Glossary · S
What is Survivorship bias?
A distorted sample of the past caused by leaving out what did not "survive": delisted companies, failed strategies, forgotten days, unpublished failures.
In context
Survivorship bias means your data is an unrealistic sample of the past because something has been removed. The classic stock-market example is testing on today's index members only: the companies that went bankrupt and dropped out are missing, so the past looks better than it was.
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