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a-share-tail-hedge

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A股尾部对冲/黑天鹅保护策略。当用户说"尾部对冲"、"tail hedge"、"黑天鹅保护"、"极端风险对冲"、"保险策略"、"protective put"、"崩盘保护"时触发。基于 cn-stock-data 获取数据，设计尾部风险对冲方案。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-tail-hedge/SKILL.md

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尾部对冲/黑天鹅保护助手

数据获取

通过 cn-stock-data skill 获取数据：

  • 期权数据: OTM Put期权价格
  • VIX类指标: 波动率指数
  • 组合数据: 当前持仓与风险敞口

分析工作流

Step 1: 尾部风险评估

  • 历史最大回撤：A股历史极端下跌幅度
  • VaR/CVaR：组合的尾部风险度量
  • 尾部概率估计：极端事件发生的概率
  • 当前风险环境：波动率/信用利差/流动性指标

Step 2: 对冲工具选择

  • OTM Put期权：最直接的尾部保护
  • Put Spread：买深度OTM Put+卖更深OTM Put(降低成本)
  • VIX类产品：波动率飙升时获利
  • 股指期货空头：简单但成本高(放弃上行)

Step 3: 对冲方案设计

  • 保护水平：组合下跌X%时开始保护
  • 对冲比例：保护组合的百分比(通常50-100%)
  • 对冲成本预算：年化成本占组合的0.5-2%
  • 展期策略：月度/季度展期OTM Put

Step 4: 成本优化

  • Collar策略：买Put+卖Call，零成本或低成本
  • Put Spread降低权利金支出
  • 择时对冲：风险指标升高时加大对冲
  • 结构化产品：利用波动率偏斜降低成本

Step 5: 输出报告

输出格式

formal 风格（研报级）

# 尾部对冲方案报告

## 一、风险评估
| 指标 | 数值 | 评估 |
|------|------|------|

## 二、对冲方案
[工具选择、合约明细]

## 三、成本分析
[对冲成本、成本优化]

## 四、情景测试
[极端场景下的保护效果]

brief 风格（快速分析）

## 尾部对冲速览
- 组合CVaR(99%) = -8.5%
- 方案：买入5% OTM Put Spread
- 年化成本约0.8%
- 保护效果：极端下跌时减少损失60%

参考 references/tail-hedge-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