Report Summary 1. Report Industry Investment Rating No industry investment rating is provided in the report. 2. Core Viewpoints - The US ETF market has new developments, with the issuance of a commodity long - short strategy product and continuous inflow of funds into stock products. Meanwhile, the performance of Korean - related ETF products is outstanding. The US non - money public funds have experienced changes in scale and redemption pressure, and recently, domestic stock funds have seen an expanded outflow [2]. 3. Summary by Relevant Catalogs 3.1 US ETF Innovation Products: Commodity Long - Short Strategy Product Issuance - Last week, 19 new products were issued in the US, more than half of which were single - stock products. These single - stock products involve 2x leveraged products and products combining options and leverage, targeting various companies such as those in the cryptocurrency, sports, health, and AI sectors [7]. - Stoneport Advisors issued a commodity long - short strategy product, which tracks an index using a quantitative method to construct a long - short strategy for US - listed commodity futures. The index determines the investable pool annually based on the S&P GSCI and Dow Jones Commodity Index, currently including 23 commodities from sectors like agriculture, precious metals, industrial metals, and energy. It decides long - short weights monthly according to the yield trend algorithm [8]. - First Trust issued a "critical metals" ETF, investing in companies mainly earning income from North America and involved in the mining of new - energy - related metals, new - energy vehicle metals, and other technology metals, ultimately selecting 50 stocks [8]. - iShares issued a large - cap core index enhancement product aiming for low tracking error against the Russell 1000 index and excess returns, managed by a quantitative team, and a European corporate bond product using euro - dollar foreign exchange hedging to reduce exchange - rate impact [10]. - KraneShares issued an options strategy product, using a Delta - neutral spread strategy by buying put options and selling call options while selecting stocks to obtain option premium differences [10]. 3.2 US ETF Dynamics 3.2.1 US ETF Funds: Stock Products Continuously Inflow - In the past week, the inflow of US ETFs exceeded $30 billion, with significant inflow into stock products and outflow from Bitcoin ETFs. BlackRock's S&P 500 ETF ranked first in inflow, short - term bond ETFs had obvious inflows, while technology - related products and Bitcoin ETFs had outflows [2][11][14]. - Gold ETFs had relatively stable fund flows last week, and among broad - based ETFs, the S&P 500 had higher inflows than the Nasdaq 100 in the past two weeks [16]. 3.2.2 US ETF Performance: Korean - Related Products Lead in Gains - US - listed stock ETFs have performed excellently this year. Two passive products have gains of over 80%, and 3x leveraged products have gains of over 300%. However, except for the largest product with a scale close to $7 billion, other products have relatively small scales [17]. 3.3 Recent US Ordinary Public Fund Fund Flows - In September 2025, the total amount of US non - money public funds was $23.47 trillion, an increase of $0.49 trillion compared to August 2025. In September, the S&P 500 rose 3.53%, the scale of US domestic equity products increased by 2.13%, and the redemption pressure increased [2][18]. - Last week, the outflow of US domestic equity funds expanded to $37 billion, and bond products also had a slight outflow [2][19].

11月10日早盘，A股核能核电概念股突然集体爆发，多只个股涨停或涨幅超过5%。表面上看，这似乎是因为即将召开的2025第四届中国核能高质量发展大 会的利好刺激。但作为一个深耕量化投资领域多年的从业者，我深知市场表象之下往往隐藏着更深层的逻辑。 数据显示，A股179只核电概念股中，164只年内上涨，占比高达92%，平均涨幅51.73%。更惊人的是，28只个股涨幅超过100%。这样的数据让我不禁思考： 在如此亮眼的行业表现背后，普通投资者真的能分到一杯羹吗？ 自从10月28日上证指数越过4000点以来，我身边不少朋友都在抱怨"赚了指数不赚钱"。这种现象并非偶然。根据我的量化系统统计，从4月7日上证指数止跌 企稳到10月30日突破4000点期间，虽然指数上涨了19.6%，但仅有四成个股跑赢指数。 更值得玩味的是，在这期间上涨的4200家个股中，有4000余家的振幅大于30%。这意味着市场并非没有机会，而是大多数投资者没有把握住恰当的时机。就 像这次核电概念股的异动，很多人看到消息后才匆忙入场，殊不知机构资金可能早已布局完毕。 | | 序号 | 前三季净利润 净利润同比 | | | --- | --- | --- | ...

