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A股逆向选择/信息不对称分析。当用户说"逆向选择"、"adverse selection"、"信息不对称"、"知情交易者"、"逆向选择成本"、"信息劣势"时触发。基于 cn-stock-data 获取数据，度量逆向选择与信息不对称程度。支持 formal/brief 两种输出风格。
A股量价异常检测/异动监控。当用户说"异常检测"、"异动"、"anomaly"、"量价异常"、"异常波动"、"XX有异动"时触发。量化检测股价和成交量异常。支持formal和brief风格。
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。
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| name | akshare-risk-tagging |
| description | 用于基于AkShare数据的风险标签生成场景。适用于金融工作中的基础任务单元。 |
本 Skill 使用 AkShare 提供的 A 股市场数据接口进行风险标签打标，主要包括：
stock_zh_a_spot_em：A 股实时行情快照，用于获取最新价、涨跌幅、成交量、成交额、换手率、市盈率等基础指标。stock_zh_a_hist：A 股历史行情，用于计算近 N 日波动率、回撤、均线偏离、成交额均值等风险特征。stock_individual_info_em：个股基础信息（如股票简称、总市值等），用于补充个股静态属性。说明：不同 AkShare 版本的字段命名可能略有差异，脚本中已尽量兼容常见字段名，但建议在生产使用前结合实际环境验证一次。
本 Skill 面向 A 股股票池进行风险标签打标，输出每只股票的风险标签、风险分数和综合风险等级。
st_risk：证券简称包含 ST、*ST 等特殊处理标识。high_volatility_20d：近 20 个交易日年化波动率偏高。large_drawdown_60d：近 60 个交易日最大回撤较大。low_liquidity：近 20 个交易日平均成交额偏低，流动性不足。abnormal_turnover：最新换手率异常偏高。near_limit_down：最新单日跌幅接近跌停风险区间。penny_stock：股价过低，价格脆弱性更高。below_ma20：股价低于 20 日均线，短期趋势偏弱。脚本会为每只股票输出：
low / medium / high）默认输出到：
output/risk_labels.csvoutput/risk_labels.jsonpip install akshare pandas numpy
python script/risk_labeling.py
python script/risk_labeling.py --symbols 600519,000001,300750
python script/risk_labeling.py --limit 50
python script/risk_labeling.py --output-dir ./output
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