过去一周，市场风格出现显著切换。偏防守的价值因子以及代表交易博弈的量价类因子（波动率、技术）表现强势。 而此前表现优异的成长因子和一致预期因子则有所回撤。这反映出在震荡环境下，资金暂时脱离了业绩驱逻辑，转而 寻求低估值防御。展望未来一周，考虑到年末资金避险情绪，我们预期价值因子的防御属性仍将受捧，同时量价类因 子有望延续活跃态势，而成长风格短期或需等待拥挤度消化后的企稳。 以上结果通过历史数据统计、建模和测算完成，在政策、市场环境发生变化时模型存在失效的风险。 过去一周，国内主要市场指数平稳，其中上证 50、沪深 300、中证 500 和中证 1000 涨跌幅分别为 0.61%、-0.15%、 0.01%和-0.56%。 微盘股指标监控：综合来看，当前轮动模型由于微盘股滚动 20 天斜率收负，茅指数为正斜率，当前轮动模型发出切 换至茅指数信号，中期配置茅指数的预期能有更高相对收益。从中期微盘股择时角度来看，目前风控信号还没触发， 但能看到波动率拥挤率正在快速上行，风险有明显聚集。对于持有微盘板块投资者建议做好风险控制，以及密切跟踪 相对净值、动量及中期风险指标的动态。 过去一周，政策端进入了高频落地的执行期， ...

丨证券研究报告丨 金融工程丨点评报告 [Table_Title] 2025 年有效选股因子 报告要点 [Table_Summary] 本文主要回顾 2025 年选股因子在全市场的表现情况。 分析师及联系人 [Table_Author] 郑起 覃川桃 SAC：S0490520060001 SAC：S0490513030001 SFC：BUT353 请阅读最后评级说明和重要声明 %% %% %% %% research.95579.com 1 [Table_Title2] 2025 年有效选股因子 [Table_Summary2] 2025 年因子选股全市场范围内表现较好 收益能力上看，2025 年全市场范围内选股以成交笔数、流动性、拥挤度、价格稳定和反转为代 表的量价因子选股能力更强，成长因子有一定盈利能力，但在失效区间回撤较大。 收益来源上看，分为量价和成长两大类，量价内又以价格稳定、反转为两类主要代表。 2025 年因子收益有着较为明显的区间特征 2025 年 8 月（不含）以前是所有因子的主要收益区间，8 月为因子的第一次分化，表现为量价 因子（除反转）回撤，成长因子收益正常，9 月为所有因子回撤区间，1 ...

成长因子收益边际回升 金融工程周报 基金市场回顾： 权益市场风格 2025年12月15日 周度报告 操作评级 中信五风格-成长★☆☆ 金融工程组 张婧婕 Z0022617 010-58747784 gtaxinstitute@essence.com.cn 本报告版权属于国投期货有限公司 1 不可作为投资依据，转载请注明出处 截至2025/12/12当周，通联全A（沪深京）、中证综合债与南华 商品指数周度涨跌幅分别为0.26%、0.11%、-1.21% 。 公募基金市场方面，近一周纯债策略收益小幅回升；权益策略中 普通股票策略收益表现相对偏强，贵金属ETF收益继续走高，白 银期货ETF上涨9.27%，能源化工与豆粕ETF有所回撤。 中信五风格方面，上周成长风格收涨，其余风格收跌；风格轮动 图显示成长与金融风格相对强弱边际提升，稳定风格相对强弱动 量显著走低。公募基金池方面，近一周金融风格基金平均超额表 现相对偏弱，从基金风格系数走势来看市场对周期风格偏移度有 所下降；本周拥挤度指标相比上周小幅回升，当前周期风格基金 拥挤度上升至近一年以来偏高分位区间，而金融与消费风格拥挤 度位于近一年偏低分位区间。 中性策略方 ...

