Capitol Alpha Machine

Methodology & Data

How the machine reads disclosed congressional trading data.

One reference page for the project's sources, methods, current disclosure bundle, committee-risk heuristics, and caveats.

Sources

The primary trading source is Capitol Trades public disclosure data. Returns Spectrum combines the disclosure bundle with end-of-day market price signals. Policy Proximity also uses Congress.gov public-law listings for the 118th and 119th Congresses.

Disclosure window
2023-06-30 to 2026-10-28
Disclosures read
34,800
Buy/sell rows
34,662
Disclosed volume
$2.27B

Value ranges and volume

Congressional financial disclosures use reported value ranges, not exact order sizes. The project uses representative disclosed values for visual weight and ranking. Capital Flow separates scale from direction: gross disclosed volume sums buys and sells, while net flow treats buys as positive and sells as negative.

InputHow it is usedCaveat
Disclosed value rangesRepresentative values drive visual weight and summary tables.Not exact transaction accounting.
Gross disclosed volumeShows total public trading scale across buys and sells.Not profit, performance, or intent.
Net cumulative flowBuys are positive and sells are negative.Directional visualization only.

disclosed value; gross volume sums buys and sells; net flow uses buys positive and sells negative

Timing and sector heuristics

Committee exposure and Policy Proximity are triage heuristics. They are designed to help readers inspect patterns, not to make claims about motive or inside information.

These links are not allegations. They are not evidence of causation, intent, privileged information, or unlawful conduct. The project is data art and research context, not investment advice or a legal conclusion.

Caveats

Congressional financial disclosures are incomplete as a market dataset. Some transaction types are excluded from buy/sell flow, reported values are ranges, and disclosure timing can vary. The current bundle skipped exchange and received transaction types for flow math because they are not clean buy/sell signals.

Known limitationCurrent handling
Value rangesUse representative values for visualization.
Exchange / received rowsExcluded from buy/sell flow when not directionally comparable.
Anomalous dates2 rows skipped in the current flow bundle.
Timing linksPresented as proximity heuristics only.

Data

Current disclosure bundle

A crawlable summary of the public data currently bundled into the interactive scenes, generated on 2026-11-02.

Trading disclosure window
2023-06-30 to 2026-10-28
Disclosures
34,800
Buy/sell disclosures
34,662
Total disclosed volume
$2.27B
Returns rows
5,621
Public-law events
31

Capitol Trades public 3-year volume total, read 2026-06-14

Dataset windows and sources

BundleWindowRows / events
Trading disclosures2023-06-30 to 2026-10-2834,800 disclosures from 348 source pages
Buy/sell flow2023-06-30 to 2026-10-2834,662 directionally comparable rows
Returns Spectrum2023-07-05 to 2026-08-055,621 rows from 34,800 source disclosures
Policy Proximity2024-07-09 to 2025-08-1931 public-law events linked to 372 trades
SourceUse
CAPITOL TRADESPublic congressional trading disclosures and disclosed volume.
CAPITOL TRADES + EOD PRICESReturns Spectrum rows and trailing market movement context.
Congress.gov public laws + Capitol Trades committee-risk scrapePolicy Proximity event spine and sector/date proximity links.
Congress.gov public lawshttps://www.congress.gov/public-laws/118th-congress
Congress.gov public lawshttps://www.congress.gov/public-laws/119th-congress

Data use notes

This dataset describes an editorial visualization bundle derived from public disclosure sources. Original source records remain subject to their publishers' terms. Reuse should cite Capitol Alpha Machine and the underlying public sources, preserve the caveats about disclosure ranges and timing heuristics, and avoid presenting representative values as exact holdings, profit, intent, or evidence of wrongdoing.

Top tickers and members in the returns bundle

TickerRowsRepresentative disclosed value
MSFT137$154.8M
AAPL90$53.5M
JPM63$46.7M
NVDA113$32.7M
BMO21$17.8M
WMB4$15.5M
PRU5$15.1M
PUK1$15.0M
MemberRowsRepresentative disclosed value
Michael Mccaul1,483$172.7M
Joshua Gottheimer177$144.4M
Nancy Pelosi39$96.3M
Jefferson Shreve301$81.1M
Rohit Khanna1,485$51.4M
Cleo Fields168$21.9M
Kevin Hern58$17.5M
Alan Armstrong40$17.4M

These rankings use representative disclosed values inside the returns scene bundle. They are not a complete accounting of holdings, profit, or intent.

Committee Risk

Committee-risk proximity dataset

This aggregate links public-law events to disclosed trade rows using date proximity and sector proximity. Committee-sector overlap is a heuristic flag, not a claim of causation.

Event window
2024-07-09 to 2025-08-19
Public-law events
31
Linked trade rows
372
Committees
18
Members represented
35
Representative value
$46.6M
Scores and links are visualization heuristics only. They are not evidence of intent, privileged information, causation, profit, or unlawful conduct.

Top committees in the current aggregate

CommitteeRowsRepresentative valueMembersAvg riskAvg timingTop sectors
Intelligence34$33.2M28491information-technology, industrials, communication-services
Ways & Means4$4.1M17782financials
Commerce, Science & Transportation13$3.5M28592communication-services, consumer-discretionary
Homeland Security32$2.1M58389information-technology, communication-services, industrials
Armed Services74$1.3M48890industrials, information-technology, communication-services
Environment & Public Works13$378K57275energy, utilities
Appropriations39$361K88786energy, health-care, information-technology
Financial Services38$304K38591financials
Natural Resources37$296K17977health-care, materials, energy
Budget30$240K18895financials

Rows are aggregate only. Individual committee pages are not generated.

Risk flags

FlagRows
committee sector overlap351
repeat committee sector trades 90d326
owner spouse198
reporting gap 180d plus103
owner joint79
top 10pct value46
reporting gap 45d plus46
top 25pct value42

Flags describe why a row became visually prominent inside Policy Proximity. Read them as triage labels for inspection, not conclusions.