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skills/options-strategy-advisor/README.md
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skills/options-strategy-advisor/README.md
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# Options Strategy Advisor
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Educational options trading tool providing theoretical pricing, strategy analysis, and risk management guidance using Black-Scholes model.
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## Overview
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Options Strategy Advisor helps traders understand and analyze options strategies without requiring expensive real-time options data. It uses theoretical pricing models (Black-Scholes) combined with free stock market data (FMP API) to simulate strategies and calculate Greeks.
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**Key Features:**
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- ✅ Black-Scholes pricing engine
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- ✅ All Greeks calculation (Delta, Gamma, Theta, Vega, Rho)
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- ✅ 17+ options strategies supported
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- ✅ P/L simulation and visualization
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- ✅ Earnings strategy integration
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- ✅ Historical volatility calculation
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- ✅ Risk management guidance
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## Why This Approach?
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**No expensive data subscriptions needed:**
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- Real-time options data: $99-$500/month (Polygon.io, Intrinio)
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- FMP API Free tier: $0/month (250 requests/day)
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**Educational focus:**
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- Learn how strategies work
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- Understand Greeks and risk metrics
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- Compare strategies side-by-side
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**Practical application:**
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- Theoretical prices ≈ market mid-prices
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- User can input actual IV from broker
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- Good for strategy planning and education
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## Supported Strategies
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### Income Strategies
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1. **Covered Call** - Generate income from stock holdings
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2. **Cash-Secured Put** - Get paid to buy stock
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3. **Poor Man's Covered Call** - Capital-efficient covered call
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### Protection Strategies
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4. **Protective Put** - Insurance for stock positions
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5. **Collar** - Limited risk/reward protection
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### Directional Strategies
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6. **Bull Call Spread** - Limited risk bullish play
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7. **Bull Put Spread** - Credit spread for bullish view
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8. **Bear Call Spread** - Credit spread for bearish view
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9. **Bear Put Spread** - Limited risk bearish play
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### Volatility Strategies
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10. **Long Straddle** - Profit from big moves
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11. **Long Strangle** - Cheaper straddle, bigger move needed
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12. **Short Straddle** - Profit from no movement (high risk)
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13. **Short Strangle** - Wider range straddle
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### Range-Bound Strategies
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14. **Iron Condor** - Profit from range-bound trading
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15. **Iron Butterfly** - Tight range profit
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### Advanced Strategies
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16. **Calendar Spread** - Time decay play
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17. **Diagonal Spread** - Directional + time decay
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## Installation
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### Prerequisites
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- Python 3.8+
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- FMP API key (free tier sufficient)
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### Install Dependencies
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```bash
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pip install numpy scipy requests pandas
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```
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### Get FMP API Key
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1. Visit https://financialmodelingprep.com/developer/docs
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2. Sign up for free account
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3. Copy API key
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4. Set environment variable:
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```bash
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export FMP_API_KEY="your_key_here"
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```
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## Quick Start
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### Test Black-Scholes Pricer
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```bash
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python scripts/black_scholes.py
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```
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**Example Output:**
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```
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BLACK-SCHOLES OPTIONS PRICER - EXAMPLE
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======================================================================
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Input Parameters:
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Stock Price: $180.00
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Strike Price: $185.00
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Days to Expiration: 30
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Volatility: 25.0%
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Risk-Free Rate: 5.30%
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Dividend Yield: 1.0%
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======================================================================
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CALL OPTION
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======================================================================
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Price: $2.45
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Intrinsic Value: $0.00
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Time Value: $2.45
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Greeks:
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Delta: 0.3654 ($36.54 per $1 move)
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Gamma: 0.0234 (delta changes by 0.0234)
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Theta: -$0.18/day (loses $0.18 per day)
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Vega: $0.25 per 1% IV (gains $0.25 if IV +1%)
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Rho: $0.12 per 1% rate (gains $0.12 if rate +1%)
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```
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### Use in Your Code
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```python
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from scripts.black_scholes import OptionPricer
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# Initialize pricer
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pricer = OptionPricer(
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S=180, # Stock price
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K=185, # Strike price
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T=30/365, # Time to expiration (years)
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r=0.053, # Risk-free rate (5.3%)
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sigma=0.25, # Volatility (25%)
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q=0.01 # Dividend yield (1%)
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)
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# Get call option price
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call_price = pricer.call_price()
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print(f"Call Price: ${call_price:.2f}")
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# Get all Greeks for call
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call_greeks = pricer.get_all_greeks('call')
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print(f"Delta: {call_greeks['delta']:.4f}")
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print(f"Gamma: {call_greeks['gamma']:.4f}")
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print(f"Theta: ${call_greeks['theta']:.2f}/day")
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print(f"Vega: ${call_greeks['vega']:.2f} per 1%")
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```
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### Calculate Historical Volatility
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```python
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from scripts.black_scholes import (
