Pushing towards the top means understanding that interpreting a KS test is not proof of statistical similarity on its own.
Just because a Kolmogorov-Smirnov test is performed does not mean it confirms an unconditional statistical similarity, but rather a conditional validity depending on the benchmark quality.
If the reference model is poorly specified for heavy-tailed distributions, like venture capital returns, the test only masks a crucial underlying asymmetry.
For example, a KS test may indicate similarity between a VC portfolio and a Gaussian distribution but ignore extreme events that dictate actual performance, leading to suboptimal decisions.