Identifying, Understanding, and Leveraging W-Shaped Implied Volatility in Options Markets

Abstract

In this thesis, we explore the rare and intriguing phenomenon of W-shaped implied volatility curves in options markets and its potential impact on option pricing and trading strategies. We propose a demand-based justification for the appearance of these atypical curves, suggesting that excessive demand for at-the-money options can drive up their prices, leading to the formation of W-shaped implied volatility curves. To identify these distinctive market scenarios, we develop a machine learning program capable of detecting such W-shaped patterns.

Using a dataset of six large-cap stocks, we analyzed the situations where W-shaped implied volatility curves were observed and used the identification program to examine ways to trade the situation. The results indicate that trading the W-shape with an iron butterfly options trading strategy produces statistically significant positive payoffs, suggesting a profitable approach to exploiting this unique market condition.

The study contributes to a limited body of knowledge on the factors driving the formation of W-shaped implied volatility curves and their implications for option pricing and trading strategies. This research paves the way for future investigations into the underlying market dynamics, potential risks, and opportunities associated with these rare occurrences.