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claude-code-stock-deep-research-agent

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💡 摘要

一个全面的AI驱动框架,用于进行深入的股票投资研究。

🎯 适合人群

寻求详细股票分析的个人投资者寻找高效研究工具的金融分析师需要结构化报告的投资顾问学习金融和投资策略的学生对金融建模感兴趣的数据科学家

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否执行 shell/命令行指令;是否发起外网请求(SSRF/数据外发)。以最小权限运行,并在生产环境启用前审计代码与依赖。

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:

  1. 本报告仅供教育和信息用途
  2. 部分数据需要通过官方渠道验证
  3. 过往业绩不代表未来表现
  4. 投资决策前请自行进行尽职调查
  5. 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

Table of Contents

  1. Features
  2. Repo Structure
  3. Quick Start
  4. Stock Investment Research
  5. How It Works
  6. Customization
  7. Credits & Acknowledgements
  8. 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:

  1. Ask about your investment style (价值/成长/困境/红利), holding period, risk tolerance
  2. Deploy ~28 parallel research agents across 7 phases
  3. 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

  1. Investment Style Adaptation: Research approach tailored to value, growth, turnaround, or dividend investing
  2. Parallel Multi-Agent Execution: ~28 agents working concurrently for efficiency
  3. Mandatory Cross-Validation: Profit vs. cash flow, company vs. peers, bear case analysis
  4. Structured Output: Standardized 20-file report format
  5. 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 automatical

五维分析
清晰度8/10
创新性9/10
实用性9/10
完整性9/10
可维护性8/10
优缺点分析

优点

  • 全面的多智能体研究能力
  • 结构化输出,标准化报告
  • 适应各种投资风格
  • 强制交叉验证以确保质量

缺点

  • 复杂的设置可能会让普通用户却步
  • 需要理解投资概念
  • 全面报告耗时较长
  • 依赖外部数据的质量

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 liangdabiao.