What Is Reverse Survivorship Bias?
Reverse survivorship bias describes a situation where there is a tendency for low performers to remain in the game, while high performers are inadvertently dropped from the running. This is the opposite of survivorship bias, which occurs when only strong and successful members of a group survive and remain in the group.
Reverse survivorship bias can be seen when some process becomes locked-in to path dependency, such as the dominance of VHS over Betamax video cassette tapes; or the dominance of the QWERTY keyboard, which is suboptimal to other layouts.
- Reverse survivorship bias describes a relatively uncommon situation where low-performers or suboptimal members remain, while higher performers exit.
- Survivorship bias, where winners prevail and losers are not counted, is a more common and concerning phenomena.
- An example of reverse survivorship in finance can be observed in the Russell 2000, a subset of the 2000 smallest securities from the Russell 3000 that contains essentially less successful companies' shares.
Understanding Reverse Survivorship Bias
Reverse survivorship bias can be applied to a variety of vehicles ranging from the housing market, stock indexes, and even investors' behaviors and capabilities. Whereas survivorship bias can bias returns or results of a group upward, reverse survivorship bias can have the opposite effect and push the overall return of the group downward. This is due to the best performers, who would've lifted overall results, being dropped from the group. The phenomenon occurs when calculating performance based solely on past performances, without taking into account extenuating circumstances such as the economic standpoint at which decisions were made.
Reverse survivorship bias can be attributed, in some cases, to path dependency. Path dependency explains the continued use of a product or practice based on historical preference or use. The use of a product or practice may persist even if newer, more efficient alternatives are available. Path dependency occurs because it is often easier or more cost-effective to continue along an already set path than to create an entirely new one.
Survivorship bias often occurs when comparing performance of portfolio managers. This bias pushes returns higher because only the exceptional managers stay in business and are able to be measured. The bad managers cannot be measured because they no longer exist. Survivorship bias can also pertain to the companies in a benchmark index, as companies that have gone bankrupt or have lagged will be dropped from the index and no longer count in its calculation.
Example of Reverse Survivorship Bias in Finance
An example of reverse survivorship can be observed in the Russell 2000 index that is a subset of the 2000 smallest securities from the Russell 3000. The "loser" stocks stay small and stay in the small cap index while the winners leave the index once they become too big and successful.
Thus, the Russell 2000 essentially collects the relatively unsuccessful stocks that do not advance to the Russell 1000, or the subset of the Russell 3000 stocks that represents the largest one thousand publicly traded American companies by market capitalization.