Core Viewpoint - The article discusses the recent market trends in A-shares, bonds, commodities, and overseas assets, highlighting the impact of the Central Economic Work Conference and the Federal Reserve's interest rate decisions on various sectors [2][3][25][37]. A-share Market - A-shares experienced a slight recovery with average daily trading volume exceeding 200 billion yuan, reversing a previous decline [2]. - The Shanghai Composite Index managed to fill the gap from November 21, but the market remains in a consolidation phase between the October high and November low [2]. - The communication, defense, and electronics sectors showed the highest gains, while coal, oil, and steel sectors faced declines [2][23]. Bond Market - The bond market showed signs of recovery with a balanced and slightly loose funding environment, leading to stronger performance in government bonds compared to credit bonds [2][28]. - The CPI rose by 0.7% year-on-year, marking a recent high, while PPI showed a positive month-on-month change, having minimal impact on the bond market [2][37]. - The Central Economic Work Conference indicated a commitment to maintaining necessary fiscal deficits and debt levels, alleviating previous concerns about special government bond issuance [2]. Commodity Market - COMEX gold reached a new high since November, driven by expectations of Federal Reserve rate cuts and ongoing global central bank purchases amid persistent geopolitical risks [3][34]. - The article emphasizes a bullish sentiment in the gold market, suggesting a clear long-term trend for gold investments due to global monetary expansion [8]. Overseas Market - U.S. stocks experienced high volatility at elevated levels, with small-cap stocks outperforming [3]. - The Federal Reserve's recent decision to cut rates by 25 basis points aligns with market expectations, and the overall fundamentals of the U.S. market remain robust despite high valuations [3][9]. - Investors are encouraged to consider diversified overseas investments through QDII funds, as the daily subscription limits continue to decrease [9]. Market Activity - The trading activity in the A-share market improved significantly, with notable increases in turnover rates for major indices like the CSI 300 and CSI 500 [14][15]. - The volatility of major indices such as the CSI 300 and CSI 500 has decreased compared to historical averages, indicating a more stable trading environment [19][22]. Industry Performance - The communication, defense, and electronics sectors led the weekly performance among the Shenwan first-level industries, with respective gains of 6.27%, 2.80%, and 2.63% [23][24]. - Conversely, the coal and oil sectors faced significant declines, reflecting broader market trends [23]. Key Events - The Central Economic Work Conference held on December 10-11 focused on summarizing 2025's economic work and planning for 2026, which is expected to influence market sentiment and investment strategies [25][30]. - The Federal Reserve's decision to lower interest rates and the release of inflation data are pivotal events that will shape market dynamics in the near term [37].

【导读】指增产品"工具化"崛起，公募指数增强迈入"产品矩阵"竞争新时代 2025年，指数增强基金迎来爆发式增长，无论是数量还是规模均超越过去三年的总和；近九成增强指数 型ETF实现正超额收益，部分产品业绩表现突出，展现出显著的"增强"效应；头部量化与非头部公司齐 发力，形成前所未有的"机构梯队入场潮"。 业内人士表示，公募指数增强业务逐渐从小众策略演进为核心工具型产品，基金公司加大力度打造体系 化产品矩阵，以匹配不同风险偏好投资者的多元化配置需求。 规模与业绩齐飞 数据显示，截至12月12日，今年以来新成立指增基金168只，合计募集规模达924.76亿元，数量和规模 均超过过去三年的总和。业绩方面，近九成增强指数型ETF实现正超额收益，年内最高超额收益达 22%。 对于指数增强基金大发展的主要原因，永赢基金指数与量化投资部总经理蔡路平表示，首先，市场环境 提供沃土。A股市场今年呈现明显的结构性分化特征，这为通过量化策略获取超额收益提供了有利环 境。今年中小盘风格表现亮眼，以中证500指数、中证1000指数、中证2000指数等中小盘宽基指数为基 准的增强产品更容易取得超额收益。 鲜明的产品矩阵 在指数增强基金大 ...

