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Option Returns and Volatility Mispricing

Last Updated on 10 February, 2024 by Rejaul Karim

In their investigation titled “Option Returns and Volatility Mispricing,” Amit Goyal and Alessio Saretto delve into the intriguing realm of individual equity options. Focusing on the disparity between historical realized volatility and market implied volatility, the authors employ a zero-cost trading strategy.

This strategy involves strategically going long or short in straddles, particularly targeting options with a substantial positive or negative difference in volatility measures. Remarkably, the study unveils a noteworthy and statistically significant average monthly return.

The findings persist across diverse market conditions, various risk characteristics, industry classifications, and liquidity considerations, standing independent of linear factor models. This exploration sheds light on an impactful source of mispricing within the realm of stock options.

Abstract Of Paper

We study the cross-section of stock options returns and find an economically important source of mispricing in individual equity options. Sorting stocks based on the difference between historical realized volatility and market implied volatility, we find that a zero-cost trading strategy that is long (short) in straddles, with a large positive (negative) difference in these two volatility measures, produces an economically important and statistically significant average monthly return. The results are robust to different market conditions, to firm risk-characteristics, to various industry groupings, to options liquidity characteristics, and are not explained by linear factor models.

Original paper – Download PDF

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Author

Amit Goyal
University of Lausanne; Swiss Finance Institute

Alessio Saretto
Federal Reserve Banks – Federal Reserve Bank of Dallas

Conclusion

In conclusion, the exploration of option returns reveals a notable source of mispricing in individual equity options. The strategic sorting based on the variance between historical realized volatility and market implied volatility uncovers a compelling zero-cost trading approach.

Specifically, adopting long (short) positions in straddles with a substantial positive (negative) difference in volatility measures yields both economically substantial and statistically significant average monthly returns. Importantly, these findings persist across diverse market conditions, firm risk characteristics, industry groupings, and options liquidity features.

Notably, these results defy explanation by conventional linear factor models, emphasizing the unique and exploitable nature of the observed volatility mispricing.

Related Reading:

Equity Volatility Term Structures and the Cross-Section of Option Returns

Slow Trading and Stock Return Predictability

FAQ

1. What is the primary focus of the study “Option Returns and Volatility Mispricing”?

The study focuses on exploring the cross-section of stock options returns, specifically investigating the disparity between historical realized volatility and market implied volatility. The authors aim to uncover mispricing in individual equity options and evaluate the performance of a zero-cost trading strategy based on this volatility difference.

2. Can you explain the zero-cost trading strategy employed in the study?

The zero-cost trading strategy involves taking long (short) positions in straddles, targeting options with a substantial positive (negative) difference between historical realized volatility and market implied volatility. This strategic approach is designed to exploit the observed mispricing in volatility measures.

3. What are the key findings of the study regarding option returns and volatility mispricing?

The study reveals that the zero-cost trading strategy produces a noteworthy and statistically significant average monthly return. The strategy involves taking long positions in straddles with a large positive difference in volatility measures and short positions in straddles with a substantial negative difference. Importantly, these findings persist across diverse market conditions, firm risk characteristics, industry groupings, and options liquidity features. The results are not explained by conventional linear factor models.

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