Core Viewpoint - The article discusses the shift in investment styles driven by fundamental factors, indicating a transition from growth to value investing as economic indicators improve and market trends are confirmed [3][5][67]. Group 1: Factor Performance - Growth factors have shown strong performance this year, with cumulative returns of 37.93% in the CSI 300 index, while momentum and dividend factors have underperformed [8][11]. - Low volatility factors have performed poorly in the CSI 300, reflecting the high volatility characteristics of the market this year [10][12]. - The performance of long-term momentum factors has been weak, indicating rapid rotation among industries and sectors [10][14]. Group 2: Macro Quantitative Framework - The macroeconomic cycle has been switching more frequently in the past three years compared to before 2020, with economic indicators suggesting a downturn in the first half of 2025 followed by a recovery towards the end of the year [32][38]. - The liquidity indicators have shown a weak overall trend, with market trading rates rising, indicating a correction in liquidity expected in the second half of 2025 [40][46]. - Credit indicators have shown a preference for expansion in the first half of 2025, aligning with social financing, but are expected to shift towards contraction in the second half [53][48]. Group 3: 2026 Equity Quantitative Outlook - The investment strategy for 2026 is expected to be driven by fundamental factors, with a focus on value before growth as economic conditions improve [5][54]. - The market is currently in a consolidation phase, with a trend confirmation expected to benefit value and long-term momentum factors, while growth factors are anticipated to perform better in a volatile environment [75][80]. - Industry rotation speed has slowed down, indicating potential for the formation of main lines in the market, with a focus on industries with low crowding and emerging trends [82][85].

========= Content: --------- <doc id='2'>任瞳 S1090519080004 rentong@cmschina.com.cn 刘凯 S1090524120001 liukai11@ cmschina.com.cn 杨航 S1090523010004 yanghang4@cmschina.com.cn 证券研究报告 | 金融工程 2025 年 11 月 15 日 专题报告 ❑ 成长因子表现：以招商证券量化团队因子库中的成长因子为例，对其有效 性进行测试。综合来看，标准化预期外盈利因子（SUE）表现较为优异。 除此以外，单季度 ROE 同比因子表现同样较优。相关性方面，净利润同 比加速度因子、标准化预期外收入因子与其他因子的相关性相对较低。 ❑ 假设已知下一期上市公司的净利润增速，从而构建净利润增长的投资组 合，先验测算该组合的业绩表现。已知未来成长确定性的未来成长组合能 够稳定的战胜历史增长组合，2010 年以来每年均能战胜历史成长组合。 ❑ 通过上市公司业绩增长的转移矩阵可以发现，当前的业绩高增速仅能部分 反映公司当前的成长性，而未来的成长性仍有较大的不确定性。按照双变 量分组的方法，我们发现部分指标能够提升对下一期业绩增速的预期，包 括单季度 ROE、单季度 ROE 斜率、单季度净利润同比增速斜率、SUE、 单季度营业收入同比增速、单季度经营性现金流净额。 ❑ 综合筛选出的基本面指标构建成长预期组合，区间年化收益接近 26%，夏 普比率 0.95，卡玛比率 0.59。相对比中证 500 指数，超额年化收益接近 19%，从 2012 年以来每年均能战胜中证 500 指数。自 2012 年以来该组合 平均持仓 175 只，平均单边换手约为 32%。 ❑ 进一步地，探究什么样的量价指标可以进一步提升成长预期组合表现。1） 盈余公告次日开盘超额较高的股票组合，其业绩表现是受到市场认可的， 未来业绩表现更好；2）换手率均线标准差较小的组合表现较为优异；3） Amihud 非流动性大的组合业绩表现则较为亮眼。 ❑ 运用上述指标构建技术面精选成长预期组合，回测区间年化收益超过 40%，夏普比率（1.45）与卡玛比率（1.07）均超过 1。相比中证 500 指 数，组合超额年化收益高达 33%。从 2012 年以来每年均能战胜中证 500 指数，且每年超额均在 10%以上。组合平均单边换手约为 67%，各期平均 市值为 113 亿元。</doc> <doc id='22'>资料来源：招商证券、Wind 我们以招商证券量化团队因子库中的成长因子为例，对其有效性进行测试。 表 1 中我们列出了因子回测的框架。回测区间为 2010 年 1 月 1 日至 2025 年 6 月 30 日，每个月最后一个交易日进行调仓，股票权重为等权方式，股票样本池 为全市场，剔除上市不足 180 天、停牌、涨跌停、ST 股票。如无特殊说明，本 文的因子测试均采用此因子回测框架。</doc> <doc id='23'>表 1：因子回测框架 | 项目 | 内容 | | --- | --- | | 回测区间 | 2010.1.1-2025.6.30 | | 调仓频率 | 月度 | | 调仓日 | 最后一个交易日 | | 样本空间 | 全市场 | | 股票筛选 | 剔除上市不足 天、停牌、涨停和 股票 180 ST | | 市值行业中性化 是 | | | IC 测试 IC | 指标为因子值与下一期股票收益率的秩相关系数 | | | 在每个月最后一个交易日后，根据因子值大小将样本空间内的股 | | 分组测试 | 票分成 10 组，每组组内进行等权配置计算各组历史表现。多头 | | | 组为因子值最大的组，空头组为因子值最小的组 | | 基准 | 样本空间内股票的等权组合 | | 交易费率 | 暂不考虑交易费率 | | 资料来源：Wind 资讯、招商证券 | | 如图 4 所示，招商证券量化团队因子库中涵盖单季度净利润同比增速、标准 化预期化盈利、单季度 ROE 同比、净利润增速加速度等指标。除此以外，还有 许多成长因子，正如我们上文所介绍的，但是由于该部分并不是本文研究的重点， 这里我们暂且不做一一展示，感兴趣的投资者欢迎与我们做进一步的交流。</doc> <doc id='24'>图 4：招商证券量化团队因子库成长因子概述 | 因子名称 | 构造方式 | 参考方向 | | --- | --- | --- | | 单李废净利润同比增速 | 单李度归母净利润同比增长率 | 正向 | | 单李度营业收入同比增速 | 单季度营业收入同比增长率 | 正向 | | 单季度营业利润同比增速 | 单率度营业利润同比增长率 | 正向 | | 标准化预期外盈利 | (当前李度归母净利润 -(去年同期单度归母净利润+过去 8个 李度单率归母净利润同比增长均值) / / 过去 8个季度的单 | 正向 | | | 李度归母净利润同比增长值的标准差 | | | 标准化预期外收入 | (当前李度营业收入 - (去年同期单度营业收入+过去 8个 李度单率度营业收入同比增长均值)/过去8个季度的单 | 正向 | | | 李营业收入同比增长值的标准差 | | | 单季度ROE同比 | ROE单季度同比变化 | 正向 | | 单季度ROA同比 | ROA单季度同比变化 | 正向 | | 净利润同比加速度 | 单率度营业利润同比增速的一阶差分 | 正向 | | 净利润TTM环比增速 | 净利润TTM环比增长率 | 正向 | 资料来源：招商证券 表 2 我们具体展示了净利润 TTM 环比增速因子的回测表现。