GOVGREED CONGRESSIONAL INTELLIGENCE PLATFORM
—  ·  — ACTIVE SIGNALS
Congressional Trading Intelligence

Greed is
predictable.

Congressional committee members vote on bills that move stocks. They own those stocks. We track both — and flag the pattern while the 45-day disclosure window is still open.

99K
Deduplicated Trades
353
Members Trading
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Active Predictions
42K
Bills Scored
📊 See Live Signals How it works ↓
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THE PREDICTION WINDOW

Every bill leaves a trail. We follow the money.

The legislative pipeline has 7 stages. At one critical moment — the markup — committee members know the bill is moving. That's when they buy. That's when GovGreed fires a signal.

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1 — Committee Assignment
A bill lands in committee. The same people who vote on it own the stocks it affects. Armed Services. Finance. Healthcare. Energy. They know the outcome before anyone else.
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2 — GovGreed Signal Fires
7 intelligence layers run simultaneously: committee seat, herd activity, bill timing, technical indicators, sector momentum, lobbying patterns, campaign contributions. When 3+ layers converge, the signal multiplies. Prediction fires days before the trade.
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3 — +60 Days: Stock Moves
Up to 45 days later the trade appears in a STOCK Act filing. You can compare what was flagged with what was disclosed — the record is public either way.
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The 45-Day Disclosure Lag Problem
The STOCK Act gives members of Congress 45 days to disclose trades. By the time it hits the news, the move has already happened. GovGreed flags the committee pattern while that window is open. Whether a flagged member actually trades is only known when the filing lands.
The Method

What a signal is — and what it isn't.

A GovGreed signal is a score attached to a disclosed trade or an upcoming committee event. It tells you where committee seats, herd activity, bill timing, lobbying, and donor money overlap. It does not tell you a stock will go up, and no signal is right every time. Tier-level backtest results, with their sample sizes and limits, are on the methodology page.

📊 See live signals →
The System

Seven intelligence layers. One prediction.

GovGreed's engine cross-references 7 independent data sources simultaneously. When multiple layers converge on the same politician + stock, a convergence multiplier fires — up to 2× the base score.

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Layer 1 — 20% weight
Committee Position
We track every committee assignment — Armed Services, Finance, Healthcare, Energy. When a bill in their sector hits markup, the member is flagged.
IF bill.sector ∈ member.committees → MATCH
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Layer 2 — 20% weight
Herd Activity
When 3+ politicians buy the same ticker within 30 days, a herd signal fires. Congressional convergence is statistically non-random — 31 active herds tracked.
IF congress_buyers ≥ 3 → HERD SIGNAL
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Layer 3 — 16% weight
Bill-Trade Timing
Bill-trade correlations mapped across 14 years. We know the average days-before-markup when each politician historically buys.
IF days_until_markup < 30 → FIRE SIGNAL
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Layer 4 — 12% weight
Technical Context
RSI, SMA-200, and volume surge on every tracked ticker. Insider buying is more predictive when confirmed by technical momentum.
IF rsi < 65 AND is_uptrend → BOOST
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Layer 5 — 12% weight
Sector Momentum
Sector heat across 11 market sectors scored daily. HOT sector status amplifies congressional insider signals that align with macro tailwinds.
IF sector_tier = 'HOT' → MULTIPLIER
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Layer 6 — 10% weight
Lobbying Activity
2,101 lobbying patterns mapped to congressional trading timelines. Lobbying spend preceding a stock buy is a documented pre-trade signal.
IF lobby_spend → recent buy → CORRELATE
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Layer 7 — 10% weight
Campaign Contributions
565 contribution patterns: donors fund politicians who then trade in the donor's industry. 14 years of FEC data confirms the pattern.
IF donor.industry = trade.sector → PATTERN
7-Layer Signal Score Formula
score = committee 20% + herd 20% + bill timing 16% + technical 12% + sector 12% + lobbying 10% + contributions 10%
S ≥ 75 A+ ≥ 60 A ≥ 50 B ≥ 40 C/D/F below Convergence: 3 layers = 1.3× · 4 = 1.5× · 5+ = 2.0×
Watchlist

8 members to watch.

Members whose disclosed trades often fall in sectors their committees oversee, drawn from 99,546 deduplicated STOCK Act trades. The score is a GovGreed confidence score, not a return.

CONGRESSIONAL WATCHLIST — COMMITTEE / SECTOR OVERLAP
WATCHLIST
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Maximum Convergence — Rep. Ro Khanna: Sits on the Armed Services Committee and represents Silicon Valley. His disclosed trades concentrate in technology and industrials, where committee, herd, and lobbying layers overlap — the convergence pattern the signal engine is built to flag.
Live Intelligence

Active predictions right now.

Updated nightly. Each prediction represents a committee member with a documented pattern of trading before an upcoming markup. These are live signals — not historical.

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🏛️ Bill Pipeline → 📊 Paper Trade Signals →
By The Numbers

The dataset behind it.

Counts from GovGreed's deduplicated STOCK Act dataset, 2012–2026. Data as of 2026-09-25.

99,546
Deduplicated Trades
Every disclosed congressional stock trade on file, 2012–2026, each counted once.
353
Members Trading
Members of Congress with at least one disclosed trade in the dataset.
12.5%
Filed Late
12,766 trades disclosed more than 45 days after the trade date.
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Active Signals
Live predictions in the system today.
Access
Get the signal before
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