The Disclosure-Lag Trap: Why Following Congress Doesn't Work

An industry built on seeing what politicians see

The Stop Trading on Congressional Knowledge Act of 2012 was meant to deter insider trading by members of Congress and their families by requiring public disclosure of every individual security trade within 45 days. The premise was accountability. Within a few years, the disclosure feed itself became a product. Capitol Trades aggregates the filings into a clean searchable database. Quiver Quantitative monetises the same data behind a subscription paywall. Unusual Whales pushes filings to options-trading retail. r/WallStreetBets has long-running threads dedicated to Nancy Pelosi's portfolio.

The two pure-play ETFs are the clearest expression of the thesis. Subversive Capital's Unusual Whales Subversive Democratic Trading ETF (ticker NANC) launched in February 2023 to systematically mirror Democratic members' trades. Its Republican counterpart, KRUZ, does the same for Republican filings. Both charge 0.75% in annual fees. Both pitch themselves on the implicit claim that congressional trading contains information that retail investors can profitably follow.

This report tests that premise against the data. The conclusion is that the disclosure-following industry is selling a structurally broken product. Not because politicians have no edge, but because the disclosure machinery destroys any edge that might exist before the public can act on it.

By the time you see the trade, it is nearly a month old

The first problem with disclosure-driven strategies is the disclosure timeline itself. The STOCK Act allows up to 45 days between trade execution and public filing, and members routinely use most of that window. Across 29,071 valid disclosures in this dataset, the median lag from trade to disclosure is 27 calendar days. The mean is 31 days. Roughly one in fifteen filings (6.8%) exceeds the 45-day statutory limit, with the worst offenders disclosing months late.

The implication for any disclosure-driven strategy is direct. A signal triggered by a politician's filing is, on average, reacting to information that is already four weeks old. Whatever price impact the original trade might have had through information leakage, order flow, or follow-the-smart-money behaviour, that impact has had four weeks to play out in the open market before anyone outside the politician's circle can see it. The follower buys at a post-leak price, not the politician's price.

The same mega-caps everyone else already owns

Even setting the disclosure lag aside, the second problem is the universe of stocks Congress actually trades. If congressional members held genuine informational advantages, you would expect their high-conviction herds to concentrate in less-followed securities where private information is more likely to matter. Instead, the data shows the opposite. The most herded names in the 2023 to 2026 sample are Microsoft, Apple, Google, Nvidia, JPMorgan, and Amazon. These are the most analysed equities in global markets. There is no information edge to be had in MSFT that is not already priced into a stock owned by every index fund on earth.

The party composition reinforces the point. Of the 389 herding events with complete party data at the primary threshold, 88% involve both parties buying simultaneously. There are essentially no exclusively Democratic or exclusively Republican high-conviction herds. Whatever drives the herding, it is not partisan-specific information. Both sides of the aisle converge on the same large-cap names independently, which is what you would expect if the underlying behaviour were a function of mainstream financial advisor recommendations and brand-name familiarity rather than committee-jurisdiction or insider channels.

Largest individual herding events

10-day excess returns by sector

Even the politicians do not beat the market

The standard pushback against disclosure-lag critiques is that politicians clearly profit from their trades, and even if the public misses some of that gain, what remains might still be a worthwhile signal. To check this realistically, the analysis maps each individual politician's buy trade within a herd to their subsequent sell trade for the same stock, or marks it to market if the position is still open. We then compare the politician's exact holding period return against what a follower would earn by mirroring the exact same entries and exits, but delayed by the disclosure lag.

Over the median 26-day initial lag window, the herded stocks rose +2.8% in absolute terms. That sounds informative until you compare against the market. SPY rose +3.1% over the same windows. The herded stocks actually underperformed the index by -0.3% during the politicians' own initial holding window. Only 47.7% of these stocks beat SPY during the lag period, meaning 52.3% underperformed even before any follower could enter.

The cumulative P&L chart above models the total nominal profit if you had allocated $1,000 into every congressional stock pick over their exact holding periods. Across 449 such trades, politicians generated $58,504 in aggregate profit. A hypothetical follower mirroring those exact trades but entering on the disclosure date would make $55,011. However, allocating those exact same dollars into the S&P 500 (SPY) over the identical holding periods generated $64,540.

What this means is that the disclosure-follower is not missing alpha. They are missing a chunk of pure market beta. Congress is buying stocks that go up because the market goes up, not because their picks beat the market. In fact, politicians underperformed SPY in absolute dollars. NANC and KRUZ simply deliver a beta-heavy, mega-cap-tilted basket dressed up as an information-based product.

No edge where you would expect one to actually exist

If congressional alpha exists anywhere, the strongest theoretical case is jurisdiction-specific information. Members on the House Financial Services Committee see proposed banking legislation before the public. Senate Armed Services members see defense procurement details. House Energy and Commerce members see EPA rule-makings months in advance. This is the academic literature's main remaining defense of the politician-trading thesis, and it is testable.

