XTech will be at Convene, One Liberty Plaza on 17 September as a Bronze Sponsor of Neudata's inaugural New York Traditional and Market Data Summit.
Morgan Slade presents Exponential on the main stage at 10:40, and our booth is open all day. Come and see the two datasets behind our record: investor flow decoded from the order book, which explains roughly 80% of open-to-close price moves in US equities, and a CPI forecast that has beaten consensus for eight years — and called the March 2026 energy shock within 6 basis points.
Exponential Technology is a Bronze Sponsor of the New York Traditional and Market Data Summit 2026, hosted by Neudata on Thursday 17 September at Convene, One Liberty Plaza, 1 Liberty Street, from 9am to 5pm EDT.
Market Challenger Spotlight: Morgan Slade on the main stage, 10:40–11:20
Morgan Slade, CEO and Head of Research, presents Exponential in the Market Challenger Spotlight sessions on the main event stage. Morgan covers the whole picture: what Exponential offers, the empirical research the datasets rest on, and the technology that turns full-depth order-book reconstruction into signals a desk can act on.
It is the one slot in the day where the flow analytics, the macro forecasts and the research programme are presented as a single system rather than three separate products. If you only have time for one thing from us, make it this.
Two numbers we are bringing to New York
Institutional flow, decoded from full-depth order-book data, explains roughly 80% of open-to-close price moves in US equities.
Not a correlation observed after the fact, but a decomposition of who was buying and who was selling, reconstructed from the book itself. Once a move can be attributed to institutional accumulation rather than market-maker inventory or retail participation, the question of whether it is temporary impact or genuine repricing on new information has an answer rather than a narrative.
Our CPI forecast has outperformed consensus polls on every headline metric since November 2017 — and Q1 2026 was its stress test.
February 2026 was exact on all four rounded measures. In March, when the Strait of Hormuz closed and gasoline posted its largest monthly increase since 1967, XTech's Final Forecast called headline CPI at +0.8% against a printed +0.9% — a 6 basis point error through the sharpest monthly acceleration since June 2022, with core matched exactly. Maximum error across all four March measures was 10 basis points. Read the full Q1 2026 scorecard.
What you can see at our booth
Three of us are making the trip: Morgan Slade, CEO and Head of Research; Timmy Cai, Senior Quantitative Researcher; and Geof Dallennes, Director of Marketing. Between them they cover the full stack of what we are showing — the research programme and the strategy behind it, the model internals and inference methods underneath the flow and CPI datasets, and how firms are putting both to work.
Bring the hard questions; Timmy will answer them. Morgan will be at the booth after his 10:40 session for anyone who wants to follow up on it.
We are not taking part in the summit's 1-2-1 meeting programme this year, so the booth is the place to find us. No booking required — walk up.
Investor-flow analytics by investor type.
XTech decodes full-depth order-book data into net buying and selling activity by investor type — institutional, market-maker and retail — across equities, ETFs, options and futures. Where most market data offerings rely on consolidated feeds, XTech US Equity Flow is built on BMLL's harmonised Level 3 data across all US equity venues, with over six years of history from January 2020 and delivery at one-minute, hourly, daily and weekly intervals. Advanced tiers decompose flow into HFT, fund and retail activity per exchange and per ticker. On the futures side, the same approach separates managed-money positioning from producer and commercial hedging, so a move in a curve can be attributed rather than assumed.
"The market data function is being rebuilt around a question consolidated feeds cannot answer: who is on the other side. We are bringing the order-book evidence to New York." — Morgan Slade, CEO and Head of Research, Exponential Technology
Macro forecasts built from the bottom up
Twelve category models — gasoline, shelter, food, medical, transportation, used vehicles and others — each trained on real-time alternative data, proprietary consumer surveys and transaction-level price series, then aggregated at official BLS expenditure weights. That architecture is why the accuracy advantage holds when conditions shift violently rather than deteriorating. PCE, ISM and Michigan Consumer Sentiment forecasts sit alongside CPI.
The empirical research behind the datasets
Every claim above traces to published work, and we will have it with us: the flow impact study measuring price response per unit of managed-money and producer flow; the CPI benchmark study behind the table above; and our empirical estimation of temporary market impact coefficients from Level 3 order book data — measured from the book rather than assumed from a model.
Technology that makes the research usable.
A visualisation layer and analytics platform with interactive dashboards and agentic research workflows, so the datasets are not only accessible to quant teams. Minute-level flow across a configurable universe, alerts on unusual retail and institutional activity, and cumulative price performance plotted against normalised institutional flow for any two names side by side. We will run it live at the booth on whatever tickers you want to look at.
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