Skip to main content
Implied Volatility

IV Skew and Directional Bias: Why Puts and Calls Have Different Volatility

Pomegra Learn

Why Do Puts and Calls Have Different Implied Volatility?

In a perfectly efficient market, an out-of-the-money put and an out-of-the-money call on the same stock, with the same expiration, should trade at identical implied volatility. They both represent uncertainty about future price moves. But in reality, they don't. Put implied volatility is almost always higher than call implied volatility, especially for out-of-the-money options. This difference, called volatility skew or the volatility smile, reveals crucial information about market expectations, fear, and directional positioning. Understanding skew is essential for option traders because it affects pricing, reveals hedging demand, and creates trading opportunities.

Volatility skew exists because market participants have strong directional preferences. Investors and portfolio managers constantly hedge downside risk with out-of-the-money puts. Professional market makers and dealers accumulate short calls through their customer trades. The supply and demand imbalance means puts trade at higher implied volatility than calls. Additionally, market crashes are rare but violent, while market rallies are gradual. This asymmetry in realized volatility history creates an expectation that downside moves are more extreme, justifying higher put IV.

Quick definition: IV skew (or volatility skew) refers to the pattern where implied volatility differs across strike prices for the same expiration. Typically, out-of-the-money puts trade at higher implied volatility than out-of-the-money calls, creating a skewed or "smiling" volatility surface.

Key takeaways​

  • Put implied volatility exceeds call implied volatility for the same strike and expiration, creating a skew.
  • Skew reflects structural demand for downside protection and historical crashes being larger than rallies.
  • Skew widens (puts more expensive relative to calls) during market stress and uncertainty.
  • Skew narrows during calm, bullish periods as hedging demand diminishes.
  • Traders can profit from skew changes via strategies like put spreads, call ratios, or directional arbitrage.
  • Extreme skew (puts trading at 2–3x call IV) signals high fear and potential mean-reversion opportunities.
  • Skew patterns differ across stocks: defensive stocks have modest skew, growth stocks have extreme skew.

The Mechanics of Volatility Skew​

The volatility skew arises from three primary sources. First, hedging demand creates a structural supply-demand imbalance. Portfolio managers and investors face ongoing drawdown risk. They buy puts to protect against declines. This constant buying pressure pushes put prices upward. In contrast, calls don't receive the same hedging demand. Yes, some traders buy calls for upside exposure, but this demand is generally lower than put-hedging demand.

Second, realized volatility is historically asymmetric. Markets fall faster and further than they rise. The 2008 crisis saw the S&P 500 fall 57% from peak to trough, but subsequent rallies were gradual and protracted. The COVID crash fell 34% in 23 days; recovery took months. This realized asymmetry teaches market participants that downside moves are larger and more violent. Larger future downside moves justify higher implied volatility for puts.

Third, the leverage effect amplifies downside volatility. As stock prices fall, company leverage increases (debt as a percentage of equity value rises). Higher leverage means higher business risk and higher stock volatility. As prices rise, leverage decreases and risk falls. This mechanical relationship means volatility itself is inversely correlated with price direction—as the stock falls, volatility rises. This relationship is particularly pronounced for individual stocks and contributes to put volatility exceeding call volatility.

Consider a concrete example. Apple stock is trading at $195. You look at option prices for 45-day options:

  • $180 put (out-of-the-money): 28 implied volatility, cost $1.35
  • $190 put (near-the-money): 24 implied volatility, cost $2.80
  • $200 call (at-the-money): 20 implied volatility, cost $3.20
  • $210 call (out-of-the-money): 18 implied volatility, cost $1.80
  • $220 call (out-of-the-money): 16 implied volatility, cost $0.90

Notice that the $180 put (out-of-the-money, expecting a 7.7% downside move) trades at 28 IV. But the $210 call (out-of-the-money, expecting a 7.7% upside move) trades at only 18 IV. The put is 56% more expensive in terms of implied volatility. This is volatility skew.

Historical Crashes vs. Gradual Rallies​

The asymmetry between crash speed and rally gradualness reinforces skew. The 1987 Black Monday crash saw the S&P 500 fall 22% in a single day. There's no corresponding single-day 22% rally in stock market history. The closest analogs (2008's daily swings, 2020's pandemic recovery bounces) are still 4–5% daily moves, much less than the crash. This realized-volatility asymmetry teaches traders that downside tail risk is real. They price puts higher to reflect this asymmetry.

During the 1987 Black Monday aftermath, put implied volatility was stratospheric while call IV remained subdued. The market was pricing in the possibility of another major crash. During the subsequent years, as crash risk seemed to recede, skew gradually normalized. But skew never fully disappeared—it's a structural feature of markets, not a temporary anomaly.

Similarly, after the 2008 financial crisis, stock market skew remained extremely elevated for years. In 2010, puts 10% out-of-the-money traded at 3–4x the implied volatility of calls 10% out-of-the-money. As confidence in economic recovery gradually returned (2012–2014), skew normalized. But even in the calmest bull markets (2017, 2018), skew still existed; puts traded at 1.2–1.5x call IV.