规模与业绩齐飞 Wind 数据显示，截至 12 月 12 日，今年以来新成立指增基金 168 只，合计募集规模达 924.76 亿元，数量和规模均超过过去三年的总和。业绩方面，近九成增强指数型 ETF 实现 正超额收益，年内最高超额收益达 22% 。 对于指数增强基金大发展的主要原因，永赢基金指数与量化投资部总经理蔡路平表示，首 先，市场环境提供沃土。 A 股市场今年呈现明显的结构性分化特征，这为通过量化策略获取 超额收益提供了有利环境。今年中小盘风格表现亮眼，以中证 500 指数、中证 1000 指数、 中证 2000 指数等中小盘宽基指数为基准的增强产品更容易取得超额收益。 其次，量化投资技术发展与新指数提供助力。随着量化模型和 AI 大模型的快速发展，基金公 司能够构建更综合全面的选股模型，提供不同类型的 Alpha 收益来源，捕捉多元的市场投资 机会。同时，稳健可靠的全流程风险控制也提升了超额收益的稳定性。 最后，投资者认知与渠道发力。随着市场教育和产品业绩的持续验证，投资者对指数增强产 品的认知从过去的 " 可选项 " 变成 " 必要项 " 。头部代销平台逐步将业务重点转向指数增 强基金，推出 " ...

近日，中国证券报记者专访了大岩资本副总裁朱星曈，试图探寻这份"温度"的源头与内涵。在朱星曈看 来，真正的量化远不止于模型与算力——它更关乎人的凝聚、风控的执守与进化的愿望。 十余年的打磨中，大岩资本沉淀出一套有"温度"的量化管理体系：以伙伴文化凝结长期事业共同体，以 极致风控锚定行稳致远之舵，并以多维均衡的迭代节奏从容穿越周期。沿着这样的逻辑，大岩资本的路 径清晰而坚定：既要成为市场的领跑者，更要锻造一家文化深厚、基业长青的量化"百年老店"。 量化投资的舞台常被视为算力与算法的对决，数据流中闪烁的是无止境的竞争与迭代，激烈的角逐往往 让外界只看到冰冷的代码、运转的服务器与跳动的净值曲线。然而，当外界目光投向大岩资本时，一种 不同于行业刻板印象的"温度"逐渐浮现。 以人为本 锻造"百年老店" 而用，根据特长及兴趣制定发展方向，从而形成了强大的向心力。这不仅帮助大岩资本留住了资深骨 干，也吸引了大量顶尖院校的应届生的加入，为公司迭代注入了宝贵的活力。公司总经理兼首席投资官 黄铂被同事们亲切地称为"铂哥"，他每周会投入大量时间与投研人员进行一对一的深入交流，焦点不仅 在于项目进度，更在于倾听研究中的灵感火花与潜在瓶 ...

