Claude-trading-skills pead-screener
Screen post-earnings gap-up stocks for PEAD (Post-Earnings Announcement Drift) patterns. Analyzes weekly candle formation to detect red candle pullbacks and breakout signals. Supports two input modes - FMP earnings calendar (Mode A) or earnings-trade-analyzer JSON output (Mode B). Use when user asks about PEAD screening, post-earnings drift, earnings gap follow-through, red candle breakout patterns, or weekly earnings momentum setups.
git clone https://github.com/tradermonty/claude-trading-skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/tradermonty/claude-trading-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/pead-screener" ~/.claude/skills/tradermonty-claude-trading-skills-pead-screener && rm -rf "$T"
skills/pead-screener/SKILL.mdPEAD 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
environment variable or passFMP_API_KEY
)--api-keyexport 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
for PEAD theory and pattern contextreferences/pead_strategy.md - Load
for trade management rulesreferences/entry_exit_rules.md
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
- Structured results with stage classificationpead_screener_YYYY-MM-DD_HHMMSS.json
- Human-readable report grouped by stagepead_screener_YYYY-MM-DD_HHMMSS.md
Resources
- PEAD theory and weekly candle approachreferences/pead_strategy.md
- Entry, exit, and position sizing rulesreferences/entry_exit_rules.md