vcp-screener

Este extracto es una copia guardada durante la revisión. La fuente externa contiene la versión completa y actual.

---
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 ref