Claude Code Stock Deep Research Agent

Investment Research Edition - 专业股票投资尽调系统

⚖️ 免责声明

本研究报告不构成投资建议或推荐。所有投资存在风险，包括本金损失。

重要提示:

本报告仅供教育和信息用途
部分数据需要通过官方渠道验证
过往业绩不代表未来表现
投资决策前请自行进行尽职调查
建议咨询合格的财务顾问

🎓 研究框架

本研究基于 Claude Code Deep Research 系统：

方法论: 8阶段股票投资尽调框架
智能体: 28个并行研究智能体
工具: WebSearch、WebFetch、综合分析
质量: 多空平衡、明确风险、数据验证

Features
Repo Structure
Quick Start
Stock Investment Research
How It Works
Customization
Credits & Acknowledgements
License

Features

This repository contains two specialized deep research frameworks for Claude Code:

1. 🎯 Stock Investment Research (股票投资尽调系统) ⭐ PRIMARY

An 8-phase investment due diligence framework for analyzing publicly traded companies, inspired by professional investment research methodologies.

Key Capabilities:

📊 Comprehensive Analysis: Business model, industry dynamics, financial quality, governance, valuation
🤖 Multi-Agent Research: ~28 parallel research agents working concurrently
📈 Investment Style Adaptation: Value, growth, turnaround, dividend investing
💰 Valuation Models: DCF, reverse DCF, relative valuation, scenario analysis
🛡️ Risk Assessment: Bear case, black swans, monitoring checklist
✅ Quality Assurance: Cross-validation (profit vs. cash flow, company vs. peers)
📝 Structured Output: 20-file standardized due diligence report

Research Coverage:

A-shares (A股) - 中国大陆股市
Hong Kong stocks (港股)
US stocks (美股)
Other global markets

Output: Signal rating (🟢🟢🟢 Strong Buy / 🟡🟡🟡 Hold / 🔴🔴 Avoid) based on fundamental analysis

2. 📚 General Deep Research (通用深度研究系统)

A flexible 7-phase framework for general research topics (business, technology, academic, etc.).

Repo Structure

File/Folder	Purpose
CLAUDE.md	Master instructions for Claude Code
.claude/skills/stock-question-refiner/	Stock research question refinement skill
.claude/skills/stock-research-executor/	8-phase investment due diligence executor
.claude/commands/stock-research.md	Main stock research command
.claude/skills/citation-validator/	Citation verification skill
.claude/skills/got-controller/	Graph of Thoughts controller
.claude/skills/synthesizer/	Findings synthesis skill
STOCK_RESEARCH_IMPLEMENTATION_PLAN.md	Stock research system design document
CLAUDE2.md	Graph of Thoughts implementation details
PROJECT_UNDERSTANDING.md	Architecture deep dive
IMPLEMENTATION_GUIDE.md	User guide

Quick Start

Stock Research (股票投资尽调)

# Start Claude Code
claude

# Set model (optional, but recommended)
/model opus

# Execute stock research
/stock-research [股票代码或公司名称]

# Examples:
/stock-research 600519              # 贵州茅台 (A-share)
/stock-research AAPL                # 苹果公司 (US)
/stock-research 腾讯 00700.HK       # 腾讯控股 (HK)

The system will:

Ask about your investment style (价值/成长/困境/红利), holding period, risk tolerance
Deploy ~28 parallel research agents across 7 phases
Generate comprehensive due diligence report in RESEARCH/STOCK_[ticker]_[company]/

Time: 2-4 hours for standard due diligence

Output Example

RESEARCH/STOCK_600519_Kweichow_Moutai/
├── 00_Executive_Summary.md        # 🟡🟡🟡 Hold / Fairly Valued
├── 01_Business_Foundation.md      # Products, revenue, customers
├── 02_Industry_Analysis.md        # Industry cycle, competition
├── 03_Business_Breakdown.md       # Profit drivers, economics
├── 04_Financial_Quality.md        # Cash flow, margins, red flags
├── 05_Governance_Analysis.md      # Ownership, management
├── 06_Market_Sentiment.md         # Bull/bear cases
├── 07_Valuation_Moat.md           # Moat rating, valuation
├── Financial_Data/                # Metrics, trends, peer comparison
├── Valuation/                     # DCF, scenarios
├── Risk_Monitoring/               # Bear case, monitoring checklist
└── sources/                       # Citations with quality ratings