Skew as a Fear Gauge​

The magnitude of skew—how much higher put IV is relative to call IV—serves as a gauge of market fear and uncertainty. In calm, bullish markets, skew is modest. A 10% out-of-the-money put might trade at 1.2x the IV of a 10% out-of-the-money call. This reflects normal hedging demand. During stress or uncertainty, skew widens dramatically. A 10% out-of-the-money put might trade at 2.0–2.5x the IV of the call. This reflects panic hedging, where investors are willing to pay substantial premiums for downside protection.

Professional traders monitor the "skew ratio"—the ratio of put IV to call IV at the same moneyness and expiration. When the ratio is 1.0–1.3, it suggests calm. When the ratio is 1.5–2.0, it suggests elevated hedging demand. When the ratio exceeds 2.0, it suggests extreme fear. These extreme moments often present contrarian opportunities. Skew that widens to 2.5 or 3.0x is rarely sustained. As fear gradually subsides, skew mean-reverts back toward 1.2–1.5x, creating profit opportunities for skew sellers (those selling expensive puts relative to calls).

Consider a historical example: In March 2020, during the COVID-19 crash, put skew for the S&P 500 reached extreme levels. A 10% out-of-the-money put on the SPY traded at 150+ IV while a 10% out-of-the-money call traded at 60–70 IV. The ratio was 2.0–2.5x. By April, as markets stabilized, put IV fell to 120 while call IV rose to 90. The ratio normalized to 1.3x. Traders who sold the expensive puts in late March and covered them in early April made substantial profits from skew compression.

Skew Patterns Across Different Stock Types​

Different categories of stocks exhibit different skew patterns. Defensive stocks (utilities, staples, pharma) have modest skew because their stock prices are stable and downside risk is perceived as lower. A defensive utility might have a 10% OTM put at 1.1x the IV of the call. Growth stocks, especially unprofitable tech companies, have extreme skew. A high-growth software stock might have a 10% OTM put at 1.8–2.2x the IV of the call.

This difference reflects structural reality. Utilities and staples have stable earnings, strong balance sheets, and generate dividends. Their downside risk is genuinely lower. Growth stocks are more volatile, have higher leverage, and are more sensitive to macroeconomic conditions. Portfolio managers hedge growth stock exposure heavily. This structural hedging demand drives skew higher for growth stocks.

During various market regimes, relative skew also shifts. In bull markets, when growth outperforms, skew on growth stocks widens as investors hedge growth exposure. In bear markets, when growth crashes hardest, skew temporarily compresses (because the puts are already expensive and call demand rises), then re-widens as recovery fears mount.

Put Spreads and Skew Trading​

The difference in implied volatility between puts and calls creates profit opportunities for traders who understand skew. A "put spread"—selling a lower-strike put and buying a higher-strike put—captures the skew. The lower-strike put is deeper out-of-the-money and trades at even higher IV than the nearer-the-money put. This IV premium is often excessive, and selling it creates attractive risk-reward.

Example: XYZ stock is at $100. A trader sells the $90 put (30 IV, 6.5% out-of-the-money) for $0.80 and buys the $85 put (33 IV, 15% out-of-the-money) for $0.25. Net credit: $0.55. The position profits if the stock stays above $90. The maximum loss occurs if the stock falls below $85, where loss = $5.00 − $0.55 = $4.45. The risk-reward is favorable because the sold put (30 IV) is priced more attractively than typical put prices, reflecting the skew inefficiency.

Similarly, "call ratios"—selling two calls and buying one call at a higher strike—exploit call IV being lower than put IV. The sold calls at lower strikes are cheaper in terms of IV, creating better premiums to capture.

Skew During Earnings Announcements​

Earnings announcements create temporary but intense skew changes. Before earnings, out-of-the-money puts become expensive as investors hedge the possibility of a large miss and stock crash. Skew widens dramatically. Near-term put IV might spike from 22 to 45 while call IV rises from 18 to 28. The skew ratio widens from 1.2x to 1.6x.

After earnings, the direction of skew change depends on the result. If earnings are strong and the stock rises, skew compresses. Investors no longer need as much downside protection, and put demand falls. Put IV collapses faster than call IV. A put that was 45 IV pre-earnings might drop to 22 IV post-earnings while the call rises from 28 to 24. Skew compresses to 0.9–1.0x, sometimes even inverting briefly if the surprise was very positive.

If earnings are weak and the stock falls, put IV might remain elevated even as call IV falls (as traders buy protection against further declines). Skew widens further. Over the following days, as initial panic eases, skew gradually normalizes back to typical levels.

Skew Reversals and Mean Reversion​

Extreme skew—when puts trade at 2.5–3.0x the IV of calls—is not sustainable. These extremes occur during acute panic (March 2020, October 1987, August 2011). Over subsequent days to weeks, as uncertainty resolves and panic subsides, skew mean-reverts back toward 1.2–1.5x. Traders who recognize extreme skew can profit by:

  1. Selling the expensive puts and buying calls (a "call spread" or "skew reversal" position)
  2. Holding the position as skew normalizes and the puts lose relative value
  3. Closing for profit once skew compresses to more normal levels

This mean-reversion trade requires patience and conviction that the extreme skew won't persist. But historically, it's highly reliable. Skew that widens to 3.0x during a panic typically compresses to 1.5x within 2–4 weeks, realizing 50% or more of potential profit.

