Congress Lobbying × Trades Overlap

Cross-reference US federal lobbying disclosures with Congressional stock trading disclosures — one auditable record per overlap.

This actor joins two public disclosure systems that don't share keys: quarterly lobbying filings under the Lobbying Disclosure Act (LDA) and member stock transactions disclosed under the STOCK Act (PTR filings). It surfaces same-quarter co-occurrence: a member traded in sector X during a quarter in which sector X was the subject of lobbying activity — and, where the member sits on a committee with jurisdiction over that sector, it says so.

Every output row is traceable to specific filing IDs and source URLs. This is a records product: it reports what the filings say, in a form you can archive, query, and verify. It does not score, rank, or interpret.

An overlap is not a finding of wrongdoing. Members of Congress trade securities and industries lobby Congress; both are legal, disclosed, and continuous. Co-occurrence within a quarter is a factual observation about two public datasets, nothing more. This actor makes no claim of causation and emits no trade recommendations.

Works as a companion to the House Trading Pipeline and the Senate Trading Pipeline — it reads their trade data directly, so records stay consistent across all three.

What you get

One record per (member, quarter, sector) overlap — not one per trade, not one per filing. Each record bundles the full evidence on both sides:

{
  "member_bioguide_id": "A000379",
  "member_name": "Mark Alford",
  "chamber": "house",
  "party": "R",
  "state": "MO",
  "quarter": "2026-Q1",
  "sector": "defense",
  "mapping_rule_id": "tk:LMT->defense",
  "mapping_confidence": "high",
  "overlap_type": "committee_match",
  "disclosure_lag_days": 30,
  "trades": [
    {
      "ptr_filing_id": "4d6016b4...",
      "ptr_url": "https://disclosures-clerk.house.gov/...",
      "ticker": "LMT",
      "transaction_type": "purchase",
      "amount_range": "$1,001 - $15,000",
      "transaction_date": "2026-01-05",
      "disclosure_date": "2026-02-04"
    }
  ],
  "lobbying": [
    {
      "lda_filing_uuid": "7866327b-c892-4430-b9f0-1f0f679c58c6",
      "lda_url": "https://lda.senate.gov/api/v1/filings/7866327b-.../",
      "registrant": "Example Government Affairs LLC",
      "client": "Example Defense Corp",
      "issue_codes": ["DEF", "BUD"],
      "amount_reported": 240000.0
    }
  ],
  "lobbying_filing_count": 38,
  "committees": [
    {
      "committee_id": "HSAS",
      "committee_name": "House Committee on Armed Services",
      "jurisdiction_tags": ["defense", "aerospace"],
      "is_subcommittee": false,
      "role": "Member"
    }
  ]
}

overlap_type

• committee_match — the member sits on at least one committee whose jurisdiction covers the overlap sector. The matched committee assignments are included as evidence.
• sector_match_only — the sector overlap exists, but no committee link does.

LDA filings disclose which chamber or agency was lobbied, not which committee — so committee matching is resolved through sector jurisdiction, and the record shows exactly which committee and which jurisdiction tag produced the match.

lobbying_filing_count

Popular sectors can attract over a thousand filings in a quarter, so the lobbying[] evidence list is capped (default 100, configurable) to the filings with the largest reported amounts. lobbying_filing_count always carries the uncapped total — truncation is visible on the record, never silent.

disclosure_lag_days

Days between a trade's transaction date and its public disclosure date (earliest trade in the record). A factual, derived field — the STOCK Act allows up to 45 days.

The crosswalk is yours to audit

There is no official mapping between LDA issue codes, stock tickers, and committee jurisdictions. Every product in this space invents one — most keep it hidden. This one ships in the open, in the repo, as hand-editable YAML:

• data/crosswalk.yaml — all 79 official LDA general issue codes → sectors, plus ticker → sector rules (explicit per-ticker overrides and a GICS-sector fallback)
• data/committee_jurisdictions.yaml — every current House, Senate, and joint committee → jurisdiction sectors

Every mapping row carries a confidence grade (high / medium / low), and every output record names the exact rule that fired (mapping_rule_id, e.g. ic:HCR->healthcare, tk:LMT->defense, com:HSAS->defense). If you disagree with a mapping, you can see it, trace it, and change it — the run summary also lists every issue code, ticker, and committee the crosswalk could not resolve, so nothing is silently dropped.

If you build on this data, you know exactly what joined to what and why. That is the point.

Data sources

Source	What it provides
Senate LDA REST API (lda.senate.gov)	Quarterly lobbying filings: registrant, client, issue codes, reported amounts
House / Senate trading pipeline actors	Member stock transactions from PTR filings
unitedstates/congress-legislators	Member roster and committee membership (cached, refreshed monthly)

All sources are official or community-maintained public records. No scraping of third-party aggregators.

Input

Field	Type	Default	Description
quarters	array	last completed quarter	Quarters to cover, e.g. ["2026-Q1"]
chambers	array	["house", "senate"]	Which chambers to scan
overlap_types	array	both	Filter to committee_match and/or sector_match_only
lda_api_key	secret	—	Optional. The actor ships with a shared key sufficient for typical runs. Provide your own free key from lda.senate.gov for heavy multi-quarter backfills or guaranteed throughput.
max_concurrency	integer	5	Outbound API concurrency
lda_max_pages	integer	—	Debug cap for cheap test runs

Run summary

Every run — including runs that find zero overlaps — writes a RUN_SUMMARY to the key-value store: quarters covered, members scanned, overlap counts by type, every unmapped code/ticker/committee/name, and source freshness timestamps. A quarter with no overlaps is itself a fact worth recording.

How to use

Apify Console (no code): open the actor, pick your quarters, run. Results land in the dataset; export as JSON, CSV, or Excel.

API:

curl -X POST "https://api.apify.com/v2/acts/seralifatih~congress-lobbying-trades-overlap/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"quarters": ["2026-Q1"], "chambers": ["house", "senate"]}'

Scheduled: lobbying data is quarterly by law. A quarterly schedule a few weeks after each LDA filing deadline (Jan 20, Apr 20, Jul 20, Oct 20) keeps a complete archive with four runs a year.

Pricing

Predictable per-run pricing. A small flat start fee plus a fixed charge per quarter processed — you know the exact cost before you run, because you choose the quarters in the input. One quarter or eight, the bill follows your selection, not the number of overlaps found. A run that returns zero overlaps still delivers the run summary and the negative result, which for archival use is an answer, not a failure.

Tech

• Python 3.11, fully async (httpx, bounded concurrency)
• Strict pydantic v2 output schema — every record validated before it reaches the dataset
• Retry with exponential backoff and explicit timeouts on every external call
• Committee membership and member roster cached between runs (they change per-Congress, not per-run)

Limitations

• Federal only. State-level lobbying is out of scope.
• Quarterly granularity — that is the resolution the LDA imposes; nothing here is or can be real-time.
• Sector mapping is inherently judgment-laden. The crosswalk exposes every judgment it makes (mapping_rule_id, confidence) so you can audit or override them, but no mapping of tickers and issue codes to sectors is beyond argument.
• Trades without a listed ticker (real estate, private funds, bonds) are excluded and counted in the run summary.

Disclaimer

This actor republishes and cross-references public disclosure records. An overlap record documents that two disclosed activities occurred in the same quarter and sector — it is not evidence of impropriety by any person, and must not be presented as such. Nothing in this actor's output is investment, legal, or any other kind of advice.