一、数字狂欢背后的冷思考 最近科创板的两融数据又成了茶余饭后的谈资。2564.68亿元的总余额，东芯股份1.54亿元的净买入，这些数字在各大财经平台滚动播放。我盯着这些数 据看了许久，突然想起三年前那个燥热的夏天——当时创业板注册制刚落地，市场也是一片欢腾，但最终多少人真正从中分得一杯羹？ 数字会说话，但说的是加密语言。就像我清华实验室的同门师兄常说的："数据本身没有价值，解读数据的能力才值钱。"271只个股获得融资净买入，8 只超5000万元，这些数字背后藏着怎样的市场密码？普通投资者看到的可能是机会，而我看到的是一场认知维度的较量。 二、牛市幻觉与残酷现实 记得2015年那轮牛市，小区门口卖煎饼的大爷都开始讨论K线形态。当时有个现象特别有意思：80%的人确实赚过钱，但最终保住盈利的不足20%。这 就像在游乐场玩旋转木马——转得再欢，音乐停了才发现还在原地。 去年跟踪过一只半导体股票，走势堪称教科书级的"心理战"。股价在三个月里反复画"心电图"，论坛里骂声一片。但当我打开量化系统，看到的却是另 一番景象： 行情好的时候，多数人觉得"早涨晚涨都是涨"，结果往往是"赚过"而非"赚到" 机构用专业工具在收割认知差 ...

Core Viewpoint - The A-share market is experiencing a broad rally, with the North Securities 50 Index rising approximately 2%, driven by sectors such as non-ferrous metals, automotive manufacturing, and semiconductors, indicating a favorable time for positioning ahead of the spring market [1] Group 1: Market Performance - On December 1, the A-share market showed a strong upward trend, particularly in the North Securities 50 Index, which increased by about 2% [1] - Various sectors, including non-ferrous metals, automotive manufacturing, and semiconductors, exhibited strong performance, contributing to a positive market sentiment [1] Group 2: Investor Behavior and Risks - A reminder of the November 14 trading day highlights the risks of retail investors blindly "bottom-fishing" during market corrections, as many ended up facing significant losses [3][4] - Historical data indicates that only about 60% of stocks outperform the index during bull markets, suggesting that a substantial portion of stocks may lag behind even in favorable conditions [3] Group 3: Investment Strategies - True bottom-fishing should not rely on market trends or index fluctuations; only stocks with sustained institutional participation are likely to see continued price increases [7] - The example of Hualan Vaccine illustrates that while the index may rise, individual stocks can decline, leading to panic selling among retail investors [7] Group 4: Market Dynamics - During market downturns, retail investors often exhibit extreme behaviors, either holding onto their positions or fleeing at the slightest sign of volatility, both driven by emotional responses [10] - Quantitative data reveals that trading behavior, particularly by institutional investors, is more indicative of market trends than price movements alone [13][16] Group 5: Recommendations for Investors - Investors are advised to remain vigilant and not be misled by superficial price increases; focus should be on stocks with ongoing institutional involvement [20][21] - Utilizing quantitative tools to identify the movements of major players and establishing personal trading discipline are essential for successful investing [21]

Group 1 - The withdrawal of public fund license applications by four brokerage asset management subsidiaries indicates a strategic shift in the market, suggesting that institutions are seeking more suitable survival strategies [1][2]. - Currently, only 14 out of 30 brokerage asset management subsidiaries hold public fund licenses, with the rest shifting focus to private equity, highlighting market differentiation [2]. - The statement from Guojin Securities about focusing on core competitiveness reflects the challenges in the public fund sector, which is becoming increasingly difficult to navigate [2]. Group 2 - The article emphasizes the importance of understanding market dynamics and the true intentions behind capital flows, rather than relying solely on traditional stock selection methods [3][5]. - It discusses the phenomenon of "institutional shakeout" during market adjustments, where investors often panic and exit, missing potential accumulation opportunities by institutions [5][7]. - The need for retail investors to adapt to the changing market landscape is stressed, advocating for a quantitative approach to observe market behaviors and differentiate strategies [8].

