vcp-screener

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP). Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points. Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, or Stage 2 momentum stock scanning.

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Install skill "vcp-screener" with this command: npx skills add tradermonty/claude-trading-skills/tradermonty-claude-trading-skills-vcp-screener

VCP Screener - Minervini Volatility Contraction Pattern

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP), identifying Stage 2 uptrend stocks with contracting volatility near breakout pivot points.

When to Use

  • User asks for VCP screening or Minervini-style setups
  • User wants to find tight base / volatility contraction patterns
  • User requests Stage 2 momentum stock scanning
  • User asks for breakout candidates with defined risk

Prerequisites

  • FMP API key (set FMP_API_KEY environment variable or pass --api-key)
  • Free tier (250 calls/day) is sufficient for default screening (top 100 candidates)
  • Paid tier recommended for full S&P 500 screening (--full-sp500)

Workflow

Step 1: Prepare and Execute Screening

Run the VCP screener script:

# Default: S&P 500, top 100 candidates
python3 skills/vcp-screener/scripts/screen_vcp.py --output-dir skills/vcp-screener/scripts

# Custom universe
python3 skills/vcp-screener/scripts/screen_vcp.py --universe AAPL NVDA MSFT AMZN META --output-dir skills/vcp-screener/scripts

# Full S&P 500 (paid API tier)
python3 skills/vcp-screener/scripts/screen_vcp.py --full-sp500 --output-dir skills/vcp-screener/scripts

Advanced Tuning (for backtesting)

Adjust VCP detection parameters for research and backtesting:

python3 skills/vcp-screener/scripts/screen_vcp.py \
  --min-contractions 3 \
  --t1-depth-min 12.0 \
  --breakout-volume-ratio 2.0 \
  --trend-min-score 90 \
  --atr-multiplier 1.5 \
  --output-dir reports/
ParameterDefaultRangeEffect
--min-contractions22-4Higher = fewer but higher-quality patterns
--t1-depth-min8.0%1-50Higher = excludes shallow first corrections
--breakout-volume-ratio1.5x0.5-10Higher = stricter volume confirmation
--trend-min-score850-100Higher = stricter Stage 2 filter
--atr-multiplier1.50.5-5Lower = more sensitive swing detection
--contraction-ratio0.750.1-1Lower = requires tighter contractions
--min-contraction-days51-30Higher = longer minimum contraction
--lookback-days12030-365Longer = finds older patterns

Step 2: Review Results

  1. Read the generated JSON and Markdown reports
  2. Load references/vcp_methodology.md for pattern interpretation context
  3. Load references/scoring_system.md for score threshold guidance

Step 3: Present Analysis

For each top candidate, present:

  • VCP composite score and rating
  • Contraction details (T1/T2/T3 depths and ratios)
  • Trade setup: pivot price, stop-loss, risk percentage
  • Volume dry-up ratio
  • Relative strength rank

Step 4: Provide Actionable Guidance

Based on ratings:

  • Textbook VCP (90+): Buy at pivot with aggressive sizing
  • Strong VCP (80-89): Buy at pivot with standard sizing
  • Good VCP (70-79): Buy on volume confirmation above pivot
  • Developing (60-69): Add to watchlist, wait for tighter contraction
  • Weak/No VCP (<60): Monitor only or skip

3-Phase Pipeline

  1. Pre-Filter - Quote-based screening (price, volume, 52w position) ~101 API calls
  2. Trend Template - 7-point Stage 2 filter with 260-day histories ~100 API calls
  3. VCP Detection - Pattern analysis, scoring, report generation (no additional API calls)

Output

  • vcp_screener_YYYY-MM-DD_HHMMSS.json - Structured results
  • vcp_screener_YYYY-MM-DD_HHMMSS.md - Human-readable report

Resources

  • references/vcp_methodology.md - VCP theory and Trend Template explanation
  • references/scoring_system.md - Scoring thresholds and component weights
  • references/fmp_api_endpoints.md - API endpoints and rate limits

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