For most people investing is a loser’s game: avoiding mistakes counts more than brilliant moves.
Not losing comes first.
Your €10,000 falls 50%. Pull the line up to the gain that gets it back.
Making up a fall takes a bigger gain than the fall itself.
← Red LinesRed Line 27 of 48 The idea The numbers In your money Where it bends This game’s numbersHow strong the proof isCMixed proof Where it comes from
Professionals earn points with great shots. Amateurs mostly lose them: into the net, out of the court. The one who makes fewer mistakes comes out ahead.
In amateur tennis about 80 points in 100 are lost by mistakes, only about 20 come from a great shot. Among professionals it is the other way round.
The investor’s unforced errors: selling in a panic, chasing last year’s best performer, paying high fees, borrowing too much. Avoid them and you are ahead of most.
Professionals with a real edge play a different game.
The maths: worked out on this page
Good studies show common mistakes cost ordinary investors a lot, but none weighs avoiding mistakes against brilliant moves directly.
- The Behavior of Individual Investors Brad M. Barber & Terrance Odean, Handbook of the Economics of Finance, vol. 2B, 1533-1570, Elsevier, 2013
- The Loser’s Game Charles D. Ellis, Financial Analysts Journal 31(4), 19-26, 1975
Checked 2 Nov 2026 · How we grade
- A Strong proof: Many good studies or long official data, from different teams or countries, point the same way.
- B Good proof, with limits: Solid studies agree on the direction, but the size varies, or the data covers few places or few kinds of people.
- C Mixed proof: Some good studies for, some against, or the evidence covers only part of the line.
- D Thin proof: Mostly one book’s argument, one survey or stories. It may be wise, but it has not been tested well.
- = True by the sums: It follows from arithmetic, so no study can overturn it. We still show what real data says.
Charles D. Ellis, “The Loser’s Game”, Financial Analysts Journal (1975). In our words, not quoted.
See it in numbers: Overconfidence · Costs (From Zero)
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