那天收盘后，我盯着华兰疫苗的K线图发愣。六连阴对上证六连阳的反差，像极了上海弄堂里晾晒的衣裳——明明同处一片天空 下，有的早已干透，有的却还滴着水。手机突然震动，是朋友发来的消息："国务院又出排查通知了，这次是高层建筑火灾隐患， 你说建材股要不要跟？" 我苦笑。这场景太熟悉了，就像菜场里抢购特价鸡蛋的大妈，听见风声就一拥而上。可股市不是菜场，政策暖风未必能吹热每只股 票。就像11月14日那天，半导体板块早盘诱多，尾盘却把跟风者埋在了山顶。 引子 一、政策面与基本面的迷思 国务院安委会这纸通知来得突然，却也在意料之中。岁末年初历来是安全事故高发期，但把文件直接等同于投资机会，未免太过天 真。就像11月制造业PMI那个微妙的49.2%，大型企业数据还在下滑，小型企业却环比上升2个百分点——这分化背后，藏着多少机 构调仓的蛛丝马迹？ 财政部公布的国企数据更值得玩味。1-10月营收增长0.9%，利润却下降3%，资产负债率还攀升0.4个百分点。这些数字在量化系统 里会化成怎样的曲线？我见过太多次，当普通投资者还在争论"估值修复"时，机构早已通过高频交易完成了布局。 二、牛市幻觉与量化真相 人们总说牛市要捂股，可2025 ...

一、原来联博就是那个AllianceBernstein！ ——偶然的发现，联通了华尔街巨头与中国市场。 博格查数据时经常在海外报告里看到"Alliance"这个名字，看描述好像是一家资产管理巨头，但没深究过。 直到最近研究外资基金，看到"联博"，一查才知道中文"联博"就源自Alliance Capital（联博资本）。 二、探访联博：认识他们的"量化基本面" 最近去上海，我特意去联博办公室交流学习。 顶尖资管公司必有独到之处，才能长期保持领先。 交流中得知，他们专门为中国市场打造了一个策略——量化基本面。 简单说，就是把量化模型的数据处理能力，和基本面研究的深度洞察结合起来选股。 再仔细了解，联博集团（AllianceBernstein, 简称AB）是由华尔街两大传奇——Alliance Capital（联博资本）和Bernstein（伯恩斯坦）合并而来。 2000年，Alliance Capital以35亿美元收购Bernstein，组成了现在的全球资管巨头。 截至2025年9月30日，它在全球管理着8600亿美元（超6万亿人民币）的资产。 还有个冷知识：大名鼎鼎的"木头姐"凯西·伍德，也正是从Allian ...

Core Viewpoint - The quantitative convertible bond portfolio experienced a slight decline in November, with a year-to-date return of 20.14% and an excess return of 3.96% [1] Group 1: Portfolio and Performance - The quantitative convertible bond portfolio is generated based on three factor systems: fundamental factors, low-frequency price-volume factors, and high-frequency price-volume factors [5] - The portfolio's performance in November showed a return of -0.72% and an excess return of -0.03% [1] Group 2: Convertible Bond Factors - A total of 32 fundamental factors, 80 low-frequency price-volume factors, and 32 high-frequency price-volume factors are tracked for convertible bonds [2] - The report illustrates the latest data using the pricing deviation factor as an example [2] Group 3: Risk Warnings for Convertible Bonds - The report provides risk warnings for convertible bonds based on forced delisting rules and credit scoring methods, highlighting various risks including trading and financial delisting risks [3][13] Group 4: Timing for Convertible Bond Index - The report employs price-volume models, pricing deviations, and convertible bond elasticity for timing and position management of the CSI Convertible Bond Index, indicating a bullish signal for the end of November with a position recommendation of 1/3 [4][14] Group 5: Timing Signals - The timing signals for the CSI Convertible Bond Index from early November show a mix of bullish and neutral signals, with a position recommendation fluctuating between 0% and 67% throughout the month [15]

