---
name: aifinlab/a-share-initiation
source: https://app.decimal.ai/s/aifinlab-a-share-initiation@1/SKILL.md
source_sha256: 939aafb2d3ec
---

# A\u80A1\u4E2A\u80A1\u6DF1\u5EA6\u7814\u7A76/\u9996\u6B21\u8986\u76D6\u62A5\u544A

## \u6570\u636E\u6E90

```bash
SCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts"

# \u5B8C\u6574\u8D22\u52A1\u6307\u6807\uFF08\u591A\u671F\uFF09
python "$SCRIPTS/cn_stock_data.py" finance --code [CODE]

# \u5B9E\u65F6\u884C\u60C5
python "$SCRIPTS/cn_stock_data.py" quote --code [CODE]

# \u8FD1 2 \u5E74\u65E5\u7EBF
python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [2\u5E74\u524D\u65E5\u671F]

# \u8D44\u91D1\u6D41\u5411
python "$SCRIPTS/cn_stock_data.py" fund_flow --code [CODE] --days 30

# \u5317\u5411\u8D44\u91D1
python "$SCRIPTS/cn_stock_data.py" north_flow

# \u53EF\u6BD4\u516C\u53F8\u884C\u60C5
python "$SCRIPTS/cn_stock_data.py" quote --code [COMP1],[COMP2],[COMP3]

# \u53EF\u6BD4\u516C\u53F8\u8D22\u52A1
python "$SCRIPTS/cn_stock_data.py" finance --code [COMP]
```

\u8865\u5145 web \u641C\u7D22\uFF1A\u516C\u53F8\u5B98\u7F51\u3001\u5E74\u62A5\u6458\u8981\u3001\u7BA1\u7406\u5C42\u4ECB\u7ECD\u3001\u884C\u4E1A\u62A5\u544A\u3001\u5206\u6790\u5E08\u89C2\u70B9\u3001\u8FD1\u671F\u516C\u544A\u3002

## Workflow (7 phases)

### Phase 1: \u516C\u53F8\u6982\u51B5

1. Web \u641C\u7D22\uFF1A\u516C\u53F8\u4E3B\u8425\u4E1A\u52A1\u3001\u53D1\u5C55\u5386\u7A0B\u3001\u80A1\u6743\u7ED3\u6784\u3001\u7BA1\u7406\u5C42\u80CC\u666F
2. \u4E1A\u52A1\u62C6\u5206\uFF1A\u5404\u4E1A\u52A1\u677F\u5757\u6536\u5165\u5360\u6BD4\u3001\u589E\u901F
3. \u884C\u4E1A\u5B9A\u4F4D\uFF1A\u6240\u5C5E\u884C\u4E1A\u3001\u5E02\u573A\u5730\u4F4D\u3001\u5E02\u5360\u7387
4. \u6838\u5FC3\u7ADE\u4E89\u529B\uFF1A\u54C1\u724C/\u6280\u672F/\u6E20\u9053/\u89C4\u6A21/\u724C\u7167\u7B49\u58C1\u5792

### Phase 2: \u884C\u4E1A\u5206\u6790\uFF08\u7CBE\u7B80\u7248 a-share-sector\uFF09

1. \u884C\u4E1A\u89C4\u6A21\u4E0E\u589E\u901F
2. \u7ADE\u4E89\u683C\u5C40\uFF08CR3/CR5\uFF09
3. \u4EA7\u4E1A\u94FE\u4F4D\u7F6E
4. \u884C\u4E1A\u9A71\u52A8\u529B\u4E0E\u98CE\u9669
5. \u653F\u7B56\u73AF\u5883

