CTQL
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What's new
All three branches
Executive disclosures from OGE now live alongside congressional trades and judicial financial filings.
14 insight detectors
New: copy-trader returns, bipartisan convergence, court-trade correlation, insider echo, quiet accumulation, and more.
Smarter scoring
Insider scores now reflect actual congressional trading activity. Lobbying records and committee memberships surfaced.
Insights
· rarity ·
Events / 24h
Companies Scored
/
tracked universe
Activity Mix (24h)
What kinds of events we ingested in the last 24 hours — a quick read on which signals are firing.
No activity in the last 24 hours

Top Movers (24h)

Companies whose risk score changed the most today. Red number = risk got worse. Green = risk improved.

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No score data yet — run ingestion first

Congress Trade Activity — Day × Month

When Congress actually trades. Rows = day of week, columns = calendar month. Darker = more trades. Pure count of congressional_trades.traded_at.

Latest Events

Live feed of things happening right now: politicians trading stocks, governments handing out contracts, sanctions, lawsuits, big stock moves. The colored dot shows the type.

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Score Rankings

The most politically-exposed companies right now. Higher number = more risk. Click any row to drill in.

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Data Source Status

Where the data comes from. Green = working. Yellow = data is getting old. Red = something broke.

Who's the most politically exposed right now?

Every public company, ranked by risk score (0 = calm, 100 = on fire). Switch the dropdown to sort by sub-score: Market (price/volume action), Policy (government activity), or Insider (congressional trades + executive moves). Click any row to see what's driving the number. ⓘ

All Company Rankings

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# Ticker Name Sector Market Policy Insider Composite
No scores computed yet — run ingestion to generate data

Browse every company we track

The full universe of public companies MRDN monitors. Filter by sector to narrow it down, then click a card to see that company's score history, recent events, and political connections.

Companies

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Everything MRDN knows about this company: current risk score and how it broke down (Market / Policy / Insider), score history over time, recent events that moved the number, and the political figures connected to it. Use this to understand why a company is hot — not just that it is.

What's driving the score

Top 5 contributors in each category within the current scoring window.

Insider trades

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Government contracts

None in window

Sanctions

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Political donations

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Market moves

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Score History

Timeline

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Entity Connections

Who's moving markets from inside government?

A curated watchlist of politicians whose votes, committee seats, and personal stock trades move markets. Where disclosures exist, cards show trade counts, tickers touched, and estimated volume — ordered by real activity, not seniority.

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Congressional Trading Accountability Scoreboard - click column headers to sort
# Name Party Score▼ Trades▼ Filing Lag▼ Committee▼ Round-trips▼ Pre-event▼

Political Figures

No persons data — run EFDS ingestion

What does the data actually say?

Three signals derived directly from real House Clerk PTR filings — no inference, no prediction, no fabrication. Pick a tab: who's breaking the law on disclosure timing, when reps cluster on the same ticker in the same week, and which stocks split or unite the parties.

Federal law requires members of Congress to disclose covered stock transactions within 45 days of the trade. Every row is the gap between when the trade happened and when it was actually filed — pure subtraction, no estimation.
Trades scored
Median latency
days
Filed late (>45d)
%
trades
Worst single trade
days late

Worst offenders

No latency data — run go run ./cmd/mrdn ingest-house-trades
# Representative Trades Median P90 % late Worst Worst ticker
Source: House Clerk Periodic Transaction Reports. Latency = days between transaction date and filing date. The 45-day threshold comes from the STOCK Act of 2012 (Pub. L. 112-105). Trades missing either date are excluded.
A swarm is when ≥4 distinct representatives traded the same ticker in the same calendar week. Bucketed by ISO week, ordered most-recent first. This is one of the few times you can watch politicians visibly converging on a single stock.

Swarm clusters

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Week of Ticker Reps Trades Buys Sells R / D Who
Buckets are ISO calendar weeks. A "rep" is a unique person_id; a "trade" is a row in congressional_trades. Tickers like "--" or empty are excluded.
For each ticker bought by ≥4 representatives, who got there first? The follower lag is computed in days from the first congressional buy. This is chronology, not causation — but it's the closest you can get to "who tipped off whom" using public disclosures alone.

First in

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Fast flips — purchases sold within a short window. Each row pairs a buy with the very next sale of the same ticker by the same rep. No inference of intent — just the calendar gap and the disclosed dollar amounts. Short holds with large dollars are the ones worth reading twice.

Fast flips

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Representative Ticker Held Bought Sold Buy $ Sell $
Showing buys ≥ $15K with the next sale within 60 days. Buy/sell dollar amounts are midpoints of the disclosed STOCK Act ranges — actual amounts may be higher or lower within the disclosed bracket.
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Co-Trader Network

Representatives connected by shared trading activity within 14-day windows. Thicker lines = more tickers traded in common.

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No co-trading relationships found. Ingest trade data to populate the network.

Drag nodes to reposition. Scroll to zoom.

Which stocks does Congress actually trade?

Every public company touched by a House Clerk PTR filing, ranked by how many distinct representatives have bought or sold it. Click any ticker to see who, when, and how much. Bipartisan crowd-favorites at the top.

Top Tickers

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Ticker Sector Reps Trades Buy $ Sell $ R buyers D buyers Last trade
Buy/sell dollar amounts are midpoints of the disclosed STOCK Act ranges. R/D columns count distinct buyers per party — Independents and unflagged reps are excluded from those columns only.
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Is the data fresh, stale, or broken?

Every ingestion source MRDN runs — recency, latency, HTTP error codes, and last-error details. Down or degraded sources show in red; stale sources in yellow. Individual dashboard cards also reflect their own freshness.

Ingestion Sources

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Traded Rep Ticker Side Amount Filed
Ticker Name Subsector