Core Viewpoint - The report provides a comprehensive analysis of market performance, highlighting the performance of various factors and strategies across different stock pools, indicating potential investment opportunities and trends in the market [4][5][6][7][8][9][10]. Factor Performance - In the large-cap factor performance for the week of December 8-12, 2025, the size factor, beta factor, and non-linear market cap factor achieved positive returns of 1.18%, 0.91%, and 0.82% respectively, while the BP factor and liquidity factor recorded negative returns of -0.55% and -0.38% [4]. - In the CSI 300 stock pool, the best-performing factors included total asset growth rate (2.05%), quarterly ROA (1.71%), and turnover rate relative volatility (1.59%), while the worst-performing factors were logarithmic market cap (-1.00%), downside volatility ratio (-1.10%), and large net inflow (-1.14%) [5]. - In the CSI 500 stock pool, the top factors were quarterly EPS (1.61%), total asset growth rate (1.39%), and momentum spring factor (1.22%), with the worst being price-to-sales ratio TTM inverse (-2.49%), downside volatility ratio (-2.55%), and price-to-book ratio (-3.06%) [5]. - In the liquidity 1500 stock pool, the best factors were total asset growth rate (2.25%), quarterly revenue growth rate (2.05%), and quarterly ROA year-on-year (1.92%), while the worst were price-to-earnings ratio (-0.90%), downside volatility ratio (-0.95%), and price-to-book ratio (-0.97%) [5]. Industry Factor Performance - The net asset growth rate factor performed well in the telecommunications, comprehensive, and coal industries, while the net profit growth rate factor excelled in the telecommunications sector [6]. - The earnings per share factor showed strong performance in the telecommunications industry, and the residual volatility factor performed well in telecommunications and commercial trade sectors [6]. Strategy Performance - The PB-ROE-50 combination achieved significant excess returns across stock pools, with the CSI 500 stock pool gaining an excess return of 0.30%, the CSI 800 stock pool gaining 1.60%, and the overall market stock pool gaining 1.59% [7]. - Public fund research selection strategies and private fund research tracking strategies both yielded positive excess returns, with public fund strategies outperforming the CSI 800 by 1.79% and private fund strategies outperforming by 2.77% [8]. - The block trading combination experienced a relative excess return drawdown against the CSI All Index, with an excess return of -0.95% [9]. - The directed issuance combination also faced a relative excess return drawdown against the CSI All Index, with an excess return of -1.50% [10].

作为知名外资私募锐联景淳海外母公司锐联的创始人，许仲翔博士在量化投资与资产配置领域一直扮演 着连接东西方市场的桥梁角色。从联合发明基本面量化策略(RAFI)，到带领锐联深耕中国市场，再到8 年前锐联向华夏基金等公募机构进行策略授权，这位兼具深厚学术背景与全球资产管理经验的学者型投 资人，其观点备受市场关注。近日，许仲翔接受了中国证券报记者的专访，围绕公司的策略实践、2026 年市场前瞻及行业变革等议题，发表了自己的看法。 多元资产策略获市场认可 回顾2025年，许仲翔将公司最大的突破归结于核心策略——量化多元资产配置策略获得了市场的理解与 接纳。"过去一两年，这类配置型产品因其复杂性，投资者接受需要一个过程。"许仲翔坦言，市场环境 的变化成为了理念普及的催化剂。利率持续低位徘徊、传统"刚兑"理财消失、股市起伏震荡，这些因素 让投资者意识到，没有任何单一资产品种能持续获得收益。 "当市场处于单边趋势时，大家会追逐简单的贝塔；当有保底产品时，保守者也无需他求。但现在，我 们进入了一个'真正的大资管时代'。"许仲翔说，市场的波动不断告诉投资者：因为难以精准预测每一 类资产的涨跌，因此必须接受"通过科学配置将不同资产 ...

量化投资的舞台常被视为算力与算法的对决，数据流中闪烁的是无止境的竞争与迭代，激烈的角逐往往 让外界只看到冰冷的代码、运转的服务器与跳动的净值曲线。然而，当外界目光投向大岩资本时，一种 不同于行业刻板印象的"温度"逐渐浮现。 □本报记者 王宇露 近日，中国证券报记者专访了大岩资本副总裁朱星曈，试图探寻这份"温度"的源头与内涵。在朱星曈看 来，真正的量化远不止于模型与算力——它更关乎人的凝聚、风控的执守与进化的愿望。 十余年的打磨中，大岩资本沉淀出一套有"温度"的量化管理体系：以伙伴文化凝结长期事业共同体，以 极致风控锚定行稳致远之舵，并以多维均衡的迭代节奏从容穿越周期。沿着这样的逻辑，大岩资本的路 径清晰而坚定：既要成为市场的领跑者，更要锻造一家文化深厚、基业长青的量化"百年老店"。 以人为本 锻造"百年老店" 走进大岩资本的办公室，"石头"元素随处可寻，这不仅是品牌的视觉印记，更寓意着"翻遍每一块石 头"的极致探索。然而在朱星曈眼中，比挖掘数据因子更重要的，是挖掘并凝聚"人"的价值。 她表示："我们更愿称大岩资本人为事业伙伴，而非雇员。"这句话并非泛泛而谈，而是深深融入公司血 脉的管理逻辑。一套清晰且温暖的体 ...

