Is copying Nancy Pelosi's stock trades profitable?

In our sample of House stock purchases from 2021 through May 2026, no. She had 30 copyable stock buys, and copying them from the public filing date trailed the S&P 500 by about 0.72% per trade over 90 days. That put her almost exactly at the median of the 64 members with enough trades to rank. One important limit: her best-known trades are options, and our test covered only direct stock purchases, so this does not measure the trades she is most famous for.

Which member of Congress is the best to copy?

In our data the top performer was Tim Moore, whose 115 stock buys beat the index by 10.59% per trade. But we would not act on that. When we shuffled the same returns randomly across members while keeping each member's trade count fixed, pure chance produced a best-to-worst spread of about 13.5% routinely. Ranking 64 people and crowning the winner mostly identifies who got lucky, and last period's winner is not reliably next period's.

What share of Congress actually beats the market?

About 4 in 10. Of the 64 House members with at least 20 copyable stock purchases, 40.6% beat the S&P 500 on average over a 90-day hold. At a 30-day hold it fell to 35.9%. So picking a member at random and copying them gives you worse than even odds, which is roughly what you would expect if there were no widespread skill to find.

What is survivorship bias in copy trading?

It is what happens when you pick who to study after seeing the results. If you scan hundreds of members, notice one had a great couple of years, and then backtest that person, the strong result is partly built in before you start. Someone was always going to be at the top. The honest test is to define your rule first, apply it to everyone, and look at the whole distribution, which is what we did.

Do any members of Congress have real stock picking skill?

Possibly a few. The observed spread between our best and worst members was 22.9%, and random shuffling produced a spread that large less than 5% of the time, so the dispersion is a bit wider than chance alone explains. That is genuine evidence that some members differ from the pack. It does not tell you which ones in advance, and with 40.6% of members beating the index, the base rate is against you.

Why exclude options from a congressional trading analysis?

Options behave differently enough that mixing them into a stock backtest would produce a meaningless average. Leverage, expiry dates, and strike prices all change the return profile, and the disclosure forms do not give enough detail to reconstruct the position reliably. We restricted the test to direct stock purchases so every trade was measured the same way. It is a real limit on scope, and it means the most talked-about congressional trades sit outside our sample.

Copying Pelosi Stock Trades: What the Data Says

Search interest in copying congressional stock trades is dominated by one name. The apps are built around her, the tracker sites lead with her, and “what did Pelosi buy” is a recurring news cycle all by itself.

So when we backtested 8,329 House stock purchases from the public filings, we were curious where she’d actually land. The answer was the least dramatic one available. She landed in the middle.

Where does Pelosi rank among congressional stock traders?

At the median. Across 64 House members with at least 20 copyable stock purchases between January 2021 and May 2026, copying her stock buys from the filing date trailed the S&P 500 by about 0.72% per trade over a 90-day hold. That placed her 32nd of 64, almost exactly in the center of the distribution.

We want to flag the biggest limit on that number right up front, because it matters more here than anywhere else in this series. Her reputation rests largely on options trades, particularly long-dated call options. Our test covered direct stock purchases only. Options carry leverage and expiry that make them a different instrument, and the disclosure forms do not give enough detail to reconstruct those positions honestly. So this is not a measurement of the trades she’s best known for. It’s a measurement of her stock buying, alongside everyone else’s, on identical rules.

The whole distribution, not the winner

Here’s what 64 members looked like when we ranked every one of them:

	member	trades	vs S&P 500
best	Tim Moore	115	+10.59%
median	Nancy Pelosi	30	−0.72%
worst	Patrick Fallon	53	−12.31%

40.6% of them beat the index on average. At a 30-day hold that dropped to 35.9%.

That last figure is the one worth sitting with. If you picked a member of Congress at random and copied their stock purchases, you’d have had worse than even odds of keeping up with a fund that requires no research and no monitoring.

Someone is always at the top

Look at that table again and the obvious move is to ignore the median and copy Tim Moore. Plus 10.59% per trade across 115 trades is not a small sample or a small number.

This is exactly where copy-trading analysis usually goes wrong, and it’s worth being precise about why.

When you rank 64 people and select the best one, you are not just measuring skill. You’re also measuring luck, because the person at the top of any ranking is disproportionately likely to have had good luck on top of whatever ability they have. Backtesting that person afterward will look fantastic, because you chose them for having already looked fantastic.

The original plan we started from had this baked in. It named a specific representative as the primary pick, citing a strong prior-year return, and proposed backtesting him. That test could only confirm what selecting him had already guaranteed.

So we ran the check that separates the two. We took all 8,329 trade results, shuffled them randomly across members while keeping each member’s trade count exactly the same, and measured the best-to-worst spread you get from pure chance. Repeated 2,000 times.

	best-to-worst spread
pure chance, median outcome	13.48%
pure chance, 95th percentile	19.79%
what we actually observed	22.90%

The real spread does exceed what randomness produces, and we’re not going to overstate the null result. There is more dispersion among members than chance alone explains, which is real evidence that some of them genuinely differ from the pack.

But notice how much of that gap chance covers on its own. A 13.5% spread between best and worst shows up routinely with no skill involved anywhere. If you’d looked at a leaderboard, seen a 13-point spread, and concluded the top name had found something, you’d have been reading noise as signal.

And knowing that a few skilled members probably exist somewhere in a group of 64 does not tell you which ones. You’d be identifying them from the same past returns that chance inflates.

A few trades carry everything

The other thing hiding inside these averages is how lopsided they are.

	average vs S&P 500
all 8,329 trades	−0.71%
excluding the 10 best	−0.92%
excluding the 25 best	−1.09%
excluding the 100 best	−1.65%

Ten trades out of more than eight thousand move the overall average by a fifth of a percentage point. The top 1% of trades contribute more than the entire mean.

That’s a familiar pattern to anyone who’s looked at individual stock returns, and it’s the practical argument for owning a lot of things instead of a few. If a handful of outcomes drive the result and you can’t identify them ahead of time, holding everything is how you make sure you own them. We went through that logic in our three fund portfolio breakdown.

What we’d actually tell a friend

Following congressional trades is legitimately interesting. It’s public information about people who write laws affecting the companies they own, and paying attention to it is reasonable civic behavior.

Choosing a member to copy because their past numbers look good is a different activity, and the data doesn’t support it. Fewer than half beat the index, the most-followed name sits at the median, and most of the visible spread between the best and worst is the kind of variation randomness hands out for free.

The full test, including a portfolio result that briefly convinced us copying worked before we caught the flaw, is in our congress copy-trade backtest. We looked specifically at whether filing speed rescues the strategy in our piece on the disclosure lag. And if you want to track filings for their own sake, our guide to following congress stock trades covers the free options.

Standard caveats on our data. House filings only. Direct stock purchases only, so no options, ETFs, or bonds. And roughly 7% of buys were dropped for having no price history, usually because the company was acquired or delisted, which quietly removes bad outcomes and makes these numbers a little friendlier to copying than reality was.