⚠️ 重要提示
本报告内容基于 skillhub『股票因子』技能 获取的初始数据（各因子族 IC / IR / time_potential 等评估指标）， 由 WorkBuddy 自动分析 生成，仅供参考，不构成任何投资建议。
因子历史表现不代表未来收益；市场有风险，投资需谨慎。据此操作，盈亏自负。
股票因子分析报告
数据来源：stock-factor 技能 output/*.xlsx（自动汇总 16 个因子族）｜ 生成工具：WorkBuddy 自动分析 ｜
样本区间：2024-08-14T00:00:00.000000 ~ 2026-08-07T00:00:00.000000 ｜ 股票池：全市场约 5593 只
一、分析总览
1087
纳入因子总数
560
有效因子 (|IR|>0.3)
143
强有效因子 (|IR|>0.5)
0.3024
平均 |IR|
0.0161
平均 IC
本次共分析 1087 个因子，覆盖 16 个因子族。按 |IR|>0.3 口径， 有效因子 560 个（占比 51.5%）， 其中强有效（|IR|>0.5）143 个。IC 的正负代表因子方向： 正=因子值越大未来收益越高，负=相反。
| 因子族 | 因子数 | 有效数 | 强有效 | 平均|IR| | 平均IC | 平均time_potential | 领头牛因子 |
|---|---|---|---|---|---|---|---|
| Qlib Alpha158 | 158 | 85 | 22 | 0.3269 | -0.0033 | 0.7074 | CORR10 |
| Qlib Alpha360 | 360 | 321 | 83 | 0.4344 | 0.0584 | 0.7499 | VOLUME44 |
| WorldQuant Alpha101 | 101 | 32 | 12 | 0.2413 | 0.0174 | 0.6600 | Alpha#16 |
| 国泰君安 GTJA Alpha191 | 191 | 81 | 21 | 0.2859 | -0.0105 | 0.7175 | GTJA_Alpha83 |
| TA-Lib 技术指标 | 84 | 23 | 3 | 0.2206 | -0.0295 | 0.7464 | PLUS_DI14 |
| stock_daily 基础因子 | 12 | 3 | 0 | 0.2232 | -0.0288 | 0.7825 | 换手率-自由流通股 |
| stock_report 财务因子 | 105 | 1 | 0 | 0.0611 | 0.0038 | 0.8201 | 单位股价_资本公积 |
| Barra CNE5 风格 | 10 | 0 | 0 | 0.1741 | -0.0136 | 0.8083 | CNE5_Liquidity |
| Piotroski F-Score | 10 | 0 | 0 | 0.0734 | 0.0031 | 0.9384 | F9_dATO |
| Altman Z-Score | 6 | 0 | 0 | 0.0729 | 0.0052 | 0.8066 | Altman_X4 |
| 经典学术异象 | 9 | 4 | 0 | 0.2861 | -0.0067 | 0.7954 | ANOM_INTRADAY |
| Fama-French / HXZ | 7 | 0 | 0 | 0.1214 | -0.0009 | 0.8212 | FF_Value_BM |
| 中信/申万 风格 | 12 | 4 | 0 | 0.2367 | -0.0178 | 0.8065 | CS_Momentum |
| WorldQuant 公式化alpha扩展批 | 10 | 4 | 1 | 0.2874 | 0.0251 | 0.5938 | WQ_RANK_CORR_OV |
| 收益高阶矩/52周高 | 7 | 2 | 1 | 0.1973 | -0.0207 | 0.8226 | ANOM_SKEW |
| Merton 现金流收益率 | 5 | 0 | 0 | 0.1361 | -0.0036 | 0.8124 | MERTON_DD |
| 合计 | 1087 | 560 | 143 | 0.3024 | 0.0161 | 0.7399 | — |
各因子族规模与有效因子数
各因子族平均信息比率
二、因子有效性分布
IR（信息比率）= IC均值 / IC标准差，|IR|>0.3 通常视为有效。 下图显示全部 1087 个因子的 IR 分布：大量因子集中在 0 附近（预测力弱）， 长尾部分布在 ±0.3 之外的是具备选股信号的候选因子。
全部因子 IR 分布（红色虚线为 ±0.3 阈值）
time_potential 分布（越接近1越稳定）
三、IC - IR 关系（跨因子族）
横轴为 IC（因子值与未来收益的秩相关），纵轴为 IR。 点越靠上/下且离 0 越远，因子信号越稳定有效。不同颜色代表不同因子族，可直观比较各族整体表现。
IC-IR 散点（按因子族着色）
四、有效因子排行榜（Top 30 by |IR|）
下表为全部因子中 |IR| 最高的 30 个，按 |IR| 降序。 top10%_IR / bottom10%_IR 反映因子在头/尾极端档位的区分度（一头显著正、另一头显著负 = 多空信号可靠）。
| # | 因子名 | 族 | IC | IR | time_potential | top10%_IR | bottom10%_IR | 代码 |
|---|---|---|---|---|---|---|---|---|
