2026 年 01 月 11 日 情绪稳步修复，市场成交较上周显 著放量 ——量化择时周报 20260111 相关研究 沈思逸 A0230521070001 shensy@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 联系人 沈思逸 A0230521070001 shensy@swsresearch.com 权 益 量 化 研 究 证 券 研 究 报 告 请务必仔细阅读正文之后的各项信息披露与声明 本研究报告仅通过邮件提供给 中庚基金 使用。1 量 化 策 略 - 证券分析师 ⚫ 市场情绪稳步修复：截至 1 月 9 日，市场情绪指标数值为 1.6，较上周三的 1.35 小幅增 加，情绪得分逐步修复，从情绪角度来，模型看观点看多。 ⚫ 情绪指标维持修复，RSI 指标维持快速上升：本周价量一致性指标周内维持高位震荡，市 场价量匹配程度保持在相对较高水平，资金关注度与标的涨幅相关性较强，市场情绪整体 处于较为活跃区间；全 A 成交额环比显著回升，平均日成交额明显抬升，市场交易活跃 度较上周快速改善，资金参与意愿有所增强；科创 50 相对万得全 A ...

量化择时周报：牛市格局，聚焦哪些板块？ 证券研究报告/金融工程定期报告 2026 年 01 月 11 日 分析师：吴先兴 执业证书编号：S0740525110003 Email：wuxx02@zts.com.cn 分析师：王鹏飞 执业证书编号：S0740525060001 Email：wangpf@zts.com.cn 1、《净利润断层策略 2025 年绝对收 益 67.17%》2026-01-04 2、《量化择时周报：上行趋势仍在持 续，板块如何选择》2026-01-04 2025-12-28 报告摘要 牛市格局，聚焦哪些板块？ 请务必阅读正文之后的重要声明部分 相关报告 上周周报（20260104）认为：当前市场趋势线位于 6262 点附近，赚钱效应为 2.71%， 显著为正，上行趋势有望延续。同时，假期港股大幅上涨，有利于刺激 A 股风险偏好 的提高。综合来看，市场在赚钱效应的驱动下，增量资金有望持续入市，上行趋势有 望持续。最终 WIND 全 A 全周如期大幅上涨 5.11%。市值维度上，上周代表小市值股 票的中证 1000 上涨 7.03%，中盘股中证 500 指数上涨 7.92%，沪深 300 上 ...

广发证券首席金工分析师 安宁宁 SAC: S0260512020003 anningning@gf.com.cn 广发证券资深金工分析师 张钰东 SAC: S0260522070006 摘要 最近5个交易日，科创50指数涨9.80%，创业板指涨3.89%，大盘价值涨0.47%，大盘成长涨2.82%，上证50涨3.40%，国证2000代表的小盘涨7.21%，综合、 国防军工表现靠前，银行、交通运输表现靠后。 风险溢价，中证全指静态PE的倒数EP减去十年期国债收益率，权益与债券资产隐含收益率对比，截至2026/1/9，指标2.52%，两倍标准差边界为4.69%。 估值水平，截至2026/1/9，中证全指PETTM分位数83%，上证50与沪深300分别为76%、76%，创业板指接近62%，中证500与中证1000分别为68%、67%， 创业板指风格估值相对历史总体处于中位数水平。 使用卷积神经网络对图表化的价量数据与未来价格进行建模，并将学习的特征映射到行业主题板块中。最新配置主题为卫星和半导体等，具体包括中证卫 星产业指数、上证科创板半导体材料设备主题指数、中证半导体材料设备主题指数、国证商用卫星通信产业指数等细 ...

证券研究报告 | 金融工程 2026 年 1 月 11 日 情绪面仍为强支撑，但短期盘整概率有所增加 定期报告 ——A 股趋势与风格定量观察 20260111 ❑ 风格轮动：本周末成长价值轮动模型建议超配成长，小盘大盘轮动模型建议 超配小盘，故综合推荐小盘成长风格。 风险提示：择时和风格轮动模型结论基于合理假设前提下结合历史数据统计规 律推导而出，市场环境变化下可能导致出现模型失效风险。 敬请阅读末页的重要说明 ❑ 择时观点上，本周维持震荡偏乐观。1）建议至少维持半仓参与：基本面 数据进一步超预期且情绪面强势，未明显缩量前战略上不适合过于谨慎； 2）短期震荡整理概率增加，保持耐心：国内基本面改善仍非需求侧主 导，新增融资买入额快速上升积累风险。此外，年后海外地缘风险持续上 升且美债收益率和美元短期上行，非美地区流动性风险或再度成为压制。 ❑ PMI 与通胀数据均超预期，但结构性问题尚存，持续性有待验证。 12 月 制造业 PMI 录得 50.10，超出市场预期与季节性水平。不过，在年后全球 地缘风险上升的情况下，PMI 新订单出口能否继续超预期存疑。12 月 CPI/PPI 同比录得 0.8%/-1.9%，同 ...

