We Backtested Every Member of Congress. Exactly One Beat the S&P 500

Congress trading is now its own cottage industry — copy-trading accounts, newsletters, even ETFs — and the premise behind all of them is that members of Congress know something. Maybe they do. The question nobody seems to run properly is whether you could have made money from it — buying when the filing became public, which is the only moment you could have acted.

So we ran it on all of them.

153 members. 19,667 disclosed buys. Entry at the first opening price after each filing went public. Same rules for everyone, no cherry-picking, no hindsight about who turned out to be interesting.

The result

One member out of 153 finished ahead of a plain index fund, by nine points. The other 152 did not, and the typical one trailed the S&P 500 by more than 200 percentage points.

The single most famous name in congressional trading is in the losing group. More on that below.

Is this just a data artifact?

Fair question, and we asked it first, because a previous version of this leaderboard was an artifact and we had to throw it away.

Some members disclose so many trades at once that a simulated account can't fund all of them, and the ones it skips are dropped. If the skipping is uneven, the ranking measures truncation rather than skill. So we re-ran the whole thing restricted to members whose simulation actually filled at least 80% of their disclosed buys:

Near-identical, and if anything the well-covered group looks slightly worse. The conclusion survives the filter, which is what makes it worth publishing.

For the record, this run priced 89.5% of all disclosed buys (17,605 of 19,667). The rest are tickers with no available price history — mostly delisted names and one-off obscurities.

Why 153 and not 318

Congress has far more members than this, and 318 appear in our filings. Three rules cut it down, all deliberately:

• At least three disclosed buys. 124 members fall out here. Ranking someone on one or two trades is ranking a coin flip.
• At least three years of history. Another 33 fall out. This one we added after an earlier version of this article, because the board was publishing a member who had one day of history — eight buys that became public the day before the board was computed, showing +0.03% against the index. Enough trades in no time at all is not a track record.
• At least three positions the simulation could actually fill. Another 8. Disclosed buys and copied positions are not the same number: a member can disclose five and have one priced, and one fill is not a strategy.

Three years was picked by measuring what each threshold costs, not by taste: one year admitted members whose entire record was a few weeks, and five removed a further chunk of the field without changing which members came out on top. Three spans at least one full market cycle, which one year does not.

All three exist because the same mistake kept appearing on a different axis: enough of one thing, none of another.

Worth stating plainly: every one of those thresholds makes our own headline worse. Fewer members beat the index, and the median trails further. That is what tells you the filters aren't there to flatter the result.

What the numbers are, and what they aren't

This matters more than the headline, so it goes above the fold rather than in the footer.

These numbers are the second version, and the first one was wrong.

An earlier draft of this article reported far higher returns — Nancy Pelosi at +340%, Josh Gottheimer at +514% and "one of only 13 members who beat the market". It also carried a confident explanation for why the simulated drawdowns were so small: the portfolio was mostly in cash, so it couldn't fall far.

Both were wrong, and they were the same bug. One planned entry whose ticker had a dead price series — a company renamed years earlier, leaving a stub — blocked every entry queued behind it. Accounts froze for years, then executed the entire backlog at original prices with current cash, booking years of appreciation risk-free. The flat equity curve I read as "mostly in cash" was an account that had stopped trading.

With it fixed, the same portfolios run 38% to 98% invested with maximum drawdowns of 24% to 41% — an ordinary equity strategy, and a far worse one. We are leaving this paragraph in rather than quietly restating the figures, because a page that publishes returns should show its corrections.

The win rates are flattering by construction. A position is only scored win-or-lose once the member sells it and the simulation mirrors that exit. Positions nobody ever closed stay open and never count. Since people are famously more willing to sell winners than losers, a high win rate describes the trades a member chose to close — not their judgement.

Options are modelled as shares. A filing gives a ticker, a date and a dollar band. It gives no strike and no expiry, so an option purchase cannot literally be copied. We buy the underlying instead. Across the whole corpus that's a rounding error — 1.6% of buys — but for two well-known members it isn't: Nancy Pelosi at 30.7% and Tommy Tuberville at 25.1%. For those two, a meaningful slice of the copied book is a leveraged bet flattened into a plain share purchase. It reflects what a reader could actually have done. It does not reflect what the member did.

Amounts are bands, not sizes. Every position is equal-weighted at 5% because the filings genuinely do not say how much was bought.

Why the lag is the whole game

Members have 30 to 45 days to report. The median gap between trade and disclosure is 28 days, and one in five transactions breaks the 45-day limit entirely — 8% surface more than a year later.

So a headline like "member X made 60% on this stock" is describing a return that began at a price you were never offered. By the time the document is public, the first move has usually happened. Every number on this page starts from the filing date for that reason.

Nancy Pelosi trailed the index

The most-followed portfolio in American politics returned 80.2% in this simulation against the S&P 500's 356.3% over the same window — 276.0 points behind, which ranks her 96th of 153.

An earlier version of this article had her 16th and 15.9 points behind. That was the fill-queue bug above; on the corrected engine she is mid-table.

Two caveats specific to her, both stated above and both load-bearing: 30.7% of her disclosed buys were options modelled here as shares, and 110 of the 128 transactions on her filings belong to her spouse. The filings are joint; the trading is not hers alone.

So should you copy Congress?

On this evidence, following a member at random is worse than an index fund essentially every time. That's the finding that generalises, and it got stronger every time we fixed a bug in our own engine.

Whether following a specific member is worth it is a different question, and the honest answer is that picking the right one in advance is the entire problem. The one member who beat the index is identifiable only in hindsight, and by nine points. Nothing here says it will be the same member next year, or that there will be one.

What the data does support, less excitingly: congressional filings are a source of ideas with a timestamp, not a signal with an edge. Treated that way — as a screen to investigate rather than a trade to mirror — the lag matters less and the absence of an edge matters less too.

Run it yourself

The board, every member's fill count beside their return, and the option to combine several members into one strategy: congress trading backtester.

The fine print

Simulation runs on daily closes from the first open after each filing became public, 5% of equity per position, mirroring the member's own disclosed exits. It runs on adjusted closes, so dividends are reinvested; it excludes taxes and market impact, and charges no commission. It can only price still-listed or historically-covered tickers (89.5% of disclosed buys here). Past performance predicts nothing, this is educational analysis and not investment advice, and none of it is a claim about any individual's conduct — only about what a mechanical copy of public filings would have returned.