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A-Share DCF Valuation

DCF valuation modeling for A-share listed companies. Pass stock code to automatically fetch financial data, calculate WACC, run conservative/base/optimistic...

personAuthor: laigenhubclawhub
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A-share DCF Valuation Modeling

Trigger Conditions

Use when user requests DCF (Discounted Cash Flow) valuation analysis for an A-share stock.

Environment Requirements

Required Environment Variables

| Variable | Description | How to Obtain | |----------|-------------|---------------| | TUSHARE_TOKEN | Tushare API token (mandatory) | Register at https://tushare.pro, get token from user center | | OPENCLAW_WORKSPACE | Workspace root path (optional) | Defaults to ~/.openclaw/workspace |

Python Dependencies

| Package | Version | Purpose | |---------|---------|--------| | tushare | Latest | A-share financial data API | | pandas | ≥1.0 | Data processing | | numpy | ≥1.18 | Numerical calculations | | scipy | ≥1.4 | Beta regression (stats module) |

Setup Instructions

  1. Configure Tushare Token:

    # Add to ~/.bashrc or ~/.bash_profile
export TUSHARE_TOKEN="your_token_here"
source ~/.bashrc

  2. Install Python Dependencies:

    pip install tushare pandas numpy scipy

  3. Verify Setup:

    python3 -c "import tushare as ts; ts.set_token('$TUSHARE_TOKEN'); pro = ts.pro_api(); print(pro.stock_basic(ts_code='600519.SH'))"

Troubleshooting

| Error | Cause | Solution | |-------|-------|----------| | 未设置 TUSHARE_TOKEN 环境变量 | Token not configured | Add export to shell profile | | Tushare API 获取失败 | Invalid token or network issue | Verify token, check network | | No module named 'tushare' | Package not installed | pip install tushare | | Beta 回归数据不足 | Stock newly listed | Use industry default Beta |

Quick Start

User input: "对 贵州茅台 600519 做 DCF 估值"
→ Run: python3 scripts/a_share_dcf.py 600519.SH
→ Report saved to: reports/dcf_贵州茅台_YYYY-MM-DD.md

Valuation Methodology

Method: Two-stage FCFF (Free Cash Flow to Firm) discount model

Formulas:

  • FCFF = Operating Cash Flow - Capital Expenditure
  • WACC = We×Re + Wd×Rd×(1-T)
  • Terminal Value = FCFF_n × (1+g) / (WACC - g)
  • Equity Value = EV - Net Debt
  • Per-share Value = Equity Value / Total Shares

Three-Scenario Assumptions:

| Scenario | WACC | Growth Rate | Perpetual Growth | |----------|------|-------------|------------------| | Conservative | WACC + 3% (min 14%) | 50% of 3-year avg | 2% | | Base | Calculated WACC | 80% of 3-year avg | 3% | | Optimistic | WACC - 3% (min 7%) | 100% of 3-year avg | 4% |

Scenario Assumption Rationale

Conservative Scenario: Higher WACC reflects elevated risk premium; reduced growth rate accounts for potential downside from competition, regulation, or macro headwinds. Suitable for risk-averse investors.

Base Scenario: Uses calculated WACC from company-specific beta and capital structure; growth rate anchored to historical average but tempered for maturity trajectory. Represents most likely outcome under normal conditions.

Optimistic Scenario: Lower WACC assumes favorable risk environment; full historical growth reflects best-case execution. Appropriate for growth-oriented analysis or upside case.

Execution Steps

1. Determine Stock Code Format

Tushare uses XXXXXX.SH (Shanghai) or XXXXXX.SZ (Shenzhen) format:

# Auto conversion
if code.startswith('6'): 
    ts_code = f"{code}.SH"
elif code.startswith(('0', '3')):
    ts_code = f"{code}.SZ"

2. Run Valuation Script

cd $OPENCLAW_WORKSPACE && python3 skills/a-share-dcf-valuation/scripts/a_share_dcf.py <TS_CODE> [公司名]
# Example: python3 skills/a-share-dcf-valuation/scripts/a_share_dcf.py 600519.SH 贵州茅台

Note: $OPENCLAW_WORKSPACE defaults to ~/.openclaw/workspace. Use relative paths from workspace root for portability.

3. Check Output

  • Terminal displays real-time progress and key metrics
  • Markdown report saved to reports/dcf_{公司名}_{日期}.md
  • Verify report contains all required sections

4. Report to User

First provide summary conclusion, then report path:

## DCF 估值完成 — {公司名}

| 场景 | DCF每股价值 | vs 当前股价 |
|------|------------|------------|
| 保守 | ¥XX.XX     | -XX.X%     |
| 中性 | ¥XX.XX     | -XX.X%     |
| 乐观 | ¥XX.XX     | -XX.X%     |

当前股价: ¥XXX.XX
完整报告: reports/dcf_{公司名}_{日期}.md

Important Notes

Data Source

  • Tushare is the sole data source (requires TUSHARE_TOKEN environment variable)
  • If Tushare fetch fails, inform user that data is unavailable; do not fabricate data

Beta Calculation

  • Use ~500 trading days (~2 years) regression against CSI 300 (000300.SH)
  • If regression R² < 0.1 or insufficient data, use industry default Beta:
    • Tech/Semiconductor: 1.5
    • Consumer/Healthcare: 0.8
    • Financial/Banking: 1.0
    • Cyclical/Manufacturing: 1.2
    • Others: 1.2

WACC Parameters (Dynamic Calculation)

The following parameters are NOT hardcoded fixed values. They are dynamically determined with explicit data sources and rationale:

1. Risk-Free Rate (RF)

| Approach | Source | Value Range | |----------|--------|-------------| | Primary | China 10-year Treasury yield | 1.8% - 4.5% (historical) | | Reference | 中债估值 | ~2.1% - 2.5% (2024-2025) | | Fallback | Recent 10Y bond average | 2.25% (default) |

Method: Query public bond yield data; if unavailable, use recent reference value with explicit notation.

