Volatility Skew Trading: How to Spot Mispriced Options

When you look at an option chain, you might expect all calls at the same expiry to trade at roughly similar implied volatility levels. In reality, they often don’t. Different strikes on the same underlying—and different expiries—frequently show meaningfully different implied volatilities, creating what traders call a volatility skew. Learning to identify and trade these discrepancies is a core edge in volatility-focused strategies.

Understanding the Implied Volatility Spread

Implied volatility represents the annualized volatility rate that, when plugged into a pricing model, returns the current market price of an option. Every single option has its own implied volatility. Even within the same series—say, all April calls on the NIFTY 50 index—you will routinely see implied volatilities that differ by multiple percentage points.

Why does this happen? Market participants price options based on supply, demand, perceived risk at each strike, time remaining, and collective hedging flows. An out-of-the-money put might trade at 28% implied volatility while an at-the-money call trades at 22%, and an even further out-of-the-money call sits at 18%. These are not errors; they are often reflections of real market structure and expectations.

The key question for a volatility trader is simple: When is the spread between these implied volatilities large enough to be tradeable?

Why Different Strikes Have Different Implied Volatilities

Consider a real NIFTY scenario. Suppose NIFTY is trading at 22,000. You observe weekly options (expiring in five days) on the following strikes:

22,000 call: 26% implied volatility, trading at ₹180
22,500 call: 24% implied volatility, trading at ₹95
21,500 call: 28% implied volatility, trading at ₹320

Why would the out-of-the-money 22,500 call trade at a lower implied volatility than the at-the-money 22,000? And why would the further out-of-the-money 21,500 call (which is, in this direction, in-the-money) trade at a higher implied volatility than both?

Several structural reasons exist. First, speculators often chase the cheapest options by absolute dollar cost, which can push out-of-the-money calls lower in price and therefore lower in implied volatility. Second, hedgers (those protecting downside) may be aggressively bidding up out-of-the-money puts and in-the-money calls, inverting the usual pattern. Third, there may be rumors or events that affect certain strikes differently—perhaps elevated tail-risk pricing on puts, or cheap calls because sentiment is bullish.

A as a general rule of thumb (not a law), longer-dated options tend to trade at lower implied volatilities than short-term ones, and at-the-money options often sit near the middle of the implied volatility range. But exceptions are common and often the most profitable to trade.

The Risk of Skew Distortions

Before you leap into a skew trade, you must understand what is driving it. Suppose you notice that OTM puts are trading at 32% implied volatility while ATM calls are at 18%. Your first instinct might be to buy the cheap calls and sell the expensive puts. But if there is a valid reason for the discrepancy—such as a genuine increase in tail-risk hedging demand, or a takeover rumor that is pushing speculative demand into cheap OTM calls—then selling naked calls could expose you to losses you did not anticipate.

A neutral approach is safer: structure a position with enough directional room to protect yourself, or build a ratio spread (buying more at one strike than you sell at another) to handle the skew asymmetrically. The key is to ask yourself: Is this skew a temporary pricing error, or a signal of real market conviction?

Measuring Skew: The Implied Deviation Approach

How do you know whether the differences in implied volatilities are large enough to act on? The answer is to calculate the implied deviation—essentially, the standard deviation of all the implied volatilities in a chain.

Here’s how it works. Suppose you have a series of calls on the same underlying with these implied volatilities:

Strike	Implied Volatility
10% OTM	19%
5% OTM	22%
ATM	25%
5% ITM	27%
10% ITM	29%

First, calculate the average: (19 + 22 + 25 + 27 + 29) / 5 = 24.4%.

Next, find how far each one deviates from that average: - 19% is 5.4 points below
- 22% is 2.4 points below
- 25% is 0.6 points above
- 27% is 2.6 points above
- 29% is 4.6 points above

Square each difference and sum them: 5.4² + 2.4² + 0.6² + 2.6² + 4.6² = 29.16 + 5.76 + 0.36 + 6.76 + 21.16 = 63.2.

Divide by the number of options minus one: 63.2 / 4 = 15.8.

Take the square root: √15.8 ≈ 3.97. This is the raw implied deviation.

To make it comparable across different underlyings and market conditions, convert it to a percentage by dividing by the average implied volatility: 3.97 / 24.4 ≈ 16.3%.

The 15% Threshold

This percentage figure—16.3% in the example above—is your signal. If it is larger than 15%, the skew is large enough to warrant action. You have meaningful discrepancies between the implied volatilities in the chain, and neutral spreading strategies may be profitable.

Why 15%? Empirically, when the percentage deviation falls below 15%, the differences in implied volatility are usually small enough that transaction costs (commissions, bid-ask spreads, slippage) consume any edge you might capture. When it exceeds 15%, you have a larger cushion to work with.