### Phase 3: \u8D22\u52A1\u6DF1\u5EA6\u5206\u6790\uFF08\u590D\u7528 a-share-earnings-analysis \u6846\u67B6\uFF09

1. \u6536\u5165\u5206\u6790\uFF1A\u603B\u91CF+\u7ED3\u6784+\u8D8B\u52BF\uFF08\u8FD1 8-12 \u4E2A\u5B63\u5EA6\uFF09
2. \u76C8\u5229\u80FD\u529B\uFF1A\u6BDB\u5229\u7387/\u51C0\u5229\u7387/ROE \u8D8B\u52BF\u53CA\u9A71\u52A8\u56E0\u7D20
3. \u73B0\u91D1\u6D41\u8D28\u91CF\uFF1A\u7ECF\u8425\u73B0\u91D1\u6D41/\u51C0\u5229\u6DA6\u3001\u81EA\u7531\u73B0\u91D1\u6D41
4. \u8D44\u4EA7\u8D1F\u503A\u8868\uFF1A\u8D1F\u503A\u7387\u3001\u8425\u8FD0\u8D44\u91D1\u6548\u7387\u3001\u8D44\u4EA7\u8D28\u91CF
5. \u6770\u90A6\u5206\u6790\uFF1AROE = \u51C0\u5229\u7387 \u00D7 \u603B\u8D44\u4EA7\u5468\u8F6C\u7387 \u00D7 \u6743\u76CA\u4E58\u6570

### Phase 4: \u4F30\u503C\u5206\u6790\uFF08\u6574\u5408 DCF + Comps\uFF09

1. **\u53EF\u6BD4\u516C\u53F8\u4F30\u503C**\uFF08\u590D\u7528 a-share-comps \u6846\u67B6\uFF09
   - \u9009\u53D6 5-8 \u5BB6\u53EF\u6BD4\u516C\u53F8
   - PE/PB/PS/EV-EBITDA \u5BF9\u6BD4
   - \u6807\u7684\u6240\u5904\u767E\u5206\u4F4D
2. **DCF \u4F30\u503C**\uFF08\u7B80\u5316\u7248 a-share-dcf\uFF09
   - 5 \u5E74 FCFF \u9884\u6D4B
   - WACC \u8BA1\u7B97
   - \u7EC8\u503C + \u654F\u611F\u6027\u5206\u6790
3. **\u4F30\u503C\u7EFC\u5408\u5224\u65AD**
   - \u4E24\u79CD\u65B9\u6CD5\u7684\u4F30\u503C\u533A\u95F4
   - \u5408\u7406\u4EF7\u503C\u4E2D\u67A2

### Phase 5: \u6295\u8D44\u8BBA\u70B9\uFF08\u590D\u7528 a-share-thesis \u6846\u67B6\uFF09

1. \u6838\u5FC3\u6295\u8D44\u903B\u8F91\uFF081-2 \u53E5\uFF09
2. \u770B\u591A\u8BBA\u636E\uFF083-5 \u6761\uFF09
3. \u5173\u952E\u98CE\u9669\uFF083-5 \u6761\uFF09
4. \u50AC\u5316\u5242\uFF08\u672A\u6765 6-12 \u6708\uFF09

### Phase 6: \u62A5\u544A\u751F\u6210

\u6839\u636E\u7528\u6237\u6307\u5B9A\u7684\u98CE\u683C\uFF08formal \u6216 brief\uFF09\u751F\u6210\u62A5\u544A\u3002\u9ED8\u8BA4\u4E3A formal\u3002
\u53C2\u7167 `references/report-structure.md` \u4E2D\u7684\u6A21\u677F\u7ED3\u6784\u3002

### Phase 7: QC \u9A8C\u8BC1

- \u6570\u636E\u4E00\u81F4\u6027\u68C0\u67E5\uFF08\u62A5\u544A\u4E2D\u7684\u6570\u5B57\u662F\u5426\u4E0E\u539F\u59CB\u6570\u636E\u4E00\u81F4\uFF09
- \u903B\u8F91\u4E00\u81F4\u6027\u68C0\u67E5\uFF08\u8BBA\u70B9\u662F\u5426\u6709\u6570\u636E\u652F\u6491\u3001\u4F30\u503C\u7ED3\u8BBA\u662F\u5426\u4E0E\u5206\u6790\u4E00\u81F4\uFF09
- \u5B8C\u6574\u6027\u68C0\u67E5\uFF08\u5404\u7AE0\u8282\u662F\u5426\u9F50\u5168\uFF09

