more conservative; both agree no anchor adds value above consensus)
- vs_analyst_expectations: X=inline vs Y=unclear -> used inline (X better justified; both find no basis to beat estimates)
- confidence: X=4 vs Y=3 -> used 3 (lowered on conflict, ~average)
| Field | Opus 4.8 | GPT-5.5 |
|---|
| Rev uplift % | – | – |
| EPS uplift % | – | – |
| Priced in | medium | high |
| vs analysts | inline | unclear |
| Confidence | 4 | 3 |
| Top line | AIX is a genuine, deepening differentiator — ETF automated trades +70% YoY (group) and US ETF +28% QoQ — but every claim is a trade-COUNT growth rate on the ETF/equities sub-segment, which is a minor slice of the $2,052.4M base, with no disclosed ETF revenue to anchor it. Trades != revenue (AIX automates small tickets). The $600B AI-capex line is a macro tailwind to rates trading, not a Tradeweb dollar figure. Net: directionally supportive of continued volume-led growth, but not separately sizeable as a revenue uplift. | Management cites strong AIX engagement growth, including over 70% YoY ETF average daily trade growth and 28% QoQ US ETF AIX growth, but without an ETF AIX revenue base or fee capture the revenue uplift is unquantifiable. The $600B AI infrastructure spend claim is not TW revenue and has no disclosed conversion to rates trading fees. |
| Bottom line | No EPS uplift can be computed: with zero sizeable revenue anchor there is no incremental net income to flow through. AIX automation is plausibly margin-accretive (it scales execution without proportional headcount), but management gave no cost or savings figure, so any EPS effect is already subsumed in the volume growth consensus models — not separable. | No cost-saving or margin-expansion claim was quantified. With no incremental revenue dollars, EPS uplift cannot be computed against $812.8M current net income. |
| Reasoning | Consensus already bakes in +14.7% FY26 revenue growth ($2,052.4M -> $2,353.8M) and +17.5% adjusted EPS growth ($3.44 -> $4.05) — a volume-and-automation-driven trajectory. The AIX 70%/28% trade-growth and the $600B capex narrative are exactly the kind of volume tailwind that growth path assumes; none of them points to revenue ABOVE consensus by a quantifiable margin. So the AI story supports, rather than exceeds, the priced-in trajectory. | Consensus revenue rises from $2.054B in 2025 to $2.354B in 2026, a $299.6M increase or 14.6%, and to $2.614B in 2027, another $260.5M or 11.1%. Consensus EPS rises from $3.4425 to $4.0464 in 2026, up 17.5%, then to $4.5721 in 2027, up 13.0%. The AI claims provide no hard incremental TW revenue or EPS dollars above that trajectory, so there is no arithmetic basis to call estimates too low. |
Rows highlighted where the two models disagreed.
QUANTIFICATIONS
AIX ETF average daily trades: over 70% (Q1 FY2026 year-over-year, topline)
“Our AIX automation solution continues to be a key differentiator with our ETF clients with average daily trade increasing over 70% year-over-year with double-digit growth across European and U.S. ETFs.”
AIX ETF average daily trades: over 70% (Q4 FY2025 year-over-year, topline)
“Our AIX automation solution has been a key differentiator with our ETF clients with average daily trades increasing over 70% year-over-year.”
US ETF AIX average daily trades: up 28% (Q4 FY2025 quarter-over-quarter, topline)
“While AIX is deeply penetrated across European ETFs, we continue to see strong adoption across US ETFs. With AIX average daily trades up 28% quarter-over-quarter.”
AI infrastructure spend driving rates trading: $600 billion (2026 outlook, topline)
“the numbers that are you know, that we're talking about, $600 billion of AI infrastructure spent. Right? That's going to lead to more rates trading.”
PAST (realized)
- Our clients engage with the platform at record levels and increasingly capitalized on our automation solution, AIX.
- Our AIX automation solution has been a key differentiator with our ETF clients with average daily trades increasing over 70% year-over-year.
- While AIX is deeply penetrated across European ETFs, we continue to see strong adoption across US ETFs. With AIX average daily trades up 28% quarter-over-quarter.
- We've always been built around providing ultimately more efficient workflow tools for our clients.
CURRENT (now)
- we have continued to invest in our enhanced dealer selection tool, Snaps, which enables our clients to dynamically target dealers most likely to engage and win a given inquiry. Based on both historical and real-time trading data.
- We have our own kind of AI-powered assistant named, we're calling it Terra.
- On the predictive side, we're tracking -- tackling and working on I think 1 of the fixed income is probably hardest problems, which is price discovery.
- We think about AI and how it's tightly linked, you know, truthfully to how we make money.
