About pead-screener
pead-screener is a skill for screening stocks after earnings gap-ups for Post-Earnings Announcement Drift patterns. It analyzes weekly candles to classify setup stages and produce reports with pattern details, trade levels, and liquidity measures.
Key features
- 01FMP earnings-calendar screening
- 02JSON candidate-input mode
- 03Weekly candle pattern analysis
- 04Stage classification and composite ratings
- 05Entry, stop, target, and liquidity reporting
Use cases
- 01Finding post-earnings gap-up candidates
- 02Tracking red-candle breakout setups
- 03Reviewing earnings-trade-analyzer candidates
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ mphinance/ alpha-skills --skill pead-screenerAfter installing, type/pead-screenerin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
README.mdreferences/entry_exit_rules.mdpead_strategy.mdscripts/fmp_client.pyreport_generator.pyscorer.pyscreen_pead.pyscripts/calculators/__init__.pybreakout_calculator.pyliquidity_calculator.pyrisk_reward_calculator.pyweekly_candle_calculator.pyscripts/tests/conftest.pytest_pead_screener.pyDetails
From the project READMEPEAD 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_KEYenvironment 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.mdfor PEAD theory and pattern context - Load
references/entry_exit_rules.mdfor 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 classificationpead_screener_YYYY-MM-DD_HHMMSS.md- Human-readable report grouped by stage
Resources
references/pead_strategy.md- PEAD theory and weekly candle approachreferences/entry_exit_rules.md- Entry, exit, and position sizing rules