Skill detail
vcp-screener
Finds momentum breakout setups for stock trading.
Inspect before use
Automated review checks relevance, not safety or endorsement. Read the source instructions before using this skill.
SKILL.md
The saved excerpt is a snapshot from review. The external source remains the complete and most current version.
--- name: vcp-screener description: Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points; in historical single-ticker mode walks a multi-year history and emits every VCP that formed with forward-outcome stats (breakout / stop-hit / timeout). Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, Stage 2 momentum stock scanning, or historical VCP pattern study on a specific ticker (e.g. FIX, TSLA). --- # 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 - User asks "find every historical VCP in <TICKER>" or wants to study one ticker's past VCP setups with forward outcomes (`--history --ticker SYM`) ## 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: ```bash # 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 ``` ### Strict Mode (Minervini pure setup) Only return stocks with `valid_vcp=True` AND `execution_state` in `(Pre-breakout, Breakout)`: ```bash python3 skills/vcp-screener/scripts/screen_vcp.py --strict --output-dir reports/ ``` ### Historical single-ticker mode Walk one ticker's multi-year history, detect every VCP that ever formed, and attach forward-outcome stats (breakout / stop-hit / timeout, days-to-outcome, max gain, max loss) per detection. Useful for pattern study and backtesting context — not a real-time screener. ```bash # Default: scan ~5 years (1260 trading days), 5-day stride, 60-day outcome window python3 skills/vcp-screener/scripts/screen_vcp.py \ --history --ticker FIX --output-dir reports/ # Custom scan length: 750 trading days (~3 years), 90-day outcome window python3 skills/vcp-screener/scripts/screen_vcp.py \ --history 750 --ticker TSLA \ --stride-days 5 --outcome-days 90 \ --output-dir reports/ # Long scan: 10 years (2520 trading days) python3 skills/vcp-screener/scripts/screen_vcp.py \ --history 2520 --ticker NVDA --output-dir reports/ ``` Outputs (timestamped): - `vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.json` — timeline of detections with full analyzer payload + `forward_outcome` per detection + summary stats. - `vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.md` — human-readable timeline. Mode-specific flags: | Parameter | Default | Range | Effect | |-----------|---------|-------|--------| | `--history [DAYS]` | (off) / 1260 if bare | 100-5040 | Enable historical mode; optionally specify trading-day scan window (requires `--ticker`) | | `--ticker SYM` | — | — | Ticker to scan | | `--stride-days` | 5 | 1-60 | Trading-day step between as-of cursor positions | | `--outcome-days` | 60 | 5-252 | Forward window evaluated per detection | Notes: - Two FMP API calls per scan (ticker + SPY history), not 100+ like the cross-sectional pipeline. - `marketCap` and absolute RS percentile refRead the full source on GitHub (opens external page)