AlphaSMO vs Dataroma: Curated Superinvestor List or the Full Dataset?

Dataroma is the tool a lot of value-investing readers already trust — a simple, free, manually-curated list of roughly 83 well-known "superinvestor" portfolios (Buffett, Ackman, Klarman, and similar names), built and maintained by one person for years. This post compares it directly against AlphaSMO, the site you're reading this on, so you can decide whether Dataroma's curated simplicity is actually what you need, or whether the fuller institutional dataset elsewhere covers more of what you're looking for.

Quick comparison

	Dataroma	AlphaSMO
Coverage	~83 curated "superinvestor" portfolios	Full institutional 13F universe
Data verification	Manually checked against EDGAR by the site's operator	Automated ingestion from SEC EDGAR
Cost	Free	Free
Insider (Form 4) trading	No	Yes
13F + insider overlap signal	No	Yes
Congressional STOCK Act trades	No	Yes
Search across all institutions	No — curated list only	Yes
Public REST API	No	Yes, free
MCP server for AI agents	No	Yes
Site design	Minimalist tables, no ads	Modern dashboard

(Feature details reflect what's publicly available on Dataroma as of this writing — the site is actively maintained but doesn't publish a formal changelog, so double-check current functionality directly.)

What Dataroma actually gets right

Dataroma's whole value proposition is curation and trust, and it delivers on both. Rather than showing you every institutional filer — most of which are index funds, market makers, and firms with no distinctive investment thesis — it narrows the field to a hand-picked list of investors with genuinely notable long-term track records. For someone specifically interested in "what is Warren Buffett's portfolio doing this quarter" or "what did Bill Ackman buy," that curation is the whole point: less noise, faster answers, no need to know which of the thousands of 13F filers are actually worth following. The site's operator manually verifies filings against EDGAR rather than relying purely on automated parsing, which is a genuine trust signal in a category where automated ingestion pipelines do occasionally misparse a filing. And it's been free and ad-light for a long time, run by one person rather than a venture-backed company chasing a monetization pivot — that kind of longevity and stability is worth something on its own.

If your actual need is "I follow a specific short list of famous investors and want a clean, trustworthy view of their quarterly moves," Dataroma is arguably the single best tool for exactly that, and we're not going to claim AlphaSMO replaces it.

Where AlphaSMO does something different

We don't manually curate a list of famous names, and we don't claim the same decade-plus single-operator track record. What we built instead:

The full institutional universe, not a curated slice. Dataroma's ~83 tracked managers are a deliberate, useful subset — but if the institution you care about isn't a famous value investor (a large pension fund, a sector-focused hedge fund, an insurance company's investment arm), Dataroma simply doesn't cover it. AlphaSMO indexes the broader 13F filer universe and lets you search any institution directly, not just a pre-selected list.

Institutional + insider overlap, automatically. Dataroma tracks 13F only — no Form 4 insider trading data, and no cross-referencing between the two. AlphaSMO's smart-money convergence signal scans for tickers where institutional accumulation and insider buying are both happening in the same window and scores the overlap. Live numbers as of this writing: Simon Property Group (SPG) shows a convergence score of 79.06 with 11 distinct institutional buyers; KKR shows 80.48 with 5 buyers; Elevance Health (ELV) and W.R. Berkley (WRB) both show 70.0 with 2 buyers each; International Paper (IP) shows 62.59 with 3 buyers. Live, not backtested, updating as filings land.

A free public API and MCP server. Dataroma has no API at all — if you want its data programmatically, you're looking at scraping its HTML, which is fragile and arguably not in the spirit of a small, manually-run site. AlphaSMO's API is built for exactly this use case, with no paywall, plus an MCP server for AI agents.

Congressional trading data. A separate data type Dataroma doesn't track at all.

An honest note on what curation costs you

It's worth naming the actual tradeoff rather than just listing feature gaps. Dataroma's curation is a feature, not a limitation, for its intended use case — it deliberately filters out the 99%+ of 13F filers who aren't interesting to a value-investing-focused reader, and that filtering is done by a human with judgment, not an algorithm. AlphaSMO doesn't do that filtering for you by default; you get the full dataset and either search for what you're looking for or lean on tools like the convergence signal to surface something you weren't already looking for. Neither is strictly better — a curated list is faster if you already know who you care about, and a searchable full dataset is more useful if you don't, or if the institution you care about was never going to make a hand-picked "famous investors" list in the first place.

A concrete case where the difference actually matters

Say you're interested in a mid-cap industrial company that isn't a household name and isn't held by any of Dataroma's ~83 tracked managers — a pension fund, a regional bank's investment arm, or a sector-specialist fund most retail investors have never heard of are accumulating it. On Dataroma, that activity is simply invisible; the site was never built to surface it, because it only shows you what's happening inside its curated list. On AlphaSMO, you can search the ticker directly and see every 13F filer that holds or has recently changed a position in it, whether or not that fund is famous. That's the practical difference between a curated list and a searchable full dataset: one is faster when you already know who to look at, the other is the only option when you don't.

The reverse is also true, though. If you already know you only care about Buffett, Ackman, Klarman, and a handful of other well-known names, Dataroma's focus means you're not wading through thousands of irrelevant institutional filers to get to the answer — that's a real usability advantage AlphaSMO's broader, unfiltered dataset doesn't replicate by default.

Decision guide, in one paragraph

If you can answer yes to any of these, lean Dataroma: you specifically follow a short list of famous value investors and want the cleanest possible read on their quarterly moves, you value a track record of careful manual verification, or you just want the simplest possible interface with zero setup. If you can answer yes to any of these instead, lean AlphaSMO: you need to look up an institution that isn't a famous name, you want institutional and insider buying automatically cross-referenced, you want programmatic access via a free API or MCP server, or you're interested in congressional trading data. If you answered yes to items on both lists, that's a real signal to use both — they don't overlap much, so there's little redundancy in checking both.

A few quick questions people ask

Does AlphaSMO have a curated "best investors" list like Dataroma? Not in the same manually-curated sense — the closest equivalent is the smart-money convergence signal, which surfaces tickers algorithmically rather than tracking specific named investors.

Is Dataroma's data actually more accurate than an automated pipeline? Manual verification against EDGAR is a real quality signal, especially for catching parsing edge cases. Automated pipelines (including AlphaSMO's) can in principle scale further and update faster, but manual review has real value at the margins.

Will Dataroma ever add insider trading or an API? We can't speak for another site's roadmap — it's been a stable, minimalist tool for years, and there's no indication that's changing.

Do people use both? Yes — Dataroma for a fast, trusted read on a specific well-known investor's quarterly moves, AlphaSMO for broader institutional search, the convergence signal, congress data, and free API access.

If you want to see the convergence signal for yourself, the smart money convergence page is free to browse, and the public API docs are open with no signup wall for read access.