Skew (distribution)

Skew measures how lopsided a distribution is.

• Skew ≈ 0 — roughly symmetric. Upside and downside tails are comparable.
• Negative skew (e.g. −0.55) — more paths drift down than up; the downside tail is longer and fatter. Downside surprises are more likely than upside ones.
• Positive skew — longer upside tail; upside surprises are over-represented.

In Monte Carlo, skew comes from the GEX warping and the IV surface (call/put richness). Negative skew on a chart that looks centred is a warning: the median may be benign, but the cone hides a thicker tail on one side.

Not to be confused with 25Δ Risk Reversal, which measures skew in implied volatility rather than in the simulated terminal distribution.