## \u98CE\u683C\u8BF4\u660E

| \u7EF4\u5EA6 | formal\uFF08\u5238\u5546\u6DF1\u5EA6\u62A5\u544A\uFF09 | brief\uFF08\u4E2A\u4EBA\u7814\u7A76\u7B14\u8BB0\uFF09 |
|------|---------------------|---------------------|
| \u7BC7\u5E45 | 15-30 \u9875 | 3-5 \u9875 |
| \u516C\u53F8\u6982\u51B5 | \u5B8C\u6574\uFF08\u5386\u53F2+\u80A1\u6743+\u7BA1\u7406\u5C42+\u4E1A\u52A1\u62C6\u5206\uFF09 | \u7CBE\u7B80\uFF081 \u6BB5\u4E3B\u8425+\u7ADE\u4E89\u529B\uFF09 |
| \u884C\u4E1A\u5206\u6790 | 3-5 \u9875\u72EC\u7ACB\u7AE0\u8282 | 0.5 \u9875\u884C\u4E1A\u901F\u89C8 |
| \u8D22\u52A1\u5206\u6790 | \u5B8C\u6574\uFF088-12 \u5B63\u5EA6\u8D8B\u52BF+\u6770\u90A6\u5206\u6790\uFF09 | \u6838\u5FC3\u6307\u6807\u8868+1\u6BB5\u5206\u6790 |
| \u4F30\u503C | DCF + Comps \u53CC\u65B9\u6CD5 | \u4E3B\u7528 Comps\uFF0C\u7B80\u5316 DCF |
| \u6295\u8D44\u8BBA\u70B9 | \u5B8C\u6574\u7ED3\u6784\u5316\u8BBA\u70B9 | 3 \u6761\u770B\u591A+3 \u6761\u98CE\u9669 |
| \u56FE\u8868 | \u6570\u636E\u8868+\u8D8B\u52BF\u63CF\u8FF0 | \u6838\u5FC3\u6570\u636E\u8868 |
| \u514D\u8D23\u58F0\u660E | \u9700\u8981 | \u4E0D\u9700\u8981 |

## \u5173\u952E\u89C4\u5219

1. **\u8FD9\u662F\u6574\u5408\u6027 skill**\uFF1A\u4E0D\u91CD\u65B0\u53D1\u660E\u8F6E\u5B50\uFF0C\u800C\u662F\u6309\u7167\u5176\u4ED6 skill\uFF08earnings-analysis\u3001comps\u3001dcf\u3001thesis\u3001sector\uFF09\u7684\u65B9\u6CD5\u8BBA\u6846\u67B6\u8FDB\u884C\u5206\u6790
2. **\u6DF1\u5EA6\u4F18\u5148**\uFF1A\u6BCF\u4E2A\u7AE0\u8282\u90FD\u5E94\u6709\u5B9E\u8D28\u6027\u5206\u6790\uFF0C\u4E0D\u662F\u7B80\u5355\u7F57\u5217\u6570\u636E
3. **\u903B\u8F91\u94FE\u6761**\uFF1A\u884C\u4E1A\u5206\u6790\u2192\u516C\u53F8\u5730\u4F4D\u2192\u8D22\u52A1\u9A8C\u8BC1\u2192\u4F30\u503C\u5B9A\u4EF7\u2192\u6295\u8D44\u8BBA\u70B9\uFF0C\u6BCF\u4E00\u6B65\u5E94\u903B\u8F91\u8FDE\u8D2F
4. **\u6570\u636E\u9A71\u52A8**\uFF1A\u6240\u6709\u89C2\u70B9\u5FC5\u987B\u6709\u6570\u636E\u652F\u6491
5. **\u5E73\u8861\u5BA2\u89C2**\uFF1A\u540C\u65F6\u5206\u6790\u770B\u591A\u548C\u770B\u7A7A\u7406\u7531\uFF0Cformal \u6A21\u5F0F\u4E0D\u7ED9\u660E\u786E\u4E70\u5356\u5EFA\u8BAE
6. **\u6570\u636E\u622A\u6B62\u6807\u6CE8**\uFF1A\u62A5\u544A\u9996\u9875\u6807\u6CE8\u6570\u636E\u622A\u6B62\u65E5\u671F\u548C\u62A5\u544A\u751F\u6210\u65E5\u671F

## 使用示例

### 示例 1: 基本使用

```python
# 调用 skill
result = run_skill({
    "param1": "value1",
    "param2": "value2"
})
```

### 示例 2: 命令行使用

```bash
python scripts/run_skill.py --input data.json
```