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a-share-stop-loss

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A股止损策略/风控规则量化。当用户说"止损"、"stop loss"、"止盈"、"风控"、"该不该割肉"、"设在哪"、"止损位"时触发。量化设计止损止盈策略。支持formal和brief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-stop-loss/SKILL.md

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A股止损策略/风控规则量化

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: 获取标的数据

Step 2: 止损方法计算

  • 固定比例止损：从买入价下跌 N% 止损
  • ATR止损：买入价 - N × ATR(14)
  • 移动止损：从最高价回撤 N% 止损
  • 支撑位止损：跌破关键技术支撑位

Step 3: 历史回测

回测各止损方法在该股上的历史表现（避免的亏损 vs 误杀的盈利）

Step 4: 最优止损参数

根据标的波动特征选择最优止损幅度

Step 5: 输出

维度formalbrief
止损方案多方法对比建议止损位
回测结果各方法胜率+收益推荐方法
止盈建议止盈策略目标价位
默认风格：brief。

关键规则

  1. 止损是风控底线——没有止损的交易不是投资
  2. 止损幅度应匹配标的波动率——高波动股需更宽止损
  3. A 股 T+1 下无法当日止损——需更谨慎的仓位管理
  4. 止损位不应频繁修改——避免情绪化调整
  5. 好的止损策略是在减少大亏和避免误杀之间的平衡

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