vcp-screener

📁 tradermonty/claude-trading-skills 📅 12 days ago
28
总安装量
26
周安装量
#13262
全站排名
安装命令
npx skills add https://github.com/tradermonty/claude-trading-skills --skill vcp-screener

Agent 安装分布

gemini-cli 26
opencode 25
github-copilot 25
amp 25
codex 25
kimi-cli 25

Skill 文档

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/
Parameter Default Range Effect
--min-contractions 2 2-4 Higher = fewer but higher-quality patterns
--t1-depth-min 8.0% 1-50 Higher = excludes shallow first corrections
--breakout-volume-ratio 1.5x 0.5-10 Higher = stricter volume confirmation
--trend-min-score 85 0-100 Higher = stricter Stage 2 filter
--atr-multiplier 1.5 0.5-5 Lower = more sensitive swing detection
--contraction-ratio 0.75 0.1-1 Lower = requires tighter contractions
--min-contraction-days 5 1-30 Higher = longer minimum contraction
--lookback-days 120 30-365 Longer = 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