Group 1 - The core idea of the article revolves around the emergence of AI tools like DeepSeek in the investment landscape, highlighting their potential to enhance trading methods and optimize investment strategies [1][2] - The article emphasizes the evolution of quantitative investing over the past two to three decades, focusing on the importance of data collection, pattern recognition, and algorithmic trading to achieve superior performance [2][3] - The introduction of DeepSeek by its parent company, Huansheng Quantitative, marks a significant development in the quantitative investment space, with its R1 version being a direct competitor to ChatGPT, showcasing impressive capabilities at a fraction of the cost [3][4] Group 2 - DeepSeek's standout feature is its ability to "precisely understand human intent," which allows it to gather information and perform deep reasoning to produce high-quality outputs, aligning closely with the investment decision-making process [3][4] - Despite its advanced capabilities, DeepSeek is not yet able to generate "perfect strategies" autonomously, as quantitative funds still rely on niche data and hidden patterns for competitive advantage [4][5] - The article suggests that integrating AI tools like DeepSeek into daily investment practices can help reduce emotional trading and deepen understanding of targets and industries [2][3]

本文首发于公众号"私募排排网"。 （点击↑↑ 上图查看详情 ） 8月份，A股三大股指继续强势上涨，同时，成交额来到了历史高位水平，市场交投活跃。8月份，上证指数的涨幅为7.97%，深证成指的涨幅为 15.32%，创业板指的涨幅为24.13%。 在这样的市场背景下， 有 3321只私募产品（在私募排排网有业绩展示且成立满1年）在今年8月份净值曾创下历史新高，占成立满1年的私募产 品的比例约为71.19%。 按产品类型来看，量化产品占 1303只，非量化产品占2018只 。 按照产品策略（一级策略）来看，股票策略产品最多（主要是主观多头和量化 多头），有 2135只，占比约64%； 其次是多资产策略产品占471只，期货及衍生品策略产品占305只，债券策略产品占302只，组合基金产品占 108只。 按公司规模来看，来自5亿以下规模私募的产品最多，有1347只，占比超4成；来自百亿私募的产品有456只。 为了给读者提供一些参考， 笔者在创新高私募产品中按照产品策略分别梳理出了 "股票策略-主观多头、股票策略-量化多头、期货及衍生品策 略、多资产策略、债券策略"近一年收益居前20强的私募产品（公司规模在5亿以上）； 此 ...

在指数化投资深入发展的新时代，资管行业正经历结构性的变革。如何在可控风险下实现稳定超额收益， 成为行业高质量发展的核心课题。指数化投资不仅为被动投资者提供了低成本、高透明度的配置渠道，也 为传统主观投资者开启了"系统性、可复制、可验证"的投研新范式。主观判断与量化逻辑的结合、数据驱 动的投资决策，正成为越来越多专业人士的选择。 Wind 始终致力于用科技与数据重构投研流程。基于对指数策略发展趋势的深刻洞察， Wind 重磅推出 2025 ALPHA 进化论 ·Alice AI 指数增强擂台赛 ，依托全球首个自然语言生成指数策略增强平台 —— Wind Alice AI 指数策略平台 ，旨在打造一个人人可参与、高手齐竞技、思想与策略共振的专业舞台。 本次大赛面向 Wind 金融终端全部用户 开放，不设门槛、鼓励探索。你可以用最天马行空的想法、最独特 的策略视角，在这个没有代码壁垒的平台上，尽情展现你的策略创造力与投资洞察力。风起于青萍之末， 浪成于微澜之间。在技术跃迁与理念变革的交汇点上，让我们共同见证，谁将引领 ALPHA 进化新浪潮。 【评选规则】 Alice Al 指 数 增 强 擂 台 正 / 式 / ...

引子 第二是冷热假象。就像现在，传媒、新材料板块被机构持续加仓，但多数散户还在追逐前期热门题材。 最近市场热闹非凡，上证指数稳稳站上3400点，成交量持续放大，个股涨跌比达到2.57:1。表面上看，这似乎是个遍地黄金的行情。但作为一 个浸淫市场多年的量化投资者，我看到的却是另一番景象——106只个股连续5天以上获得主力资金净买入，其中万凯新材和长江传媒更是连续 13天被机构青睐。这让我想起格雷厄姆那句警世箴言："牛市是普通投资者亏损的主要原因。" 一、牛市里的四大迷思 市场越是火热，假象就越是层出不穷。我总结出当前市场最典型的四个认知误区： 第一是待涨假象。很多人看着指数上涨就认为所有股票都会雨露均沾，实际上即便在如此"牛市"中，涨幅超过6%的个股也不到五成。 第三是涨跌假象。股价上涨未必是真涨，下跌也未必是真跌，关键要看背后的资金性质。 第四是高低假象。估值高低不能简单看PE，更要看资金介入程度。有些看似高估的股票反而被机构持续买入。 二、焦虑的根源在于视角 投资中最折磨人的不是亏损，而是焦虑。涨了怕踏空，跌了怕套牢；赚钱怕回吐，亏钱怕深套。这种煎熬我太熟悉了——十年前我刚入市时也 是这样患得患失。 后来我 ...