在风起云涌的量化投资江湖中，淳厚基金量化与指数投资部总监周俊凭借着扎实的投研功底与均衡的投 资视角，逐渐在行业中崭露头角。 拥有12年量化投研①经验的他，曾亲历私募量化大发展期，2023年9月，他选择加入淳厚基金，开启在 公募领域的新征程。 在投资中，周俊始终强调量化策略的"可解释性"。他从因子挖掘到组合构建的过程中均保持逻辑清晰， 避免过度依赖"端到端"的机器学习。他希望通过"强因子弱模型"的投资架构，在因子层面追求逻辑清 晰、低相关性，在模型层面控制复杂度，确保策略出现波动时可追溯、可修复。这种均衡而稳健的风 格，正是周俊在量化行业中行健致远的关键。 坚持均衡投资 以多周期策略捕捉市场机遇 周俊的职业生涯贯穿了公私募两大资管细分领域。量化投资在中国刚启蒙的时候周俊便进入了行业，从 量化研究员成长为核心团队骨干。在量化行业快速发展期，他加入了一家中小型私募，作为核心基金经 理之一，亲历了公司规模从20亿元增长至400亿元的过程，自己也积累了丰富的投资经验。此后，他选 择"私转公"，于2023年9月加入淳厚基金，投身公募行业。 周俊所构建的量化模型，致力于追求以"多周期预测"为核心、兼顾逻辑透明与风险可控的均 ...

在风起云涌的量化投资江湖中，淳厚基金量化与指数投资部总监周俊凭借着扎实的投研功底与均衡的 投资视角，逐渐在行业中崭露头角。 拥有 12 年量化投研 经验的他，曾亲历私募量化大发展期， 2023 年 9 月，他选择加入淳厚基金， 开启在公募领域的新征程。 在投资中，周俊始终强调量化策略的 " 可解释性 " 。他从因子挖掘到组合构建的过程中均保持逻辑 清晰，避免过度依赖 " 端到端 " 的机器学习。他希望通过 " 强因子弱模型 " 的投资架构，在因子层 面追求逻辑清晰、低相关性，在模型层面控制复杂度，确保策略出现波动时可追溯、可修复。这种均 衡而稳健的风格，正是周俊在量化行业中行健致远的关键。 坚持均衡投资 以多周期策略捕捉市场机遇 周俊的职业生涯贯穿了公私募两大资管细分领域。量化投资在中国刚启蒙的时候周俊便进入了行业， 从量化研究员成长为核心团队骨干。在量化行业快速发展期，他加入了一家中小型私募，作为核心基 金经理之一，亲历了公司规模从 20 亿元增长至 400 亿元的过程，自己也积累了丰富的投资经验。 此后，他选择 " 私转公 " ，于 2023 年 9 月加入淳厚基金，投身公募行业。 周俊所构建的量化模型， ...

- 中加中证A500指数增强基金自建仓以来累计收益率达到22.82%，相比于中证A500指数超额收益率为4.60%[20][22] - 中加中证A500指数增强基金的周度超额胜率达到67.65%，在同类产品中排名2/14[22] - 中加中证A500指数增强基金的Barra风格因子分析显示其偏好低估值、高盈利、低波动、小市值的个股[28][30] - 中加专精特新量化选股基金自成立以来累计收益率达到60.01%，在同类产品中位列前5%[47][48] - 中加专精特新量化选股基金的最大回撤仅为-12.77%，显著优于中证2000指数的-19.65%[47][50] - 中加专精特新量化选股基金的Barra风格因子分析显示其偏好低估值、高盈利、低波动、小市值的个股[65] - 中加紫金基金自接管以来累计收益率达到50.36%，在同类产品中位列前7%[76][78] - 中加紫金基金的Barra风格因子分析显示其偏好盈利能力强、估值低的个股[95] - 中加北证50成份指数增强基金正在发行，目标是通过量化投资方法实现超越标的指数的投资收益[141]

