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a-share-execution-benchmark

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A股执行基准/Implementation Shortfall分析。当用户说"执行基准"、"IS分析"、"implementation shortfall"、"执行质量"、"到达价"、"arrival price"、"执行评估"时触发。基于 cn-stock-data 获取数据，评估交易执行质量。支持 formal/brief 两种输出风格。

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How to use this skill

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Source SKILL.md: https://github.com/aifinlab/FinClaw/blob/HEAD/skills/a-share-execution-benchmark/SKILL.md

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Copying this prompt does not install or run the skill. Review third-party files before use. Codex skill guide

执行基准/IS分析助手

数据获取

通过 cn-stock-data skill 获取数据：

  • 成交记录: 实际成交价格与时间
  • 行情数据: 决策时/下单时/成交时价格
  • 基准数据: VWAP/TWAP/收盘价

分析工作流

Step 1: 基准选择

  • 到达价(Arrival Price)：下单时的市场价格
  • VWAP：成交量加权平均价
  • TWAP：时间加权平均价
  • 收盘价(Close)：适合MOC订单评估

Step 2: IS计算

  • IS = (实际均价 - 基准价) / 基准价 × 方向
  • 买入IS：实际均价>基准价为正(不利)
  • 卖出IS：实际均价<基准价为正(不利)
  • IS越小执行质量越好

Step 3: IS归因分解

  • 延迟成本：决策价→下单价的变动
  • 市场冲击：下单价→成交均价的变动
  • 时机成本：市场自然波动的影响
  • 机会成本：未成交部分的潜在损失

Step 4: 执行质量评估

  • IS vs 预期IS：实际是否优于模型预测
  • IS分布：统计所有交易的IS分布
  • 按维度分析：标的/时段/订单大小/算法
  • 改进建议：针对IS最大的维度优化

Step 5: 输出报告

输出格式

formal 风格（研报级）

# 执行质量评估报告

## 一、IS汇总
| 基准 | IS(bps) | 评级 |
|------|---------|------|

## 二、IS归因
[延迟/冲击/时机/机会成本]

## 三、维度分析
[按标的/时段/算法的IS]

## 四、改进建议

brief 风格（快速分析）

## 执行质量速览
- Arrival Price IS = 5.2bps
- VWAP IS = -1.3bps (优于VWAP)
- 主要成本：市场冲击3.8bps
- 评级：良好(优于行业中位数)

参考 references/execution-benchmark-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