Core Viewpoint - Quantitative investment has seen significant growth in scale due to its impressive returns, but individual investors face challenges in selecting reliable quantitative private fund managers [3] Group 1: Common Quantitative Strategies - Common quantitative strategies include T0 strategy, which is a high-frequency trading strategy requiring daily buy-sell transactions to profit from price differences, showing low correlation with market trends and relatively stable Alpha [4] - Medium and low-frequency strategies, such as index enhancement, leverage fundamental data and alternative data to score stocks, buying those with the highest scores [4] - Market-neutral strategies use derivatives to hedge against market risks while aiming for absolute returns based on Alpha [5] - Other niche strategies include CTA (Commodity Trading Advisor) strategies, options arbitrage, and cross-market investments, which are typically smaller in scale and require professional management for effective tracking and allocation [5] Group 2: Risk Management in Selecting Fund Managers - Ensuring asset safety is prioritized over return considerations, as high returns are meaningless without guaranteed fund safety [6] - A strict risk control process is established to screen private funds, including avoiding non-compliant structures, ensuring fund custody by reputable brokers, and limiting investment scope to exclude illiquid assets [6] - Professional due diligence involves assessing fund managers' strategies, sources of returns, and risk management systems to ensure alignment between stated and actual performance [6][7] Group 3: Due Diligence Process - The due diligence process focuses on meeting with research personnel rather than marketing staff to gain deeper insights into investment strategies [7] - Key areas of inquiry include modeling, risk control, and partnerships with reputable institutions to assess the robustness of the fund's risk management and compliance [7] - Continuous performance tracking is essential to verify if fund managers' actions align with their claims, using net value sequences and characteristic curves for validation [8] Group 4: Post-Investment Monitoring - Continuous observation of fund managers is conducted to identify any significant changes in investment style, with communication initiated if discrepancies arise [9] - A "racehorse" mechanism is established for ongoing performance analysis of invested funds, focusing on various metrics to optimize the portfolio based on fund performance and future outlook [9] Group 5: Advice for Individual Investors - Individual investors should assess their risk tolerance and understand the risk-return characteristics of investment targets before making decisions, avoiding impulsive investments based on hearsay [10]

