A股质量因子/盈利质量量化分析

SkillDev tools

Quantitative analysis of A-share quality factors / earnings quality. Triggered when the user says "质量因子", "quality factor", "盈利质量", "高质量", "ROE质量", or "应计". Quantitatively constructs and analyzes quality factors. 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股质量因子/盈利质量量化分析 skill

What this skill tells your AI

The instructions your AI receives, as published by aifinlab/finclaw in skills/a-share-quality-factor/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: 获取财务数据

Step 2: 构建质量因子

  • 盈利能力: ROE/ROIC/毛利率
  • 盈利稳定性: ROE标准差(过去5年)
  • 应计质量: (净利润-经营现金流)/总资产
  • 资产负债质量: 负债率/流动比率

Step 3: 因子检验

IC/IR分析、分组回测

Step 4: 输出

维度formalbrief
因子值多维度质量评分综合质量分
因子效果IC/IR+分组收益因子有效性
默认风格:brief。

关键规则

  1. 质量因子在熊市表现更突出(防御性)
  2. 低应计比例=高盈利质量(现金利润占比高)
  3. ROE高但自由现金流差→质量存疑
  4. 质量因子与价值因子结合效果更好
  5. A股财务造假风险需特别关注应计异常

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-quality-factor
Source
github.com/aifinlab/finclaw