Stock Investment Research

8-Phase Due Diligence Process

Phase	Focus	Output
1. Business Foundation	公司事实底座	Products, revenue mix, customers, value chain, strategy
2. Industry Analysis	行业周期分析	Cycle stage, supply-demand, competition, policy impacts
3. Business Breakdown	业务拆解	Segments, profit engines, pricing power, economics
4. Financial Quality	财务质量	Metrics trends, cash flow vs. earnings, red flags, peers
5. Governance Analysis	股权治理	Ownership, management, capital allocation, ROIC
6. Market Sentiment	市场分歧	Bull case, bear case, key debates, verification nodes
7. Valuation & Moat	估值护城河	Moat rating (0-5), relative/absolute valuation, risks
8. Final Synthesis	综合报告	Signal rating, thesis, monitoring checklist

Investment Style Adaptation

The system adapts research approach based on investment style:

Style	Focus	Valuation Methods	Key Metrics
Value (价值投资)	Intrinsic value, margin of safety	P/B, EV/EBITDA, DCF (conservative)	P/B, normalized earnings, FCF yield
Growth (成长投资)	TAM, competitive positioning	PEG, DCF (aggressive), user models	Revenue growth, moat, TAM penetration
Turnaround (困境反转)	Liquidity, solvency, catalysts	Liquidation value, option value	Debt ratios, cash runway, catalyst timeline
Dividend (红利投资)	Dividend sustainability	DDM, FCF yield, yield comparison	Dividend yield, payout ratio, FCF coverage

Quality Standards

Mandatory Cross-Validation:

✅ Profit vs. cash flow (OCF/NI ratio analysis)
✅ Company vs. peer comparison (key ratios, margins)
✅ Bear case analysis (3-5 key risks identified)

Citation Requirements:

Every factual claim must include: Author, Date, Title, URL
Source quality rated (A-E scale)
A-grade sources: Annual reports, regulatory filings
B-grade: Industry reports, analyst research
C-grade: News articles, expert commentary

Signal Rating (based on fundamentals only):

🟢🟢🟢 Strong Buy: Significant margin of safety, strong moat, attractive valuation
🟡🟡🟡 Hold: Fairly valued or limited margin of safety
🔴🔴 Avoid: Overvalued, deteriorating fundamentals, excessive risks

Example Usage

User: /stock-research 贵州茅台 600519

Claude: 我可以帮您研究贵州茅台。让我先了解您的投资需求：

       1. 投资风格：价值投资/成长投资/困境反转/红利投资？
       2. 持有周期：短期(<6月)/中期(6-18月)/长期(1-3年以上)?
       3. 关注重点：生意质量/财务质量/估值/公司治理 (选2-3个)
       4. 风险偏好：保守/平衡/激进？

User: 价值投资，长期持有3年以上，关注：生意质量、公司治理、估值，风险保守

Claude: [Generating research plan...]
       [Deploying 28 parallel research agents...]
       [Analyzing 5-10 years of financial data...]
       [Comparing with Wuliangye, Yanghe, Fenjiu...]
       [Assessing competitive moat...]
       [DCF valuation with 3 scenarios...]
       [Identifying bear case risks...]

Output: RESEARCH/STOCK_600519_Kweichow_Moutai/

🟡🟡🟡 Hold / Fairly Valued

Investment Thesis:
茅台是中国领先的白酒品牌，拥有强大的品牌护城河和定价能力。然而当前估值（P/E 32x）安全边际有限。建议继续持有现有仓位，但新投资应等待10-15%回调至¥1,750-1,850区间。

Key Metrics:
- Market Cap: ¥2.8T
- P/E (TTM): 32x (above 5-year average)
- Gross Margin: 91.2%
- ROE: 31%
- Moat Rating: 5/5 (Very Strong)

Top 3 Reasons to Consider:
1. Unassailable brand moat with 800-year heritage
2. Exceptional margins (91% gross, 53% net)
3. Strong cash generation (OCF/NI > 1.0)

Top 3 Reasons to Avoid:
1. Full valuation (P/E 32x, limited margin of safety)
2. Regulatory risk (government scrutiny of luxury pricing)
3. Competitive intensification (Wuliangwa narrowing gap)

Monitoring Checklist:
✅ Strengthen: Price pulls back 10-15% to ¥1,750-1,850
❌ Exit: Price drops below ¥1,300 (-35%), net margin < 45%

[Full report: 20 files, 127 sources, 50+ pages]

