Survivorship bias

Survivorship bias is testing a strategy only on the instruments that still exist today, ignoring the ones that were delisted, went bankrupt, or were acquired. Those failures drop out of a naive dataset, so the strategy never has to face them, and it looks safer and more profitable than it would have been in real time, when you couldn’t have known which names would survive.

It shows up most when an equity universe is built from today’s index membership applied to the past, or in “buy the dip” logic that looks brilliant only because the data contains just the companies that recovered. Avoiding it means using data that includes delisted and dead instruments, and building your historical universe from what was actually tradable at the time, not from today’s roster.