| 1 | Alpha#16 | Alpha101 | 0.0597 | 0.9053 | 0.7830 | -0.2855 | 0.8707 | 查看代码ah = d['high'] * d['adj_factor']; vol = d['vol']; out = -1 * row_rank(row_rank(ah).rolling(5).cov(row_rank(vol))) |
| 2 | GTJA_Alpha83 | GTJA191 | 0.0597 | 0.9053 | 0.7830 | -0.2855 | 0.8707 | 查看代码hi = d['high'] * d['adj_factor']; cov5 = row_rank(hi).rolling(5).cov(row_rank(d['vol'])); out = -1 * row_rank(cov5) |
| 3 | Alpha#13 | Alpha101 | 0.0583 | 0.8923 | 0.7581 | -0.3878 | 0.8706 | 查看代码ac = d['close'] * d['adj_factor']; vol = d['vol']; out = -1 * row_rank(row_rank(ac).rolling(5).cov(row_rank(vol))) |
| 4 | GTJA_Alpha99 | GTJA191 | 0.0583 | 0.8923 | 0.7581 | -0.3878 | 0.8706 | 查看代码ac = d['close'] * d['adj_factor']; cov5 = row_rank(ac).rolling(5).cov(row_rank(d['vol'])); out = -1 * row_rank(cov5) |
| 5 | Alpha#44 | Alpha101 | 0.0542 | 0.8542 | 0.7042 | 0.1071 | 0.2325 | 查看代码ah = d['high'] * d['adj_factor']; vol = d['vol']; out = -1 * ah.rolling(5).corr(row_rank(vol)) |
| 6 | GTJA_Alpha62 | GTJA191 | 0.0542 | 0.8542 | 0.7042 | 0.1071 | 0.2325 | 查看代码hi = d['high'] * d['adj_factor']; out = -1 * hi.rolling(5).corr(row_rank(d['vol'])) |
| 7 | CORR10 | Alpha158 | -0.0638 | -0.7474 | 0.7940 | -0.5551 | 0.0381 | 查看代码ac=d['close']*d['adj_factor']; vol=d['vol']; out=ac.rolling(10).corr(np.log(vol+1)) |
| 8 | CORR5 | Alpha158 | -0.0584 | -0.7436 | 0.6720 | -0.2872 | -0.0309 | 查看代码ac=d['close']*d['adj_factor']; vol=d['vol']; out=ac.rolling(5).corr(np.log(vol+1)) |
| 9 | GTJA_Alpha90 | GTJA191 | 0.0422 | 0.7290 | 0.7255 | 0.0818 | 0.2275 | 查看代码vwap = d['amount'] / d['vol'].replace(0, np.nan); corr5 = row_rank(vwap).rolling(5).corr(row_rank(d['vol'])); out = -1 * row_rank(corr5) |
| 10 | Alpha#15 | Alpha101 | 0.0386 | 0.7215 | 0.7626 | 0.1778 | 0.0535 | 查看代码ah = d['high'] * d['adj_factor']; vol = d['vol']; corr3 = row_rank(ah).rolling(3).corr(row_rank(vol)); out = -1 * row_rank(corr3).rolling(3).sum() |
| 11 | Alpha#55 | Alpha101 | 0.0383 | 0.7125 | 0.7667 | 0.2510 | 0.2869 | 查看代码ac = d['close'] * d['adj_factor']; ah = d['high'] * d['adj_factor']; al = d['low'] * d['adj_factor']; vol = d['vol']; ts_min_low12 = al.rolling(12).min(); ts_max_high12 = ah.rolling(12).max(); expr = (ac - ts_min_low12) / (ts_max_high12 - ts_min_low12); rank_expr = row_rank(expr); rank_vol = row_rank(vol); out = -1 * rank_expr.rolling(6).corr(rank_vol) |
| 12 | GTJA_Alpha176 | GTJA191 | -0.0383 | -0.7125 | 0.7667 | -0.2828 | -0.2501 | 查看代码ac = d['close'] * d['adj_factor']; hi = d['high'] * d['adj_factor']; lo = d['low'] * d['adj_factor']; wpr = (ac - lo.rolling(12).min()) / (hi.rolling(12).max() - lo.rolling(12).min()).replace(0, np.nan); out = row_rank(wpr).rolling(6).corr(row_rank(d['vol'])) |