Core Viewpoint - The private equity fund management industry in China is undergoing significant changes, with a notable number of firms exiting the market due to stricter regulations and a focus on compliance, leading to a more stable industry landscape. Group 1: Industry Exit and Regulation - As of December 14, 2023, a total of 1,155 private equity fund managers have completed deregistration this year, reflecting a 20.12% year-on-year decrease in deregistrations [3] - The number of private equity fund managers has decreased from over 24,000 at the end of 2019 to 19,367 by October 2025, indicating a significant reduction in the industry [2] - The trend of deregistration is slowing down, suggesting that high-risk institutions have largely been cleared out, and the remaining firms are stabilizing [3] Group 2: Industry Growth and Fund Performance - The total assets under management for private equity funds reached a historical high of 22.05 trillion yuan by October 2025, an increase of 1.31 trillion yuan from the previous period [4] - The private equity fund industry has seen a significant increase in dividend distributions, with a total of 1,658 dividends amounting to 17.338 billion yuan distributed in 2025, a 236.59% increase compared to the previous year [4] - The growth in fund size and increased dividend payouts reflect a shift towards higher quality development within the private equity sector [4] Group 3: Future Outlook and Trends - The tightening of regulations is expected to continue, leading to further specialization and compliance among private equity firms, with a focus on innovative investment strategies [6] - The introduction of regular dividend clauses by more private equity firms aims to enhance product attractiveness and meet investor demands for realized returns [6] - The industry is anticipated to expand steadily, with a concentration of resources towards compliant leading firms, driven by advancements in quantitative investment and AI technologies [6]

- The report does not contain any specific quantitative models or factors for analysis[1][2][3] - The report primarily focuses on market trends, style performance, valuation metrics, and fund flows without detailing quantitative models or factor construction[1][2][3] - Key metrics such as PE_TTM, ERP, and style indices are discussed, but no explicit quantitative model or factor development process is provided[1][2][3]

