Understanding Horizontal Skew in Options Trading

When traders look at options markets, they quickly notice something interesting: the price volatility changes not just by strike price, but also by expiration date. This phenomenon reveals market expectations and helps inform smarter trading decisions. One of the most important concepts in this landscape is horizontal skew, which shows how volatility behaves across different time horizons for the same strike price.

What is Volatility Skew and How It Forms

Implied volatility (IV) doesn’t stay constant across all options on the same underlying asset. Instead, IV varies depending on both the strike price and when the option expires. When you plot these different IV values, you create a volatility curve. If this curve is symmetric, traders call it a volatility smile. If it tilts to one side, it becomes a volatility smirk. The degree of this tilt is measured by skewness—essentially, how steep the curve slopes.

This variation reflects how the market prices uncertainty at different levels. Some strike prices are more heavily demanded than others, driving their prices and implied volatilities higher. Understanding where and why this demand concentrates helps traders identify opportunities.

Horizontal Skew vs. Vertical Skew: The Time Factor

Options traders distinguish between two main types of skew. The first is horizontal skew, which examines how volatility changes for the same strike price across different expiration dates. For instance, if you compare a strike price at the one-month expiration to the same strike at the three-month expiration, you might see different IV values—that’s horizontal skew at work.

In contrast, vertical skew looks at how IV varies among different strike prices within the same expiration period. A trader looking at all options expiring in March might notice that out-of-the-money (OTM) calls have higher volatility than at-the-money (ATM) calls. That’s vertical skew.

Most traders focus primarily on vertical skew when making trading decisions, as it impacts their immediate options strategies. However, understanding horizontal skew matters too, especially when building multi-month hedges or comparing the cost of strategies across different time frames.

Forward and Reverse Skews: Reading Market Sentiment

Beyond the time dimension, skew also has direction. A forward skew occurs when higher strike price options carry higher implied volatilities than lower strikes—typically signaling bullish market sentiment. The market is pricing in greater probability of upside moves, so call options become relatively more expensive.

The opposite pattern, reverse skew, emerges when lower strike prices have higher IVs than higher strikes. This usually indicates bearish expectations, with put options commanding premium valuations as traders hedge downside risk.

Interestingly, reverse skew appears more frequently in many cryptocurrency and emerging markets. This happens because shorting mechanisms are either unavailable or prohibitively expensive. Instead of directly shorting, investors use put options as a primary hedging tool, which drives up put option premiums and creates the reverse skew pattern.

Practical Trading Applications for Different Skew Patterns

Reading the shape of a volatility curve gives you actionable intelligence. In bull markets, traders typically favor bull call spreads, buying call options at lower strikes while selling calls at higher strikes. This strategy profits from price appreciation while keeping costs down.

However, if forward skew is modest—meaning the slope isn’t steep—consider switching to bull put spreads instead. In this approach, you sell puts at lower strikes and buy puts at higher strikes. This costs less to implement because put premiums haven’t inflated as much due to weaker forward skew.

By carefully analyzing horizontal skew alongside vertical patterns, you gain a comprehensive view of how options are priced across both time horizons and strike levels. This layered understanding separates casual options traders from those who consistently extract value from volatility variations.