Congress Trading ETFs: NANC vs KRUZ
Two ETFs let you mirror congressional stock trades — NANC tracks Democrats, KRUZ tracks Republicans. NANC returned +35% in 2024. KRUZ returned +18%. But both are built on disclosures that arrive 45+ days late. Here is what the data actually shows — and what signal intelligence adds beyond passive replication.
What Are Congress Trading ETFs?
Congress trading ETFs are exchange-traded funds that attempt to replicate the stock portfolios of members of Congress. The concept is straightforward: if senators and representatives consistently outperform the market — and GovGreed's data shows many do — then mirroring their trades should capture some of that excess return.
Two funds currently exist. NANC (the Unusual Whales Subversive Democratic Trading ETF) mirrors trades disclosed by Democratic members of Congress. KRUZ (the Unusual Whales Subversive Republican Trading ETF) does the same for Republicans. Both were launched in February 2023 by Subversive ETFs, using trade data sourced from Unusual Whales. Together, they were the first ETFs to directly package congressional STOCK Act disclosures into a tradeable investment product.
The underlying premise has merit. Across GovGreed's database of 189,595 STOCK Act filings from 343 politicians spanning 2012–2026, certain politicians demonstrate statistically significant excess returns. GovGreed's backtest data shows that A+ tier signals achieve a 72.7% win rate with +10.7% average 30-day excess return. But the ETFs face a structural problem that limits how much of that edge they can capture: the STOCK Act disclosure delay.
Both NANC and KRUZ are managed by Subversive ETFs (subversiveetfs.com) and use trade data from Unusual Whales. GovGreed is an independent platform that provides its own analysis of the same public STOCK Act filings. An academic study published in ScienceDirect has analyzed the performance characteristics of these ETFs.
See the individual trades that make up NANC and KRUZ — before the ETFs rebalance.
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NANC vs KRUZ: Head-to-Head Comparison
The two congress trading ETFs differ significantly in sector allocation, top holdings, and performance. NANC's heavy technology weighting has driven higher returns in bull markets, while KRUZ's diversification across energy, financials, and industrials provides a more balanced exposure.
| Feature | NANC (Democrat) | KRUZ (Republican) |
|---|---|---|
| Full Name | Unusual Whales Subversive Democratic Trading ETF | Unusual Whales Subversive Republican Trading ETF |
| Launch Date | February 2023 | February 2023 |
| Expense Ratio | ~0.75% | ~0.75% |
| Top Holdings | NVDA (8.9%), MSFT (8.0%), AMZN (5.2%) | JPM (4.3%), T (2.9%), FIX (2.9%) |
| Sector Weight | Tech-heavy (NVDA, MSFT, AMZN dominate) | Balanced (energy, financials, industrials) |
| 2024 Return | +35% | +18% |
| Annualized Return | ~27% | ~13% |
| 2026 YTD | -4% | ~-3% |
| Data Source | Unusual Whales (STOCK Act filings) | Unusual Whales (STOCK Act filings) |
| Disclosure Delay | 45+ days (STOCK Act mandated) | 45+ days (STOCK Act mandated) |
NANC's 2024 outperformance (+35% vs S&P 500's +25%) is largely attributable to its concentration in NVDA, MSFT, and AMZN — the same megacap tech stocks that drove the broader market rally. Democratic members of Congress, including Nancy Pelosi, have been among the most active technology stock traders in Congress. KRUZ's more diversified allocation reflects Republican members' heavier exposure to energy, defense, and financial services sectors.
Why ETFs Have a Disclosure Delay Problem
The core limitation of any congress trading ETF is the STOCK Act's 45-day disclosure window. When a senator buys NVDA on January 1, the public may not learn about it until February 15 — or later. Across GovGreed's database, 23,426 trades (12.5%) were filed beyond even the 45-day deadline. The average disclosure gap across all 343 trading politicians is 44.9 days. The worst single filing gap in the database is 997 days.
