Does Option Implied Volatility Predict Stock Returns?

Does Option Implied Volatility Predict Stock Returns?

November 14, 2014 Research Insights
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(Last Updated On: January 18, 2017)

The Joint Cross Section of Stocks and Options


Stocks with large increases in call (put) implied volatilities over the previous month tend to have high (low) future returns. Sorting stocks ranked into decile portfolios by past call implied volatilities produces spreads in average returns of approximately 1% per month, and the return differences persist up to six months. The cross section of stock returns also predicts option-implied volatilities, with stocks with high past returns tending to have call and put option contracts that exhibit increases in implied volatility over the next month, but with decreasing realized volatility. These predictability patterns are consistent with rational models of informed trading.

Alpha Highlight:

Observed changes in the implied volatilities of options can be considered a good measure of news arrival in the option market. Additionally, if some informed investors trade in option markets before trading in the underlying stock, option prices might predict future stock price movements. Indeed, this study finds that changes in option implied volatilities are correlated with subsequent stock returns.

Portfolio returns are sorted based on changes in option implied volatilities. Panel A in the table below shows decile portfolios of stocks sorted by changes in implied volatility of call options, or ΔCVOL (Panel B based on ΔPVOL is omitted here).

  • Portfolio 1 (Low ΔCVOL) contains stocks with the lowest changes in call option implied volatilities in the previous month;
  • Portfolio 10 (High ΔCVOL) includes stocks with the highest changes in call option implied volatilities in the previous month.

The results show that a long/short strategy going long (short) stocks with call options with the highest (lowest) changes in implied volatilities earns returns of approximately 1% per month. Call option volatility appears to be a good predictor for future stock returns. Also, this predictability is persistent, lasting up to 6 months (see table V).

2014-08-19 12_24_09-
The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

Intriguingly, the paper also explores using both call and put option volatility, potentially to greater effect.

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Definitions of common statistics used in our analysis are available here (towards the bottom)

About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes,, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.

  • Isaac Presley

    Is the fundamental rationale momentum (e.g., under reaction to new information)?

  • basically

  • Denys Glushkov

    This paper uses Optionmetrics data. The major problem with the findings in this paper is the look-ahead bias in the nature of Optionmetrics data relative to the underlying equity data. Here is what we are talking about: the option price used in implied vol calculation is an average between max bid and min ask. These are selected across all exchanges the contract is traded on. Option prices used in implied vol calculations up to Mar 4, 2008 are end of day prices (i.e., 4.15 PM)! Starting from Mar 2008, Optionmetrics has been capturing best bid and best offer as close to 4 pm as possible in an attempt to better synchronize the option price with the underlying close.

    Now, how big is the impact of look-ahead bias in the paper? Huge! Replicating this paper’s strategy for two separate periods, 1996/01 and 2008/02 (where 4.15 pm prices were used) and 2008/03-2013/12 (where 4.00pm or 3.59 prices were used) shows that the spread drops from 1.08% (t-stat=2.93) to 0.23% with t-stat of 0.68. Investors need to be aware of this issue before trusting results of the paper completely.

  • awesome. Love the insight, Denys. Highlights why it is so important to take all these academic papers at face value and do the replications in-house.