A股日内模式/分时走势量化分析
SkillCommerce & financeQuantitative analysis of A-share intraday patterns and time-share price movements. Triggered when the user says "日内模式", "intraday", "分时", "盘中走势", "几点涨", or "尾盘规律". Quantitatively analyzes A-share intraday trading patterns. Supports formal and brief styles.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the A股日内模式/分时走势量化分析 skill
What this skill tells your AI
The instructions your AI receives, as published by aifinlab/finclaw in skills/a-share-intraday-pattern/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: 获取分钟级K线
Step 2: 日内收益率分布
各时段(开盘/早盘/午盘/尾盘)的平均涨跌幅
Step 3: 日内量能分布
各时段成交量占比和变化规律
Step 4: 日内模式识别
- U型成交量(开盘尾盘放量,盘中缩量)
- 尾盘效应(最后30分钟异常)
- 午后效应
Step 5: 输出
| 维度 | formal | brief |
|---|---|---|
| 时段分析 | 各时段详细统计 | 关键时段 |
| 量能分布 | 分时量能图 | U型特征 |
| 规律总结 | 历史统计验证 | 今日模式 |
| 默认风格:brief。 |
关键规则
- A股开盘30分钟和收盘30分钟波动最大
- 集合竞价(9:15-9:25)反映隔夜消息消化
- 午后1:00-1:30常有政策/消息发布影响
- 尾盘集合竞价(14:57-15:00)可能被操纵
- 日内模式在不同市场状态下会变化
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-intraday-pattern- Source
- github.com/aifinlab/finclaw