净利润 TTM 环比增速因子在回测区间内的 IC 均值为 2.91%，ICIR 为 0.57，t 值为 7.8。从 分组测试来看，该因子在全 A 市场中分 10 组年化收益单调性一般，但多头组收 益最高，年化收益 15.14%，年化超额 6.28%。</doc> <doc id='25'>表 2：净利润 TTM 环比增速因子回测数据展示 | Rank_IC | Rank_IC 均值 | 胜率（%） | IC_IR | t 统计量 | 最大值 | 最小值 | | --- | --- | --- | --- | --- | --- | --- | | 数据 | 2.91% | 71.51 | 0.57 | 7.80 | 16.79% | -12.50% | | 多空组合 | 年化收益 | 多空卡玛 | 多头年化收益 | 多头年化超额 | 多头夏普 | 多头双边换手 | | | 10.28% | 0.60 | 15.14% | 6.28% | 0.54 | 5.46 | 资料来源：Wind，招商证券；2010/1/1-2025/6/30</doc> <doc id='30'>资料来源：Wind，招商证券；2010/1/1-2025/6/30 资料来源：Wind，招商证券；2010/1/1-2025/6/30 受篇幅限制，其他成长因子的因子测试结果我们就不一一列示，图 7 中我们 统一列出了其他成长因子的表现。综合来看，标准化预期外盈利因子（SUE） 表现较为优异。SUE 因子在回测区间内的 IC 均值为 3.06%，t 值为 6.65，较为 显著；多头组超额年化

Investment Strategy Overview - The report emphasizes a fundamental-driven style factor switch, awaiting confirmation of trend movements for 2026 [1][4][8] Factor Performance - Growth factors have shown strong performance, while low volatility and momentum factors have retreated, indicating a rapid rotation among market sectors and themes this year [4][10][12] - Year-to-date performance of various factors in different indices shows growth at 37.93% in CSI 300, while low volatility and liquidity factors have negative returns [10][12] Macro Quantitative Framework - The macroeconomic cycle has shifted more frequently in the past three years, with leading indicators suggesting a downturn in the first half of 2025, followed by a recovery signal towards the end of the year [4][38][43] - The liquidity indicators have shown a weak overall trend, with market trading rates rising, indicating a correction in liquidity for the second half of 2025 [50][54][60] - Credit indicators have shown a preference for expansion in the first half of 2025, transitioning to contraction by November [65][66] 2026 Equity Quantitative Outlook - The report anticipates a fundamental-driven style switch, with a focus on economic fundamentals becoming the key driver, transitioning from liquidity concerns to economic and inflation factors [4][86][91] - Market trends indicate a shift to a consolidation phase since August, with an increasing probability of trend confirmation from late October [92][97] - Emotional indicators have shown a supportive trend since July, with overall sentiment remaining warm and moderate [102][105] Industry Rotation and Focus - The speed of industry rotation has slowed down in 2025, with potential for a main trend to form, particularly in sectors with lower crowding and emerging trends [106][112] - Key sectors to watch include electronics and computing, which have shown lower crowding and are in a trend initiation phase [113][116]

Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - In a unilateral rising market, the momentum factor can amplify returns by concentrating on strong-performing stocks, resulting in significant excess returns. When combined with the growth factor, it can capture trends while adding a fundamental safety net to the investment portfolio, making it suitable for medium-risk preference investors. The "growth + momentum" dual-factor investment logic is systematically implemented in the ChiNext Momentum Growth Index and its linked product, the Huaxia ChiNext Growth ETF [1][11]. Summary According to the Directory Product Fund - Huaxia ChiNext Growth ETF (159967) - **Investment Attributes and Returns**: The Huaxia ChiNext Growth ETF closely tracks the ChiNext Momentum Growth Index, serving as a passive investment tool for high-growth and strong-momentum portfolios on the ChiNext board. Since its establishment in June 2019, it has achieved a cumulative return of 113.97%, significantly outperforming broad-based indices such as the CSI 300. In the rising market since May 2025, it has shown outstanding performance with a six-month return of 46.51%, demonstrating its offensive nature in a bull market. However, it has high volatility, with a three-year return of 1.10% significantly trailing the CSI 300's 22.70% [2][11][14]. - **Fund Manager and Fund Company**: The fund is managed by Rong Ying, who