| 13 | GTJA_Alpha16 | GTJA191 | 0.0440 | 0.7115 | 0.7937 | 0.0057 | 0.2507 | 查看代码vwap = d['amount'] / d['vol']; vwap = vwap.where(d['vol'] > 0, np.nan); rank_vol = row_rank(d['vol']); rank_vwap = row_rank(vwap); corr_5 = rank_vol.rolling(5).corr(rank_vwap); out = -1 * row_rank(corr_5).rolling(5).max() |
| 14 | GTJA_Alpha32 | GTJA191 | 0.0378 | 0.7076 | 0.7604 | 0.2055 | 0.0308 | 查看代码rank_high = row_rank(d['high'] * d['adj_factor']); rank_vol = row_rank(d['vol']); corr3 = rank_high.rolling(3).corr(rank_vol); out = -1 * corr3.rolling(3).sum() |
| 15 | Alpha#50 | Alpha101 | 0.0437 | 0.7023 | 0.7972 | -0.0470 | 0.1300 | 查看代码vol = d['vol']; avwap = (d['amount'] / (d['vol'] + 1e-12)) * d['adj_factor']; corr5 = row_rank(vol).rolling(5).corr(row_rank(avwap)); rank_corr = row_rank(corr5); out = -1 * rank_corr.rolling(5).max() |
| 16 | GTJA_Alpha64 | GTJA191 | 0.0385 | 0.6955 | 0.7995 | 0.1099 | -0.0150 | 查看代码ac = d['close'] * d['adj_factor']; vwap = d['amount'] / d['vol'].replace(0, np.nan); corr1 = row_rank(vwap).rolling(4).corr(row_rank(d['vol'])); rank1 = row_rank(rolling_decay_linear(corr1, 4)); corr2 = row_rank(ac).rolling(4).corr(row_rank(d['vol'].rolling(60).mean())); rank2 = row_rank(rolling_decay_linear(corr2.rolling(13).max(), 14)); out = -1 * np.maximum(rank1, rank2) |
| 17 | VOLUME44 | Alpha360 | 0.0643 | 0.6851 | 0.7921 | -0.0004 | 0.9277 | 查看代码out = ((d['vol']).shift(44)/(d['vol']+1e-12)) |
| 18 | VOLUME45 | Alpha360 | 0.0652 | 0.6736 | 0.7910 | 0.0013 | 0.9490 | 查看代码out = ((d['vol']).shift(45)/(d['vol']+1e-12)) |
| 19 | GTJA_Alpha179 | GTJA191 | -0.0435 | -0.6641 | 0.7043 | -0.5528 | 0.0064 | 查看代码vwap = d['amount'] / d['vol'].replace(0, np.nan); lo = d['low'] * d['adj_factor']; r1 = row_rank(vwap.rolling(4).corr(d['vol'])); corr12 = row_rank(lo).rolling(12).corr(row_rank(d['vol'].rolling(50).mean())); r2 = row_rank(corr12); out = r1 * r2 |
| 20 | VOLUME46 | Alpha360 | 0.0646 | 0.6626 | 0.7906 | -0.0006 | 0.9571 | 查看代码out = ((d['vol']).shift(46)/(d['vol']+1e-12)) |
| 21 | VOLUME59 | Alpha360 | 0.0643 | 0.6608 | 0.7944 | 0.0265 | 0.9840 | 查看代码out = ((d['vol']).shift(59)/(d['vol']+1e-12)) |
| 22 | Alpha#26 | Alpha101 | 0.0457 | 0.6587 | 0.7562 | 0.1567 | 0.4330 | 查看代码vol = d['vol']; ah = d['high'] * d['adj_factor']; ts_rank5_vol = rolling_rank(vol, 5); ts_rank5_high = rolling_rank(ah, 5); corr5 = ts_rank5_vol.rolling(5).corr(ts_rank5_high); out = -1 * corr5.rolling(3).max() |