- The report highlights that the A-share market has seen an overall increase this week, with the CSI 300 index rising by 0.8%[18][19] - The relative crowding and excess net value of growth versus dividend stocks are at historically high levels, indicating a potential risk in allocating to growth stocks[2][57] - The relative crowding and excess net value of small-cap versus large-cap stocks are not at historically high levels, suggesting that small-cap stocks currently offer a higher cost-performance ratio[2][57] - The relative crowding and excess net value of micro-cap stocks versus the CSI 800 index remain at historically high levels, indicating a potential risk in allocating to micro-cap stocks[2][57] - The rolling quarterly Sharpe ratio of the Wind All A index is at a historically high level, suggesting a need to monitor subsequent adjustment risks[8][34] - The current PE_TTM of the A-share market is at a historically high percentile, with marginal increases observed in the past week[8][38] - The equity risk premium (ERP) for the CSI 300 index is at a balanced percentile, while the ERP for the CSI 500 index is at a relatively high percentile, and the ERP for the ChiNext index is at an extremely high percentile[48][56] - The report notes that the total amount of active equity funds is in a long-term decline phase, which historically favors the reversal style over the momentum style[83][84] - The main fund indices showed mixed performance over the past week, with the national team index and social security heavy index leading the gains[85][89]

近一年，指数增强型基金业绩表现亮眼，平均回报高达27%。业内人士认为，市场结构性机会与量化策 略的契合、风控框架的优化以及资金对"贝塔+阿尔法"双收益的追求，共同造就了此类产品的亮眼表 现。与此同时，人工智能技术的深度融入，正为量化投资策略带来革命性变化，并有望重塑整个行业的 生态格局。 近一年，指数增强型基金业绩表现亮眼，平均回报高达27%。业内人士认为，市场结构性机会与量化策 略的契合、风控框架的优化以及资金对"贝塔+阿尔法"双收益的追求，共同造就了此类产品的亮眼表 现。与此同时，人工智能技术的深度融入，正为量化投资策略带来革命性变化，并有望重塑整个行业的 生态格局。 Wind数据显示，近一年，指数增强型基金平均回报为27%，其中，九成以上产品获得正收益，中小盘 产品表现尤为突出。具体来看：招商中证2000增强策略ETF以60.35%的回报排名首位；长信中证科创创 业50指数增强、华泰柏瑞中证2000指数增强、汇添富国证2000指数增强等产品回报均超50%。 近年来，越来越多机构将AI等新技术融入指数增强产品的量化模型与投资策略之中。王晓京认为，AI 在量化投资策略中的应用与在其他行业的影响类似，对行业发 ...

Core Viewpoint - The article provides a comprehensive analysis of market performance, highlighting the varying returns of different factors and strategies within the stock market, indicating a mixed sentiment among investors and the potential for selective investment opportunities [4][5][6][7][8][9][10]. Factor Performance - In the overall market, the valuation factor achieved a positive return of 0.40%, while the market capitalization factor and non-linear market capitalization factor recorded negative returns of -0.72% and -0.40% respectively, suggesting a small-cap style market performance [4]. - In the CSI 300 stock pool, the best-performing factors included the inverse TTM price-to-earnings ratio (3.05%), price-to-earnings ratio (2.30%), and price-to-book ratio (2.06%), while the worst performers were TTM gross profit margin (-2.11%), total asset growth rate (-1.80%), and quarterly gross profit margin (-1.58%) [5]. - In the CSI 500 stock pool, the top factors were the inverse TTM price-to-earnings ratio (2.71%), price-to-book ratio (2.07%), and price-to-earnings ratio (1.74%), with the lowest performers being TTM gross profit margin (-2.13%), quarterly gross profit margin (-2.02%), and quarterly ROA year-on-year (-1.50%) [5]. - In the liquidity 1500 stock pool, the leading factors were the inverse TTM price-to-earnings ratio (1.74%), price-to-earnings ratio (1.68%), and price-to-book ratio (1.34%), while the worst were post-opening returns (-3.00%), TTM gross profit margin (-2.64%), and quarterly gross profit margin (-2.50%) [5]. Industry Factor Performance - The fundamental factors showed varied performance across industries, with net asset growth rate, net profit growth rate, earnings per share, and TTM operating profit factors yielding positive returns in the oil and petrochemical industry [6]. - Among valuation factors, the BP factor performed well, achieving positive returns across most industries, while residual volatility and liquidity factors showed significant positive returns in the comprehensive industry [6]. - The market exhibited a notable small-cap style across most industries during the week [6]. Strategy Performance - The PB-ROE-50 combination achieved positive excess returns in the CSI 500 and CSI 800 stock pools, with excess returns of 1.00% and 0.48% respectively, while the overall market stock pool recorded an excess return of -2.00% [7]. - The private equity research tracking strategy yielded negative excess returns, while the public equity research selection strategy achieved an excess return of 0.00% relative to the CSI 800, and the private equity tracking strategy had an excess return of -1.96% [8]. - The block trading combination achieved positive excess returns relative to the CSI All Share Index, with an excess return of 1.08% [9]. - The targeted issuance combination also recorded positive excess returns relative to the CSI All Share Index, with an excess return of 1.93% [10].

