Options trading strategy analysis and simulation tool. Provides theoretical pricing using Black-Scholes model, Greeks calculation, strategy P/L simulation, and risk management guidance. Use when user requests options strategy analysis, covered calls, protective puts, spreads, iron condors, earnings

Options Strategy Advisor Overview This skill provides comprehensive options strategy analysis and education using theoretical pricing models. It helps traders understand, analyze, and simulate options strategies without requiring real time market data subscriptions. Core Capabilities: Black Scholes Pricing : Theoretical option prices and Greeks calculation Strategy Simulation : P/L analysis for major options strategies Earnings Strategies : Pre earnings volatility plays integrated with Earnings Calendar Risk Management : Position sizing, Greeks exposure, max loss/profit analysis Educational Focus : Detailed explanations of strategies and risk metrics Data Sources: FMP API: Stock prices, historical volatility, dividends, earnings dates User Input: Implied volatility (IV), risk free rate Theoretical Models: Black Scholes for pricing and Greeks Prerequisites Required: Python 3.9+ with numpy , scipy , requests Optional: FMP API key (for real time stock prices and historical volatility) Set via FMP API KEY environment variable or api key argument Without API key: Use manual inputs for stock price and volatility Installation: Quick Start Examples: When to Use This Skill Use this skill when: User asks about options strategies ("What's a covered call?", "How does an iron condor work?") User wants to simulate strategy P/L ("What's my max profit on a bull call spread?") User needs Greeks analysis ("What's my delta exposure?") User asks about earnings strategies ("Should I buy a straddle before earnings?") User wants to compare strategies ("Covered call vs protective put?") User needs position sizing guidance ("How many contracts should I trade?") User asks about volatility ("Is IV high right now?") Example requests: "Analyze a covered call on AAPL" "What's the P/L on a $100/$105 bull call spread on MSFT?" "Should I trade a straddle before NVDA earnings?" "Calculate Greeks for my iron condor position" "Compare protective put vs covered call for downside protection" Supported Strategies Income Strategies 1. Covered Call Own stock, sell call (generate income, cap upside) 2. Cash Secured Put Sell put with cash backing (collect premium, willing to buy stock) 3. Poor Man's Covered Call LEAPS call + short near term call (capital efficient) Protection Strategies 4. Protective Put Own stock, buy put (insurance, limited downside) 5. Collar Own stock, sell call + buy put (limited upside/downside) Directional Strategies 6. Bull Call Spread Buy lower strike call, sell higher strike call (limited risk/reward bullish) 7. Bull Put Spread Sell higher strike put, buy lower strike put (credit spread, bullish) 8. Bear Call Spread Sell lower strike call, buy higher strike call (credit spread, bearish) 9. Bear Put Spread Buy higher strike put, sell lower strike put (limited risk/reward bearish) Volatility Strategies 10. Long Straddle Buy ATM call + ATM put (profit from big move either direction) 11. Long Strangle Buy OTM call + OTM put (cheaper than straddle, bigger move needed) 12. Short Straddle Sell ATM call + ATM put (profit from no movement, unlimited risk) 13. Short Strangle Sell OTM call + OTM put (profit from no movement, wider range) Range Bound Strategies 14. Iron Condor Bull put spread + bear call spread (profit from range bound movement) 15. Iron Butterfly Sell ATM straddle, buy OTM strangle (profit from tight range) Advanced Strategies 16. Calendar Spread Sell near term option, buy longer term option (profit from time decay) 17. Diagonal Spread Calendar spread with different strikes (directional + time decay) 18. Ratio Spread Unbalanced spread (more contracts on one leg) Analysis Workflow Step 1: Gather Input Data Required from User: Ticker symbol Strategy type Strike prices Expiration date(s) Position size (number of contracts) Optional from User: Implied Volatility (IV) if not provided, use Historical Volatility (HV) Risk free rate default to current 3 month T bill rate (~5.3% as of 2025) Fetched from FMP API: Current stock price Historical prices (for HV calculation) Dividend yield Upcoming earnings date (for earnings strategies) Example User Input: Step 2: Calculate Historical Volatility (if IV not provided) Objective: Estimate volatility from historical price movements. Method: Output: Historical Volatility (annualized percentage) Note to user: "HV = 24.5%, consider using current market IV for more accuracy" User Can Override: Provide IV from broker platform (ThinkorSwim, TastyTrade, etc.) Script accepts iv 28.0 parameter Step 3: Price Options Using Black Scholes Black Scholes Model: For European style options: Adjustments: Subtract present value of dividends from S for calls American options: Use approximation or note "European pricing, may undervalue American options" Python Implementation: Output for Each Option Leg: Theoretical price Note: "Market price may differ due to bid ask spread and American vs European pricing" Step 4: Calculate