backtest-expert
Expert guidance for systematic backtesting of trading strategies. Use when developing,…
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
$ npx -y skills add tradermonty/claude-trading-skills --skill pead-screener --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/pead-screenerContext preview
The summary Claude sees to decide when to auto-load this skill.
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
name: pead-screener description: 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.
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.
export FMP_API_KEY=your_api_key_here
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/
**Scheduled US-equity routine pitfall:** Prefer Mode B for pre-market / US-equity cron briefs after running `earnings-trade-analyzer`. Mode A can pull the global FMP earnings calendar, spend the API budget on non-US symbols, and return weak/non-actionable foreign listings before reaching the intended US watchlist. If Mode A is used anyway and the script reports budget trimming or non-US symbols, mark PEAD output as degraded and treat it as manual-review only rather than a clean candidate source.
1. Read the generated JSON and Markdown reports 2. Load `references/pead_strategy.md` for PEAD theory and pattern context 3. Load `references/entry_exit_rules.md` for trade management rules
For each candidate, present:
Based on stages and ratings:
FMP does not confirm a bmo/amc session for every earnings row; unconfirmed rows carry `earnings_timing: "unknown"` in Mode A and the price gap calculation assumes the AMC window as a fallback. The Mode A report shows `timing_unknown_count` out of `timing_candidates_total` so this assumption stays visible (Mode B reports `n/a` since timing is inherited from the input JSON). `timing_candidates_total` is the post-budget-trim population that was actually analyzed, not the raw earnings-calendar row count.
Claude Trading Skills started as a personal project to use AI to improve my own trading process. Claude Trading Skills is a Claude Skills-based trading workflow toolkit for time-constrained individual investors.
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