For each herding event in the primary sample, the analysis joins to congress-legislators committee-membership data (184 of 201 trader names matched, 91.5%). An event is flagged "in-jurisdiction" if the ticker falls in the committee's sectoral jurisdiction and at least one herd member sits on that committee. The cleanest test cohort is Information Technology, where 148 herd events involve members on Judiciary, Commerce, or Oversight committees with technology jurisdiction. Those in-jurisdiction tech herds posted mean 10-day excess returns of +0.0%. The same members buying outside their committee's jurisdiction did slightly better, at +2.0% mean excess.

The cleanest reading is that there is no detectable jurisdiction-specific edge in the data where the data permit a test. Members who sit on technology-related committees and herd into technology stocks do worse than when they herd into stocks outside their jurisdiction. This is the opposite of what an information-advantage hypothesis predicts.

NANC, KRUZ, and the products selling the story

Two ETFs operationalise the congressional-trading premise. NANC, launched February 2023 by Subversive Capital, tracks disclosed Democratic-side trades. KRUZ does the same for Republican filings. Both charge 0.75% annually. Both have over 22 months of post-inception data to evaluate.

The headline numbers tell two stories. NANC's +92.1% cumulative return narrowly beat SPY's +79.6% in absolute terms, but its risk-adjusted return (Sharpe +1.45) trailed SPY's +1.52. NANC took more risk to deliver a modestly higher return, which is consistent with a portfolio that overweights tech mega-caps. Tech crushed the market in 2023 and 2026. A portfolio that herds into the same names Congress herds into, also herds into the names that drove the bull market. That is sector beta, not informational alpha.

KRUZ is the sharper indictment. The Republican-tracking ETF returned +74.0% cumulative over the same period, trailing SPY by roughly 20 percentage points. Sharpe of +1.42 is significantly below SPY's +1.52. If congressional information were valuable, KRUZ should at minimum match the index. It does not. Investors paying 0.75% annually to follow Republican members' trades have underperformed by a margin that swamps the expense ratio many times over.

What you actually get from mechanically following the feed

Pulling everything together, the aggregate backtest mechanically buys every herding event on the first trading day on or after the disclosure date and holds for 10 days. Across 442 events with complete return data in the primary parameter set (3+ politicians, 30-day rolling window), the win rate is 48.6%. Mean 10-day excess return versus SPY is +0.1%. Sharpe is +0.12. The t-statistic of +0.50 is well within noise.

No parameter combination in the 4×3 sensitivity grid produces a meaningfully positive edge. Tightening the threshold to 4 or 5 politicians reduces the sample size to where any apparent signal is dominated by noise. Loosening to 2 politicians produces the largest samples but excess returns remain anchored near zero. Furthermore, even the tiny fractions of a percent of positive excess return seen in some cells would likely be entirely wiped out by bid-ask spreads, slippage, and trading commissions in a real-world retail environment. The structural conclusion from Section 04 plays out exactly as expected in the aggregate strategy result.

Just as noisy as the buys, with no edge to be found

The buy-side signal is conclusively null. Applying the exact same primary definition (3+ politicians, 30-day rolling window) to disclosed sales rather than buys produces 519 sell-herding events with complete 10-day returns. If politicians possessed genuine insider edge, we would expect stocks to underperform SPY following a sell herd as negative catalysts materialize.

Instead, the mean 10-day excess return after a sell-herd is +0.1%, with a 48.8% win rate and a t-statistic of +0.45. This means the stocks actually slightly outperformed the index after the politicians dumped them. The sell signal is just as noisy and devoid of alpha as the buy signal.

Even if there were a theoretical edge hidden in the noise, it could not be operationalised. The median 27-day disclosure lag means the news is nearly a month old by the time a follower can act. Furthermore, capitalising on a sell signal requires shorting individual equities, which carries borrow fees, recall risk, and tax inefficiency that would easily consume any marginal alpha. The wrappers tracking this space (NANC and KRUZ) are long-only and cannot even express these trades.

The literature has known this for over a decade. The industry keeps selling it anyway.

Eggers and Hainmueller (2013) examined 16 years of congressional trades and found that, on a portfolio-weighted basis, members of Congress earned returns indistinguishable from random selection within their stated investment universe. Belmont and Tilelli (2022) updated the analysis and reached substantially the same conclusion. The academic consensus has held for over a decade. The disclosure-tracking industry has not noticeably contracted in response. NANC and KRUZ launched in 2023 to the explicit pitch that they capture an edge that the literature already demonstrated does not exist.

The results in this report, built on 35,343 STOCK Act filings and 10-day forward returns across 442 high-conviction buy herds, are consistent with that consensus. The 27-day median disclosure lag is the proximate killer of any informational edge, but the deeper finding is that even at the politicians' own entry point, the herded stocks underperform SPY. There is no edge to be lost. The retail-facing wrappers (NANC, KRUZ, Pelosi-tracker subscriptions) are selling investors a beta-heavy mega-cap portfolio wrapped in a narrative about insider access.