Feature Comparison 1 layer of raw data vs. 7 layers of intelligence — side by side
| Feature | GovGreed | Capitol Trades |
|---|---|---|
| STOCK Act trade filingsHouse and Senate periodic transaction reports | ✓ 189,595 trades | ✓ Comprehensive |
| Composite signal scoreCombines politician quality, herds, bills, technicals, sector, contributions, lobbying | ✓ 2,790 scored signals | — |
| Bill-trade correlationsCross-referencing trades with bill timing and committee activity | ✓ 256,112 correlations | — |
| Herd detection3+ politicians converging on the same ticker | ✓ 31 active herds | — |
| ML trade predictionsForecasting which politicians will trade which sectors next | ✓ 819 active predictions | — |
| AI chatbotNatural language queries against the full database | ✓ Claude-powered | — |
| Campaign contribution mappingFEC data linked to trading patterns | ✓ 565 patterns | — |
| Lobbying-trade alignmentSenate LDA filings cross-referenced with trades | ✓ 2,101 patterns | — |
| Politician quality scoringWin rates, trading styles, options usage, committee alignment | ✓ 251 profiles scored | — |
| REST APIProgrammatic JSON access for bots and models | ✓ Free tier available | — No API |
| Disclosure gap analysisHow late each politician files (avg 44.9 days) | ✓ 23,426 late filings flagged | Partial |
| Institutional media credibilityCited by WSJ, NYT, Reuters | — Newer platform | ✓ Major media citations |
| Data history depthYears of historical coverage | ✓ 2012–2026 | ✓ Longest history |
| Starting price | Free access | Free browsing |
The 7 Intelligence Layers Capitol Trades Doesn't Have Why raw filings alone miss the signal
Politician Quality Scoring
251 politicians scored on historical win rates, options usage, sector specialization, and committee alignment. A trader with a 72% buy win rate gets a different score than one at 38%.
Herd Detection
When 3 or more politicians buy the same ticker within a rolling window, that convergence is a qualitatively different signal. 31 active herd signals detected, quality-weighted by politician tier.
Bill-Trade Correlation
256,112 trade-bill timing correlations. When a committee member trades a sector days before a markup on legislation affecting that sector, the timing is scored and ranked.
Technical Context
RSI, volume surge detection, SMA crossovers, and trend analysis. A congressional buy during an oversold RSI with volume surge is weighted differently than a buy at all-time highs.
Sector Momentum
Congressional buying and selling aggregated by sector. When Congress is net buying Technology while selling Energy, the sector direction becomes a scoring input.
Campaign Contributions
565 FEC contribution-trade patterns matched. When a politician receives campaign money from an industry and then trades stocks in that industry, the pattern strength is scored.
Lobbying Alignment
2,101 lobbying-trade alignment patterns from Senate LDA filings. Trades that coincide with active lobbying on related legislation receive a lobbying alignment score.
Convergence Multipliers
When multiple layers fire simultaneously, the signal is amplified. 3 signals = 1.3x multiplier. 4 signals = 1.5x. 5+ signals = 2.0x ("Perfect Storm"). The A+ tier has a backtested 72.7% win rate with +10.7% average 30-day return. Capitol Trades shows none of this.
4 Prediction Engines
Committee markup predictions, recurring purchase pattern detection, signal-score bridging, and bill-correlation forecasting. 819 active predictions across 76 politicians. Capitol Trades is retrospective only — it shows what already happened.
What Capitol Trades does well
Capitol Trades, built by 2iQ Research (a German data analytics firm), has earned a strong reputation as the go-to source for raw congressional trading data. Major publications — the Wall Street Journal, New York Times, Reuters, and Bloomberg — cite Capitol Trades regularly. That institutional credibility matters if you're a journalist, researcher, or analyst who needs a source that editors trust.
Their interface is clean and professional. Trades are presented clearly with politician names, tickers, amounts, and filing dates. For someone who just wants to browse recent congressional trades without complexity, Capitol Trades delivers a polished experience.
They also have among the deepest historical coverage of any congressional trading tracker, with data going back years before many competitors existed.
The intelligence gap
The fundamental limitation of Capitol Trades is that it's a data presentation layer, not an intelligence platform. It shows you that Senator X bought $50,000-$100,000 of ticker Y on a given date. It does not tell you:
- Whether that senator has a 72% or 38% win rate on similar trades (politician quality scoring)
- Whether 4 other senators also bought the same ticker that week (herd detection)
- Whether that senator sits on a committee with a markup scheduled on legislation affecting that sector (bill-trade correlation)
- Whether the industry lobbied that senator's committee in the months before the trade (lobbying alignment)
- Whether FEC records show campaign contributions from that industry to that politician (contribution patterns)
- Whether the stock is technically oversold or overbought when Congress starts buying (technical context)
GovGreed computes all of this automatically for every qualifying trade. The result is a composite score from 0-100, with tier labels (S, A+, A, B, C, D, F) that tell you at a glance which trades have the most intelligence behind them.
When Capitol Trades is the right choice
- You need a media-credible source: If you're writing for a publication, Capitol Trades' citation history with major outlets gives it editorial trust that newer platforms haven't yet earned.
- You want simplicity: Capitol Trades shows raw filings without complexity. If you just want to check what Pelosi traded this month, it's straightforward.
- You value track record: Capitol Trades has operated for years with institutional backing from 2iQ Research. Longevity matters for some users.
When GovGreed is the right choice
- You want to understand why a trade matters: GovGreed cross-references each trade against bills, lobbying, contributions, herds, technicals, and sector momentum. One number tells you more than a raw filing ever could.
- You need predictions, not just history: 819 active forward predictions across 76 politicians. Capitol Trades is retrospective only.
- You're building a trading bot or model: GovGreed's REST API provides programmatic JSON access. Capitol Trades has no API.
- You want AI-assisted research: Ask the GovGreed chatbot "which senators on the Finance Committee have been buying healthcare stocks?" and get an answer in seconds, with data citations.
- You care about disclosure gaps: GovGreed flags all 23,426 late filings (12.5% of all trades) and calculates the exact disclosure gap for every trade. The average is 44.9 days — nearly the full 45-day legal limit.
Pricing Comparison
- ✓ Signal scoring across 2,790 trades
- ✓ 819 forward-looking predictions
- ✓ AI chatbot with full database access
- ✓ REST API — 30 days free for waitlist
- ✓ 189,595 historical trades (2012–2026)
- ✓ Herd detection, bill correlations, lobbying
- ✓ Congressional trade filings (STOCK Act)
- ✓ Clean, professional interface
- ✓ Institutional credibility (WSJ, NYT citations)
- ✓ Deep historical data
- — No signal scoring or intelligence layer
- — No API, no predictions, no AI