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 ...

证券分析师 沈思逸 A0230521070001 shensy@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 2025 年 12 月 29 日 部分指标震荡修复，市场情绪有望 筑底 ——量化择时周报 20251228 相关研究 量 化 策 略 - ⚫ 市场情绪得分震荡回升：截至 12 月 26 日，市场情绪指标数值为 1.1，较上周五的 1.1 持 平，情绪得分震荡维稳，从情绪角度来看观点偏中性。从所有分项指标的变化来看，本周 情绪指数综合得分周内有所改善，市场交易活跃度出现反转回升迹象。 ⚫ 情绪出现修复改善，指标分化仍存：本周价量一致性指标周内维持震荡走势，周后段出现 明显回升，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 ...

Quantitative Models and Construction Methods 1. Model Name: Industry Crowding Monitoring Model - **Model Construction Idea**: This model is designed to monitor the crowding levels of industries on a daily basis, using the Shenwan First-Level Industry Index as the benchmark[3] - **Model Construction Process**: The model calculates the crowding levels of various industries based on daily data. It identifies industries with high crowding levels (e.g., military and building materials) and low crowding levels (e.g., banking, computing, and media). The model also tracks changes in crowding levels over time to highlight significant variations, such as the large changes observed in the building decoration and real estate sectors[3] - **Model Evaluation**: The model provides actionable insights into industry crowding trends, helping investors identify potential opportunities and risks in specific sectors[3] 2. Model Name: Premium Rate Z-Score Model - **Model Construction Idea**: This model is used to identify potential arbitrage opportunities in ETF products by calculating the Z-score of premium rates[4] - **Model Construction Process**: The model employs a rolling calculation of the Z-score for the premium rates of ETF products. The Z-score is used to determine whether an ETF is overvalued or undervalued relative to its historical premium rate distribution. This helps in identifying ETFs with potential arbitrage opportunities while also warning of potential pullback risks[4] - **Model Evaluation**: The model is effective in screening ETF products for arbitrage opportunities and provides a systematic approach to risk management[4] --- Model Backtesting Results 1. Industry Crowding Monitoring Model - **Key Observations**: - High crowding levels were observed in the military and building materials industries, while banking, computing, and media showed low crowding levels[3] - Significant changes in crowding levels were noted in the building decoration and real estate sectors[3] 2. Premium Rate Z-Score Model - **Key Observations**: - The model identified ETFs with potential arbitrage opportunities based on their premium rate Z-scores, though specific numerical results were not disclosed in the report[4] --- Quantitative Factors and Construction Methods No specific quantitative factors were explicitly mentioned in the report. --- Factor Backtesting Results No specific factor backtesting results were explicitly mentioned in the report. --- Additional Notes - The report primarily focuses on the construction and application of quantitative models for industry crowding monitoring and ETF product screening. It does not delve into individual quantitative factors or their backtesting results. - The models provide valuable insights for identifying market trends and potential investment opportunities, but specific numerical backtesting metrics (e.g., IR or Sharpe ratios) were not provided.

金 金融工程点评 [Table_Title] [Table_Message]2025-12-22 金工 ETF 点评：宽基 ETF 单日净流入 110.75 亿元；汽车、食饮、煤炭拥挤变幅较大 [Table_Author] 证券分析师：刘晓锋 电话：13401163428 E-MAIL：liuxf@tpyzq.com 执业资格证书编码：S1190522090001 证券分析师：孙弋轩 电话：18910596766 E-MAIL：sunyixuan@tpyzq.com 执业资格证书编码：S1190525080001 一、资金流向 三、ETF 产品关注信号 ◼ 根据溢价率 Z-score 模型搭建相关 ETF 产品筛选信号模型，通过滚动测算提 供存在潜在套利机会的标的，此外需警惕标的回调风险。 风险提示：本报告结论完全基于公开历史数据，建议关注的行业指数与 ETF 产品基于 构建的量化模型，仅供大家参考阅读，不构成任何投资建议。 融 工 程 点 评 太 平 洋 证 券 股 份 有 限 公 司 证 券 研 究 报 告 ETF [Table_Summary] 数据截止日：2025/12/19 二、行业拥挤度监测 ◼ ...

Group 1 - The market sentiment score has slightly decreased to 1.1 as of December 21, down from 1.35 the previous week, indicating a neutral outlook despite a recent rebound on Friday [1][6] - The overall sentiment index has shown significant improvement this week, with signs of a rebound in market trading activity [1][6] - The price-volume consistency indicator has improved, suggesting a better correlation between capital attention and stock price increases, although the risk appetite remains insufficient as indicated by the declining proportion of the STAR 50 index's trading volume [1][9] Group 2 - The total trading volume for the entire A-share market decreased by 9.86% week-on-week, with an average daily trading volume of 17,604.84 billion yuan, reflecting a decline in market activity compared to the previous week [1][12] - The short-term scores for industries such as beauty care, pharmaceuticals, non-bank financials, agriculture, and retail have shown upward trends, with the communication sector having the highest short-term score of 79.66 [1][33] - The correlation between trading congestion and weekly price changes is strong, with high congestion sectors like retail and light manufacturing leading in gains, while sectors with lower congestion such as power equipment and computers lag behind [1][38] Group 3 - The current model indicates a preference for small-cap and growth styles, with the 5-day RSI showing a decline relative to the 20-day RSI, suggesting potential weakening of signals [1][42] - The financing balance ratio continues to rise, reaching a new high for the phase, indicating increased risk appetite and active capital utilization in the market [1][22] - The main capital inflow has broken through the fluctuation range, reflecting a stronger willingness of institutional funds to enter the market, which supports a bullish momentum [1][28]