Core Insights - Quantitative investment has evolved from a niche strategy to a crucial component in China's public fund market, with total scale exceeding 400 billion yuan by Q3 2025 [1] - Bodao Fund has emerged as a leading player in the quantitative space, managing approximately 27 billion yuan, showcasing how smaller firms can leverage quantitative strategies for growth [1] Group 1: Evolution of Quantitative Investment - The development of Bodao Fund's quantitative business reflects a continuous competition with market effectiveness, starting from private equity and launching live trading in 2013 [2] - The firm successfully navigated market challenges, including the "black swan" event in 2014, by employing the Barra risk model, which laid the groundwork for growth in 2015 [2] - In 2023, Bodao's quantitative team integrated AI methodologies across the entire process, resulting in a performance improvement of approximately 30-40% [2] Group 2: Investment Methodology - The "Dual Equilibrium" multi-factor model is central to Bodao's pursuit of excess returns, focusing on accurately predicting price through earnings per share (EPS) and price-to-earnings (PE) ratios [4] - The first equilibrium balances traditional human-driven frameworks with AI-driven processes, each contributing 50% to the overall strategy [4] - The second equilibrium ensures that factor sources are evenly weighted between predicting EPS trends and PE fluctuations, thus capturing both long-term growth and short-term mean reversion opportunities [4] Group 3: Product Strategy - Bodao Fund has established a clear "Index+" product matrix, which includes standard index enhancements, flexible strategies, and Smart Beta products [5] - All products in the "Index+" series are designed to enhance returns, addressing the significant excess return potential still present in the A-share market [5] - The firm suggests that for individual investors, actively managed funds may require careful selection, while quantitative products can serve as a stable core in investment portfolios [5] Group 4: Future Outlook - The company expresses confidence in the future of quantitative investment in China, noting a shift in investor focus from high volatility to stable excess returns [5]

贝莱德基金权益、量化及多资产首席投资官王晓京对上海证券报记者表示，从获取超额收益的角度来 看，中小盘指数增强产品通常具备几方面优势：首先，中小盘指数的成分股数量普遍多于大盘指数，这 拓宽了投资选择空间，增强了策略的灵活性；其次，中小盘股指期货往往存在较明显的贴水现象，这为 构建超额收益提供了天然工具；最后，在成交量有限但市场流动性总体稳定的环境下，例如在小微盘股 票中，量价因子与极短持股周期的策略组合通常能发挥显著作用。 "今年以来，市场行情主要集中在中小盘宽基指数和科技类股票，流动性驱动的行情催生了较高的贝塔 收益。在此背景下，中小盘指增产品在主动选股部分也能受益于额外的贝塔贡献，从而增厚超额收 益。"王晓京称。 AI塑造量化投资新生态 ◎记者 王彭 近一年，指数增强型基金业绩表现亮眼，平均回报高达27%。业内人士认为，市场结构性机会与量化策 略的契合、风控框架的优化以及资金对"贝塔+阿尔法"双收益的追求，共同造就了此类产品的亮眼表 现。与此同时，人工智能技术的深度融入，正为量化投资策略带来革命性变化，并有望重塑整个行业的 生态格局。 Wind数据显示，近一年，指数增强型基金平均回报为27%，其中，九成以上 ...