Quantitative Models and Construction Methods 1. Model Name: PB-ROE-50 Combination - **Model Construction Idea**: This model focuses on selecting stocks with low Price-to-Book (PB) ratios and high Return on Equity (ROE) to construct a portfolio that aims to achieve excess returns[24] - **Model Construction Process**: The portfolio is constructed by screening stocks based on their PB and ROE metrics. Stocks with the lowest PB ratios and highest ROE values are selected to form the top 50 stocks in the portfolio. The portfolio is rebalanced periodically to maintain the selection criteria[24] - **Model Evaluation**: The model demonstrates significant excess returns in the all-market stock pool, though it underperforms in specific indices like the CSI 500 and CSI 800[24][25] 2. Model Name: Public and Private Institutional Research Combination - **Model Construction Idea**: This model leverages the stock selection strategies of public and private institutional research to identify stocks with potential for excess returns[27] - **Model Construction Process**: The portfolio is constructed by tracking the stocks that public and private institutions have recently researched. Stocks with higher research frequency or positive sentiment are included in the portfolio. The portfolio is rebalanced periodically to reflect updated research data[27] - **Model Evaluation**: The public institutional research strategy shows significant excess returns compared to the CSI 800 index, while the private institutional research strategy also achieves positive but smaller excess returns[27][28] 3. Model Name: Block Trade Combination - **Model Construction Idea**: This model identifies stocks with high block trade activity and low volatility, as these characteristics are associated with better subsequent performance[31] - **Model Construction Process**: The portfolio is constructed based on two key metrics: "block trade transaction amount ratio" and "6-day transaction amount volatility." Stocks with higher transaction ratios and lower volatility are selected. The portfolio is rebalanced monthly[31] - **Model Evaluation**: The model experienced a drawdown in the past week, with negative excess returns relative to the CSI All Share Index[31][32] 4. Model Name: Directed Issuance Combination - **Model Construction Idea**: This model focuses on stocks involved in directed issuance events, which are analyzed for their potential investment value based on event-driven factors[37] - **Model Construction Process**: The portfolio is constructed by identifying stocks with directed issuance announcements. Factors such as market capitalization, rebalancing cycles, and position control are considered. The portfolio is rebalanced periodically to reflect new issuance events[37] - **Model Evaluation**: The model experienced a drawdown in the past week, with negative excess returns relative to the CSI All Share Index[37][38] --- Model Backtesting Results 1. PB-ROE-50 Combination - **Weekly Excess Return**: All-market stock pool: +0.79%; CSI 500: -0.57%; CSI 800: -0.02%[24][25] - **Year-to-Date Excess Return**: All-market stock pool: +22.30%; CSI 500: +3.00%; CSI 800: +16.16%[25] - **Weekly Absolute Return**: All-market stock pool: +2.87%; CSI 500: +2.79%; CSI 800: +1.89%[25] - **Year-to-Date Absolute Return**: All-market stock pool: +48.27%; CSI 500: +28.59%; CSI 800: +36.42%[25] 2. Public and Private Institutional Research Combination - **Weekly Excess Return**: Public research: +3.82%; Private research: +0.51%[27][28] - **Year-to-Date Excess Return**: Public research: +8.10%; Private research: +12.02%[28] - **Weekly Absolute Return**: Public research: +5.81%; Private research: +2.44%[28] - **Year-to-Date Absolute Return**: Public research: +26.96%; Private research: +31.56%[28] 3. Block Trade Combination - **Weekly Excess Return**: -1.77%[31][32] - **Year-to-Date Excess Return**: +0.26%[32] - **Weekly Absolute Return**: Not explicitly stated - **Year-to-Date Absolute Return**: +62.65%[32] 4. Directed Issuance Combination - **Weekly Excess Return**: -1.71%[37][38] - **Year-to-Date Excess Return**: -0.77%[38] - **Weekly Absolute Return**: Not explicitly stated - **Year-to-Date Absolute Return**: +20.29%[38] --- Quantitative Factors and Construction Methods 1. Factor Name: Beta Factor - **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements, capturing systematic risk[20] - **Factor Construction Process**: Beta is calculated using regression analysis of a stock's returns against the market index over a specified period[20] - **Factor Evaluation**: Demonstrated significant positive returns in the past week, indicating a preference for high-beta stocks[20] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the tendency of stocks with strong past performance to continue performing well in the short term[20] - **Factor Construction Process**: Momentum is calculated based on the cumulative returns of a stock over a specific lookback period, such as 1 month or 5 days[20][22] - **Factor Evaluation**: Significant positive returns were observed, with notable momentum effects in sectors like media, real estate, and agriculture[20][22] 3. Factor Name: Scale Factor - **Factor Construction Idea**: Reflects the size effect, where larger-cap stocks tend to outperform smaller-cap stocks in certain market conditions[20] - **Factor Construction Process**: Scale is measured using market capitalization, with adjustments for sector and industry effects[20] - **Factor Evaluation**: Demonstrated positive returns, indicating a preference for large-cap stocks in the past week[20] --- Factor Backtesting Results 1. Beta Factor - **Weekly Return**: +0.70%[20] 2. Momentum Factor - **Weekly Return**: +0.46%[20] 3. Scale Factor - **Weekly Return**: +0.16%[20]

明汯投资始终坚持"科技为先，人才为本"的核心发展理念，将人才视为驱动量化投资技术创新的核心引 擎。通过构建多元化、扁平化、体系化的人才梯队建设机制，公司致力于为员工提供全球化成长平台， 培养具备国际竞争力的专业化团队，以实际行动践行金融行业人才建设的社会责任。 广纳全球英才 构建三维人才生态体系 国际化与多元化布局：全球视野 多元碰撞 一是选拔机制。 "逆商+自驱力+工程能力"的多维评估，面试中通过灵活多变的代码问题考察实战能力，弱化单一标 签，聚焦技术深度与工程能力。 二是培养体系。 新人配备完整"导师制"，通过项目实践快速成长。投入指数级增长的算力资源（高性能计算集群+混合 云方案），支持AI等前沿技术研究。 自成立以来，明汯致力于成为"国际一流量化投资公司"，在"成为国际主要资本市场的重要参与者、拥 有国际一流人才梯队与组织文化"两个维度同步发力。在持续提升自身竞争力、招揽全球英才的过程 中，前瞻性推进全球人才网络建设。目前已在纽约、中国香港、新加坡等国际金融枢纽设立办公室，吸 引海外顶尖量化人才。团队学科背景覆盖数学、计算机、物理、化学等多领域，通过跨学科、跨文化碰 撞激发创新活力，确保在不同市场中都 ...