This means NANC and KRUZ are systematically rebalancing on information that is 6 to 12 weeks old. In fast-moving markets, that delay can mean the difference between capturing an edge and buying at the top. An academic study published in ScienceDirect analyzing these ETFs found that the disclosure lag significantly erodes the informational advantage that makes congressional trading profitable in the first place.
The timing gap: ETFs react to disclosures. By the time a congress trading ETF rebalances around a politician's trade, that trade is already 45+ days old. The market has often already priced in whatever information drove the original decision.
Consider Tommy Tuberville, who has 132 STOCK Act violations — trades disclosed far beyond the 45-day window. An ETF tracking his trades would be rebalancing on data that is months stale. The same pattern applies across Congress: 12.5% of all trades are filed late.
The disclosure delay creates a structural disadvantage for passive ETF replication. To address this, GovGreed's approach focuses on prediction rather than replication. Instead of waiting for disclosures, GovGreed analyzes committee schedules, recurring buy patterns, signal convergence, and bill-trade correlations to forecast trades before they appear in STOCK Act filings.
What GovGreed Adds Beyond an ETF
Congress trading ETFs copy trades blindly — every disclosed purchase gets added to the portfolio, regardless of context. GovGreed takes the opposite approach: scoring each trade against the full intelligence stack — bills, donors, lobbyists, committees, herds — to separate signal from noise, then predicting future trades before they are disclosed.
- 7-Layer Signal Scoring: Each trade is scored across politician quality, herd behavior, bill correlation, technical context, sector momentum, campaign contributions, and lobbying alignment. ETFs treat a $5,000 trade by a freshman representative the same as a $500,000 trade by a committee chair — GovGreed does not.
- Herd Signal Detection: When 3+ politicians buy the same stock within a short window, GovGreed flags it as a herd signal. The database currently tracks 31 herd signals. ETFs have no mechanism to detect coordinated buying.
- Bill-Trade Correlation: GovGreed cross-references trades against 256,112 bill-trade correlations to identify when politicians trade stocks affected by legislation they are writing or voting on. ETFs do not track legislative activity at all.
- Predictive Intelligence: Rather than waiting for disclosures, GovGreed maintains 819 active predictions from 4 separate engines (committee markup, pattern analysis, signal bridge, and bill correlation) covering 76 politicians. Backtest data shows A+ tier signals achieve a 72.7% win rate with +10.7% average 30-day excess return.
- Real-Time Alerts vs Quarterly Rebalance: GovGreed sends alerts when new filings appear, when herd signals fire, or when signal scores cross threshold tiers. ETFs rebalance on a periodic schedule, missing the time-sensitive nature of trade intelligence.
Performance Analysis: Congress vs the Market
The question behind both ETFs and platforms like GovGreed is the same: do members of Congress consistently outperform the market? GovGreed's backtest data, derived from 189,595 trades across 14 years, provides a nuanced answer.
Not all congressional trades are equal. GovGreed's signal engine filters out small trades (below $50,000 midpoint), exercises, donations, and other low-information transactions. The resulting 2,790 scored signals across 61 politicians represent the highest-conviction subset of congressional trading activity. This selective approach is fundamentally different from ETFs that replicate every disclosed trade regardless of size, context, or quality.
The data also reveals an important nuance: NANC's outperformance is largely a tech sector story. Democratic members of Congress — particularly those on committees overseeing technology regulation — are among the heaviest tech stock traders. When tech rallies, NANC benefits. When tech corrects (as in early 2026), NANC underperforms. GovGreed's sector-agnostic signal scoring avoids this concentration risk by evaluating trades on their own merits rather than aggregating by party affiliation. Not financial advice.
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About This Data: ETF performance figures sourced from public market data providers and fund disclosures. Congressional trading statistics from GovGreed's database: 189,595 trades, 343 politicians, 14 years (2012–2026). Signal backtest statistics from our backtested-performance methodology. GovGreed is not affiliated with Subversive ETFs or Unusual Whales. Not financial advice. All congressional data from public federal disclosures.