Why trading more makes results worse

One study put an exact number on this. It followed 66,465 households for six years and compared their returns by how much each one traded. The heaviest traders earned six and a half points a year less than the market. Not from picking worse: from trading more.

What the study on trading frequency found

Brad Barber and Terrance Odean, of the universities of California at Davis and Berkeley, analysed the accounts of 66,465 households at a large US discount broker between 1991 and 1996. They published the result in 2000 in The Journal of Finance, under a title summarising the conclusion: "trading is hazardous to your wealth."

The figures

Group	Annual return
The market	17.9%
The average household	16.4%
The households that traded most	11.4%

The average household came in a point and a half below the market. The heaviest traders came in six and a half points below.

And one figure setting the scale of "trading a lot": average portfolio turnover was 75% a year. Meaning the average household sold and replaced three quarters of what it held every year.

Why it happens

The explanation the authors themselves give is the bias from the previous session: overconfidence explains high trading levels, and those high levels explain the poor performance.

The mechanism isn't mysterious and you already know it in full from Chapter 3. Every trade pays spread, commission and, where currency is involved, conversion. None of that depends on being right. Multiply those costs by 75% annual turnover and the gap appears on its own, without any single decision having been bad.

It's Chapter 3's arithmetic applied to six years of real accounts.

The replication that rules out coincidence

A result from one broker in one country could be a quirk. The same authors, with Yi-Tsung Lee and Yu-Jane Liu, replicated it in 2007 across something far harder to dispute: the complete set of individual investors in Taiwan, not a sample.

The pattern repeated. It's the same market the course's first session drew its figures from, for the same reason: every trade there gets logged in full detail.

The uncomfortable finding about who trades more

The same researchers published work in 2001 under a title that became well known, "Boys Will Be Boys," on the relationship between gender, overconfidence, and results.

They found men traded 45% more than women and earned 1.4% less in risk-adjusted return. Among single investors, where no shared decisions soften the effect, the gap reached 2.3%.

The finding doesn't say women pick better. It says they traded less, and trading less turned out better — which is exactly the main study's conclusion seen from another angle.

If trading costs no commission today, does the study still hold?

It's the first question worth asking. That data runs from 1991 to 1996, when trading cost considerably more than today. If the problem was cost, and cost has vanished, the problem should have vanished with it.

Three reasons it hasn't.

Commissions fell, the other costs didn't. Chapter 3 broke out four of them and commission was the smallest. Spread still gets paid on every trade, currency conversion gets paid twice, and high turnover also brings the tax bill forward. A zero-commission broker eliminates none of the three.

The authors' explanation wasn't cost, it was overconfidence. Cost is the mechanism by which excessive trading does damage; the cause of excessive trading is the previous chapter's. Making the mechanism cheaper doesn't touch the cause.

And trading is far easier now than it was then. In 1996 it meant a phone call or a desktop computer. Today it's two taps on a phone, with notifications inviting you to look. If the cause was impulse, everything that has changed since pushes the wrong way.

The honest conclusion: the study measures an effect that today would be cheaper per trade and probably more frequent. Which of the two weighs more we don't know with equivalent data, and saying otherwise would be invention.

How FOMO and social feeds work on an investment decision

Fear of missing out is a normal, entirely human impulse. What has changed in recent years isn't the impulse: it's how many times a day something triggers it.

The figure

A 2023 study by the FINRA Investor Education Foundation and the CFA Institute, two organizations that train investors and analysts, found that 41% of investors aged 18 to 25 surveyed in the United States and Canada admitted to investing out of fear of missing out.

Four in ten, admitting it. It's reasonable to think the real number who did it is higher than the number who own up to it.

Why feeds amplify it

Through a mechanism with nothing to do with investing and everything to do with what gets published.

Only the wins get shared. Nobody posts a screenshot of the trade that went wrong. The result is a completely skewed sample: you see thousands of people's wins and none of their losses, so the impression you take away is that everyone is getting it right except you.

It's the survivorship bias we saw with funds in the course's first session, applied to people rather than products. And it has its own section, under its full name, in this chapter's final session.

And the urgency is constant. A market doesn't generate urgent opportunities every day, but a stream of posts does. That mismatch between the speed of content and the speed of sensible decisions is what pushes toward overtrading.

The check that cuts the impulse

One question, and it's the course's first session: can I explain this decision with concrete data, or is the reason that it's risen a lot and I don't want to miss out?

If it's the second, there's nothing disastrous about admitting it. What it means is that this is speculating, and speculating while knowing you're speculating is a completely different situation from believing you're investing.

And there's a gap behind this that isn't about willpower. The urge to trade on what appears in a feed shows up precisely when there's nothing better to check it against. With the context in front of you — what's expected from that company, how much it normally moves, what's at stake in the event coming up — the question above has an answer. Without it, it only has a feeling.

That's the work Volatly does in the background: leaving that context written before the event happens, in plain language, so the decision doesn't depend on what showed up on screen that morning.

What to do after a bad run

This is where everything above gets tested, because a bad run triggers several of the previous session's biases at once.

First: the run probably means nothing

Recall the previous chapter's figure. At a 55% hit rate, five losses in a row have a 1.85% probability in any stretch, and appear about twice per hundred trades.

A long run is what the mathematics predicts will happen occasionally even when the method is good. Feeling it as proof something has broken is exactly what happens, and it isn't information.

Second: the impulse runs the opposite way

The previous session's prospect theory anticipates it: while in a loss, willingness to take risk increases.

Translated into what people do: raising the size of the next position to win it back at once. It's the most expensive impulse there is, because it arrives precisely when capital is smaller and therefore when each percentage weighs more.

Remember the arithmetic: risking 1% per trade, eight consecutive losses leave capital around 92%. Risking 10%, around 43%. The run is the same; what decides is a choice made before it started.

Third: what does get reviewed

Reviewing nothing isn't the answer either. What gets reviewed is the process, which is the only thing a small sample allows you to judge:

Did I follow what was written? The size decided, the exit point set, the entry criterion. That's checkable instantly and doesn't depend on the outcome.

Did I lose more than planned on any of them? Losing above what you'd decided to risk is an execution failure, and one trade reveals it.

Did trades appear that weren't in the plan? It's the most reliable sign that impulse won, and it's completely objective: either it was in the plan or it wasn't.

And what doesn't get done

Changing methods over three losses. Three losses aren't information about a method, they're noise. Changing on noise guarantees never accumulating a meaningful sample of anything, leaving whoever does it hopping between systems without ever learning whether any of them worked.

Nor stopping entirely out of embarrassment. Closing the app and not looking again is the passive version of the same problem: it avoids the pain of reviewing and forfeits the only useful information a bad run produces, which is knowing whether the failure was in the process or only in the outcome.

What to remember

• Across 66,465 households between 1991 and 1996, the heaviest traders earned 11.4% annually against the market's 17.9%: a six-and-a-half-point gap.
• Average turnover was 75% a year, and the cost of that turnover explains the gap without any decision having to be bad.
• Men traded 45% more than women and earned 1.4% less risk-adjusted; among single investors, 2.3% less.
• After a bad run you review the process, not the outcome, because a small sample doesn't let you judge the second.

Published August 3, 2026. Last reviewed: August 3, 2026.

Related: what every trade really costs you · drawdowns, streaks, and sample size