Real-world examples​

Apple During 2022 Bear Market. In September–October 2022, as tech stocks crashed, Apple skew widened significantly. A 10% out-of-the-money put on Apple traded at 45 IV while the 10% OTM call traded at 22 IV (2.0x ratio). By December, as markets stabilized, the put IV fell to 28 while call IV rose to 20, compressing the ratio to 1.4x. A trader who sold 30-day put spreads in late October and covered them in early November captured the compression for 30–40% profit.

Fed Rate Decision (March 2023). Before the Fed decision on bank failures (SVB collapse context), market skew on SPY widened to extreme levels. A 5% OTM put traded at 52 IV while a 5% OTM call traded at 28 IV (1.85x). By the following week, as the Fed stabilized credit markets, skew compressed to 1.3x as traders reduced hedging. Volatility sellers who understood that extreme skew was unsustainable profited from the compression.

Tesla Earnings Volatility (2023). Tesla stock exhibits naturally high skew due to its growth-stock status and volatility. Before earnings, skew widens to 1.7–1.9x. Astute traders sell the expensive puts and buy calls, capturing the skew expansion before earnings and the compression after. Over multiple earnings cycles, this strategy has generated consistent returns.

Common mistakes​

Assuming all puts are overpriced relative to calls. While puts do trade at higher IV on average, extreme skew represents temporary mispricings that mean-revert. Selling puts blindly without considering where skew is in its historical range can trap you selling into further expansion.

Ignoring stock-specific vs. market-wide skew. A single stock might have extreme skew (due to upcoming earnings) while market-wide skew is normal. Conversely, market-wide skew might be extreme (due to geopolitical risk) while individual stocks have normal skew. You need to monitor both levels.

Holding skew trades through catalysts. If you sold expensive puts and are waiting for skew to compress, but earnings or another major catalyst occurs, skew might widen further before compressing. Protect yourself by setting profit targets at 50% max gain rather than waiting for full mean reversion.

Confusing skew with realized volatility changes. Skew compression (put IV falling faster than call IV) creates profit for skew sellers. But if realized volatility of the stock also falls sharply, the absolute IV level drops, which also hurts long put positions. Don't confuse the two effects.

Overweighting extreme historical skew examples. You might read about the 3.0x skew during COVID and try to replicate it by selling massive put positions ahead of the "next crisis." But extreme skew that wide happens rarely and unpredictably. Most profits come from trading skew compression in the 1.5–2.0x range, not waiting for 3.0x extremes.

FAQ​

Why do puts always have higher IV than calls?​

Structural hedging demand (portfolio managers buying puts), realized volatility asymmetry (crashes are larger than rallies), and the leverage effect (downside volatility is higher) all contribute. It's not a market inefficiency; it's a fundamental structural feature.

Can I profit from selling puts if they're overpriced?​

Yes, but skew is normal, not an inefficiency. Selling puts is profitable primarily due to theta decay (time value), not skew. If you sell puts expecting skew to compress and skew doesn't change, theta still generates profit.

What's a reasonable level of skew to consider "normal"?​

For index options like SPY or QQQ, 1.2–1.4x is calm and normal. For individual growth stocks, 1.4–1.7x is normal. Skew above 1.8x starts to look elevated. Skew above 2.0x is extreme and usually mean-reverts within weeks.

How do I trade skew mean reversion?​

Buy the overpriced puts (or sell put spreads) relative to calls when skew is extreme. Wait for skew to compress toward normal levels, then close for profit. The position benefits from put IV falling faster than call IV, regardless of the underlying price.

Does skew change during the trading day?​

Yes. Morning skew often reflects overnight news (earnings, geopolitical events). Intraday, if the market rallies, skew often compresses. If the market falls, skew often widens. Close to close, skew also changes based on new information and trader positioning.

Why do defensive stocks have less skew than growth stocks?​

Defensive stocks are less volatile and have lower business risk. Their downside is limited. Growth stocks are more volatile and more sensitive to economic changes. Investors hedge growth exposure more aggressively, driving put demand and skew higher.

Can I see skew in my broker's platform?​

Most platforms show IV by strike price. You can calculate skew manually by comparing the IV of a put to the IV of a call at similar distances from the current price. Some advanced platforms display skew metrics directly.

Summary​

Volatility skew refers to the pattern where out-of-the-money puts trade at higher implied volatility than out-of-the-money calls on the same stock and expiration. This skew reflects structural hedging demand for downside protection and the historical reality that market crashes are larger and faster than rallies. Skew widens during panic (when puts become expensive relative to calls) and compresses during calm periods (when hedging demand falls). Extreme skew above 2.0x is rare and typically mean-reverts within weeks, creating profit opportunities for traders who sell expensive puts and buy calls. Understanding skew helps traders select more favorable entry prices and identify mean-reversion trades.

Next​

→ The IV Surface