manages 21 funds with a total scale of approximately 138.292 billion yuan. As of October 22, 2025, the Huaxia ChiNext Growth ETF has a scale of 30.39 billion yuan. Huaxia Fund, the fund manager, has a total public fund management scale of 2041.571 billion yuan as of October 22, 2025, with 114 ETFs worth 896.351 billion yuan and 13 money market funds worth 774.607 billion yuan, consolidating its leading position in public offering index investment [15][19]. Tracking Index - ChiNext Momentum Growth Index (399296.SZ) - **Index Composition and Calculation**: The index is compiled by Guozheng Index Company, selecting 50 listed company securities with good growth ability and obvious momentum effects from the ChiNext board. It uses a Paasche weighting method with a single stock weight cap of 15% and adjusts samples and weights quarterly. The sample selection involves screening stocks based on liquidity and then using growth and momentum factors to calculate scores and determine the final 50 stocks [20][21][27]. - **Performance and Returns**: Since its release in 2019, the index has achieved a cumulative return of 157.46%, significantly higher than mainstream broad-based indices. In 2020, it had a return of 97.14%, showing high growth elasticity. In the period from May 1 to October 22, 2025, it had a cumulative return of 40.24%, also outperforming major broad-based indices [4][31][35]. - **Weighted Stocks and Industry Distribution**: The top ten component stocks account for 76.63% of the total weight, with high concentration in the technology growth sector. The top four industries (communications, power equipment, electronics, and non-bank finance) account for nearly 80% of the total weight, highlighting the index's focus on the technology growth sector [3][37][52]. - **Valuation and Earnings**: As of October 22, 2025, the index's PE TTM is 40.83 times, slightly lower than the historical median of 44.73 times, indicating a reasonable valuation. From 2019 to 2024, the index's component stocks showed strong growth in revenue and net profit, and it is expected to maintain double-digit growth from 2025 to 2026 [61][64]. - **Sources of High Growth and Excess Returns**: The index's high growth elasticity and excess returns stem from its precise sample screening, factor tilt weighting, high-growth and high-elasticity asset characteristics, and regular dynamic adjustments [71]. Sample Space - ChiNext Composite Index - **Market Value and Industry Structure**: The index shows a pattern where small-cap stocks dominate in number and large-cap stocks dominate in weight. The industry structure has been evolving towards power equipment, electronics, and communications, with the power equipment industry's weight increasing from 13.89% in 2020 to 23.46% in 2025, and the communications industry's weight rising from 2.90% to 9.69% [76][78]. - **Growth and Profitability**: The index has shown strong growth momentum in revenue, with its growth rate consistently higher than that of major market indices from 2020 to 2024. Its average net profit growth rate from 2020 to 2024 was 11.73%, significantly higher than that of mainstream broad-based indices. The average ROE in the past five years was 6.86%, indicating relatively good profitability [79][81][83]. - **Industry Focus and New Productivity Layout**: The index's industry structure focuses on technology growth, with a low financial sector weight and high weights in emerging technology fields such as communications and computers, reflecting the trend of new productivity development and industrial upgrading [88].

