a-share-market-impact

Business

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。

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How to use this skill

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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

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

示例 2: 命令行使用

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