Earnings Trade Analyzer - Post-Earnings 5-Factor Scoring Analyze recent post-earnings stocks using a 5-factor weighted scoring system to identify the strongest earnings reactions for potential momentum trades. When to Use User asks for post-earnings trade analysis or earnings gap screening User wants to find the best recent earnings reactions User requests earnings momentum scoring or grading User asks about post-earnings accumulation day (PEAD) candidates Prerequisites FMP API key (set FMP_API_KEY environment variable or pass --api-key ) Free tier (250 calls/day) is sufficient for default screening (lookback 2 days, top 20) Paid tier recommended for larger lookback windows or full screening Workflow Step 1: Run the Earnings Trade Analyzer Execute the analyzer script:

Default: last 2 days of earnings, top 20 results

python3 skills/earnings-trade-analyzer/scripts/analyze_earnings_trades.py --output-dir reports/

Custom lookback and market cap filter

python3 skills/earnings-trade-analyzer/scripts/analyze_earnings_trades.py \ --lookback-days 5 \ --min-market-cap 1000000000 \ --top 30 \ --output-dir reports/

With entry quality filter

python3 skills/earnings-trade-analyzer/scripts/analyze_earnings_trades.py \ --apply-entry-filter \ --output-dir reports/ Step 2: Review Results Read the generated JSON and Markdown reports Load references/scoring_methodology.md for scoring interpretation context Focus on Grade A and B stocks for actionable setups Step 3: Present Analysis For each top candidate, present: Composite score and letter grade (A/B/C/D) Earnings gap size and direction Pre-earnings 20-day trend Volume ratio (20-day vs 60-day average) Position relative to 200-day and 50-day moving averages Weakest and strongest scoring components Step 4: Provide Actionable Guidance Based on grades: Grade A (85+): Strong earnings reaction with institutional accumulation - consider entry Grade B (70-84): Good earnings reaction worth monitoring - wait for pullback or confirmation Grade C (55-69): Mixed signals - use caution, additional analysis needed Grade D (<55): Weak setup - avoid or wait for better conditions Output earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json - Structured results with schema_version "1.0" earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.md - Human-readable report with tables Resources references/scoring_methodology.md - 5-factor scoring system, grade thresholds, and entry quality filter rules