Greeks The Greeks measure option price sensitivity to various factors: Delta (Δ): Change in option price per $1 change in stock price Gamma (Γ): Change in delta per $1 change in stock price Theta (Θ): Change in option price per day (time decay) Vega (ν): Change in option price per 1% change in volatility Rho (ρ): Change in option price per 1% change in interest rate Position Greeks: For a strategy with multiple legs, sum Greeks across all legs: Greeks Interpretation: Greek Meaning Example Delta Directional exposure Δ = 0.50 → $50 profit if stock +$1 Gamma Delta acceleration Γ = 0.05 → Delta increases by 0.05 if stock +$1 Theta Daily time decay Θ = $5 → Lose $5/day from time passing Vega Volatility sensitivity ν = $10 → Gain $10 if IV increases 1% Rho Interest rate sensitivity ρ = $2 → Gain $2 if rates increase 1% Step 5: Simulate Strategy P/L Objective: Calculate profit/loss at various stock prices at expiration. Method: Generate stock price range (e.g., ±30% from current price): For each price point, calculate P/L: Key Metrics: Max Profit : Highest possible P/L Max Loss : Worst possible P/L Breakeven Point(s) : Stock price(s) where P/L = 0 Profit Probability : Percentage of price range that's profitable (simplified) Example Output: Step 6: Generate P/L Diagram (ASCII Art) Visual representation of P/L across stock prices: Example Output: Step 7: Strategy Specific Analysis Provide tailored guidance based on strategy type: Covered Call: Protective Put: Iron Condor: Step 8: Earnings Strategy Analysis Integration with Earnings Calendar: When user asks about earnings strategies, fetch earnings date: Pre Earnings Strategies: Long Straddle/Strangle: Short Iron Condor: Step 9: Risk Management Guidance Position Sizing: Portfolio Greeks Management: Adjustments and Exits: Output Format Strategy Analysis Report Template: File Naming Convention: Example: options analysis AAPL BullCallSpread 2025 11 08.md Key Principles Theoretical Pricing Limitations What Users Should Know: 1. Black Scholes Assumptions: European style options (can't exercise early) Constant volatility (IV changes in reality) No transaction costs Continuous trading 2. Real vs Theoretical: Bid ask spread: Actual cost higher than theoretical American options: Can be exercised early (especially ITM puts) Liquidity: Wide markets on illiquid options Dividends: Ex dividend dates affect pricing 3. Best Practices: Use as educational tool and comparative analysis Get real quotes from broker before trading Understand theoretical price ≈ mid market price Account for commissions and slippage Volatility Guidance Historical vs Implied Volatility: IV Percentile: User provides current IV, we calculate percentile: Integration with Other Skills Earnings Calendar: Fetch earnings dates automatically Suggest earnings specific strategies Calculate days to earnings (DTE critical for IV) Warn about IV crush risk Technical Analyst: Use support/resistance for strike selection Trend analysis for directional strategies Breakout potential for straddle/strangle timing US Stock Analysis: Fundamental analysis for longer term strategies (LEAPS) Dividend yield for covered call/put analysis Earnings quality for earnings plays Bubble Detector: High bubble risk → focus on protective puts Low risk → bullish strategies Critical risk → avoid long premium (theta hurts) Portfolio Manager: Track options positions alongside stock positions Aggregate Greeks across portfolio Options as hedging tool for stock positions Important Notes All analysis in English Educational focus : Strategies explained clearly Theoretical pricing : Black Scholes approximation User IV input : Optional, defaults to HV No real time data required : FMP Free tier sufficient Dependencies : Python 3.9+, numpy, scipy, requests Common Use Cases Use Case 1: Learn Strategy Use Case 2: Analyze Specific Trade Use Case 3: Earnings Strategy Use Case 4: Portfolio Greeks Check Troubleshooting Problem: IV not available Solution: Use HV as proxy, note to user Ask user to provide IV from broker platform Problem: Negative option price Solution: Check inputs (strike vs stock price) Deep ITM options may have numerical issues Problem: Greeks seem wrong Solution: Verify inputs (T, sigma, r) Check if using annual vs daily values Problem: Strategy too complex Solution: Break into legs, analyze separately Refer to references for strategy details Resources References: references/black scholes methodology.md Black Scholes formulas, Greeks, and interpretation references/strategies guide.md All 17+ strategies explained (future) references/greeks explained.md Greeks deep dive (future) references/volatility guide.md HV vs IV, when to trade (future) Scripts: scripts/black scholes.py Pricing engine and Greeks scripts/strategy analyzer.py Strategy simulation scripts/earnings strategy.py Earnings specific analysis External Resources: Options Playbook: https://www.optionsplaybook.com/ CBOE Education: https://www.cboe.com/education/ Black Scholes Calculator: Various online tools for verification Version : 1.0 Last Updated : 2025 11 08 Dependencies : Python 3.9+, numpy, scipy, requests API : FMP API (Free tier sufficient)

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