FactSet Alternative for Point-in-Time Fundamentals

If you're searching for a "FactSet alternative for point-in-time fundamentals," you probably already know what FactSet is and why it's not an option right now — no enterprise contract, no six-figure budget, no procurement cycle you can start this afternoon. This page is not a claim that Tradevo Data replaces FactSet. It doesn't. It's a narrower tool for a narrower job: backtests and research where you need first-filed, as-of-date-correct US equity fundamentals and you need them today, at a price you can put on a personal card.

What FactSet actually gives you

FactSet is an institutional research and data platform used by analysts, portfolio managers, and quant teams at firms that can afford it. Its point-in-time fundamentals are part of a much larger system: global equity and fixed income coverage, estimates data, ownership data, full-text filings search, a desktop application, APIs, dedicated support, and integration with a firm's existing workflow. Pricing is negotiated per seat and per dataset and is not published — see FactSet's pricing page (factset.com) for current terms.

For point-in-time correctness specifically, FactSet's fundamentals are built and maintained by a team whose full-time job is exactly this: capturing what was known, when, across a global universe, with the depth of history and quality control that comes from decades of institutional revenue funding it. If your firm has that contract, you should use it. There is no honest argument that a $29/mo tool built by one person beats that.

What Tradevo Data gives you instead

Tradevo Data is a much smaller, much cheaper, single-purpose tool: point-in-time US equity fundamentals sourced directly from SEC EDGAR, which is public-domain data. It covers 5,170 US companies and 633,394 annual point-in-time rows across 16 annual concepts, up to 12 fiscal years of history, plus 1,090,751 quarterly rows across 5,377 companies and 7 quarterly concepts. Q4 is reported where it's tagged or derivable and labeled as such where the underlying data supports it; there's no derived Q4 EPS/diluted-shares, no TTM, and no non-US or delisted coverage.

Every row carries first_filed (when the value became public), original_value (the first-reported, backtest-safe number), latest_value (the current revision), a restated flag (flagged when the same tag changes by more than 0.5%, including amendments), and a qa_status. 37,941 restatements are labeled in the dataset.

The entire thing — API access plus bulk /v1/download and /v1/snapshot?as_of endpoints for both annual and quarterly periods — is $29/mo. Parquet format is not included. No seat licensing, no annual minimum, no sales call. You check out via Stripe, get a key instantly, and query /v1/fundamentals?ticker&as_of with a server-side as_of filter (first_filed on or before that date, same-day inclusive). 5,000 requests/day. Docs are public at /docs. Cancel anytime.

There's also a free, no-signup sample on GitHub (40 companies, 6,969 rows) with the full methodology written out, so you can inspect exactly how point-in-time logic is implemented before you pay for anything — including a measured lookahead of 43.2 days mean, 61 days max, on that 40-company sample's reliable-filing rows specifically. That figure describes the sample only; we haven't measured or published an equivalent lag statistic for the full dataset, so we won't guess at one here — check the methodology yourself if this matters to your use case.

Side-by-side

See the lookahead leak on real filings — 40 companies, 6,969 rows, CC0, no signup. Three minutes in a notebook, before you decide anything.

Read that table honestly: FactSet wins almost every row that isn't price or inspectability. That's not false modesty — it's the actual trade you're making.

When FactSet (or another enterprise platform) is the better choice

If you work at a firm that already has or can justify a FactSet, Bloomberg, or S&P Capital IQ contract, use it. You get global coverage, deeper concept sets, delisted companies, TTM and derived figures, analyst support, and a vendor who will answer the phone when something looks wrong. If your research depends on non-US names, long history with corporate-action adjustments, or fundamentals tied into estimates and ownership data, no $29/mo tool — ours or anyone else's — is a substitute. Don't let a lower price talk you into a dataset that's missing exactly the coverage your strategy needs.

It's also worth saying plainly: FactSet isn't the only credible option in this space, expensive or otherwise. Sharadar, Tiingo, and QuantConnect all offer point-in-time or point-in-time-adjacent fundamentals at various price points and levels of institutional polish (see their respective pricing pages) — worth comparing against your specific requirements rather than assuming any one vendor, including us, is the only cheap option.

When to build it yourself

If your universe is small, US-only, and limited to a handful of core line items, building your own EDGAR scraper is a legitimate option — the underlying filings are public and free. The real cost is engineering time: parsing XBRL correctly, handling amendments and restatements, deciding what "point-in-time" means for your specific tagging edge cases, and maintaining it as filers change formats. That's the work Tradevo Data has already done. If your time is worth more than $29/mo and you'd spend more than a few hours a month on upkeep, buying it back is usually the better trade. If you enjoy the plumbing and want full control, building it yourself is entirely reasonable — start with the free sample's methodology notes either way, since they document the exact decisions you'd otherwise have to make from scratch.

Where Tradevo Data fits

This is the tool for the gap between "no PIT data at all" and "an enterprise contract I don't have." It's for US equity backtests where survivorship and lookahead bias matter, where you want to see original_value versus latest_value on every row, and where $29/mo and an instant API key beat a procurement process you can't start. For background on why point-in-time data matters for backtests in the first place, see /blog/lookahead-bias-fundamental-backtests and /blog/point-in-time-fundamentals-data.

Start with the free sample to check the methodology yourself: github.com/christianpichichero-max/pit-fundamentals. If it holds up, the full API is at https://tradevodata.com/?utm_content=alt-factset for $29/mo.

Not investment advice. Verify FactSet's (and any other vendor's) current pricing and coverage directly with them before deciding.