skillfed

earnings-trade-analyzer

Evaluate recent earnings reactions by scoring stocks across gap magnitude, pre-earnings momentum, volume trends, and moving average positioning. The skill assigns composite scores and letter grades (A–D) to rank candidates for potential swing trades, with detailed breakdowns of each factor's contribution to the overall setup quality.

Earnings Trade Analyzer scores recent post-earnings stocks on a 5-factor system to identify momentum trade candidates.

AI-generated summary based on this skill's SKILL.md

2,514 586 MIT updated by tradermonty

Install

tradermonty/claude-trading-skills/earnings-trade-analyzer · repository language: Python

git clone https://github.com/tradermonty/claude-trading-skills
cp -r claude-trading-skills/skills/earnings-trade-analyzer ~/.claude/skills/earnings-trade-analyzer
npx skillfed install tradermonty/claude-trading-skills/earnings-trade-analyzer

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

What is earnings-trade-analyzer and how does it work?

earnings-trade-analyzer evaluates recent earnings reactions by scoring stocks across gap magnitude, pre-earnings momentum, volume trends, and moving average positioning. The skill assigns composite scores and letter grades (A–D) to rank candidates for potential swing trades, with detailed breakdowns of each factor's contribution to the overall setup quality.

How does earnings-trade-analyzer use a 5-factor scoring system?

earnings-trade-analyzer analyzes recent post-earnings stock reactions using a 5-factor scoring methodology. This approach evaluates gap size, momentum strength, volume confirmation, technical positioning, and institutional accumulation signals to produce a composite score that helps traders identify high-probability setups.

Can earnings-trade-analyzer screen for best earnings reactions?

Yes. earnings-trade-analyzer screens for the best earnings gap trades and momentum candidates by ranking post-earnings stocks based on reaction quality and technical confirmation. It grades and ranks candidates by institutional accumulation patterns and identifies actionable setups with strong technical signals.

What post earnings stock screening does earnings-trade-analyzer provide?

earnings-trade-analyzer performs post earnings stock screening to find PEAD (post-earnings announcement drift) trading opportunities and momentum trades. It identifies recent earnings stock performance patterns and surfaces candidates showing strong accumulation activity and favorable technical setups for swing trading.

How does earnings-trade-analyzer grade post-earnings stocks?

earnings-trade-analyzer assigns letter grades (A–D) to rank post-earnings stocks by institutional accumulation and overall setup quality. Each grade reflects the composite score derived from gap magnitude, momentum, volume trends, moving average positioning, and technical confirmation factors.

What earnings trade setup finder features does this skill offer?

earnings-trade-analyzer functions as an earnings trade setup finder by identifying actionable earnings reaction setups with technical confirmation. It combines gap analysis, momentum scoring, and accumulation grading to surface the most promising post-earnings candidates for traders seeking swing trade opportunities.

SKILL.md

rendered from the published skill — quoted content, verbatim

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

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Read as markdown · JSON record · Browse the source repository

File tree — 15 files
skills/earnings-trade-analyzer/SKILL.md
skills/earnings-trade-analyzer/references/scoring_methodology.md
skills/earnings-trade-analyzer/scripts/_fmp_compat.py
skills/earnings-trade-analyzer/scripts/analyze_earnings_trades.py
skills/earnings-trade-analyzer/scripts/calculators/__init__.py
skills/earnings-trade-analyzer/scripts/calculators/gap_size_calculator.py
skills/earnings-trade-analyzer/scripts/calculators/ma200_calculator.py
skills/earnings-trade-analyzer/scripts/calculators/ma50_calculator.py
skills/earnings-trade-analyzer/scripts/calculators/pre_earnings_trend_calculator.py
skills/earnings-trade-analyzer/scripts/calculators/volume_trend_calculator.py
skills/earnings-trade-analyzer/scripts/fmp_client.py
skills/earnings-trade-analyzer/scripts/report_generator.py
skills/earnings-trade-analyzer/scripts/scorer.py
skills/earnings-trade-analyzer/scripts/tests/conftest.py
skills/earnings-trade-analyzer/scripts/tests/test_earnings_trade_analyzer.py

Related skills

Tags

earnings-momentum gap-analysis stock-screening technical-scoring trade-setup-finder post-event-trading institutional-accumulation multi-factor-ranking