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calculate_historical_volatility,
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fetch_historical_prices_for_hv
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)
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# Fetch prices from FMP
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api_key = "your_key"
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prices = fetch_historical_prices_for_hv("AAPL", api_key, days=90)
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# Calculate 30-day HV
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hv = calculate_historical_volatility(prices, window=30)
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print(f"30-Day HV: {hv*100:.2f}%")
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```
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## Understanding the Metrics
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### Option Price Components
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**Intrinsic Value:**
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- Call: max(0, Stock Price - Strike Price)
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- Put: max(0, Strike Price - Stock Price)
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**Time Value:**
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- Option Price - Intrinsic Value
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- Decays to $0 at expiration
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### The Greeks
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**Delta (Δ)** - Directional Exposure
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```
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Range: 0 to 1 (calls), -1 to 0 (puts)
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Meaning: Change in option price per $1 stock move
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Example: Δ = 0.50
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→ If stock +$1, option +$0.50
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→ If stock -$1, option -$0.50
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```
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**Gamma (Γ)** - Delta Acceleration
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```
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Meaning: Change in delta per $1 stock move
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Peak: ATM options
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Low: Deep ITM or OTM
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Example: Γ = 0.05, Δ currently = 0.50
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→ If stock +$1, delta becomes 0.55
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```
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**Theta (Θ)** - Time Decay
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```
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Meaning: Change in option price per day
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Sign: Usually negative (options lose value over time)
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Peak: Last 30 days before expiration
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Example: Θ = -$0.15/day
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→ Tomorrow, option loses $0.15 if nothing else changes
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```
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**Vega (ν)** - Volatility Sensitivity
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```
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Meaning: Change in option price per 1% IV change
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Sign: Always positive (options gain value when vol increases)
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Example: ν = $0.25 per 1%
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→ If IV increases from 25% to 26%, option +$0.25
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```
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**Rho (ρ)** - Interest Rate Sensitivity
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```
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Meaning: Change in option price per 1% rate change
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Sign: Positive for calls, negative for puts
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Impact: Usually small unless long-dated options
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Example: ρ = $0.10 per 1%
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→ If interest rate increases 1%, option +$0.10
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```
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### Volatility: HV vs IV
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**Historical Volatility (HV):**
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- Calculated from past price movements
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- Objective, based on actual data
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- Available free (from price data)
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**Implied Volatility (IV):**
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- Derived from option market prices
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- Subjective, based on supply/demand
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- Requires real-time options data (or user input)
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**Comparison:**
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```
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IV > HV: Options expensive → Consider selling premium
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IV < HV: Options cheap → Consider buying options
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IV = HV: Fairly priced → Any strategy works
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```
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## Common Workflows
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### 1. Analyze a Strategy
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```python
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from scripts.black_scholes import OptionPricer
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# Stock: AAPL @ $180
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# Strategy: Bull Call Spread $180/$185 (30 DTE)
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# Price long call ($180 strike)
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long_call = OptionPricer(S=180, K=180, T=30/365, r=0.053, sigma=0.25)
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long_price = long_call.call_price()
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long_delta = long_call.call_delta()
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# Price short call ($185 strike)
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short_call = OptionPricer(S=180, K=185, T=30/365, r=0.053, sigma=0.25)
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short_price = short_call.call_price()
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short_delta = short_call.call_delta()
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# Strategy metrics
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net_debit = long_price - short_price
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max_profit = (185 - 180) - net_debit
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max_loss = -net_debit
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position_delta = long_delta - short_delta
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print(f"Bull Call Spread $180/$185")
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print(f"Net Debit: ${net_debit:.2f}")
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print(f"Max Profit: ${max_profit:.2f} (at $185+)")
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print(f"Max Loss: ${max_loss:.2f} (at $180-)")
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print(f"Position Delta: {position_delta:.4f}")
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```
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### 2. Compare IV to HV
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```python
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# Get HV
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prices = fetch_historical_prices_for_hv("AAPL", api_key, days=90)
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hv = calculate_historical_volatility(prices, window=30)
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# User provides IV (from broker platform)
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iv = 0.28 # 28% from ThinkorSwim
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print(f"Historical Volatility: {hv*100:.2f}%")
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print(f"Implied Volatility: {iv*100:.1f}%")
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if iv > hv * 1.1:
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print("→ Options expensive (IV > HV) - Consider selling premium")
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elif iv < hv * 0.9:
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print("→ Options cheap (IV < HV) - Consider buying options")
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else:
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print("→ Fairly priced")
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```
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### 3. Earnings Strategy
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Check if earnings coming up (use Earnings Calendar skill):
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```python
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# If earnings in 7 days:
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# - IV typically elevated (30-50% higher)
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# - Consider straddle/strangle (profit from big move)
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# - Or sell iron condor (profit from IV crush)
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# Example: Long Straddle
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straddle_cost = call_price + put_price
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breakeven_up = stock_price + straddle_cost
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breakeven_down = stock_price - straddle_cost
