Options are powerful tools. They serve not only as an effective instrument for risk management and speculation, but they also provide valuable information about the underlying asset. That is, we can use option‐implied signals to predict the underlying. For example, when the correlation between the S&P 500 and its implied volatility turns positive, it often precedes a market correction.
Reference [1] conducts similar research. It uses implied volatility and the option Greeks of U.S. stocks to predict the direction of the underlying using a machine learning technique. The authors constructed a long/short portfolio and achieved superior risk-adjusted returns. By studying call and put options of exchange-listed U.S. stocks—including end-of-day bid and ask prices, volume, and implied volatility—from 1996 to December 2022, they pointed out,
This study provides empirical evidence that option‐implied volatility and Greeks are valuable predictors of extreme stock returns. The results demonstrate that incorporating these option‐related variables via machine learning significantly enhances predictive accuracy compared with traditional logistic regression models. The long–short portfolio constructed by a model utilizing option variables delivers strong financial performance, significantly outperforming a benchmark portfolio using only stock characteristics. Implied volatility and delta emerge as the most important option‐related variables, while the other Greeks, gamma, theta, and vega, also add value when considered through nonlinear interactions. The results also reveal that put options are more informative than call options in predicting extreme returns and that crashes are easier to predict than jumps. This paper contributes to the asset pricing literature by showing that options provide leading information about extreme stock returns, beyond what can be inferred from stock characteristics.
In short, this study shows that option-implied volatility and Greeks are powerful predictors of extreme stock returns. A long–short portfolio built on option signals delivers strong performance, with implied volatility and delta as the most influential predictors and put options proving more informative than calls.
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References
[1] Panayiotis C. Andreou, Chulwoo Han, Nan Li, Predicting Stock Jumps and Crashes Using Options, Journal of Futures Markets, 2025; 1–20
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