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Strategy #0000000017 · Options information and cross-sectional factors

Implied-volatility change signal
Compare call and put implied-volatility changes, then test subsequent stock returns.

Measure monthly changes in call and put implied volatility at a consistent 30-day, at-the-money definition; rank stocks and compare their later returns.

Beginner-friendlyAbout 8 minutesEvidence and practical analysis

Three ways in

Understand the story. Then inspect the risk.

Start with a familiar situation, check the payoff, then test how the numbers change.

The idea · in two minutes

Rose first checks whether the two option quotes are comparable

Rose sees two companies but refuses to compare a seven-day out-of-the-money call with a 90-day in-the-money put. She fixes maturity and delta and uses a consistent surface method to estimate comparable ATM implied volatility.

The rule measures the prior month’s IV change. An, Ang, Bali and Cakici report that stocks with larger past call-IV increases tended to have higher subsequent returns, while put-IV sorts showed a different direction in their sample. That evidence can reflect information, risk compensation, supply and demand, or option pricing.

Jack claims rising call IV means a stock will rise. Rose turns that claim into a test: with point-in-time option data, fixed contract definitions and costs, does ranking call and put IV changes predict relative stock returns next period?

  • Call IV 變化高分位Assumed next-period return for the high call-IV-change group.
  • Put IV 變化高分位Assumed next-period return for the high put-IV-change group.
  • Call − put 訊號價差1.4% − (−0.3%) − assumed 0.3% cost = 1.4%; illustrative arithmetic only.

Illustrative research examples only. They are not live signals or a recommendation.

Variants · same family, different risk levers

Option information signals can use changes, levels, skew or volume.

The core lesson studies monthly ATM call/put IV changes; neighbouring signals replace the statistic or mechanism.

Related strategyRelationshipWhat changesNew cost or risk
Change in call IVATM call changeRanks stocks by the monthly change in fixed-maturity ATM call IV.Option demand, earnings events and surface updates also affect IV.
Change in put IVATM put changeRanks by the matching monthly change in ATM put IV.Put skew and downside-insurance demand may dominate the signal.
Call-minus-put IVWing spreadCompares call and put IV levels or changes to capture relative demand or jump information.Mismatched delta, expiry or quote quality makes the spread unreliable.
Realised-minus-implied volatilityVolatility-risk premiumCompares realised volatility with risk-neutral implied volatility.Forecast error in realised volatility can be confused with the premium.
Option-to-stock volumeTrading activityUses option volume relative to stock volume as an information-activity proxy.Contract multipliers, zero volume and multi-leg trades complicate interpretation.
Volatility smirk / skewSurface shapeMeasures IV differences across strikes or deltas.Requires a liquid and synchronised volatility surface.
Risk-neutral skewnessRisk-neutral distributionInfers risk-neutral skew from option prices to test tail information.Higher moments are sensitive to far-out-of-the-money quotes and interpolation.
Systematic vs idiosyncratic IV innovationsRisk decompositionSeparates common volatility shocks from stock-specific IV changes.A misspecified factor model can misclassify common risk as information.

IV is not realised volatility or a directional forecast. Keep expiry, delta, timestamp and surface construction consistent.

Read beyond the summary

References

Primary sources and research used to describe the strategy and its limits.

  1. 01An, Ang, Bali & Cakici (2014), The Joint Cross Section of Stocks and Options.research
  2. 02Bali & Hovakimian (2009), Volatility Spreads and Expected Stock Returns.research
  3. 03Xing, Zhang & Zhao (2010), What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?research
  4. 04Chen & Zimmermann, Open Source Cross-Sectional Asset Pricing.dataset
  5. 05Kakushadze & Serur (2018), 151 Trading Strategies, §3.5.source