Survivorship bias

Drawing conclusions from the examples that lasted long enough to be visible, while the ones that failed have quietly left the sample.

Example

A list of the habits of great investors is assembled from people whose results made them famous; identical habits among those who lost money produced no list at all.

Important

Survivorship bias makes strategies look far more reliable than they are, because the failures are not merely under-reported - they are usually missing from the data entirely.

Related terms

• Selection bias — Any situation where the sample in front of you was not assembled in a way that represents the whole population, so conclusions drawn from it do not generalise.
• Base rate — How often an outcome occurs across the whole population of similar cases, before you know anything specific about the one in front of you.
• Variance — How widely actual outcomes spread around their average. High variance means individual results routinely land far from the expected value, in both directions.

Lessons that explain it

• This belongs in the money you could genuinely lose, sized small, and held for reasons beyond the return — The apparent low correlation with financial markets is partly real and partly an artefact of how these assets are valued - and once round-trip costs and total-loss risk are honestly priced in, this asset class fits only as a small, patient allocation of money whose absence would not change anyone's plans. (10 min)
• Why what comes to you is a biased sample — The opportunities that push hardest for your attention are drawn from a worse pool than the ones that do not need to push, and urgency is the tell. (9 min)
• The mistake library — Losses are cheaper to learn from when they are someone else's. This is the practice of keeping a written record of both kinds so the same error cannot arrive twice wearing a different name. (13 min)
• Appraising one opportunity: evidence of the outcome, not the promise of it — Before paying for a course, qualification or programme, look for evidence that people like you achieved the outcome you want, check completion and employer demand, and compare cheaper routes. (12 min)
• Survivorship bias — Almost every success story you can read about was selected for having succeeded. The ones that would have made the lesson honest are not in the sample. (8 min)
• A good decision can lose, and a bad one can win — Outcomes are made of judgement and luck in unknown proportions. Judging the decision by the result means learning from the luck, which teaches the wrong thing in both directions. (13 min)

All 578 terms in the Investing glossary