Forget what we have already invested in this idea: performing Kolmogorov-Smirnov tests is not sufficient operational proof of statistical similarity.
These tests do not capture the subtleties of market mechanisms or the specific conditions shaping distributions.
With fresh eyes, we would ask whether this distributional similarity is still relevant if the local regulatory context is not considered.
For example, RBI policies on liquidity can distort comparability, making a purely statistical similarity misleading for decision-making.
We must ask ourselves: would we enter this market based solely on a statistical concordance without evaluating local constraints or geopolitical risks?