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Point-in-Time Equity Universe API
Build a developer-first API that returns historical index membership, delisted securities, and point-in-time tradable universes for equities. The product solves the most common early-stage quant mistake: using today's constituents and incomplete free data to test historical stock-picking strategies.
Why this matters
You start with an ordinary stock-selection idea, pull prices from a free source, and only later discover your test universe quietly excluded many names that disappeared, merged, or left the index. The result looks cleaner than reality because your historical screen is built from survivors and incomplete constituent lists. Paid institutional datasets exist, but they feel expensive and operationally heavy when you are still validating ideas. What you really need is a simple way to ask, for any date, which names were actually eligible, which later delisted, and how exits should be represented so your research is not invalid from the first line of code.
- · Built for Independent quant traders, small systematic funds, and research engineers building stock-selection backtests in Python who need valid historical universes without institutional data budgets..
- · Most likely monetization: SaaS subscription.
The Pain · Narrative
You start with an ordinary stock-selection idea, pull prices from a free source, and only later discover your test universe quietly excluded many names that disappeared, merged, or left the index. The result looks cleaner than reality because your historical screen is built from survivors and incomplete constituent lists. Paid institutional datasets exist, but they feel expensive and operationally heavy when you are still validating ideas. What you really need is a simple way to ask, for any date, which names were actually eligible, which later delisted, and how exits should be represented so your research is not invalid from the first line of code.
Score Breakdown
Market Signal
Go-to-Market
Solo and small-team quant researchers running equity backtests in Python who currently rely on yfinance or ad hoc CSV universes.
~20K-60K active globally
SEO long-tail
$49/month
20 paying users who connect the API to a live notebook or backtest within 30 days
MVP Scope · 1–2 weeks
- Define MVP scope as one index family plus US equities only
- Ingest public index change logs into dated membership tables
- Create a simple schema for security, listing, active date range, and status
- Build a basic API endpoint that returns members for a given index and date
- Prepare a notebook showing the difference between current and historical constituents
- Add delisted symbol handling with terminal event types such as acquisition or delisting
- Ship a Python SDK wrapper for date-based universe queries
- Add CSV and Parquet export for downloaded universes
- Implement a basic bias checker that flags use of current constituents in historical periods
- Launch a landing page with one sample backtest case study and Stripe checkout
Differentiation
Why This Might Fail
Self-rebuttal — the most important trust signal
- 1Users may prefer established data vendors once they realize data quality matters, making it hard to win on trust alone.
- 2Historical universe accuracy may require data sources that are too costly to support attractive pricing.
- 3Some hobbyists only need a one-time download and will not sustain recurring subscription revenue.
Evidence Summary
How AI synthesized this insight — no verbatim quotes
The discussion repeatedly returns to one issue: valid stock-selection backtests require date-correct index membership and delisted names, while common free workflows do not provide either. Roughly a dozen comments reinforced that historical constituent data is essential and that many users eventually pay for it. Several also pointed out that the problem affects even short backtests, making this a recurring need rather than a niche archival feature.
Action Plan
Validate this opportunity before writing code
Recommended Next Step
Build
Strong demand signals detected. Real pain, real willingness to pay — start building an MVP.
Landing Page Copy Kit
Ready-to-paste copy based on real Reddit community language — no editing required
Headline
Point-in-Time Equity Universe API
Sub-headline
Build a developer-first API that returns historical index membership, delisted securities, and point-in-time tradable universes for equities. The product solves the most common early-stage quant mistake: using today's constituents and incomplete free data to test historical stock-picking strategies.
Who It's For
For Independent quant traders, small systematic funds, and research engineers building stock-selection backtests in Python who need valid historical universes without institutional data budgets.
Feature List
✓ API for historical index constituents by date ✓ Delisted and acquired security coverage with exit return handling ✓ Point-in-time eligibility filters such as listing age and liquidity thresholds ✓ CSV/Parquet export plus Python SDK ✓ Bias warnings when users request impossible historical universes
Where to Validate
Share your landing page in r/r/algotrading — that's exactly where these pain points were discovered.
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