Quantitative Models and Construction Methods 1. Model Name: Three-Strategy Fusion ETF Rotation Strategy - **Model Construction Idea**: The strategy integrates three dimensions: fundamental-driven rotation, quality low-volatility style rotation, and distressed reversal industry discovery. It aims to achieve factor and style complementarity while reducing the risk of single-strategy exposure[35][36] - **Model Construction Process**: 1. **Fundamental Rotation Strategy**: Selects industries based on factors such as exceeding expected prosperity, industry leadership effects, momentum, crowding, and inflation beta[36] 2. **Quality Low-Volatility Style Strategy**: Focuses on individual stock quality, momentum, and low volatility to enhance defensiveness[36] 3. **Distressed Reversal Strategy**: Utilizes PB z-score, long-term analyst expectations, and short-term chip exchange to capture valuation recovery and performance reversal opportunities[36] 4. Combines the three strategies equally to form a composite ETF rotation strategy, achieving multi-dimensional industry screening and reducing single-strategy risks[35][36] - **Model Evaluation**: The strategy effectively balances factor complementarity and style adaptation, providing robust performance across different market conditions[35][36] 2. Model Name: Hotspot Trend ETF Strategy - **Model Construction Idea**: This strategy identifies ETFs with strong upward trends and high market attention, constructing a risk-parity portfolio based on support-resistance factors and turnover ratios[30] - **Model Construction Process**: 1. Select ETFs where both the highest and lowest prices exhibit an upward trend[30] 2. Calculate the relative steepness of the regression coefficients for the highest and lowest prices over the past 20 days to construct support-resistance factors[30] 3. Choose the top 10 ETFs with the highest 5-day turnover ratio/20-day turnover ratio from the long group of the support-resistance factor, indicating increased short-term market attention[30] 4. Construct a risk-parity portfolio using these ETFs[30] - **Model Evaluation**: The strategy demonstrates strong performance, achieving significant excess returns compared to the benchmark[30] 3. Model Name: Capital Flow Resonance Strategy - **Model Construction Idea**: This strategy identifies industries with resonant capital flows by combining financing margin and active large-order capital flow factors, aiming to enhance stability and reduce drawdowns[42][44][45] - **Model Construction Process**: 1. Define the financing margin factor as the market-neutralized financing net buy-in minus securities lending net sell-out, calculated as the two-week change in the 50-day moving average[45] 2. Define the active large-order capital flow factor as the market-neutralized net inflow ranking of industry trading volume over the past year, using the 10-day moving average[45] 3. Exclude extreme industries from the active large-order factor and apply a negative exclusion for the financing margin factor to improve strategy stability[45] 4. Perform weekly rebalancing to select industries with resonant capital flows for long positions[45] - **Model Evaluation**: The strategy achieves stable positive excess returns with reduced drawdowns compared to other capital flow strategies[45] --- Model Backtesting Results 1. Three-Strategy Fusion ETF Rotation Strategy - **2025 YTD Performance**: Portfolio return 25.60%, benchmark return 21.83%, excess return 3.77%, Sharpe ratio 0.24, maximum drawdown -7.18%[39][40] - **Overall Performance (2017-2025)**: Annualized excess return 10.28%, Sharpe ratio 1.09, maximum drawdown -24.55%[40] 2. Hotspot Trend ETF Strategy - **2025 YTD Performance**: Portfolio return 34.49%, benchmark (CSI 300) excess return 19.58%[30] 3. Capital Flow Resonance Strategy - **2018-Present Performance**: Annualized excess return 14.3%, IR 1.4, reduced drawdowns compared to Northbound-Large Order Resonance Strategy[45] - **Last Week Performance**: Absolute return -0.27%, excess return 0.37% (relative to industry equal weight)[45] --- Quantitative Factors and Construction Methods 1. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the continuation of stock price trends over a specific period[53] - **Factor Construction Process**: 1. Calculate the 1-year momentum as the return over the past 12 months, excluding the most recent month[53] 2. Rank stocks based on momentum and form quintile portfolios[53] - **Factor Evaluation**: Demonstrates strong performance, with the 1-year momentum factor achieving a weekly excess return of 1.13%[53] 2. Factor Name: R&D to Total Assets Ratio - **Factor Construction Idea**: Measures the proportion of R&D investment relative to total assets, reflecting innovation capability[56] - **Factor Construction Process**: 1. Calculate the ratio of total R&D expenses to total assets for each stock[56] 2. Rank stocks based on this ratio and form quintile portfolios[56] - **Factor Evaluation**: Performs well in small-cap indices, with an excess return of 20.25% in the CSI 500 index[56] 3. Factor Name: Single-Quarter ROA YoY Change - **Factor Construction Idea**: Tracks the year-over-year change in return on assets (ROA) for a single quarter, reflecting profitability trends[56] - **Factor Construction Process**: 1. Calculate the year-over-year change in ROA for the most recent quarter, considering preliminary and forecasted data[56] 2. Rank stocks based on this change and form quintile portfolios[56] - **Factor Evaluation**: Excels in large-cap indices, with an excess return of 25.52% in the CSI 300 index[56] --- Factor Backtesting Results 1. Momentum Factor - **Weekly Excess Return**: 1.13%[53] 2. R&D to Total Assets Ratio - **Excess Return in CSI 500**: 20.25%[56] 3. Single-Quarter ROA YoY Change - **Excess Return in CSI 300**: 25.52%[56] - **Excess Return in CSI 500**: 10.16%[56] - **Excess Return in CSI 1000**: 21.98%[56]