Strategy #0000000098 · Options and volatility factors
Cross-sectional realised versus implied volatility
Enter realised/implied vol for high/low-gap baskets, notional per variance point and costs for a spread scenario.
Goyal and Saretto sort stocks by historical realised volatility relative to current implied volatility, buying straddles with the largest gaps and shorting those with the smallest. Straddle returns depend on direction, volatility risk premia, skew, costs and jumps; a variance gap alone is not full option P&L.
The variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps.
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
What is the scenario spread between high and low realised-minus-implied variance baskets?
Goyal and Saretto sort stocks by historical realised volatility relative to current implied volatility, buying straddles with the largest gaps and shorting those with the smallest. Straddle returns depend on direction, volatility risk premia, skew, costs and jumps; a variance gap alone is not full option P&L.
Enter realised/implied vol for high/low-gap baskets, notional per variance point and costs for a spread scenario.
The variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps.
- Input assumptionsEnter realised/implied vol for high/low-gap baskets, notional per variance point and costs for a spread scenario.
- Model outputThe variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Gap_i=\sigma^2_{realised,i}-\sigma^2_{implied,i},\quad Spread=Gap_{high}-Gap_{low}-C
Volatility is entered in percentage points; the gap is in vol-pct squared and notional scaling is user-set.
Greeks: the directional intuition
- 模型
- Measures sensitivity to implied volatility.
- 尾部
- Measures sensitivity to implied volatility.
- 執行
- Measures sensitivity to implied volatility.
Gap_i=\sigma^2_{realised,i}-\sigma^2_{implied,i},\quad Spread=Gap_{high}-Gap_{low}-C
Practical context · published observations
Cross-sectional realised versus implied volatility: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
The variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps. Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Related structures use different exposures and loss conditions.
Compare allocation, financing and payoff assumptions.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Base structure | Scenario allocation | Goyal and Saretto sort stocks by historical realised volatility relative to current implied volatility, buying straddles with the largest gaps and shorting those with the smallest. Straddle returns depend on direction, volatility risk premia, skew, costs and jumps; a variance gap alone is not full option P&L. | The variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps. |
| Conservative version | Lower exposure | Reduce notional, leverage or multiplier. | May reduce upside participation. |
| Dynamic version | Periodic rebalance | Reset exposure by risk or regime. | Needs more trading and model governance. |
The variance-gap proxy omits straddle premium, delta hedging, term structure and tail jumps.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.