Claude Equity Research

by carolinacherry

🤖 Built entirely with Claude Code - demonstrating AI-native development workflows for professional-grade financial tools.

Professional equity research and trading analysis powered by Claude AI, delivering institutional-grade investment insights with Goldman Sachs-style formatting and comprehensive risk assessment.

What It Does

• Institutional-Grade Analysis: Generates professional equity research reports matching Wall Street standards
• AI-Powered Intelligence: Leverages Claude AI for comprehensive fundamental and technical analysis
• Real-Time Data Integration: Pulls live market data, earnings reports, and analyst coverage
• Risk-Adjusted Recommendations: Provides buy/sell/hold ratings with specific price targets and position sizing
• Advanced Market Intelligence: Includes options flow analysis, insider trading activity, and sector positioning

Key Features

Core Analysis Framework

• Executive Summary: Investment thesis with price target and 12-month timeframe
• Fundamental Analysis: Revenue growth, margins, peer comparisons, and forward estimates
• Catalyst Analysis: Near-term and medium-term market drivers with specific dates
• Valuation Models: Bull/base/bear scenarios with probability weighting
• Risk Assessment: Company-specific and macro risks with position sizing guidance (1-5%)
• Technical Context: Support/resistance levels, momentum indicators, and volume analysis

Enhanced Intelligence Features

• Options Flow Analysis: Unusual activity, put/call ratios, implied volatility trends
• Insider Activity Monitoring: Executive buying/selling patterns with dollar amounts
• Sector Positioning: Rotation trends and relative strength vs market indices
• ESG & Governance: Sustainability scores and regulatory compliance assessment

Professional Standards

• Institutional Terminology: EBITDA, P/E ratios, EV/Sales, conviction levels
• Probability Weighting: Bull/base/bear scenarios with percentage allocations
• Legal Protection: Comprehensive disclaimers for educational use
• Data Sourcing: Real-time web search with analyst firm citations

Installation & Setup

Prerequisites

• Claude Code CLI (version 2.0.11 or higher)
• Claude paid subscription (Pro, Team, or Enterprise)
• Internet connection for real-time data retrieval

Installation via Claude Code Plugin (Recommended)

Quick Install - Interactive Menu:

# Step 1: Add the marketplace
/plugin marketplace add quant-sentiment-ai/claude-equity-research

# Step 2: Open the plugin menu
/plugin

# Step 3: Select "Browse Plugins" → find "claude-equity-research" → "Install now"

Alternative - Direct Install:

/plugin marketplace add quant-sentiment-ai/claude-equity-research
/plugin install trading-ideas@claude-equity-research-marketplace

Verify Installation:

/help  # Confirm /trading-ideas:research command is listed

Start Analyzing:

/trading-ideas:research AAPL
/trading-ideas:research NVDA --detailed

Claude Code namespaces plugin commands as <plugin-name>:<command-name>, so the invocation is /trading-ideas:research (not the bare /trading-ideas). If you prefer the bare form, use the manual install below — it copies the command file into your personal ~/.claude/commands/ and registers it as /trading-ideas.

💡 Tip: Restart Claude Code after installation for best results.

For comprehensive plugin documentation, see PLUGIN.md.

mkdir -p ~/.claude/commands
curl -o ~/.claude/commands/trading-ideas.md https://raw.githubusercontent.com/quant-sentiment-ai/claude-equity-research/main/commands/trading-ideas/commands/research.md

/trading-ideas AAPL

/trading-ideas HOOD --detailed

git clone https://github.com/quant-sentiment-ai/claude-equity-research.git
cd claude-equity-research

cp commands/trading-ideas/commands/research.md ~/.claude/commands/trading-ideas.md

Usage Examples

Examples below use the plugin install invocation (/trading-ideas:research). If you followed the manual install path, drop the :research suffix and use the bare /trading-ideas form.

Basic Equity Analysis

/trading-ideas:research AAPL

Output: Comprehensive institutional research report with BUY/SELL/HOLD recommendation

Technology Sector Analysis

/trading-ideas:research NVDA

Features: AI/semiconductor sector positioning, relative valuation vs peers

Financial Services Analysis

/trading-ideas:research JPM

Includes: Interest rate sensitivity, regulatory environment, book value analysis

Growth Stock Analysis

/trading-ideas:research TSLA

Focus: Growth metrics, competitive positioning, volatility assessment

Sample Output Format

# APPLE INC (AAPL) - ENHANCED EQUITY RESEARCH

## EXECUTIVE SUMMARY
BUY with $250 price target (9% upside) over 12 months. Strong Q4 2024 
results driven by iPhone 16 launch and AI integration provide foundation 
for premium product cycle. Balanced risk-reward with established ecosystem moat.

