A股止损策略/风控规则量化
SkillDev toolsOnce added, your AI can design stop-loss and take-profit strategies for A-shares (the Chinese stock market) using quantitative rules instead of guesswork. Ask it where to set a stop, whether to cut a losing position, or how to manage risk on a holding, and it will work out a concrete answer. It can reply as a formal analysis or a short summary.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding it, ask your AI a question like 'where should I set my stop-loss?' or 'should I cut my losses?' and it will respond with a quantified strategy. Mention if you want the formal version or the brief one.
Then ask your AI: use the A股止损策略/风控规则量化 skill
What your AI can do with it
- Design stop-loss and take-profit strategies for A-shares with quantitative rules
- Recommend where to set a stop-loss level on a position
- Help you decide whether to cut a losing position or hold on
- Turn vague risk-control questions into concrete rules
- Answer in a formal write-up or a brief summary, whichever you ask for
What this skill tells your AI
The instructions your AI receives, as published by aifinlab/finclaw in skills/a-share-stop-loss/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: 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 | formal | brief |
|---|---|---|
| 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
- 止损是风控底线——没有止损的交易不是投资
- 止损幅度应匹配标的波动率——高波动股需更宽止损
- A 股 T+1 下无法当日止损——需更谨慎的仓位管理
- 止损位不应频繁修改——避免情绪化调整
- 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
Signals
- GitHub stars
- 241
- Forks
- 38
- Last commit
- May 2026
Advanced
- Catalog kind
- skill
- Gateway key
a-share-stop-loss- Source
- github.com/aifinlab/finclaw