PMCC Scanner

Finds optimal Poor Man's Covered Call setups by scoring symbols on option chain quality.

What is PMCC?

Buy deep ITM LEAPS call (delta ~0.80) + Sell short-term OTM call (delta ~0.20) against it. Cheaper alternative to covered calls.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/scan.py SYMBOLS [options]

Arguments

• SYMBOLS - Comma-separated tickers or path to JSON file from bullish scanner
• --min-leaps-days - Minimum LEAPS expiration in days (default: 270 = 9 months)
• --leaps-delta - Target LEAPS delta (default: 0.80)
• --short-delta - Target short call delta (default: 0.20)
• --output - Save results to JSON file (use this; Claude generates the report from the JSON)
• --report - Save auto-generated markdown to file (programmatic fallback only — prefer Claude-generated reports)

Scoring System (max possible: 14, range: -8 to 14)

Category	Condition	Points
Delta Accuracy	LEAPS within ±0.05	+2
	LEAPS within ±0.10	+1
	Short within ±0.05	+1
	Short within ±0.10	+0.5
Liquidity	LEAPS vol+OI > 100	+1
	LEAPS vol+OI > 20	+0.5
	Short vol+OI > 500	+1
	Short vol+OI > 100	+0.5
Spread	LEAPS spread < 5%	+1
	LEAPS spread < 10%	+0.5
	Short spread < 10%	+1
	Short spread < 20%	+0.5
IV Level	25-50% (ideal)	+2
	20-60%	+1
Yield	Annual > 50%	+2
	Annual > 30%	+1
	Annual > 15%	+0.5
Trend	Price > SMA50	+1 / -1
	RSI > 50	+0.5 / -0.5
	MACD > signal	+0.5 / -0.5
Earnings	Next earnings > 45 days	+1.0
	Earnings within 45 days	-1.0
	Earnings within short expiry	-2.0
Weekly Options	No weekly options listed	-1
Strike Density	< 3 strikes spot→short	-2
	< 5 strikes spot→short	-1
Short Premium	Short mid < $0.10	-1
	Short mid < $0.50	-0.5

Weekly-options, strike-density, and short-premium are penalty-only (0 at best), so max_possible_score stays 14 while the theoretical minimum is -8 (base 0, trend -2, earnings -2, weekly -1, strike -2, short premium -1).

Output

Returns JSON with:

• criteria - Scan parameters used
• results - Array sorted by score:
  • symbol, price, iv_pct, pmcc_score, max_possible_score (always 14)
  • industry - GICS industry (falls back to sector), or null
  • description - one-sentence company description, or null
  • has_weeklies - whether the symbol lists weekly options (bool)
  • short_window - short-expiry window actually used: "7-21" or "5-30 (fallback)"
  • dividend_yield - continuous dividend yield (fraction) used in the BS/IV math
  • leaps - expiry, strike, delta, iv (calculated from bid/ask), last_price, bid/ask, spread%, volume, OI
  • short - expiry, strike, delta, iv (calculated from bid/ask), last_price, bid/ask, spread%, volume, OI
  • earnings_date - next earnings date (YYYY-MM-DD) or null
  • metrics - net_debit, short_yield% (period yield over the short window), annual_yield%, capital_required
  • score_breakdown - every scoring component as a <name>_delta (float) + <name> (explanation string) pair:
    • Base: leaps_delta, short_delta, leaps_liquidity, short_liquidity, leaps_spread, short_spread, iv, yield
    • Trend: trend_delta, trend (per-indicator dict)
    • Earnings: earnings_delta, earnings
    • Weekly options: weekly_options_delta, weekly_options
    • Strike density: strike_density_delta, strike_density
    • Short premium: short_premium_delta, short_premium
    • All _delta values sum to pmcc_score
• errors - Symbols that failed (no options, insufficient data)

Report Generation

When the user asks for a report, a written analysis, or a saved document:

1. Run the scanner with --output to capture JSON data:

   uv run python scripts/scan.py SYMBOLS --output sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.json
   

2. Read the JSON output.

3. Generate the markdown report yourself using the template defined in templates/markdown-template.md. Do not use the --report flag — that produces mechanical string output. Claude-generated reports include real analysis, contextual warnings, and trader-relevant narrative.

4. Save the generated markdown to sandbox/PMCC_Scan_YYYY-MM-DD_HHmm.md (match the JSON timestamp).

5. Display the full report to the user.

Examples

# Scan specific symbols
uv run python scripts/scan.py AAPL,MSFT,GOOGL,NVDA

# Scan and save JSON for report generation
uv run python scripts/scan.py AAPL,MSFT,GOOGL --output sandbox/PMCC_Scan_2026-01-15_1430.json

# Use output from bullish scanner
uv run python scripts/scan.py bullish_results.json

# Custom delta targets
uv run python scripts/scan.py AAPL,MSFT --leaps-delta 0.70 --short-delta 0.15

# Longer LEAPS (1 year minimum)
uv run python scripts/scan.py AAPL,MSFT --min-leaps-days 365

IV Calculation

IV is always computed from market price data via Black-Scholes, never taken from Yahoo Finance's impliedVolatility column:

• During trading hours: IV derived from bid/ask mid price
• Off-hours (bid=ask=0): IV derived from last price, using the option's last trade timestamp as the pricing moment (not current wall-clock time)

This applies to both compute_atm_iv (used for scanner baseline IV) and per-option delta calculations.

Dividends: the Black-Scholes inversion uses the underlying's continuous dividend yield (Merton model). Ignoring it biases recovered IV downward for calls on dividend payers — badly for high yielders (e.g. a 7%-yield name would read ~12% IV instead of ~24%). The yield is normalized from yfinance's inconsistent fields (dividendRate/price, then trailingAnnualDividendYield, then dividendYield) and reported as dividend_yield (a fraction) in each result. The same yield feeds the strike-selection deltas and the max-profit repricing.

Key Constraints

• Short strike must be above LEAPS strike
• Options with bid = 0 and no last price are skipped
• Moderate IV (25-50%) scores highest

Interpretation

• Score > 12: Excellent candidate (strong structure + bullish trend + clear earnings runway)
• Score 10-12: Good candidate
• Score 6-10: Acceptable with caveats
• Score < 6: Poor structure, bearish trend, or earnings risk
• max_possible_score is always 14 — use pmcc_score / max_possible_score to gauge how close a candidate is to perfect
• Off-hours scores are not comparable to market-hours scores. When bid/ask aren't both > 0 (outside trading hours), spread_pct is forced to 100%, which zeroes out both spread scores (−2 vs a live scan). A candidate can look up to 2 points worse simply because it was scanned off-hours. Compare candidates only within the same scan.

Dependencies

• numpy
• pandas
• scipy
• yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.