2026年01月05日 市场情绪逐步修复， 价量: 速上升 -量化择时周报 20260104 量化策略 相关研究 证券分析师 沈思逸 A0230521070001 shensv@swsresearch.com 邓虎 A0230520070003 denqhu@swsresearch.com 联系人 沈思逸 A0230521070001 shensy@swsresearch.com 请务必仔细阅读正文之后的各项信息披露与声明 ○ 市场情绪逐步修复：截至 12 月 31 日，市场情绪指标数值为 1.35，较上周五的 1.1 小幅 增加,情绪得分逐步修复,从情绪角度来看观点看多。从所有分项指标分数之和的变化来 看，本周情绪指数综合得分同样较上周有所提升，市场交易活跃度出现反转回升迹象。 情绪指标逐步修复,价量一致性快速上升：本周价量一致性指标周内快速上升,较前期有 ● 所改善,市场价量匹配程度回升,资金关注度与标的涨幅相关性增强,情绪端呈现边际回 暖; 科创 50 相对万得全 A 成交占比延续下行趋势, 反映高弹性板块参与度仍偏低, 风险 偏好修复仍显不足; 行业间交易波动率持续下降并下穿布林带上界, 资金在不同行 ...

2026 年 01 月 05 日 市场情绪逐步修复，价量一致性快 速上升 ——量化择时周报 20260104 相关研究 证券分析师 证 券 研 究 报 告 请务必仔细阅读正文之后的各项信息披露与声明 本研究报告仅通过邮件提供给 中庚基金 使用。1 量 化 策 略 - ⚫ 市场情绪逐步修复：截至 12 月 31 日，市场情绪指标数值为 1.35，较上周五的 1.1 小幅 增加，情绪得分逐步修复，从情绪角度来看观点看多。从所有分项指标分数之和的变化来 看，本周情绪指数综合得分同样较上周有所提升，市场交易活跃度出现反转回升迹象。 ⚫ 情绪指标逐步修复，价量一致性快速上升：本周价量一致性指标周内快速上升，较前期有 所改善，市场价量匹配程度回升，资金关注度与标的涨幅相关性增强，情绪端呈现边际回 暖；科创 50 相对万得全 A 成交占比延续下行趋势，反映高弹性板块参与度仍偏低，风险 偏好修复仍显不足；行业间交易波动率持续下降并下穿布林带上界，资金在不同行业间切 换节奏放缓，跨行业轮动意愿减弱，流动性边际趋缓；行业涨跌趋势性指标维持在布林带 上界附近震荡，行业观点一致性较高，板块 β 效应仍占主导；融资余额占比持续上行并创 ...

证券研究报告 [Table_Page] 金融工程|定期报告 2026 年 1 月 4 日 请注意，张钰东并非香港证券及期货事务监察委员会的注 册持牌人，不可在香港从事受监管活动。 | DocReport] [Table_ 相关研究： | | | --- | --- | | 金融工程：AI 识图关注化 | 2025-12-28 | | 工、非银、通信和卫星:A 股 | | | 量化择时研究报告 | | | 本周部分因子表现调 | 2025-12-23 | | 整:Alpha 因子跟踪周报 | | | （2025.12.19） | | | 金融工程：AI 识图关注非 | 2025-12-21 | | 银、卫星、化工:A 股量化择 | | | 时研究报告 | | [Table_Title] 金融工程：AI 识图关注化工、非银 A 股量化择时研究报告 | ] [Table_Summary 市场回顾（本期是指 | 2025 年 25 日—2025 31 日） | 12 月 | | 年 12 月 | | --- | --- | --- | --- | --- | | 结构表现 | 中证 沪深 国证 | 中证 | 中证 | ...