How It Works

Stock Research Workflow

User: /stock-research [ticker]
  ↓
stock-question-refiner skill
  - Asks: Investment style? Holding period? Focus areas? Risk tolerance?
  ↓
Structured Research Prompt (investment parameters, priorities, constraints)
  ↓
stock-research-executor skill
  ├─ Phase 1: Business Foundation (4 parallel agents)
  ├─ Phase 2: Industry Analysis (4 parallel agents)
  ├─ Phase 3: Business Breakdown (4 parallel agents)
  ├─ Phase 4: Financial Quality (4 parallel agents)
  ├─ Phase 5: Governance Analysis (4 parallel agents)
  ├─ Phase 6: Market Sentiment (4 parallel agents)
  └─ Phase 7: Valuation & Moat (4 parallel agents)
  ↓
citation-validator skill
  - Verifies all claims have citations
  - Rates source quality (A-E)
  ↓
Comprehensive Investment Due Diligence Report
  - Signal rating
  - 8 phase reports
  - Financial data tables
  - Valuation analysis
  - Risk monitoring checklist

Key Innovations

Investment Style Adaptation: Research approach tailored to value, growth, turnaround, or dividend investing
Parallel Multi-Agent Execution: ~28 agents working concurrently for efficiency
Mandatory Cross-Validation: Profit vs. cash flow, company vs. peers, bear case analysis
Structured Output: Standardized 20-file report format
Quality Assurance: A-E source quality rating, citation verification

General Research Workflow (Secondary)

[ Question ] → [ stock-question-refiner ]
      ↓
[ Structured Prompt ]
      ↓
[ research-executor ]
      ├─ Planning (break into subtopics)
      ├─ Multi-Agent Research (parallel)
      ├─ Source Triangulation (A-E rating)
      └─ Synthesis (combine findings)
      ↓
[ Citation Validation ]
      ↓
[ Research Report ]

Customization

Adapting Stock Research Parameters

The system automatically adapts based on:

Investment Style:
- Value: Emphasize balance sheet, normalized earnings, margin of safety
- Growth: Emphasize TAM, competitive positioning, growth sustainability
- Turnaround: Emphasize liquidity, solvency, catalysts
- Dividend: Emphasize payout sustainability, FCF generation
Holding Period:
- Short-term (<6 months): Focus on near-term catalysts, sentiment
- Medium-term (6-18 months): Balanced approach
- Long-term (1-3+ years): Emphasize business sustainability, moat, intrinsic value
Risk Tolerance:
- Conservative: Add filters (debt limits, minimum profitability)
- Balanced: Standard risk checks
- Aggressive: Accept higher volatility, focus on upside scenarios

Customizing Output

Adjust research parameters by answering the question-refiner's questions with your specific needs:

Geographic focus (China, US, global)
Timeframe (3 years, 5 years, 10 years of data)
Source preferences (annual reports only, include news, etc.)
Language (Chinese, English, or bilingual)
Valuation methods (DCF required? sum-of-parts?)

Credits & Acknowledgements

Stock Research Framework

8-Phase Methodology: Based on professional investment due diligence best practices
Graph of Thoughts Framework: SPCL, ETH Zürich (MIT License)
Quality Standards: Inspired by institutional investment research processes

Core System

Research Methodology: Inspired by OpenAI and Google Gemini deep research playbooks
Prompt Generation: Eliminates need for external question-refinement tools
Claude Code Integration: Leverages native Skills and Commands capabilities

Development

Developed by: Ankit at My Business Care Team (MyBCAT)
Stock Research Edition: December 2025
License: MIT License (see LICENSE file)

License

MIT License. See LICENSE file for full details.

Important Disclaimer

⚠️ WARNING / 重要提示:

Stock Research System:

This system does NOT provide investment advice
This system does NOT predict stock prices or provide target prices
Signal ratings (🟢🟢🟢/🟡🟡🟡/🔴🔴) are based ONLY on fundamental analysis (business quality, financial health, valuation, competitive moat)
All investments involve risk, including the loss of principal
Past performance does not guarantee future results
Always conduct your own due diligence and consult with qualified financial advisors before making investment decisions

股票研究系统：

本系统不构成投资建议
本系统不预测股价
信号灯评级仅基于基本面分析（业务质量、财务健康、估值、护城河）
所有投资均有风险，包括本金损失
过往表现不代表未来结果
请自行进行尽职调查并在做出投资决策前咨询合格的财务顾问
提示词参考来源：https://mp.weixin.qq.com/s/EFT5S-cCeCnEIDZOD_DYbA

Support

For detailed documentation:

See CLAUDE.md for Claude Code instructions
See STOCK_RESEARCH_IMPLEMENTATION_PLAN.md for system design
See .claude/skills/*/ for skill-specific instructions

stock-question-refiner