| 23 | GTJA_Alpha5 | GTJA191 | 0.0457 | 0.6587 | 0.7562 | 0.1567 | 0.4330 | 查看代码ac = d['close'] * d['adj_factor']; ah = d['high'] * d['adj_factor']; volume = d['vol']; ts_rank_vol = volume.rolling(5).rank(pct=True, method='max'); ts_rank_high = ah.rolling(5).rank(pct=True, method='max'); corr_5 = ts_rank_vol.rolling(5).corr(ts_rank_high); tsmax_3 = corr_5.rolling(3).max(); out = -1 * tsmax_3 |
| 24 | VOLUME55 | Alpha360 | 0.0633 | 0.6557 | 0.7829 | 0.0814 | 1.0188 | 查看代码out = ((d['vol']).shift(55)/(d['vol']+1e-12)) |
| 25 | VSUMP60 | Alpha158 | -0.0631 | -0.6542 | 0.7906 | -0.9791 | -0.1668 | 查看代码vol=d['vol']; dvol=vol-vol.shift(1); pos=dvol.clip(lower=0); absdvol=dvol.abs(); out=pos.rolling(60).sum()/(absdvol.rolling(60).sum()+1e-12) |
| 26 | VSUMN60 | Alpha158 | 0.0631 | 0.6542 | 0.7906 | 0.1676 | 0.9799 | 查看代码vol=d['vol']; dvol=vol-vol.shift(1); neg=(-dvol).clip(lower=0); absdvol=dvol.abs(); out=neg.rolling(60).sum()/(absdvol.rolling(60).sum()+1e-12) |
| 27 | VSUMD60 | Alpha158 | -0.0631 | -0.6542 | 0.7906 | -0.9791 | -0.1668 | 查看代码vol=d['vol']; dvol=vol-vol.shift(1); pos=dvol.clip(lower=0); neg=(-dvol).clip(lower=0); absdvol=dvol.abs(); out=(pos.rolling(60).sum()-neg.rolling(60).sum())/(absdvol.rolling(60).sum()+1e-12) |
| 28 | VOLUME56 | Alpha360 | 0.0634 | 0.6540 | 0.7799 | 0.0582 | 0.9845 | 查看代码out = ((d['vol']).shift(56)/(d['vol']+1e-12)) |
| 29 | VOLUME43 | Alpha360 | 0.0617 | 0.6531 | 0.7807 | -0.0314 | 0.9248 | 查看代码out = ((d['vol']).shift(43)/(d['vol']+1e-12)) |
| 30 | VOLUME58 | Alpha360 | 0.0636 | 0.6522 | 0.7915 | 0.0594 | 1.0177 | 查看代码out = ((d['vol']).shift(58)/(d['vol']+1e-12)) |
Top 20 因子 |IR|（红=负向因子，绿=正向因子）
五、各因子族明细（Top 10 by |IR|）
Qlib Alpha158 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| CORR10 | -0.0638 | -0.7474 | 0.7940 | -0.5551 | 0.0381 |
| CORR5 | -0.0584 | -0.7436 | 0.6720 | -0.2872 | -0.0309 |
| VSUMD60 | -0.0631 | -0.6542 | 0.7906 | -0.9791 | -0.1668 |
| VSUMP60 | -0.0631 | -0.6542 | 0.7906 | -0.9791 | -0.1668 |
| VSUMN60 | 0.0631 | 0.6542 | 0.7906 | 0.1676 | 0.9799 |
| VSUMP30 | -0.0558 | -0.6166 | 0.7384 | -1.0164 | -0.1610 |
| VSUMN30 | 0.0558 | 0.6166 | 0.7384 | 0.1633 | 1.0120 |
| VSUMD30 | -0.0558 | -0.6166 | 0.7384 | -1.0164 | -0.1610 |
| CORR20 | -0.0542 | -0.6131 | 0.8227 | -0.3896 | 0.1605 |
| VMA60 | 0.0617 | 0.6075 | 0.7618 | -0.1326 | 1.0868 |