2. Equity Risk Premium (ERP)

Correct Terminology: ERP (Equity Risk Premium), not MRP (Market Risk Premium).

| Source | ERP Estimate | |--------|--------------| | Damodaran (2024) | 6.5% for China | | 中金/中信研报 | 5% - 8% | | 程晓明等学术研究 | 6.0% - 7.5% | | Historical calculation (A股20年平均收益率 - RF) | 5.5% - 7.0% |

Industry Adjustment:

  • Tech/Semiconductor: +1.0% to 1.5%
  • Financial: -1.0%
  • Consumer/Healthcare: 0%

Method: Base ERP 6.5% + industry-specific risk adjustment.

3. Debt Cost (Rd)

| Approach | Formula | |----------|---------| | Primary | LPR 1Y + Credit Spread | | LPR Reference | 3.1% (2025 1-year LPR) | | Credit Spread | 0.5% - 1.5% based on rating |

| Company Profile | Estimated Rd | |-----------------|--------------| | Low debt (<10%), strong credit | 3.6% (LPR + 0.5%) | | Moderate debt (10-50%) | 4.0% (LPR + 0.9%) | | High debt (>50%) | 5.0% (LPR + 1.9%) |

Method: Estimate based on company's debt ratio and implied credit quality.

4. Tax Rate (Tax)

| Source | Rate | |--------|------| | Primary | Actual effective tax rate from financial statements | | High-tech enterprise | 15% (qualified) | | General corporate | 25% |

High-tech Identification Criteria:

  1. Industry: 电子、半导体、计算机、通信、医药生物、医疗器械、新能源、电力设备
  2. Gross margin > 30% (common indicator of tech companies)

Method: First attempt to extract actual tax rate from income statement; if unavailable, determine based on industry and gross margin characteristics.

Special Cases

  • Financial stocks (banks/insurers/brokers): Standard DCF not applicable (FCFF meaningless), use PB-ROE or DDM model, inform user
  • Loss-making companies: When FCFF is negative with no recovery signs, DCF not applicable, use alternative methods
  • *ST/ST stocks: Alert user to delisting risk

Report Quality

  • All amounts in "亿元" (100 million yuan)
  • Growth rates in percentage
  • Two decimal places
  • Annotate data source and timeliness
  • Must include disclaimer

Risk Disclosure (Dynamic Generation)

The "Risk Disclosure" section must be dynamically generated based on company and industry characteristics, NOT hardcoded. The script should:

  1. Industry-specific risks: Map company's industry to relevant risk factors
  2. Company-specific risks: Analyze financial data to identify company-level risks
  3. Model risks: Always include DCF sensitivity to WACC and perpetual growth
  4. Macro risks: General economic, interest rate, and policy risks

Industry Risk Mapping:

| Industry | Key Risk Factors | |----------|------------------| | 科技/半导体 | 技术迭代快、研发投入大、国际竞争、供应链风险 | | 消费/食品饮料 | 品牌溢价风险、消费降级、渠道变革 | | 医药/医疗 | 政策监管（集采）、研发失败、专利到期 | | 金融/银行 | 利率周期、信用风险、监管趋严 | | 周期/制造 | 经济周期敏感、产能过剩、环保政策 | | 新能源/光伏 | 技术路线竞争、产能扩张过快、补贴退坡 | | 房地产/建材 | 政策调控、去杠杆、销售疲软 | | 互联网/传媒 | 用户增长放缓、监管趋严、变现模式受限 | | 交通运输 | 油价波动、需求周期、基础设施投资 | | 其他 | 行业竞争格局变化、政策不确定性 |

Report Structure (Markdown, output in Chinese)

# DCF 估值报告 — {公司名} ({TS_CODE})

> 估值日期 | 当前股价 | 总市值 | PE | PB

## 一、公司基本面概览
- 公司简介
- 历史财务数据表(7年)
- 关键财务指标(最新年报)

## 二、WACC 计算
- 参数表格(Rf, Beta, MRP, Re, Rd, Tax, We, Wd, WACC)

## 三、三场景 DCF 估值
- 场景假设表(含设定依据说明)
- 估值结果表

## 四、敏感性分析
- WACC × 永续增长率 矩阵

## 五、关键假设
- 列出核心假设

## 六、风险提示(Dynamic)
- 根据公司行业特性、财务状况动态生成针对性风险提示

## 七、结论
- 估值区间
- 与当前股价对比
- 简要分析

> 免责声明

File Organization

All paths should be relative to the workspace root ($OPENCLAW_WORKSPACE or ~/.openclaw/workspace):

  • Script: skills/a-share-dcf-valuation/scripts/a_share_dcf.py
  • Report: reports/dcf_{公司名}_{YYYY-MM-DD}.md

Important: Avoid absolute paths like /home/laigen/ in the script. Use environment variable $OPENCLAW_WORKSPACE or relative paths for portability.