## FUNDAMENTAL ANALYSIS
Q4 2024: Revenue $94.9B (+6% YoY), EPS $1.64 (+12% YoY). iPhone revenue 
$46.2B (~49% of total), Services +12% to $25B with recurring characteristics.

## VALUATION & PRICE TARGETS
Consensus: $242 (range $200-$280)
Bull case: $280 | Base case: $250 | Bear case: $200
Probability weighting: 25%/55%/20%

## RECOMMENDATION: BUY | Conviction: High | Price Target: $250

Command Reference

Repository Structure

claude-equity-research/
├── README.md                     # This file
├── LICENSE                       # MIT License
├── commands/
│   ├── trading-ideas/            # Plugin directory (installed via marketplace)
│   │   ├── .claude-plugin/
│   │   │   └── plugin.json       # Plugin manifest
│   │   └── commands/
│   │       └── research.md       # Slash command (invoked as /trading-ideas:research)
│   └── README.md                 # Command documentation
├── config/
│   ├── config.example.json       # Template configuration
│   └── prompts/                  # Analysis prompt templates
├── examples/
│   └── sample_reports/           # Example analyses (AAPL, HOOD, etc.)
├── docs/
│   ├── methodology.md            # Detailed analysis framework
│   ├── installation.md           # Setup instructions
│   └── customization.md          # Customization guide
├── utils/
│   ├── data_sources.md           # Data source documentation
│   └── validation.py             # Analysis validation tools
└── tests/
    └── test_command.py           # Command functionality tests

Analysis Methodology

Our research framework combines:

Quantitative Analysis

• Financial Statements: Revenue, margins, cash flow analysis
• Valuation Models: Multiple approaches (DCF, comparable company, precedent transaction)
• Technical Indicators: Support/resistance, momentum, relative strength
• Options Analytics: Implied volatility, unusual activity, sentiment indicators

Qualitative Assessment

• Competitive Positioning: Market share, competitive advantages, moat analysis
• Management Quality: Track record, capital allocation, strategic vision
• Regulatory Environment: Industry-specific risks, compliance issues
• ESG Factors: Environmental, social, governance considerations

Risk Management

• Scenario Analysis: Bull/base/bear cases with probability weighting
• Position Sizing: Risk-adjusted allocation recommendations (1-5% typical)
• Stop-Loss Guidance: Downside protection levels
• Correlation Analysis: Portfolio diversification considerations

Data Sources

• Financial Data: SEC filings, earnings reports, company guidance
• Market Data: Real-time pricing, volume, technical indicators
• Analyst Coverage: Wall Street research, price target updates
• News & Sentiment: Financial media, regulatory announcements
• Options Data: Unusual activity, implied volatility, positioning
• Insider Activity: Form 4 filings, executive transactions

Professional Disclaimers

⚠️ Important Legal Notice

This tool is designed for educational and research purposes only. All analysis and recommendations are:

• Not financial advice - For informational purposes only
• Not personalized - Does not consider individual circumstances
• Historical data based - Past performance doesn't guarantee future results
• Requiring due diligence - Users must conduct independent research
• Risk warning included - All investments carry risk of loss

Risk Warnings

• Stock prices are volatile and unpredictable
• AI analysis may contain errors or biases
• Market conditions change rapidly
• Regulatory and company-specific risks may not be fully captured
• Position sizing recommendations are general guidelines only

Professional Consultation

Always consult with qualified financial professionals before making investment decisions. This tool does not replace professional financial advice.

Contributing

We welcome contributions! Please see our Contributing Guidelines:

Development Areas

• Enhanced data source integration
• Improved technical analysis algorithms
• Additional sector-specific metrics
• ESG scoring improvements
• Risk model enhancements

Code Contributions

# Fork the repository
git fork https://github.com/quant-sentiment-ai/claude-equity-research

# Create feature branch
git checkout -b feature/your-enhancement

# Submit pull request with detailed description

Star History

_{Generated from this repo's own stargazer data — GitHub restricted the public stargazer API on 2026-06-30, which broke third-party star-history charts everywhere. Refresh with python3 scripts/update-star-history.py.}

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support & Community

• 📖 Documentation
• 🐛 Report Issues
• 💬 Discussions
• 🔄 Changelog

Author

Created and maintained by carolinacherry.

Acknowledgments

• Built for Claude Code - Anthropic's official CLI
• Inspired by institutional equity research standards
• Community-driven development and feedback

Remember: This tool provides educational insights only. Always conduct your own due diligence and consult qualified financial professionals before making investment decisions. Past performance does not guarantee future results.