Qlib Alpha360 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| VOLUME44 | 0.0643 | 0.6851 | 0.7921 | -0.0004 | 0.9277 |
| VOLUME45 | 0.0652 | 0.6736 | 0.7910 | 0.0013 | 0.9490 |
| VOLUME46 | 0.0646 | 0.6626 | 0.7906 | -0.0006 | 0.9571 |
| VOLUME59 | 0.0643 | 0.6608 | 0.7944 | 0.0265 | 0.9840 |
| VOLUME55 | 0.0633 | 0.6557 | 0.7829 | 0.0814 | 1.0188 |
| VOLUME56 | 0.0634 | 0.6540 | 0.7799 | 0.0582 | 0.9845 |
| VOLUME43 | 0.0617 | 0.6531 | 0.7807 | -0.0314 | 0.9248 |
| VOLUME58 | 0.0636 | 0.6522 | 0.7915 | 0.0594 | 1.0177 |
| VOLUME57 | 0.0629 | 0.6490 | 0.7902 | 0.0800 | 1.0539 |
| VOLUME47 | 0.0635 | 0.6444 | 0.7924 | -0.0149 | 0.9588 |
WorldQuant Alpha101 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| Alpha#16 | 0.0597 | 0.9053 | 0.7830 | -0.2855 | 0.8707 |
| Alpha#13 | 0.0583 | 0.8923 | 0.7581 | -0.3878 | 0.8706 |
| Alpha#44 | 0.0542 | 0.8542 | 0.7042 | 0.1071 | 0.2325 |
| Alpha#15 | 0.0386 | 0.7215 | 0.7626 | 0.1778 | 0.0535 |
| Alpha#55 | 0.0383 | 0.7125 | 0.7667 | 0.2510 | 0.2869 |
| Alpha#50 | 0.0437 | 0.7023 | 0.7972 | -0.0470 | 0.1300 |
| Alpha#26 | 0.0457 | 0.6587 | 0.7562 | 0.1567 | 0.4330 |
| Alpha#27 | 0.0359 | 0.6404 | 0.7868 | — | — |
| Alpha#3 | 0.0373 | 0.6291 | 0.8092 | 0.1952 | 0.1550 |
| Alpha#88 | 0.0640 | 0.6095 | 0.7935 | -0.0384 | 0.8811 |
国泰君安 GTJA Alpha191 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| GTJA_Alpha83 | 0.0597 | 0.9053 | 0.7830 | -0.2855 | 0.8707 |
| GTJA_Alpha99 | 0.0583 | 0.8923 | 0.7581 | -0.3878 | 0.8706 |
| GTJA_Alpha62 | 0.0542 | 0.8542 | 0.7042 | 0.1071 | 0.2325 |
| GTJA_Alpha90 | 0.0422 | 0.7290 | 0.7255 | 0.0818 | 0.2275 |
| GTJA_Alpha176 | -0.0383 | -0.7125 | 0.7667 | -0.2828 | -0.2501 |
| GTJA_Alpha16 | 0.0440 | 0.7115 | 0.7937 | 0.0057 | 0.2507 |
| GTJA_Alpha32 | 0.0378 | 0.7076 | 0.7604 | 0.2055 | 0.0308 |
| GTJA_Alpha64 | 0.0385 | 0.6955 | 0.7995 | 0.1099 | -0.0150 |
| GTJA_Alpha179 | -0.0435 | -0.6641 | 0.7043 | -0.5528 | 0.0064 |
| GTJA_Alpha5 | 0.0457 | 0.6587 | 0.7562 | 0.1567 | 0.4330 |
TA-Lib 技术指标 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| PLUS_DI14 | -0.0768 | -0.6341 | 0.7661 | -0.6353 | 0.2760 |
| CORREL20 | -0.0558 | -0.6149 | 0.8202 | -0.5120 | 0.1285 |
| PVO | -0.0554 | -0.5430 | 0.7769 | -0.9964 | -0.0330 |
| IMI14 | -0.0540 | -0.4270 | 0.6903 | -0.6005 | 0.0751 |
| PPO | -0.0633 | -0.4088 | 0.7609 | -0.4928 | 0.2766 |
| MINUS_DI14 | 0.0510 | 0.3998 | 0.7323 | -0.1566 | 0.6985 |
| AROON_UP20 | -0.0437 | -0.3904 | 0.7619 | -0.2293 | -0.0007 |
| MFI14 | -0.0439 | -0.3890 | 0.7103 | -0.5006 | 0.0338 |