FORWARD (guidance)
- We're on track to launch that in the second quarter, which gives traders like a single natural conversation to surface insights around liquidity conditions, market participation, historical execution behavior and relative pricing dynamics.
- We're launching what we call AI Price 2.0 at the end of the second quarter.
- data advantage, I think, reinforces network effects and I think that opens up new revenue opportunities smarter, faster ways for our clients to trade and execute in the marketplace
- the numbers that are you know, that we're talking about, $600 billion of AI infrastructure spent. Right? That's going to lead to more rates trading.
TRACK RECORD — PROMISE vs DELIVERY
—/100 (no quantified promises) no-quantified-promises 6 calls reviewed
Tradeweb repeatedly reports quantified adoption and performance for its automation/electronic-workflow capabilities (AiEX intelligent automation, Snaps dealer-selection, RFM/RFQ, dealer algos, package trading) — e.g. AiEX average daily trades up 70-125% YoY — but these always appear as backward-looking results or broad opportunities, never as forward targets pairing a specific number with a future timeframe or milestone. With no testable prior quantified AI promise across the six calls, their AI promise-vs-delivery track record cannot be scored.
PRICED-IN (REFINED)
HIGH (already in)Est. revisions rising · Fwd P/E 28.5 · EV/Sales 8.8x
AI claim maps to Transaction Fee Revenue, Market Data Revenue, Subscription Fee Revenue
Analyst ratings have migrated modestly upward since January, the latest monthly price-target average is above the quarterly and yearly averages, and consensus already models double-digit revenue and EPS growth through 2027. The stock is also valued richly at 28.5x forward earnings and 8.8x EV/Sales, so rising estimates make the AI upside more priced-in, not less. Any AI benefit would most plausibly show up in transaction fees, market data, or subscription revenue, and the current valuation already appears to capitalize that growth path.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
6Q4 FY20247Q1 FY20257Q2 FY20257Q3 FY20258Q4 FY20257Q1 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
Automation moved from recurring AiEX adoption metrics to broader data-driven workflows, dealer algos, and automated ETF solutions tied to growth.
BUSINESS IMPACT - QUALITATIVE MATERIALITY
7/10 qualitative impact material near-term · mixed evidence
Where AI matters: trading workflow automation and price discovery
AI/automation is tied directly to Tradeweb's electronic trading workflow: AIX adoption is quantified with ETF average daily trades up over 70% YoY, while Snaps, Terra, and AI Price 2.0 aim to improve dealer selection, insight generation, and price discovery. The upside is material but not transformational because the disclosed metrics are trade-count engagement in narrower segments, not companywide revenue or EPS contribution.
Caveats: AIX growth is disclosed as trade-count growth, not revenue or fee capture; ETF automation may be a relatively small slice of total transaction revenue; Competitors with strong data and distribution could replicate AI workflow features; Model quality, explainability, and regulatory constraints matter in fixed-income execution
AI DISRUPTION / CANNIBALIZATION RISK tailwind · 2/10
AI is more likely to accelerate electronification and deepen Tradeweb's data/network advantages than automate away its marketplace model. The core monetization depends on liquidity, participants, workflow integration, and proprietary transaction data, which are not easily commoditized by generic AI tools.
OPTIONS / MARKET STRUCTURE
option liquidity: fair
proxy inputs — dollar-ADV $148M · beta 0.667 · px $97.98
source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.
CONFIRMATION — INSIDERS · 13F · LANGUAGE
Mixed — insiders selling, institutions adding, management language 7/10 committed.
INSIDERS selling 21 open-market sell(s) vs 0 buy(s) — net distribution
INSTITUTIONS (13F) adding as of 2026-03-31: 95 new / 71 closed positions; 331 increased / 187 reduced; institutional ownership -0.94pp; +24 net 13F holders
MGMT LANGUAGE 7/10 committed Automation language is concrete and results-based, though AI discussion is limited and broader growth claims remain somewhat qualified.
commit “Our clients engage with the platform at record levels and increasingly capitalized on our automation solution, AIX.”
commit “Our AIX automation solution continues to be a key differentiator with our ETF clients with average daily trade increasing over 70% year-over-year”
hedge “we believe this advantage will only grow as we expand our presence across regions”
VERBATIM AI QUOTES
“Our clients engage with the platform at record levels and increasingly capitalized on our automation solution, AIX.”
— William Hult, Q1 FY2026
“Our AIX automation solution continues to be a key differentiator with our ETF clients with average daily trade increasing over 70% year-over-year with double-digit growth across European and U.S. ETFs.”
— William Hult, Q1 FY2026
“we have continued to invest in our enhanced dealer selection tool, Snaps, which enables our clients to dynamically target dealers most likely to engage and win a given inquiry. Based on both historical and real-time trading data.”
