SystemTrader
StocksAdvancedLong-Only / Long-Short

Implied Volatility Strategy

Use changes in option implied volatilities to predict stock returns. Rising call IV signals good news; rising put IV signals bad news. The options market often knows first.

Primary Signal
ΔCall IV - ΔPut IV
Historical Premium
~1% / month
Lookback Period
1 month
Rebalance
Monthly

Overview

The implied volatility strategy exploits information embedded in options prices. When call implied volatility rises relative to put implied volatility, informed traders are likely buying calls in anticipation of good news. The reverse signals bad news.

In plain terms: the options market often knows before the stock market. Informed traders prefer options for leverage and anonymity. Their activity shows up as changes in implied volatility before the news hits stock prices.

Stocks with large increases in call IV outperform by about 1% per month. Stocks with large increases in put IV underperform by a similar amount. The spread between these groups exceeds 2% monthly, making this one of the strongest short-term predictors in academic finance.

Key Insight

Options Lead Stocks
Informed traders reveal their hand
High Turnover Strategy
Monthly rebalancing required

Options Market Signals: Reading Informed Trading

Changes in implied volatility reveal where informed traders are placing bets. When call IV rises faster than put IV, it signals positive news ahead.

The Signal
Signal = ΔCall IV − ΔPut IV
Bullish Signal
+8%
Call IV
+2%
Put IV
Signal: +6%
Buy signal
Bearish Signal
+1%
Call IV
+10%
Put IV
Signal: -9%
Sell/avoid signal
Top Decile
Highest signal stocks
Call IV rising fastInformed buying
Next month return:+1.5%
Bottom Decile
Lowest signal stocks
Put IV rising fastInformed selling
Next month return:-0.5%
Why do options lead stocks?

Informed traders prefer options for leverage and anonymity. When they have good news, they buy calls (pushing up call IV). When they have bad news, they buy puts. The spread in IV changes reveals their bets before the news hits stock prices.

Call IV change
Put IV change
~2% monthly spread between deciles

Research

Eight landmark papers documenting the predictive power of option-implied information.

The Mathematics

In Plain English

The math behind this strategy is straightforward. Here's what you're actually doing:

  1. 1
    Get implied volatilities for ATM call and put options on each stock. Most brokers and data providers supply these.
  2. 2
    Calculate monthly changes in call IV and put IV separately. ΔCall IV = This month's call IV minus last month's call IV.
  3. 3
    Compute the spread: ΔCall IV - ΔPut IV. Positive values mean call IV rose more than put IV (bullish signal).
  4. 4
    Rank and trade: Buy stocks with the highest spread (top decile). Short or avoid stocks with the lowest spread (bottom decile).

That's it. The formulas below just express this process precisely.

Technical Formulas

1
IV Change Signal

Formula
Signal = ΔIV_call - ΔIV_put

Where ΔIV = IV(t) - IV(t-1). Positive signal = bullish (call IV rising faster than put IV).

2
Monthly IV Change

Formula
ΔIV_call = IV_call(t) - IV_call(t-1)

One-month change in ATM call implied volatility. Use 30-day ATM options for consistency.

3
Alternative: IV Spread Level

Formula
IVS = IV_call - IV_put

Cremers & Weinbaum approach: use the level of the spread rather than changes. Positive IVS = calls expensive relative to puts.

Strategy Rules

Entry Rules

  1. 1Calculate ΔCall IV and ΔPut IV for all optionable stocks
  2. 2Compute signal: ΔCall IV - ΔPut IV
  3. 3Rank stocks by signal (highest to lowest)
  4. 4Buy top decile (highest signal = most bullish)
  5. 5Short bottom decile (lowest signal = most bearish)

Exit Rules

  1. 1Hold for one month (signal has short-term predictability)
  2. 2Exit all positions at monthly rebalance
  3. 3Re-rank and rebuild portfolio each month
  4. 4No early exits based on price movement

Data Requirements

  1. ATM call and put implied volatilities
  2. 30-day options preferred (or nearest maturity)
  3. End-of-month snapshots for signal calculation
  4. Minimum option volume/open interest for reliability

Position Sizing

  1. Equal-weight within each decile
  2. Dollar-neutral: Long = Short exposure
  3. Portfolio size: 50-100 stocks per side
  4. Adjust for liquidity in smaller names

Implementation Guide

This strategy requires options data, making it more complex than pure equity strategies. The payoff is strong predictive power, but implementation demands careful attention to data quality and execution.