2025 年 12 月 22 日 市场情绪细分指标出现修复、改善 ——量化择时周报 20251221 相关研究 证券分析师 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 - ⚫ 市场情绪得分周内继续回落：截至 12 月 21 日，市场情绪指标得分为 1.1，较上周五的 1.35 小幅降低，但周五情绪得分出现回升，从情绪角度来看观点偏中性。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周内出现较明显改善，市场交易活跃度出 现反转回升迹象。 ⚫ 情绪出现修复改善，指标分化仍存：本周价量一致性指标较上周出现一定改善，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，情绪端边际回暖；科创 50 相对全 A 成交占比仍处下行通道，风险偏好修复 ...

报告导读： 从技术面来看，情绪模型信号依旧处于弱势震荡状态；与此同时，均线强弱指 数同样处于震荡区间。因此，我们认为，市场短期震荡格局较难被打破。 下周（ 20251222-20251226 ，后文同）市场观点： 市场短期震荡格局较难被打破。 从量化指标上看，基于沪深 300 指数的流动性冲击指标周五为 0.41 ，低于前一周（ 0.51 ），意味着当前市场的流动性高于过去一年平均水平 0.41 倍标准差。上证 50ETF 期权成交量的 PUT-CALL 比率震荡下降，周五为 0.83 ，低于前一周（ 1.08 ），投资者对上证 50ETF 短期走势谨慎程度下降。上证综指和 Wind 全 A 五日平均换手率分别为 1.05% 和 1.60% ，处于 2005 年以来的 68.85% 和 73.75% 分位点，交易活跃度有所下降。从宏观因子上看，上周人民币汇率震荡，在岸和离岸汇率周涨幅分别为 0.2% 、 0.28% 。事件驱动上， 1. 上周美股市场出现震荡。道琼斯工业指数、标普 500 指数和纳斯达克指数周收益率分别为 -0.67% 、 0.1% 、 0.48% 。根据 Wind ，美国 11 月非农就业人 ...

量化择时和拥挤度预警周报（20251221） [Table_Authors] 郑雅斌(分析师) 市场短期震荡格局较难被打破 本报告导读： 从技术面来看，情绪模型信号依旧处于弱势震荡状态；与此同时，均线强弱指数同 样处于震荡区间。因此，我们认为，市场短期震荡格局较难被打破。 投资要点： 金 融 工 程 周 报 证 券 研 究 报 告 | [Table_Summary] 下周（20251222-20251226，后文同）市场观点：市场短期震荡格局 | | --- | | 较难被打破。从量化指标上看，基于沪深 300 指数的流动性冲击指 | | 标周五为 0.41，低于前一周（0.51），意味着当前市场的流动性高于 | | 过去一年平均水平 倍标准差。上证 期权成交量的 0.41 50ETF PUT | | CALL 比率震荡下降，周五为 0.83，低于前一周（1.08），投资者对 | | 上证 50ETF 短期走势谨慎程度下降。上证综指和 Wind 全 A 五日平 | | 均换手率分别为 1.05%和 1.60%，处于 年以来的 68.85%和 2005 | | 73.75%分位点，交易活跃度有所下降。从宏观因子 ...

- The report introduces an **industry crowding monitoring model** to track the crowding levels of Shenwan primary industry indices on a daily basis. The model identifies industries with high crowding levels (e.g., agriculture, military, building materials) and low crowding levels (e.g., computers, home appliances, media) based on the previous trading day's data. It also highlights significant changes in crowding levels for industries such as automobiles, petrochemicals, and social services[3] - A **Z-score premium model** is constructed to screen ETF products for potential arbitrage opportunities. The model uses rolling calculations to identify ETFs with significant deviations in premium rates, which may indicate arbitrage opportunities or potential risks of price corrections[4] - The report provides detailed data on **ETF fund flows**, categorizing them into broad-based ETFs, industry-themed ETFs, style-strategy ETFs, and cross-border ETFs. For example, broad-based ETFs saw a net inflow of 60.55 billion yuan in a single day, with the top inflows being the CSI A500 ETF (+10.42 billion yuan), CSI A500 ETF South (+10.23 billion yuan), and STAR 50 ETF (+8.62 billion yuan)[5] - The report highlights **industry crowding levels** over the past 30 trading days, presenting a heatmap that shows the relative crowding levels of various industries. For instance, industries like public utilities, agriculture, and military defense exhibit high crowding levels, while industries like computers and media show relatively low levels[9] - The report identifies **key ETF trading signals**, recommending attention to specific ETFs such as the CSI 1000 Enhanced ETF, Chuangzhongpan 88 ETF, and Medical Device ETF based on their potential for investment opportunities[11]