A股市场冲击/价格影响分析。当用户说"市场冲击"、"market impact"、"价格影响"、"冲击成本"、"大单冲击"、"价格冲击模型"时触发。基于 cn-stock-data 获取数据,估算交易的市场冲击成本。支持 formal/brief 两种输出风格。
Scanned 9/7/2026
Install to Claude Code
npx -y skills add aifinlab/FinClaw --skill a-share-market-impact --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: a-share-market-impact
description: A股市场冲击/价格影响分析。当用户说"市场冲击"、"market impact"、"价格影响"、"冲击成本"、"大单冲击"、"价格冲击模型"时触发。基于 cn-stock-data 获取数据,估算交易的市场冲击成本。支持 formal/brief 两种输出风格。
---
# 市场冲击/价格影响分析助手
## 数据获取
通过 cn-stock-data skill 获取数据:
- **逐笔成交**: 大单成交与价格变动
- **盘口数据**: 市场深度
- **历史数据**: 日均成交量/波动率
## 分析工作流
### Step 1: 冲击模型
- 线性模型:Impact = λ × OrderSize / ADV
- 平方根模型:Impact = σ × √(OrderSize/ADV) (Almgren)
- 临时冲击 vs 永久冲击分解
- A股经验参数:λ ≈ 0.1-0.3
### Step 2: 冲击因素分析
- 订单大小/ADV比:越大冲击越大
- 波动率:高波动时冲击更大
- 流动性:盘口深度越深冲击越小
- 执行速度:越急迫冲击越大
### Step 3: 冲击估算
- 给定订单量,估算预期冲击成本
- 置信区间:冲击的不确定性范围
- 不同执行策略的冲击对比
- 分批执行vs一次性执行的冲击差异
### Step 4: 冲击优化
- 最优执行速度:平衡冲击与风险
- 最优拆单大小:单笔订单的最优规模
- 时段选择:流动性高峰期执行降低冲击
- 暗池/大宗交易:绕过公开市场降低冲击
### Step 5: 输出报告
## 输出格式
### formal 风格(研报级)
```
# [标的] 市场冲击分析报告
## 一、冲击估算
| 订单量 | 预期冲击 | 置信区间 |
|--------|---------|----------|
## 二、冲击因素
[流动性、波动率评估]
## 三、执行方案对比
[不同策略的冲击成本]
## 四、优化建议
```
### brief 风格(快速分析)
```
## [标的] 冲击估算速览
- 订单量20万股(ADV的5%)
- 预期冲击 0.12% (±0.05%)
- 流动性良好,冲击可控
- 建议:VWAP执行,分散至全天
```
参考 `references/market-impact-guide.md` 获取详细方法论与 A股实证研究。
## 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
```
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