Before any conviction, failure risks must be analyzed.
Performing Kolmogorov-Smirnov tests, although crucial, does not guarantee the realization of statistical similarity if the data or thresholds are fundamentally flawed.
If the reference distributions do not account for the asymmetric and heavy-tailed nature of venture capital returns, the test could indicate a similarity that masks a fundamental divergence.
For example, comparing venture capital performance to a standard normal distribution, ignoring extreme events, would lead to false conclusions about true performance.
The mandate is to guard against illusory conclusions, not to confirm them hastily.