Focusing on Kolmogorov-Smirnov tests as a simple realization ignores the interpretation discipline required.
From a high level, the statistical similarity revealed by these tests is only a starting point.
Noise lies in non-nuanced inference, as minor deviations can mask significant risks in distribution tails, especially in Hong Kong where retail flows are sensitive to extremes.
For example, small divergences in the behavior of small-cap stocks could be critical for market stability, even if the overall distributions seem similar.
It is crucial to control what can be controlled, recognizing that interpreting results requires a prudent posture, not blind acceptance.