Skill

pead-screener

Screens post-earnings gap-up stocks for PEAD patterns using weekly candle analysis to detect red pullbacks and breakout signals. Supports FMP API calendar or earnings-trade-analyzer JSON input.

Python

cli-tools

automation

Install

npx claudepluginhub joshuarweaver/cascade-business-ops --plugin tradermonty-claude-trading-skills

Tool Access

This skill uses the workspace's default tool permissions.

Preview

Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns using weekly candle analysis to detect red candle pullbacks and breakout signals.

Supporting Assets

references/entry_exit_rules.mdreferences/pead_strategy.mdscripts/calculators/__init__.pyscripts/calculators/breakout_calculator.pyscripts/calculators/liquidity_calculator.pyscripts/calculators/risk_reward_calculator.pyscripts/calculators/weekly_candle_calculator.pyscripts/fmp_client.pyscripts/report_generator.pyscripts/scorer.pyscripts/screen_pead.pyscripts/tests/conftest.pyscripts/tests/test_pead_screener.py

SKILL.md

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Forks235

Last CommitMar 17, 2026

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PEAD Screener - Post-Earnings Announcement Drift

Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns using weekly candle analysis to detect red candle pullbacks and breakout signals.

When to Use

User asks for PEAD screening or post-earnings drift analysis
User wants to find earnings gap-up stocks with follow-through potential
User requests red candle breakout patterns after earnings
User asks for weekly earnings momentum setups
User provides earnings-trade-analyzer JSON output for further screening

Prerequisites

FMP API key (set FMP_API_KEY environment variable or pass --api-key)
```
export FMP_API_KEY=your_api_key_here
```
Free tier (250 calls/day) is sufficient for default screening
For Mode B: earnings-trade-analyzer JSON output file with schema_version "1.0"

Workflow

Step 1: Prepare and Execute Screening

Run the PEAD screener script in one of two modes:

Mode A (FMP earnings calendar):

# Default: last 14 days of earnings, 5-week monitoring window
python3 skills/pead-screener/scripts/screen_pead.py --output-dir reports/

# Custom parameters
python3 skills/pead-screener/scripts/screen_pead.py \
  --lookback-days 21 \
  --watch-weeks 6 \
  --min-gap 5.0 \
  --min-market-cap 1000000000 \
  --output-dir reports/

Mode B (earnings-trade-analyzer JSON input):

# From earnings-trade-analyzer output
python3 skills/pead-screener/scripts/screen_pead.py \
  --candidates-json reports/earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json \
  --min-grade B \
  --output-dir reports/

Step 2: Review Results

Read the generated JSON and Markdown reports
Load references/pead_strategy.md for PEAD theory and pattern context
Load references/entry_exit_rules.md for trade management rules

Step 3: Present Analysis

For each candidate, present:

Stage classification (MONITORING, SIGNAL_READY, BREAKOUT, EXPIRED)
Weekly candle pattern details (red candle location, breakout status)
Composite score and rating
Trade setup: entry, stop-loss, target, risk/reward ratio
Liquidity metrics (ADV20, average volume)

Step 4: Provide Actionable Guidance

Based on stages and ratings:

BREAKOUT + Strong Setup (85+): High-conviction PEAD trade, full position size
BREAKOUT + Good Setup (70-84): Solid PEAD setup, standard position size
SIGNAL_READY: Red candle formed, set alert for breakout above red candle high
MONITORING: Post-earnings, no red candle yet, add to watchlist
EXPIRED: Beyond monitoring window, remove from watchlist

Output

pead_screener_YYYY-MM-DD_HHMMSS.json - Structured results with stage classification
pead_screener_YYYY-MM-DD_HHMMSS.md - Human-readable report grouped by stage

Resources

references/pead_strategy.md - PEAD theory and weekly candle approach
references/entry_exit_rules.md - Entry, exit, and position sizing rules