Report Industry Investment Rating - The operation rating for CITIC's five - style stability is ★☆☆, indicating a bullish bias but with limited operability in the market [4] Core Viewpoints - In the week ending November 7, 2025, the weekly returns of Tonglian All - A (Shanghai, Shenzhen, Beijing), ChinaBond Composite Bond, and Nanhua Commodity Index were 0.63%, - 0.01%, and - 0.47% respectively. In the public fund market, convertible bond products performed well, the common stock strategy index declined slightly, neutral strategy products mostly rose, non - ferrous metal ETFs weakened slightly, and soybean meal ETFs had better returns. Among CITIC's five styles, only the consumer style declined last Friday, while the stable and cyclical styles were strong. The style rotation chart showed that the relative strength of the growth style decreased, and the relative strength momentum of the financial style rebounded marginally. The average returns of various style funds in the public fund pool underperformed the benchmark index. The market's deviation towards the financial style decreased. The congestion index dropped, with the growth style congestion falling to the medium - percentile range of the past year. In the neutral strategy, the contract basis weakened slightly last week, with the current IH basis close to 1 standard deviation below the three - month average. The average premium rates of IC and IM corresponding index ETFs rebounded to the medium - percentile range of the past three months. The profit factor had a good return performance in the past week, with a weekly excess return of 0.97%, and the excess of the growth factor was significantly compressed. The win - rate of the residual momentum factor decreased, but the factor itself strengthened. The cross - section rotation speed of factors rebounded slightly this week, currently at the medium - percentile range of the past year. According to the latest scoring results of the style timing model, the financial style declined marginally this week, the consumer style strengthened slightly, and the current signal favored the stable style. The return of the style timing strategy last week was 1.85%, with an excess return of 0.97% compared to the benchmark balanced allocation [4] Summary by Relevant Catalogs Fund Market Review - The weekly returns of Tonglian All - A (Shanghai, Shenzhen, Beijing), ChinaBond Composite Bond, and Nanhua Commodity Index were 0.63%, - 0.01%, and - 0.47% respectively [4] - In the public fund market, convertible bond products performed well, the common stock strategy index declined slightly, neutral strategy products mostly rose, non - ferrous metal ETFs weakened slightly, and soybean meal ETFs had better returns [4] Equity Market Style - Among CITIC's five styles, only the consumer style declined last Friday, while the stable and cyclical styles were strong. The style rotation chart showed that the relative strength of the growth style decreased, and the relative strength momentum of the financial style rebounded marginally [4] - The average returns of various style funds in the public fund pool underperformed the benchmark index. The market's deviation towards the financial style decreased. The congestion index dropped, with the growth style congestion falling to the medium - percentile range of the past year [4] Neutral Strategy - The contract basis weakened slightly last week, with the current IH basis close to 1 standard deviation below the three - month average. The average premium rates of IC and IM corresponding index ETFs rebounded to the medium - percentile range of the past three months [4] Barra Factor - The profit factor had a good return performance in the past week, with a weekly excess return of 0.97%, and the excess of the growth factor was significantly compressed. The win - rate of the residual momentum factor decreased, but the factor itself strengthened. The cross - section rotation speed of factors rebounded slightly this week, currently at the medium - percentile range of the past year [4] Style Timing Model - According to the latest scoring results of the style timing model, the financial style declined marginally this week, the consumer style strengthened slightly, and the current signal favored the stable style. The return of the style timing strategy last week was 1.85%, with an excess return of 0.97% compared to the benchmark balanced allocation [4]

