False Negative Rate

The False Negative Rate is the probability that a test fails to identify a true, profitable market effect. This represents a lost opportunity cost, as a potentially successful strategy is discarded due to a lack of statistical evidence.

In competitive crypto markets, keeping this rate low is vital for capturing alpha before other participants. Analysts manage this rate by increasing sample sizes or using more sensitive statistical tests, though this often increases the risk of Type I errors.

It is a critical component of power analysis and overall model performance evaluation. By understanding this rate, traders can assess the likelihood that they are missing out on viable market strategies.

It measures the blindness of a testing system to genuine opportunities.