Volatility Skew
Volatility skew described the empirical observation that implied volatility was not uniform across all option strikes for a given underlying and expiry, but instead varied — typically with OTM put options carrying higher implied volatility than OTM call options on equity indices — reflecting asymmetric demand for downside protection versus upside speculation.
In a world where the Black-Scholes model held perfectly, all options on the same underlying and expiry would imply the same volatility regardless of strike. Empirical markets diverged sharply from this theoretical ideal, producing what practitioners called the volatility skew or smirk. On equity index options — including Nifty 50 and Bank Nifty on NSE — the skew consistently showed that puts struck progressively lower (further OTM) carried higher implied volatility than calls struck equivalently further OTM above the current index level.
The economic intuition for this skew was demand-driven. Institutional investors — mutual funds, insurance companies, foreign portfolio investors — persistently bought OTM index puts as portfolio insurance against market crashes. This structural hedging demand inflated OTM put premiums, pushing their implied volatility higher than warranted by historical return distributions. On the upside, fewer participants systematically bought OTM calls as a hedge; speculative call buying was episodic, not structural. The imbalance created an asymmetric IV surface — high IV for low strikes, moderate IV near ATM, lower IV for high strikes.
The skew in India's Nifty options market was persistently steep, particularly at shorter tenors (weekly expirations). During periods of market stress — such as the COVID-19 crash of March 2020, the war-related volatility of early 2022, or sharp global sell-offs triggered by US Fed hawkishness — the skew steepened dramatically as demand for protective puts surged. In calm bull markets, the skew compressed somewhat but never flattened to uniformity.
Traders incorporated skew into strategy selection. Selling OTM puts in a high-skew environment generated richer premiums than selling OTM calls of equal distance from ATM, but it also exposed the seller to precisely the crash scenario the market was pricing. Strategies like the jade lizard or risk reversals were specifically designed to monetise skew differentials. Skew also affected the relative cost of vertical spreads: a bull put spread (selling a higher put and buying a lower put) collected more net premium when the skew was steep, because both put strikes were expensive.
Quantitatively, skew was measured by comparing the IV of a 25-delta put with the IV of a 25-delta call, a metric known as the 25-delta risk reversal. A large positive value indicated significant downside skew. India VIX, published by NSE, captured the aggregate market volatility expectation but did not directly show the skew; skew measurement required direct access to the full options chain across strikes.