Reading the evidence
Survivorship bias occurs when analysis includes entities that remain visible while omitting those that failed, closed or left the dataset. The survivors can make history look safer or stronger.
Make it click
Judging a race only from athletes at the finish ignores everyone who withdrew. The remaining group cannot describe the experience of all entrants.
Now put that into markets
Current index members, live funds and surviving companies exclude delistings and closures unless point-in-time data restores them.
Bias affects returns, failure rates and characteristic comparisons. Delisting proceeds and merger outcomes need explicit treatment.
Reconstruct the eligible universe at each date and track exits. Compare source coverage with independent totals.
Adding failed names without their real history can create new errors. Membership and availability must remain point-in-time.
Takeaway