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print(f"Straddle Cost: ${straddle_cost:.2f}")
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print(f"Breakevens: ${breakeven_down:.2f} / ${breakeven_up:.2f}")
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print(f"Need {abs(breakeven_up - stock_price)/stock_price*100:.1f}% move to profit")
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```
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## Limitations & Best Practices
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### Theoretical vs Market Prices
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**Black-Scholes Assumptions:**
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- European options (can't exercise early)
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- Constant volatility (changes in reality)
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- No transaction costs
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- Continuous trading
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**Real World Differences:**
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- American options (most stocks) can exercise early
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- Bid-ask spread: Actual cost higher than theoretical mid
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- Commissions and slippage
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- Liquidity: Wide markets on illiquid options
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### Best Practices
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**1. Use for Education & Planning:**
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- Learn how strategies work
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- Compare different approaches
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- Understand risk/reward before trading
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**2. Verify Before Trading:**
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- Get real quotes from your broker
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- Check bid-ask spread
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- Confirm option liquidity (open interest, volume)
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**3. Input Actual IV:**
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- Theoretical price assumes constant volatility
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- Use current market IV for accuracy
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- Check IV percentile (high/low relative to history)
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**4. Account for Dividends:**
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- Ex-dividend dates affect option prices
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- Calls lose value, puts gain value on ex-div date
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- Script supports dividend yield input
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**5. Monitor Greeks:**
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- Delta: Overall directional exposure
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- Theta: Daily time decay (seller advantage)
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- Vega: Volatility risk (watch during earnings)
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- Gamma: Risk of delta changing (avoid near expiration)
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## Integration with Other Skills
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**Earnings Calendar:**
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- Fetch earnings dates
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- Identify IV crush opportunities
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- Time earnings strategies
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**Technical Analyst:**
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- Use support/resistance for strike selection
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- Trend analysis for directional strategies
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- Breakout potential for straddle timing
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**US Stock Analysis:**
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- Fundamental analysis for LEAPS
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- Dividend yield for covered call/put
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- Earnings quality for earnings plays
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**Bubble Detector:**
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- High risk → protective puts
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- Low risk → bullish strategies
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- Critical risk → avoid long premium
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**Portfolio Manager:**
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- Track options with stock positions
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- Aggregate Greeks across portfolio
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- Options as hedging tool
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## API Usage & Costs
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**Free Tier Sufficient:**
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- Stock prices: 1 request per symbol
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- Historical prices (HV): 1 request per symbol
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- Dividend data: 1 request per symbol
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**Example Analysis Cost:**
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```
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Covered Call on AAPL:
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- Current price: 1 request
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- HV calculation: 1 request (90 days data)
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- Dividend yield: 1 request
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Total: 3 requests
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Daily budget: 250 requests / day
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→ Can analyze ~80 strategies per day
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```
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## Troubleshooting
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### Negative Option Price
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**Cause:** Invalid inputs (strike vs stock price)
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**Solution:** Check that inputs make sense
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### Greeks Seem Wrong
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**Cause:** Using wrong units (annual vs daily)
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**Solution:** Verify T is in years, theta is per day
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### HV Very Different from IV
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**Normal:** IV reflects future expectations, HV is past
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**Action:** Use IV from broker for more accuracy
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### Option Price Too High/Low
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**Cause:** Volatility input incorrect
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**Solution:** Verify sigma is annual (e.g., 0.25 for 25%)
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## Resources
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### Documentation
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- `SKILL.md` - Complete workflow and strategies
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- `references/strategies_guide.md` - All strategies explained (TBD)
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- `references/greeks_explained.md` - Greeks deep dive (TBD)
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### External Resources
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- Options Playbook: https://www.optionsplaybook.com/
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- CBOE Education: https://www.cboe.com/education/
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- Black-Scholes Calculator: https://www.option-price.com/
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### Get Real IV
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- ThinkorSwim (TD Ameritrade): Free
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- TastyTrade: Free
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- Barchart: https://www.barchart.com/options
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- CBOE: http://www.cboe.com/delayedquote/
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## Future Enhancements
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**Planned:**
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- Strategy simulation script (complete P/L analysis)
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- P/L diagram generator (ASCII art)
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- Earnings strategy advisor (integrated with Earnings Calendar)
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- Complete strategy reference guides
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**Contributions Welcome:**
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- Additional strategies
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- Improved volatility models
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- Better visualization tools
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## License
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Educational use. Trade at your own risk. Options involve significant risk and are not suitable for all investors.
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---
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**Version:** 1.0
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**Last Updated:** 2025-11-08
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**Dependencies:** Python 3.8+, numpy, scipy, requests
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**API:** FMP API (Free tier sufficient)
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**Model:** Black-Scholes (European options pricing)
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