IPO AND NEW LISTING DATA
Every US IPO, linked to the security from day one.
algoseek brings IPO data together in one dataset, keyed to the ASID, so the offering record follows the security through every event that comes after it. Most IPO sources scatter the pieces: the proposed price in one place, the underwriter in another, and none of it linked to the security’s subsequent history. Here, it is connected from day one.
IPO Detailed (sample)
Reference
| Field | Type | Example |
|---|---|---|
| Ticker | string | ACME |
| FirstTradingDate | string | 2024-03-15 |
| ProposedPrice | decimal | 21.00 |
| SharePriceLowest | decimal | 18.00 |
| SharePriceHighest | decimal | 22.00 |
| InitialPrice | decimal | 24.85 |
| Underwriter | string | Goldman Sachs |
| DealType | string | IPO |
Connected from the first trade
An IPO record that does NOT break the moment the company changes.
Most IPO datasets give you a snapshot of the offering and leave it there. The ticker changes, the company merges, the shares split, and the IPO record sits in a silo with no connection to what happened next. Reconciling it back to the security’s current identity becomes your problem.
Because the IPO record shares the same ASID as the security master, tick data, and adjustment factors, you do not need to reconcile it. The proposed price, the initial listing price, the underwriter, and the deal type are one join away from the full equity history, no matter how many times the ticker or name changes afterward. That is the difference between an IPO dataset you query once and one you can actually build on.
Linked to the ASID
Every IPO record connects to the same persistent identifier used across the security master, tick data, bars, and adjustment factors. One join, no mapping tables.
Two granularity levels
The basic dataset covers every new listing with the essentials. The detailed dataset adds underwriter, deal type, pricing range, and initial listing price for deeper analysis.
Every US exchange
NYSE, Nasdaq, and every other US equity exchange. No gaps from exchange-specific sourcing.
What’s in the dataset
Two datasets, one for coverage and one for depth.
The basic dataset gives you every new listing with minimal fields. The detailed dataset adds the context a research team needs: who underwrote it, what deal type it was, where the pricing range landed, and what the initial listing price was.
Reference · Equities
IPO
Every IPO and new listing across all US equity exchanges: ticker, first trading date, and initial listing price. The minimum you need to know that a security listed and at what price.
Ticker
FirstTradingDate
InitialPrice
Reference · Equities
IPO Detailed
The full picture: underwriter, deal type, the pricing range the offering was marketed at, the proposed and initial prices, and the exchange code. Built for teams analyzing IPO performance, underwriter track records, or new-issue pricing dynamics.
Ticker
FirstTradingDate
ProposedPrice
SharePriceLowest
SharePriceHighest
InitialPrice
Underwriter
DealType
Why it matters
IPO data without a persistent identifier is a dead end.
The offering is the first event in a security’s life. If it is not connected to everything that follows, it becomes a standalone record you have to reconcile by hand every time the company changes.
A standalone IPO feed
Keyed to the ticker at listing, which may change within months.
No link to the security master, so joining the IPO to subsequent corporate events requires manual reconciliation.
Listing price only, with no underwriter, deal type, or pricing range context.
algoseek IPO data
Keyed to the ASID, which follows the security through every ticker change, merger, and delisting.
One join to the security master, tick data, bars, and adjustment factors. No mapping tables.
Two granularity levels: basic coverage for every listing, detailed with underwriter, deal type, pricing range, and initial listing price.
Take just the IPO data if that is all you need, or get it inside the Equities Package or Multi-Asset Package, where it ships alongside the security master, tick data, bars, and adjustment factors under one license with no exchange fees.
Explore the Data
Query the equity security master directly with Python or SQL. Up to a year of production data, no agreement, no credit card needed.
Talk to our team
Core team from the trading side. Integration help, licensing for redistribution, and pipeline design.