— William Hult, Q1 FY2026
“Even as market conditions became more challenging, automation remained robust, and we saw clients not only lean into inherently electronic protocols, but use them in a more sophisticated way through sending their trades out to multiple dealers amidst an environment where we have historically seen that pull back.”
— William Hult, Q1 FY2026
“AI gives us that opportunity constantly to prove that.”
— William Hult, Q1 FY2026
“We have a very strong feeling that data is the moat I think that's an important kind of thing to say our proprietary data, which we draw, as you know very well from like live markets, executable pricing, RFQ behavior, execution outcomes, client decision-making protocols across all of these assets.”
— William Hult, Q1 FY2026
“on the generative AI side, our goal is pretty simple. Move clients from data retrievable into this thing that's really important, which is like insight generation in markets that obviously like never slowed down, and that's important.”
— William Hult, Q1 FY2026
“We have our own kind of AI-powered assistant named, we're calling it Terra.”
— William Hult, Q1 FY2026
“We're on track to launch that in the second quarter, which gives traders like a single natural conversation to surface insights around liquidity conditions, market participation, historical execution behavior and relative pricing dynamics.”
— William Hult, Q1 FY2026
“On the predictive side, we're tracking -- tackling and working on I think 1 of the fixed income is probably hardest problems, which is price discovery.”
— William Hult, Q1 FY2026
“We're launching what we call AI Price 2.0 at the end of the second quarter.”
— William Hult, Q1 FY2026
“data advantage, I think, reinforces network effects and I think that opens up new revenue opportunities smarter, faster ways for our clients to trade and execute in the marketplace”
— William Hult, Q1 FY2026
“As I look back at 2025, a few thoughts that come to mind are our clients' focus on data-driven tools for larger and more complex trades, the acceleration of automation, and the growing interconnectedness of global markets.”
— Billy Hult, Q4 FY2025
“Our AIX automation solution has been a key differentiator with our ETF clients with average daily trades increasing over 70% year-over-year.”
— Billy Hult, Q4 FY2025
“While AIX is deeply penetrated across European ETFs, we continue to see strong adoption across US ETFs. With AIX average daily trades up 28% quarter-over-quarter.”
— Billy Hult, Q4 FY2025
“We're helping to drive more discrete, transparent, and efficient execution, especially through innovations like RFM and AIX.”
— Billy Hult, Q4 FY2025
“AI is real. Right? The hyperscalers will be selling bonds.”
— Billy Hult, Q4 FY2025
“the numbers that are you know, that we're talking about, $600 billion of AI infrastructure spent. Right? That's going to lead to more rates trading.”
— Billy Hult, Q4 FY2025
“We think about AI and how it's tightly linked, you know, truthfully to how we make money.”
— Billy Hult, Q4 FY2025
“We've always been built around providing ultimately more efficient workflow tools for our clients. And I think we would say clearly that AI is a natural extension of that.”
— Billy Hult, Q4 FY2025
“on the predictive AI side, I would say we are kind of looking at our proprietary datasets to help unlock what we describe as, like, the next frontier of electronification.”
— Billy Hult, Q4 FY2025
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Michael Cyprys): Wanted to ask about AI and just curious to hear your views around how you're thinking about AI's role in increasing automation across workflows particularly in credit and rates? And what are some of the KPIs you think we should be tracking?
A: Tradeweb, as you know very well, we're in the business of serving our clients, like Period. So everything we do around AI always has to be kind of triggered off that. ... on the generative AI side, our goal is pretty simple. Move clients from data retrievable into this thing that's really important, which is like insight generation ... We're on track to launch that in the second quarter ... We're launching what we call AI Price 2.0 at the end of the second quarter.
Q (Q1 FY2026, Simon Alistair Clinch): following on nicely from the last question about AI investments generally for growth. Sarah, could you expand on your philosophy for expense growth in terms of the flexibility and willingness you have to adjust investment up or down in environments of volume upside or in fact, downside?
A: that allows us to calibrate expenses while still delivering margin but still being able to invest for discretionary and opportunistic things like Billy was just talking about, whether it be AI, or opportunities in EM.
Q (Q4 FY2025, Craig Siegenthaler): We had a question on AI. And, you know, we know automation is a key component of your AIX solution. As you take a step back and look across the entire Tradeweb Markets Inc. platform, can you talk about your utilization of AI and also differentiate between both generative AI and predictive AI models?
A: We think about AI and how it's tightly linked, you know, truthfully to how we make money. ... on the predictive AI side, I would say we are kind of looking at our proprietary datasets to help unlock what we describe as, like, the next frontier of electronification.