Market Performance - The Sci-Tech 50 Index decreased by 0.59% and the ChiNext Index fell by 0.82% over the last five trading days, while the large-cap value index rose by 0.01% and the large-cap growth index declined by 0.39% [1] - The Shanghai Stock Exchange 50 Index increased by 0.20%, and the small-cap index represented by the CSI 2000 rose by 1.09%, with defense and military, as well as oil and petrochemical sectors performing well, while telecommunications and comprehensive sectors lagged [1] Valuation Levels - As of December 31, 2025, the static PE ratio of the CSI All Share Index is at the 82nd percentile, with the Shanghai 50 and CSI 300 both at 75%, and the ChiNext Index close to 58% [1] - The CSI 500 and CSI 1000 are at 62% and 64% respectively, indicating that the ChiNext Index's valuation is relatively at the historical median level [1] Fund Flows - In the last five trading days, ETF inflows amounted to 25.6 billion yuan, and the margin trading balance increased by approximately 23.8 billion yuan, with an average daily trading volume of 208.23 billion yuan across the two markets [2] Thematic Investment - The latest thematic allocation includes sectors such as chemicals, non-bank financials, and satellite communications, specifically focusing on sub-indices like the CSI Sub-Industry Chemical Index, the National Index for Commercial Satellite Communications, and the CSI 300 Non-Bank Financial Index [2][3] AI and Machine Learning Insights - A convolutional neural network (CNN) model has been utilized to analyze charted price and volume data, mapping learned features to industry thematic sectors, indicating a trend towards AI-driven investment strategies [11]

- Model Name: Timing System Model; Model Construction Idea: The model uses the distance between the long-term moving average (120 days) and the short-term moving average (20 days) to distinguish the overall market environment[2][6][11] - Model Construction Process: The model calculates the distance between the 20-day moving average and the 120-day moving average. The latest data shows the 20-day moving average at 6298 points and the 120-day moving average at 6090 points. The difference between the two lines is 3.41%, and the absolute value of the distance continues to be greater than 3%, indicating that the market is in an upward trend[2][6][11] - Model Evaluation: The model effectively identifies the market's upward trend, providing a positive signal for market timing[2][6][11] - Model Name: Industry Trend Allocation Model; Model Construction Idea: The model identifies industry trends and allocates based on medium-term reversal expectations and sector performance[2][5][7] - Model Construction Process: The model signals to focus on service consumption sectors such as tourism and media based on medium-term reversal expectations. The TWO BETA model continues to recommend the technology sector, focusing on AI applications and commercial aerospace. The industry trend model shows that the communication, industrial metals, and energy storage sectors continue their upward trend[2][5][7] - Model Evaluation: The model provides clear guidance on sector allocation, helping investors to focus on promising sectors[2][5][7] - Model Name: Position Management Model; Model Construction Idea: The model suggests stock allocation based on valuation indicators and short-term trends[5][7] - Model Construction Process: The model uses the PE and PB ratios of the WIND All A Index. The PE ratio is near the 90th percentile, indicating a relatively high valuation, while the PB ratio is at the 50th percentile, indicating a moderate level. Based on these indicators and short-term trends, the model suggests an 80% stock allocation for absolute return products[5][7] - Model Evaluation: The model provides a balanced approach to stock allocation, considering both valuation and market trends[5][7] Model Backtest Results - Timing System Model, Moving Average Distance: 3.41%[2][6][11] - Timing System Model, Market Trend Line: 6262 points[2][6][11] - Timing System Model, Profit Effect: 2.71%[2][6][11] - Position Management Model, PE Ratio: 90th percentile[5][7] - Position Management Model, PB Ratio: 50th percentile[5][7] - Position Management Model, Stock Allocation: 80%[5][7]

Group 1 - Market sentiment score has stabilized at 1.1 as of December 26, indicating a neutral outlook, with signs of improvement in trading activity [7][11][14] - The overall trading volume for the week increased by 11.63% compared to the previous week, with an average daily trading volume of 19,651.66 billion RMB, peaking at 21,811.04 billion RMB on December 26 [14][16] - The financing balance ratio continues to rise, reaching a new high, indicating an increase in leveraged funds and a recovery in risk appetite [25][27] Group 2 - The short-term scores for industries such as computers, real estate, pharmaceuticals, automobiles, and machinery have shown upward trends, with non-ferrous metals, light industry manufacturing, and communications having the highest short-term scores of 88.14 [35][36] - The industry trading volatility has decreased, indicating a slowdown in capital switching between sectors, with liquidity marginally tightening [20][22] - The correlation between industry congestion and weekly price changes is positive at 0.16, suggesting that sectors with high congestion, like defense and construction materials, have seen significant gains [39][41] Group 3 - The RSI indicator has shown significant improvement, indicating a reduction in selling pressure and a recovery in upward momentum [28][30] - The model indicates a preference for small-cap and growth styles, with the 5-day RSI relative to the 20-day RSI continuing to rise, suggesting potential strengthening of these signals [44][45] - The model's findings highlight that high congestion in sectors can lead to strong price movements but also increases the risk of rapid corrections if market expectations change [38][39]