Statistics

Survivorship Bias

Distortion caused by analysing only entities that survived, excluding those that failed.

Testing on today's index constituents excludes every company that went bankrupt or was delisted, and survival correlates with returns - so measured historical performance is inflated.

Fund databases have the same problem: poor performers close and vanish from the record.

The fix is expensive: point-in-time data reflecting what was actually in the index on each date, including entities that no longer exist.

Related. Backfill bias - databases add entities after good performance and backfill their history - biases early data favourably in the same direction.

Full guide

Survivorship Bias and Other Data Traps

The biases that make backtests look better than reality - and the questions interviewers use to find out whether you know them.

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