| BIAS24 | -0.0588 | -0.3858 | 0.7058 | -0.6283 | 0.2470 |
| MACD_DIF | -0.0583 | -0.3836 | 0.7500 | -0.0777 | 0.2092 |
stock_daily 基础因子 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| 换手率-自由流通股 | -0.0848 | -0.4789 | 0.7950 | -1.2095 | 0.1272 |
| 换手率 | -0.0759 | -0.4135 | 0.7948 | -1.1827 | 0.1325 |
| 量比 | -0.0274 | -0.3495 | 0.5880 | -0.8601 | 0.2126 |
| 市净率 | -0.0407 | -0.2386 | 0.8073 | 0.0158 | 0.0868 |
| 总市值 | -0.0328 | -0.1965 | 0.8144 | 0.0608 | 0.0526 |
| 市销率TTM | -0.0267 | -0.1773 | 0.8039 | -0.2039 | 0.0372 |
| 市销率 | -0.0246 | -0.1606 | 0.8033 | -0.1019 | 0.0403 |
| 流通市值 | -0.0244 | -0.1557 | 0.8048 | 0.0370 | 0.0529 |
| 市盈率TTM | -0.0247 | -0.1392 | 0.7963 | -0.2605 | -0.0665 |
| 市盈率 | -0.0232 | -0.1335 | 0.7937 | -0.2827 | -0.0308 |
stock_report 财务因子 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| 单位股价_资本公积 | 0.0336 | 0.4200 | 0.8357 | -0.0120 | -0.0462 |
| 单位股价_净资产 | 0.0396 | 0.2386 | 0.8064 | -0.1069 | -0.0860 |
| 每股经营现金流同比-% | 0.0047 | 0.1936 | 0.8194 | -0.0620 | -0.0046 |
| 经营现金流同比-% | 0.0045 | 0.1784 | 0.8276 | -0.0097 | 0.0111 |
| 单位股价_营业收入 | 0.0234 | 0.1699 | 0.8031 | -0.0339 | 0.1497 |
| 单位股价_营业总收入 | 0.0233 | 0.1688 | 0.8029 | -0.0348 | 0.1618 |
| 单季度营业收入同比-% | 0.0127 | 0.1439 | 0.8523 | -0.0835 | 0.1760 |
| 单位股价_企业自由现金流量 | -0.0052 | -0.1402 | 0.8387 | 0.0208 | 0.0080 |
| 单位股价_盈余公积 | 0.0262 | 0.1401 | 0.8131 | -0.0683 | 0.0272 |
| 单位股价_未分配利润 | 0.0200 | 0.1368 | 0.7938 | -0.0837 | -0.0913 |
Barra CNE5 风格 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| CNE5_Liquidity | -0.0582 | -0.2891 | 0.8014 | -0.5468 | 0.0638 |
| CNE5_NLSIZE | -0.0169 | -0.2783 | 0.7714 | -0.0469 | 0.0717 |
| CNE5_ResidualVol | -0.0595 | -0.2725 | 0.7987 | -0.3313 | -0.0743 |
| CNE5_BookToPrice | 0.0395 | 0.2377 | 0.8064 | -0.1085 | -0.0820 |
| CNE5_Size | -0.0328 | -0.1965 | 0.8144 | 0.0609 | 0.0526 |
| CNE5_EarningsYield | 0.0216 | 0.1261 | 0.7983 | 0.0873 | -0.1129 |
| CNE5_Growth | 0.0108 | 0.1133 | 0.8619 | 0.0032 | 0.1289 |
| CNE5_Momentum | -0.0217 | -0.1132 | 0.8221 | -0.1512 | 0.4585 |
| CNE5_Beta | -0.0151 | -0.0644 | 0.8195 | -0.1217 | 0.0038 |
| CNE5_Leverage | -0.0041 | -0.0503 | 0.7888 | 0.0475 | 0.0003 |
Piotroski F-Score — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| F9_dATO | 0.0054 | 0.1718 | 0.9690 | — | — |
| F8_dGM | 0.0032 | 0.1401 | 1.0209 | — | — |
| F3_dROA | 0.0043 | 0.1191 | 1.0197 | — | — |
| F2_OCF | 0.0049 | 0.0746 | 0.8242 | — | — |
