US Congressional Trading — STOCK Act Disclosures (Senate + House)

DatasetCSV.GZOpenFinanceCongressSenateHouseStock ActAlphaAlternative DataFree

Every Senate and House Periodic Transaction Report (PTR) filed under the STOCK Act, as indexed by FMP. 10,100 Senate trades + 10,100 House trades = 20,200 transactions in 2 gzipped CSVs. Each row has the politician's name, party district, transaction date, disclosure date (often weeks/months later — that lag is itself a signal), transaction type (Purchase / Sale / Exchange), asset symbol, asset description, asset type (Stock, Option, Bond, Mutual Fund), amount range (STOCK Act bins like '$1,001 – $15,000'), spouse/dependent owner flag, comment, and a direct URL to the official PDF/HTML disclosure. Read with pandas.read_csv(path, compression='gzip', parse_dates=['transactionDate', 'disclosureDate']). Polymarket-trader catnip — track Pelosi, Crapo, Tuberville, et al. in near-real-time. Useful for: lawmaker-replication strategies, sector-rotation signals from committee members trading regulated industries, and detecting unusual transaction clusters around legislation.

Use Cases

Track high-profile politician trading (Pelosi, Crapo, Tuberville) in near-real-time
Lawmaker-replication portfolios as alpha strategies
Sector-rotation signals from committee members trading regulated industries
Disclosure-lag analysis (transaction → disclosure date gap as a signal)
Insider-cluster detection around major legislation

Methodology

Paginated senate-latest and house-latest from FMP until empty (~10-15K rows per chamber, history limited by FMP's index depth). Output sorted by disclosureDate desc.

Update Schedule

Static snapshot. New disclosures filed weekly — refresh quarterly to stay current.

Attribution

Source: U.S. Senate Office of Public Records + House Clerk Public Disclosure portal via Financial Modeling Prep.

Schema

name	type
firstName	string
lastName	string
office	string
district	string
transactionDate	string
disclosureDate	string
type	string
symbol	string
assetDescription	string
assetType	string
amount	string
owner	string
comment	string
link	string

Sample Data

link	type	owner	amount	office	symbol	district	lastName	senateID	assetType	firstName	disclosureDate	transactionDate	assetDescription
https://efdsearch.senate.gov/search/view/ptr/f8d003c0-ca1e-4c39-9d66-632d220180e1/	Sale	Spouse	$1,001 - $15,000	Sheldon Whitehouse	LRCX	RI	Whitehouse	W000802	Stock	Sheldon	2026-09-02	2026-08-13	Lam Research Corp
https://efdsearch.senate.gov/search/view/ptr/f8d003c0-ca1e-4c39-9d66-632d220180e1/	Sale	Spouse	$1,001 - $15,000	Sheldon Whitehouse	AMGN	RI	Whitehouse	W000802	Stock	Sheldon	2026-09-02	2026-08-12	Amgen Inc
https://efdsearch.senate.gov/search/view/ptr/f8d003c0-ca1e-4c39-9d66-632d220180e1/	Sale	Spouse	$1,001 - $15,000	Sheldon Whitehouse	NVDA	RI	Whitehouse	W000802	Stock	Sheldon	2026-09-02	2026-08-13	NVIDIA Corporation

Get this via API

# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
#    Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
#    Cursor / Claude Code / others: mcp.json
{
  "mcpServers": {
    "dagentbase": {
      "url": "https://dagentbase.com/api/mcp",
      "headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
    }
  }
}

# 2. Then ask your agent, in plain language:
#    "Preview 'US Congressional Trading — STOCK Act Disclosures (Senate + House)' and, if it fits, claim it and download the files."
#    Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urls

# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
#    Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
#    Cursor / Claude Code / others: mcp.json
{
  "mcpServers": {
    "dagentbase": {
      "url": "https://dagentbase.com/api/mcp",
      "headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
    }
  }
}

# 2. Then ask your agent, in plain language:
#    "Preview 'US Congressional Trading — STOCK Act Disclosures (Senate + House)' and, if it fits, claim it and download the files."
#    Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urls

Free

one time · open license

Details

Date Range1990-01-01 — 2026-09-05

Rows20,200

Size336.2 KB

Files2

FormatCSV.GZ

Available formats

CSV.GZ2 files · 336.2 KB

Freeopen