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a-share-dynamic-hedging

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A股动态对冲/Delta中性策略。当用户说"动态对冲"、"Delta对冲"、"Delta中性"、"dynamic hedging"、"对冲调整"、"对冲比例"时触发。基于 cn-stock-data 获取数据，设计动态对冲方案。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-dynamic-hedging/SKILL.md

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动态对冲/Delta中性策略助手

数据获取

通过 cn-stock-data skill 获取数据：

  • 持仓数据: 股票/期权/期货持仓
  • Greeks数据: 组合Delta/Gamma
  • 实时行情: 标的价格与波动率

分析工作流

Step 1: 对冲需求分析

  • 组合Delta：当前方向性风险敞口
  • 对冲目标：完全中性/部分对冲/尾部保护
  • 对冲工具：股指期货/ETF/期权
  • 对冲比例：Beta调整后的最优对冲比

Step 2: 对冲比例计算

  • 最小方差对冲比 h* = ρ × σ_s/σ_f
  • Beta对冲：h = β × 组合市值/期货合约价值
  • 期权Delta对冲：h = 组合Delta/期权Delta
  • 跨品种对冲：用相关资产近似对冲

Step 3: 动态调整策略

  • 固定时间调整：每日/每周重新计算对冲比
  • 阈值触发调整：Delta偏离超过阈值时调整
  • Gamma scalping：利用Gamma正值做高频对冲
  • 成本约束：对冲调整频率vs交易成本的权衡

Step 4: 对冲效果评估

  • 对冲有效性：组合波动率降低比例
  • 对冲成本：期货贴水/期权权利金/交易费用
  • 基差风险：现货与对冲工具的不完美相关
  • 对冲后的残余风险分析

Step 5: 输出报告

输出格式

formal 风格（研报级）

# 动态对冲方案报告

## 一、对冲需求
| 指标 | 数值 |
|------|------|
| 组合Delta | +0.85 |

## 二、对冲方案
[工具选择、对冲比例]

## 三、调整规则
[触发条件、调整频率]

## 四、成本与效果

brief 风格（快速分析）

## 动态对冲速览
- 组合Delta +0.85，需对冲
- 方案：卖出IF期货3手
- 对冲后Delta降至+0.05
- 年化对冲成本约2%(期货贴水)

参考 references/dynamic-hedging-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