| Piotroski_FScore | 0.0045 | 0.0670 | 0.8359 | 0.1278 | 0.1614 |
| F4_Accrual | 0.0025 | 0.0578 | 0.8151 | — | — |
| F7_NoDil | 0.0023 | 0.0367 | 1.0302 | — | — |
| F6_dLiq | 0.0009 | 0.0324 | 1.0137 | — | — |
| F1_ROA | 0.0025 | 0.0315 | 0.8575 | — | — |
| F5_dLev | 0.0001 | 0.0027 | 0.9975 | — | — |
Altman Z-Score — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| Altman_X4 | 0.0396 | 0.2376 | 0.8099 | -0.1942 | -0.0128 |
| Altman_X1 | -0.0051 | -0.0832 | 0.8114 | -0.1241 | 0.0559 |
| Altman_Z | -0.0042 | -0.0480 | 0.8227 | -0.1387 | 0.0236 |
| Altman_X5 | 0.0031 | 0.0465 | 0.7819 | 0.0884 | 0.0174 |
| Altman_X2 | -0.0022 | -0.0193 | 0.7913 | -0.1372 | 0.0044 |
| Altman_X3 | -0.0003 | -0.0030 | 0.8226 | -0.1054 | 0.0276 |
经典学术异象 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| ANOM_INTRADAY | -0.0695 | -0.4980 | 0.7380 | -0.5366 | 0.0865 |
| ANOM_IDIOVOL | -0.0887 | -0.4518 | 0.7875 | -0.5120 | -0.0451 |
| ANOM_REVERSAL_M1 | 0.0639 | 0.4170 | 0.7307 | -0.1127 | 0.4773 |
| ANOM_MAX20 | -0.0722 | -0.4036 | 0.8011 | -0.0023 | -0.0174 |
| ANOM_AMIHUD | 0.0368 | 0.2544 | 0.8207 | -0.1082 | -0.0989 |
| ANOM_OVERNIGHT | 0.0199 | 0.2517 | 0.7569 | -0.5524 | 0.4890 |
| ANOM_REVERSAL_Y1 | 0.0430 | 0.2122 | 0.8459 | -0.4502 | 0.1963 |
| ANOM_ASSETGROWTH | 0.0066 | 0.0768 | 0.8566 | -0.2010 | 0.0508 |
| ANOM_ACCRUALS | -0.0005 | -0.0097 | 0.8208 | -0.0295 | 0.0739 |
Fama-French / HXZ — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| FF_Value_BM | 0.0413 | 0.2538 | 0.8070 | -0.1201 | -0.0971 |
| FF_Size | -0.0328 | -0.1965 | 0.8144 | 0.0609 | 0.0526 |
| MOM_12M | -0.0374 | -0.1939 | 0.8536 | -0.0864 | 0.3618 |
| FF_Value_EP | 0.0145 | 0.1000 | 0.8191 | 0.0147 | -0.0169 |
| FF_Investment | 0.0044 | 0.0755 | 0.7723 | 0.1219 | 0.0812 |
| HXZ_ROE | 0.0018 | 0.0152 | 0.8353 | -0.0928 | 0.0484 |
| FF_Profitability | 0.0017 | 0.0150 | 0.8466 | -0.0855 | 0.0345 |
中信/申万 风格 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| CS_Momentum | -0.0707 | -0.4836 | 0.8480 | -0.3693 | 0.2103 |
| CS_Liquidity | -0.0759 | -0.4135 | 0.7948 | -1.1827 | 0.1325 |
| CS_Reversal | 0.0610 | 0.4008 | 0.7225 | -0.1744 | 0.4862 |
| CS_Volatility | -0.0676 | -0.3141 | 0.7966 | -0.3176 | 0.0218 |
| CS_NLSize | -0.0169 | -0.2783 | 0.7714 | -0.0469 | 0.0717 |
| CS_Value_BP | -0.0407 | -0.2386 | 0.8073 | 0.0158 | 0.0868 |
| CS_Growth_Rev | 0.0116 | 0.2116 | 0.8508 | -0.1906 | 0.0672 |
| CS_Size | -0.0328 | -0.1965 | 0.8144 | 0.0609 | 0.0526 |
| CS_Growth_Profit | 0.0063 | 0.1389 | 0.8283 | -0.1707 | -0.1381 |
