iv crush survival guide
by nowrich
Eliminate losses from IV crush by modeling event-based volatility collapse and trade expectancy.
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Works with the AI tools you already use
See it in action
You say
Analyze a long call on XYZ at $100. Earnings tomorrow. ATM straddle is $8. IV is 80%, historical post-earnings IV is 40%. I expect a 10% move up.
Your agent does
Expected Move: $6.80. Scenario Analysis:
- Large Up (+10%): P/L +$6.50
- Mod Up (+3%): P/L -$0.20
- Flat: P/L -$2.20 Expectancy: -0.32. Verdict: Negative expectancy. The IV crush (50% drop) outweighs the directional edge. Consider a Bull Call Spread.
What you get
About this skill
The problem
Traders often lose money on long options during earnings or news events even when they predict the direction correctly. This happens because they fail to account for implied volatility (IV) collapse, which can drain an option's value faster than the price move can build it.
What it does
- Calculates the market's expected move using ATM straddle pricing and specific multipliers.
- Estimates post-event IV crush levels based on historical volatility and IV rank.
- Generates a structured scenario analysis table covering large moves, moderate moves, and flat outcomes.
- Computes the mathematical expectancy of a trade by weighting potential P/L against outcome probabilities.
- Identifies when to switch from long single options to spreads or neutral structures to mitigate volatility risk.
Why this beats prompting it yourself
General LLMs often treat options like simple directional bets and ignore the Greeks. This skill enforces a specific mathematical methodology that combines price magnitude, timing, and IV contraction into a single expectancy calculation, preventing "stock bets in options clothing."
Use cases
- Evaluating whether to buy calls before a high-anticipation earnings release.
- Comparing the risk-reward of a long straddle versus a iron condor for an FDA drug trial result.
- Determining if a current IV rank of 90% makes a debit spread too expensive to justify.
- Modeling the impact of a 50% volatility drop on a portfolio after a macro data print.
Known limitations
Requires the user to provide current option chain data or IV levels as it does not have a live market data feed. Results are theoretical projections based on Black-Scholes approximations.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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