Corruption Risk · 4-Vector Breakdown
Corruption isn't just trade-based. Here's the four ways political pressure can flow, scored independently from the public record.
Vector 1 · Personal Enrichment trade-based
The politician's trading is defined by a high-frequency, sector-concentrated accumulation pattern, with 1,083 purchases against 240 sales per `get_sponsor_profile.profile.trade_pattern`. Despite a poor overall win rate of 42% (`get_politician_intelligence.profile.win_rate_overall`), he exhibits significant sector-level outperformance anomalies. His energy, technology, healthcare, finance, and industrials sectors all show win rates 10.6 to 17.3 points above his overall rate, on trade counts ranging from 84 to 236 (`PRE-COMPUTED SECTOR ANOMALIES`). This suggests specialized, committee-aligned knowledge drives these concentrated bets, even as his broad portfolio underperforms with a -15.7% average excess return (`get_sponsor_profile.profile.trading_style`).
Trades 5y1,341
Volume$77.8M
Late filing—
Trader typeActive self-dealer
Vector 2 · Donor Funding money in
PAC support is broad (549 PACs) and dominated by franchise, insurance, agriculture, and energy interests (`get_sponsor_profile.profile.donor_base`). Top PAC industries by dollars are corporate_other (34.2%), trade_association (11.3%), and energy (7.5%) (`get_donor_industry_breakdown.top_industries`). Total PAC direct contributions over the period are $18.1M (`get_donor_industry_breakdown.total_pac_direct_usd`).
PAC raised$18.1M
Individual—
Donors10
Vector 3 · Committee Pressure lobbying around
Energy and franchise industries, via PAC contributions ($1.36M from energy PACs) and direct donor ties, coupled with jurisdiction over tax policy affecting these sectors (`get_donor_industry_breakdown.top_industries[2]`, `get_sponsor_profile.profile.top_pac_industries`).
energy
236 trades in energy sector with 58.1% win rate vs 42% overall (`PRE-COMPUTED SECTOR ANOMALIES`)
↳ Committee jurisdiction (Ways and Means) over tax policy affecting energy companies, combined with high trade count (236) and win rate (58.1%) in the sector
healthcare
172 trades in healthcare sector with 56.7% win rate (`PRE-COMPUTED SECTOR ANOMALIES`)
↳ Health Subcommittee membership combined with 172 trades and 56.7% win rate in healthcare sector
Top influence channels
PAC contributions
corporate_other
$18.1M
Lobbying spend targeting committees
Not specified
$2.7M
12 MONTHS PAST · 3 MONTHS FUTURE
Activity timeline · 357 votes (12mo) · 200 on passage · 95% with party on passage votes · 1 against
Votes/wk (top band)
with party
against party
present / unknown
Vote markers (passage only)
yea (with party)
nay (with party)
against party
Trades
buy
sell
Bills sponsored
★ introduced
Predictions / pipeline
model fire
committee bill
🔮 GOVGREED FORECAST · 30-DAY WINDOW
Predicted next trades · 25 active
Recent Activity
Voting Pattern
Voting attendance is 100% on 75 recent votes (`get_voting_record.attendance_pct`, `get_voting_record.total_votes`). Recent high-profile votes show support for suspension motions and passage of bills like HR.2493 and S.1020, with occasional nays on motions to recommit or passage (`get_voting_record.recent_high_profile_votes`).
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