| CS_Value_EP | 0.0145 | 0.1000 | 0.8191 | 0.0147 | -0.0169 |
WorldQuant 公式化alpha扩展批 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| WQ_RANK_CORR_OV | 0.0373 | 0.6291 | 0.8092 | 0.1952 | 0.1550 |
| WQ_RANK_CORR_RV | 0.0220 | 0.4800 | 0.7059 | 0.2150 | 0.1390 |
| WQ_VOLPRICE_DIV | 0.0381 | 0.4658 | 0.6121 | -0.2273 | 0.2138 |
| WQ_AMP_REV | 0.0697 | 0.4001 | 0.7643 | -0.1502 | 0.8616 |
| WQ_SMA_DEV | 0.0392 | 0.2751 | 0.6742 | -0.5544 | 0.7060 |
| WQ_OPEN_CLOSE | 0.0252 | 0.1744 | 0.3627 | -0.6720 | 0.6808 |
| WQ_CLOSE_VWAP | 0.0218 | 0.1467 | 0.3724 | -0.7952 | 0.8316 |
| WQ_INTRADAY | 0.0193 | 0.1408 | 0.3572 | -0.3621 | 0.2325 |
| WQ_VWAP_DEV | -0.0253 | -0.1337 | 0.8341 | 0.0818 | -0.0294 |
| WQ_LOWPRICE_REV | 0.0035 | 0.0281 | 0.4462 | -0.3709 | 0.1109 |
收益高阶矩/52周高 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| ANOM_SKEW | -0.0438 | -0.5496 | 0.8230 | -0.1379 | -0.2127 |
| ANOM_IDIOSKEW | -0.0177 | -0.3032 | 0.8458 | -0.2980 | -0.0785 |
| ANOM_DOWNSIDE_VOL | -0.0535 | -0.2557 | 0.7828 | -0.3086 | -0.0497 |
| ANOM_KURT | 0.0060 | 0.1000 | 0.8427 | -0.1443 | 0.3395 |
| ANOM_BETA | -0.0151 | -0.0644 | 0.8195 | -0.1217 | 0.0038 |
| ANOM_BETA2 | -0.0151 | -0.0644 | 0.8196 | -0.1217 | -0.0081 |
| ANOM_52WK_HIGH | -0.0060 | -0.0436 | 0.8246 | -0.4677 | 0.1872 |
Merton 现金流收益率 — Top 10 by |IR|
| 因子名 | IC | IR | time_potential | top10%_IR | bottom10%_IR |
|---|---|---|---|---|---|
| MERTON_DD | -0.0578 | -0.2486 | 0.8141 | -0.2611 | -0.1072 |
| CF_FCF_YIELD | -0.0052 | -0.1402 | 0.8387 | 0.0213 | 0.0081 |
| CF_DIV_YIELD | 0.0219 | 0.1211 | 0.7919 | 0.2172 | 0.0954 |
| CF_EBITDA_YIELD | 0.0167 | 0.0996 | 0.8046 | -0.0225 | -0.2053 |
| CF_OCF_YIELD | 0.0066 | 0.0710 | 0.8129 | 0.0199 | -0.0075 |
六、数据健康度与注意事项
- 样本覆盖：股票池中位数约 5593 只（最少 5593 只），样本区间 2024-08-14T00:00:00.000000 ~ 2026-08-07T00:00:00.000000， 评估用未来 5 日收益。
- time_potential 口径：= daily_IC.MA5.STD / daily_IC.STD，越接近 1 代表近期信号与长期一致、越稳定； 极端值可能意味着因子近期失效或样本异常。
- 头尾档位可能缺失：部分因子值大量重复（常数因子或大量同值），排序后极端档位无合适样本， 其 top10%_* / bottom10%_* 为空（显示为 —），属数据特性非代码错误。
- 常数因子：个别因子（如 CLOSE0 类）IC 异常属正常，已在初筛中跳过。
- 本报告边界：当前为「因子清单 + 初筛」，尚未做精选、去冗余、因子合成与策略回测。 下列指标仅供进一步研究的候选参考。
七、后续建议（可结合 QuantAll 全A解析）
- 在 |IR|>0.3 候选基础上精选有效因子并评级；
- 用 batch_factor_corr 做因子间去冗余（|IC|>0.8 视为冗余），降低多重共线性；
- 对精选因子做正交 / 合成，构造复合选股信号；
- 接入 strategy_backtest 做回测验证，确认实盘可行性；
- 随时间更新 IC 做版本管理，监控因子衰减。
提示：QuantAll（全A解析）MCP 已就绪，上述步骤可直接在其上调用对应工具完成。
本报告由 WorkBuddy 基于 stock-factor 技能初始数据自动生成 · 仅供参考 · 不构成投资建议