Core Insights - The article discusses the integration of macro quantification and factor momentum to identify resonant factors for investment strategies, emphasizing the importance of economic, liquidity, and credit indicators in shaping market expectations [1][3]. Group 1: Factor Scores and Market Indicators - The macroeconomic indicators show signs of recovery, with economic growth expected to improve, while liquidity is slightly weak and credit conditions are tightening [3][4]. - Value factors have seen a significant increase in scores, becoming resonant factors in the CSI 300 index, while growth factors have declined [4][6]. - The article presents a table of factor scores across different indices, indicating a preference for value and low volatility factors in the current market environment [4]. Group 2: Economic Outlook and Leading Indicators - The economic leading indicators model suggests that the economy is in a rising cycle since September 2025, with a slight upward trend expected in the coming months [6][9]. - Specific indicators such as PMI and fixed asset investment are analyzed, showing a mixed outlook with some indicators in a rising phase while others are nearing a peak [11][12]. - The article highlights the importance of monitoring leading indicators to anticipate future economic cycles and potential downturns [9][10]. Group 3: Liquidity and Credit Conditions - The liquidity environment is assessed as slightly loose despite some tightening in interest rates, with a focus on the net monetary supply and excess reserve rates [12][16]. - Credit indicators show a mixed picture, with overall credit volume and structure remaining low, but some signs of recovery are noted [17][18]. - The article suggests a cautious approach to credit-sensitive investments due to the ongoing tightening in credit conditions [17]. Group 4: Asset Allocation and Market Focus - The asset allocation strategy is adjusted to reflect a neutral to positive stance on A-shares, while reducing exposure to gold and bonds due to changing market dynamics [18]. - The focus on PPI and liquidity as key market drivers indicates a shift in investor sentiment towards these macroeconomic variables [19]. - The article emphasizes the importance of selecting industries that are sensitive to economic changes but less affected by credit conditions, with a preference for sectors like utilities and coal [21].

Core Viewpoint - The article discusses the decline of the "dividend low volatility" investment style in the market and explores whether it has become ineffective, while also investigating the potential for creating a new "low volatility miracle" using the Alice AI index strategy platform [2]. Group 1: Strategy Development and Backtesting - The company utilized the Alice AI platform to generate a strategy based on dividend yield and low volatility indicators, selecting the top 100 stocks from the CSI 800 index with quarterly rebalancing [5]. - Backtesting results showed that the CSI 800 Enhanced strategy had an annualized volatility of 13.27% and a maximum drawdown of 8.90% over the past year, indicating a steady upward trend in excess returns from 2021 to 2024, but a downturn began in August 2024 [7]. Group 2: Performance Analysis - A scenario analysis revealed that the "dividend low volatility" strategy performed well in value style periods but lagged in growth style periods, particularly in 2023 when growth dominated the market [10]. - The analysis indicated that from November 2020 to August 2021, the growth style had an excess return of -8.37%, while the value style from August 2021 to April 2023 had an excess return of 32.77% [10]. Group 3: Strategy Evolution - The company sought to evolve the strategy by incorporating growth factors such as TTM revenue growth rate and TTM net profit growth rate, resulting in improved performance and alignment with the current market environment [11][13]. - The revised "dividend low volatility + growth" strategy showed significant improvement in total returns starting in 2025, with the excess return curve rising again [21]. Group 4: AI Integration and Future Outlook - The article emphasizes the efficiency of the Alice AI platform in facilitating the entire strategy research process, from generation to backtesting and optimization, without the need for complex coding [23]. - The company suggests that the decline of the dividend low volatility style may simply be a phase of style rotation, and with Alice, there is an opportunity to actively reconstruct strategies and quickly validate them [26].