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Get Started Free →aifinlab/a-share-autocorrelation
A股自相关/序列相关性/收益率自相关结构分析。当用户说"自相关"、"autocorrelation"、"序列相关"、"收益率预测性"、"动量还是反转"、"自相关系数"、"ACF"、"PACF"、"Ljung-Box"、"收益率是否可预测"、"随机游走检验"时触发。MUST USE when user asks about return autocorrelation, serial correlation tests, or whether a stock's returns are predictable. 量化分析收益率的自相关结构（ACF/PACF、Ljung-Box检验、随机游走检验）。支持formal和brief风格。
Passed 7 of 15 test cases with the skill, and 8 of 15 without it.
1 fixed9 passed either way10 still failing3 broke
Tokens, turns and time describe resource use, not a dollar price.
The instructions your model reads when the skill loads.
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]
lag 1-20的自相关系数
检验序列是否存在显著自相关
| 维度 | formal | brief |
|---|---|---|
| ACF/PACF | 完整图表 | 关键lag |
| 检验 | LB统计量+p值 | 有无自相关 |
| 含义 | 动量/反转判断 | 交易含义 |
| 默认风格：brief。 |
# 调用 skill
result = run_skill({
"param1": "value1",
"param2": "value2"
})
test cases passed, vs 8 / 15 without
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