Group 1: Market Overview - The Shanghai Composite Index has stabilized above 3400 points, with increasing trading volume and a stock rise-fall ratio of 2.57:1, indicating a seemingly strong market [1] - However, less than 50% of stocks have risen more than 6%, suggesting underlying weaknesses in the market [1] Group 2: Illusions in the Bull Market - The approval of the national standard for pre-prepared food safety reflects a "waiting for rise" illusion, indicating potential transformation pressures for related restaurant businesses [3] - A significant drop in shipping prices, with the Ningbo Export Container Freight Index decreasing by 11.7%, highlights the "hot and cold" illusion in the market [3] - The denial by Goldman Sachs regarding the upgrade of Shenghong Technology's target price illustrates the "rise and fall" illusion, where misleading information is prevalent [3] - Despite low loan interest rates (approximately 3.1% for new loans in August), a wave of shareholder reduction plans from over 30 companies indicates a "high and low" illusion in market liquidity [3] Group 3: Quantitative Perspective - Anxiety in investment decisions stems from the tendency to speculate on market fluctuations rather than focusing on fundamental data [4] - The analysis of two stocks shows that while one stock has occasional rebounds, its "institutional inventory" has disappeared, whereas the other stock, despite a sharp decline, maintains active "institutional inventory" [6] Group 4: Global Investment Insights - Recent global events, such as the U.S. anti-dumping investigation on simulated chips and significant layoffs at Musk's AI company, emphasize the need for a broader investment perspective in a globalized economy [12] - The new regulations on pre-prepared food not only signify the beginning of industry standardization but also indicate a trend towards consumer upgrades [12] - Investors are encouraged to focus on core data that truly impacts the market, rather than being swayed by overwhelming information, to avoid traps in a bull market and seize opportunities during fluctuations [12]

2025 年 09 月 15 日 中欧基金旗下两只沪深 300 指数增 强基金的配置价值分析 ——基金经理研究系列报告之八十 相关研究 证券分析师 白皓天 A0230525070001 baiht@swsresearch.com 蒋辛 A0230521080002 jiangxin@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 联系人 邓虎 (8621)23297818× denghu@swsresearch.com 请务必仔细阅读正文之后的各项信息披露与声明 ⚫ 模型信号：多维度提示关注沪深 300 的配置价值。（1）沪深 300 指数的成交额占比近 期有所提升；（2）沪深 300 在高质量、高股息性价比与成分股待涨占比突出的三大特征。 基本面特征——高质量的宽基指数、性价比特征——股息性价比逐渐突出、成分股细拆 维度——年内高涨幅股票占比偏低，部分高质量个股仍"待涨"；（3）从市场短期价量 指标入手，模型维持提示大盘风格占优信号，短期内 5 日 RSI 相对 20 日 RSI 大幅下滑， 信号提示强烈，此时具备强大盘属性的沪深 300 指 ...

金融工程| 证券研究报告 —周报 2025 年 9 月 15 日 中银量化大类资产跟踪 中小盘反弹力度领先，微盘拥挤度降至低位 股票市场概览 本周 A 股上涨，港股上涨，美股上涨，其他海外权益市场普遍上涨。 A 股风格与拥挤度 成长 vs 红利：成长风格拥挤度及超额净值持续处于历史低位；红利风 格拥挤度近期处于历史较低位置。 小盘 vs 大盘：小盘风格超额净值及拥挤度均处于历史低位，大盘风格 拥挤度近期上升至历史较高位置。 微盘股 vs 基金重仓：微盘股拥挤度下降至历史低位；基金重仓超额累 计净值持续处于历史低位，拥挤度近期上行至历史高位。 A 股行情及成交热度 本周领涨的行业为电子、非银行金融、农林牧渔；领跌的行业为银行、综 合金融、医药。本周成交热度最高的行业为国防军工、纺织服装、纺织服 装；成交热度最低的行业为煤炭、综合金融、石油石化。 A 股估值与股债性价比 A 股资金面 机构调研活跃度 当前机构调研活跃度历史分位居前的行业为有色金属、房地产、石油石 化，居后的行业为银行、机械、医药。 利率市场 本周中国国债利率上涨，美国国债利率下跌，中美利差处于历史高位。 汇率市场 近一周在岸人民币较美元升值，离岸 ...