pead-screener

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.

Dual-market support: This skill uses bin/stock-cli for data fetching, supporting both US and KR markets. Original FMP scripts preserved in scripts/ for reference.

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

• bin/stock-cli available in the project root
• For Mode B: earnings-trade-analyzer JSON output file with schema_version "1.0"

Workflow

Step 1: Fetch Price Data for Weekly Candle Analysis

Fetch 90 days of price history per ticker to construct weekly candles and analyze PEAD patterns:

# US market — single ticker
bin/stock-cli price NVDA --market US --days 90

# KR market — single ticker
bin/stock-cli price 005930 --market KR --days 90

Note: For KR markets, use WebSearch to find Korean earnings announcement dates (e.g., search "005930 실적 발표일" or "Samsung Electronics earnings date"), as KR earnings calendars are not available through bin/stock-cli.

Repeat for each post-earnings gap-up candidate identified via an earnings calendar (use the earnings-calendar skill or WebSearch for earnings dates).

The original FMP-based script is preserved in scripts/screen_pead.py for reference.

Mode B (earnings-trade-analyzer JSON input): Use the candidate tickers from the earnings-trade-analyzer output as your ticker list, then fetch price data for each using the command above.

Step 2: Review Results

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

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