On any given day, perhaps 20 stocks and 10 futures contracts (globally speaking) will show percent deviations above 15%. On an NSE options day, you might find 3 to 8 stocks in the NIFTY 50 universe, plus a few in the broader midcap or bank indices, where the skew is large enough to trade.

Building a Neutral Spread on Skew

Once you have identified a candidate—say, a stock where out-of-the-money calls are trading at 32% implied volatility and at-the-money calls at 20%—you can build a position by buying low-IV options and selling high-IV ones.

For example, you might: - Buy 50 ATM calls at 20% IV (the cheaper side in this scenario)
- Sell 75 OTM calls at 32% IV (the expensive side)

The ratio of 50-to-75 is not arbitrary; it is determined by the delta or the notional exposure of each leg, so that the overall position has zero or minimal directional delta. This makes it a delta-neutral spread, and you profit if the spread between the two implied volatilities narrows—that is, if the expensive calls come down in IV or the cheap ones go up, or both.

Your profit is not from directional movement; it is from the collapse of the skew itself.

Risk in Skew Trading

The largest danger is that the skew does not collapse; instead, it persists or widens. If the implied volatility of the expensive calls remains pinned high and the cheap calls stay cheap, your spread loses money over time (particularly due to theta decay working against you if you are long options). Similarly, changes in the underlying stock price can shift which strikes are expensive and which are cheap, moving your break-even point.

For this reason, skew trading is typically a medium-term strategy. You hold the position long enough for the market to recognize the mispricing and correct it, but not so long that theta consumes your edge. Many traders set a target: if the percent deviation shrinks to below 10%, close the position and take the profit.

Practical Steps for Identifying Skew Trades

Scan the chain. Calculate implied deviation and percent deviation for every stock or futures contract you monitor.
Filter for candidates. Keep only those where percent deviation exceeds 15%.
Understand the reason. Ask yourself why the skew exists. Is it a rumor, hedging flow, or speculative distortion?
Structure the spread. Design a delta-neutral position using the Greeks (delta, primarily) to balance each leg.
Monitor and exit. Track the percent deviation daily. Close the trade when it shrinks to your target, or cut losses if it widens significantly.

Why Computer Assistance Matters

Calculating implied deviation by hand for every option in every chain is impractical. Traders with institutional access use screeners and real-time analytics to compute implied volatility for every option in the chain and then automatically calculate the percent deviation. In seconds, the system can surface the top five or ten candidates on any given trading day.

Retail traders can approximate this by using an options chain view with implied volatility displayed, then eyeballing the range and asking whether the spread looks unusually large. Over time, you develop a feel for what a normal 8% range versus an anomalous 18% range looks like.

Global and NSE Examples

On a U.S. equity, suppose Apple stock is at $190. You see March weekly calls with these implied volatilities: 170 call at 38%, 180 call at 31%, 190 call at 25%, 200 call at 28%, 210 call at 35%. The average is 31.4%, the range is 13 percentage points, and the percent deviation is roughly 18%. This is above 15%, signaling a candidate. The skew appears to be smiling (higher on both extremes), which often reflects tail-risk hedging or earnings uncertainty.

On NIFTY, suppose the index is at 22,500 with weekly options showing: 22,000 call at 24%, 22,500 call at 20%, 23,000 call at 19%, 23,500 call at 22%, 24,000 call at 26%. The average is 22.2%, and the percent deviation works out to around 17%. Again, above the 15% threshold, and again showing a smile pattern—suggesting that large moves (either direction) are perceived as more probable or more hedged than a smooth normal distribution would imply.

Both are tradeable setups. In both cases, you would structure a neutral spread to profit from the compression of that skew back toward a tighter, more uniform IV curve.

Key takeaways

Implied volatility varies across strikes. Even options on the same underlying, same expiry, and same underlying price can trade at different implied volatilities, creating a volatility skew.
The skew is often tradeable. When the differences are large enough (percent deviation > 15%), you can build a delta-neutral spread to profit from the eventual compression.
Measure it with implied deviation. Calculate the standard deviation of the implied volatilities in a chain, convert it to a percentage of the average IV, and use 15% as your threshold for action.
Understand the source. Before trading a skew, ask why it exists. Hedging flows, rumors, or speculative demand all leave different signatures on the IV surface.
Use spreads, not naked sales. Structure balanced positions (equal or ratio-adjusted delta legs) so you profit from skew collapse without taking directional risk you do not intend.
Monitor daily and exit at targets. Skew compression is your edge. When the percent deviation shrinks below your target (often 10%), close the position and lock in profit.
Computers accelerate screening. Implied deviation calculations are tedious by hand but trivial for a computer. Use technology to scan chains quickly and flag candidates in real time.
Skew trading fits into a larger volatility toolkit. Combined with overall IV level (buying low, selling high) and directional spreads, skew trading is one lever a volatility trader pulls to build edge.