1

Obtain Options Data

You need implied volatility data for ATM options. This is available from most options data providers and some brokers. Focus on 30-day ATM options for consistency. If exact 30-day options aren't available, interpolate or use the nearest expiration.

Tips
  • Free sources: CBOE (limited), Yahoo Finance (basic IV data)
  • Paid sources: OptionMetrics, IVolatility, LiveVol, ORATS
  • Broker platforms: ThinkorSwim, Interactive Brokers provide IV data
  • Use end-of-month snapshots for cleaner signal calculation

Data quality matters enormously. Stale quotes, low volume options, and wide bid-ask spreads can corrupt IV readings. Apply minimum volume and open interest filters.

2

Define Your Universe

Start with optionable stocks, typically larger and more liquid names. The strategy works best on stocks with active options markets where informed trading is more likely to occur. Filter out stocks with illiquid options.

Tips
  • Begin with S&P 500 or Russell 1000 constituents with listed options
  • Require minimum average option volume (e.g., 100 contracts/day)
  • Exclude stocks near earnings (IV spikes can distort signals)
  • Consider sector neutrality to avoid unintended factor bets
3

Calculate Monthly IV Changes

At each month-end, record the ATM call IV and ATM put IV for each stock. Compare to last month's values to get ΔCall IV and ΔPut IV. Then compute the signal: ΔCall IV - ΔPut IV.

Tips
  • ATM = strike closest to current stock price
  • Use mid-quote IVs to avoid bid-ask noise
  • For missing data points, exclude the stock that month
  • Store historical data to track signal persistence
4

Rank and Select Stocks

Rank all stocks by the signal (ΔCall IV - ΔPut IV) from highest to lowest. The top decile (highest values) goes into the long portfolio. The bottom decile (lowest/most negative values) goes into the short portfolio or is avoided.

Tips
  • Top decile: Stocks where call IV rose most relative to put IV (bullish)
  • Bottom decile: Stocks where put IV rose most relative to call IV (bearish)
  • Equal-weight positions within each portfolio
  • Target 30-50 stocks per side for diversification
5

Execute and Rebalance

Enter positions at month-end or first trading day of the new month. Hold for one month, then completely rebuild the portfolio. This is a high-turnover strategy with 100%+ annual turnover on each side.

Tips
  • Execute after market close using MOC orders if possible
  • Spread execution over the first 1-2 days to minimize impact
  • Account for trading costs in expected returns (~20-30 bps round-trip)
  • Consider ETF hedges if unable to short individual stocks

This strategy has high turnover and requires frequent trading. Transaction costs will significantly impact net returns. Paper trade first to understand realistic execution.

6

Monitor and Refine

Track your realized returns vs. expected returns from the academic research. The signal degrades over time as more traders exploit it. Consider combining with other factors or using more sophisticated variants.

Tips
  • Compare monthly returns to decile spreads in An et al. (2014)
  • Watch for signal decay as the strategy becomes crowded
  • Test variations: IV levels, volatility smirk, term structure
  • Consider transaction cost mitigation (holding period extension, buffers)

Tools and Data Sources

For retail traders, ThinkorSwim (TD Ameritrade/Schwab) and Interactive Brokers provide IV data on their platforms. OptionMetrics (institutional) and ORATS (retail-friendly) offer historical IV databases. IVolatility.com provides affordable IV data for backtesting. For a simpler approach, consider ETFs or managed products that implement similar strategies.

