A股Beta对冲/市场中性策略

SkillDev tools

A-share Beta hedging / market-neutral strategy. Triggers when the user says "对冲", "beta hedging", "市场中性", "对冲策略", "怎么对冲", or "空头对冲". Quantitatively builds a market-neutral portfolio. Supports formal and brief styles.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the A股Beta对冲/市场中性策略 skill

What this skill tells your AI

The instructions your AI receives, as published by aifinlab/finclaw in skills/a-share-beta-hedging/SKILL.md and read by ahel’s review.

数据源

SCRIPTS="$SKILLS_ROOT/cn-stock-data/scripts"
python "$SCRIPTS/cn_stock_data.py" kline --code [CODE] --freq daily --start [日期]
python "$SCRIPTS/cn_stock_data.py" quote --code [CODE]
python "$SCRIPTS/cn_stock_data.py" finance --code [CODE]

Workflow

Step 1: 计算个股/组合Beta

  • 回归法:R_i = α + β × R_m + ε(60日滚动)
  • 调整Beta = 0.67 × Raw Beta + 0.33 × 1

Step 2: 对冲工具选择

  • 股指期货(IF/IC/IM/IH)
  • ETF融券(如300ETF、500ETF)
  • 期权组合

Step 3: 计算对冲比率

  • 全对冲:空头名义值 = 多头名义值 × β
  • 部分对冲:根据风险预算调整对冲比例

Step 4: 基差风险分析

  • 期货贴水/升水对对冲成本的影响
  • 展期成本估算

Step 5: 输出

维度formalbrief
Beta计算多种方法对比当前Beta
对冲方案完整对冲方案推荐工具+比率
成本分析基差+展期成本年化对冲成本
默认风格:brief。

关键规则

  1. Beta不稳定——需用滚动窗口动态调整
  2. A股股指期货长期贴水——对冲成本=贴水+手续费
  3. 融券难借且成本高——限制了做空能力
  4. 对冲只消除Beta风险——Alpha也可能为负
  5. 对冲比例非一成不变——需定期再平衡

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

Signals

GitHub stars
241
Forks
38
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
a-share-beta-hedging
Source
github.com/aifinlab/finclaw