Helpful Tools & Resources

Data Providers
OptionMetrics, ORATS, IVolatility
Broker Platforms
ThinkorSwim, Interactive Brokers, Tastytrade
Screening Tools
Market Chameleon, Barchart, OptionAlpha
Backtesting
QuantConnect, Backtrader, Portfolio123

Strategy Variations

Explore different ways to implement this strategy, each with its own trade-offs and benefits.

IV Spread Level

Use the level of call IV minus put IV instead of changes. Positive spread = expensive calls = bullish. Simpler data requirements.

Cremers & Weinbaum (2010): 51 bps/week

Volatility Smirk

OTM put IV minus ATM call IV. Steep smirk = expensive downside protection = bearish. Captures different informed trading signal.

Xing et al. (2010): 10.9% annual alpha

Term Structure Signal

Compare short-term vs. long-term IV. Inverted term structure (short > long) often precedes negative news.

Kim et al. (2020): added predictive power

Combined with Earnings

Focus on stocks with upcoming earnings announcements. IV signals are strongest when information asymmetry is highest.

Higher alpha around events

Consider combining multiple variations or testing them against your specific investment goals and risk tolerance.

Risks & Limitations

High(2)
Medium(2)
Data ComplexityHigh

This strategy requires reliable options data that many retail traders lack access to. Poor data quality leads to false signals. Institutional-grade data is expensive; free sources may have errors or delays.

Impact:
High Turnover CostsHigh

Monthly rebalancing means 200%+ annual turnover (both sides). Transaction costs of 20-50 bps per trade can consume a significant portion of the ~1% monthly spread. Net returns may be much lower than gross.

Impact:
Signal DecayMedium

As more traders exploit options-based signals, predictability may decline. The strategy became well-known after 2014. Recent returns may be lower than historical backtests suggest.

Impact:
Execution RiskMedium

Signals are calculated at month-end but trades execute afterward. Price movements between signal calculation and execution can erode returns, especially in volatile markets.

Impact:
Understanding these risks is essential for proper position sizing and portfolio construction. Consider combining with other strategies to mitigate individual risk factors.

References

  • Bali, T. G., & Hovakimian, A. (2009). Volatility Spreads and Expected Stock Returns. Management Science, 55(11), 1797-1812 [Link]
  • Cremers, M., & Weinbaum, D. (2010). Deviations from Put-Call Parity and Stock Return Predictability. Journal of Financial and Quantitative Analysis, 45(2), 335-367 [Link]
  • Xing, Y., Zhang, X., & Zhao, R. (2010). What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?. Journal of Financial and Quantitative Analysis, 45(3), 641-662 [Link] [PDF]
  • An, B.-J., Ang, A., Bali, T. G., & Cakici, N. (2014). The Joint Cross Section of Stocks and Options. Journal of Finance, 69(5), 2279-2337 [Link] [PDF]
  • Chen, T.-F., Chung, S.-L., & Tsai, W.-C. (2016). Option-Implied Equity Risk and the Cross-Section of Stock Returns. Financial Analysts Journal, 72(6), 54-71 [Link]
  • Goncalves-Pinto, L., Grundy, B. D., Hameed, A., van der Heijden, T., & Zhu, Y. (2020). Why Do Option Prices Predict Stock Returns?. Management Science, 66(9), 3903-3926 [Link]
  • Kim, D., Kim, H., & Park, K. (2020). Informed Options Trading on the Implied Volatility Surface. Journal of Futures Markets, 40(5), 776-803 [Link]
  • Chordia, T., Lin, T.-C., & Xiang, V. (2021). Risk-Neutral Skewness, Informed Trading, and the Cross-Section of Stock Returns. Journal of Financial and Quantitative Analysis, 56(5), 1713-1737 [Link] [PDF]

Strategy based on research by An, Ang, Bali & Cakici (2014) and others. Requires options data access. Implementation details represent educational content only. Past performance does not guarantee future results. This is not investment advice.

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