Group 1 - The 2025 Analyst Conference highlighted the potential for a bull market in A-shares, attracting global capital inflows [1] - The speaker, Wu Qidi, emphasized the transformation of sell-side research, indicating that only the top 20 brokerage firms can earn substantial commission income, making it difficult for smaller firms to break through [3][17] - The direction of transformation includes shifting from a single institutional service model to a diversified approach that combines external services for institutions, internal wealth management, and industry research [3][17] Group 2 - The number of individual investors in the A-share market has surpassed 240 million as of June 2025, with a steady increase in their scale [3][26] - Despite the growth, the penetration rate of quantitative investment among individual investors remains low, with institutional investors still dominating the space [3] - The scale of public quantitative funds reached 312.1 billion yuan, a 5.8% increase from the end of 2024, while private quantitative funds totaled approximately 1.49 trillion yuan, growing by 6.0% [3] Group 3 - By 2026, the scale of individual quantitative investment is expected to exceed one trillion yuan, creating a market space of 15.4 billion yuan for quantitative services [4][26] - The annualized return of a selected stock pool from 50 brokerages was 7.28% from January 2018 to June 2025, with a maximum drawdown of 46.18% [19] - The research indicates that the lack of a buy-side mindset and herd mentality are reasons for the lower-than-expected returns from the selected stocks [19] Group 4 - The company aims to leverage AI and financial engineering to enhance investment strategies, with specific quantitative strategies showing annualized returns of 22.0% and 16.0% [20] - AI is transforming traditional securities research by automating data collection and analysis, significantly improving efficiency compared to manual methods [23][24] - The research emphasizes the importance of multi-dimensional data applications to better understand future market trends [24]

Core Viewpoint - The launch of the Huabao CSI 300 Enhanced Strategy ETF marks a significant addition to the growing market of enhanced index ETFs, reflecting a bullish sentiment in the A-share market and the increasing importance of the CSI 300 index as a core asset allocation tool in China [1][2]. Group 1: ETF Launch and Market Context - The Huabao CSI 300 Enhanced Strategy ETF (subscription code: 562073) officially launched on December 1, 2025, as the second enhanced index ETF introduced by Huabao Fund this year [1]. - The ETF will be listed on the Shanghai Stock Exchange under the abbreviation "CSI 300 Enhanced ETF" after its issuance [1]. - The overall A-share market is experiencing a recovery, with expectations of a slow bull market strengthening, making the performance of the new ETF highly anticipated [1][2]. Group 2: Competitive Landscape and Management - The enhanced index ETF segment has evolved from a niche category to a competitive field with numerous strong players, emphasizing the need for superior active management capabilities from fund managers [2]. - The Huabao CSI 300 Enhanced Strategy ETF will be co-managed by Wang Zheng and Xu Linming, highlighting Huabao Fund's commitment to this product [2]. - Xu Linming, the head of Huabao Fund's quantitative investment department, and Wang Zheng, a notable figure in quantitative investment, will oversee the ETF's management [2]. Group 3: Historical Performance and Strategy - The Huabao CSI 300 Enhanced Fund, managed by the same team since its inception in December 2016, has demonstrated strong long-term excess return capabilities, achieving a net value growth of 102.38% and an excess return of 51.04% as of September 30, 2025 [3][8]. - The fund has outperformed its benchmark in 7 out of 8 years from 2017 to 2024, showcasing the effectiveness of its investment strategy [3][8]. - The quantitative investment team at Huabao Fund has been dedicated to developing local quantitative investment strategies since 2005, leading to a robust track record in the market [3][8].

Core Insights - The article emphasizes that technological innovation and industrial upgrading are key drivers of high-quality economic development in China, with the Sci-Tech Innovation Board and the Growth Enterprise Market as primary platforms supporting this innovation [1][3]. Group 1: Investment Strategy - The Guojin Sci-Tech Innovation and Entrepreneurship Quantitative Stock Fund aims to leverage active quantitative investment strategies focused on the "Double Innovation" sector, selecting individual stocks to capitalize on "hard technology" and "new growth" opportunities [1][3]. - The fund invests at least 80% of its non-cash assets in the Sci-Tech Innovation Board and the Growth Enterprise Market, allowing for diversified allocation across sectors and market capitalizations [3][4]. Group 2: Market Characteristics - The "Double Innovation" sector is characterized by high levels of information, specialization, and volatility, making investment challenging; however, it also presents significant growth potential due to high R&D investments driving performance well above market averages [4][5]. - The Wande Double Innovation Index has shown significantly higher returns and risk-adjusted performance metrics compared to mainstream indices like the CSI 300 and the CSI 500 since 2020 [4]. Group 3: Quantitative Investment Approach - The fund employs a systematic model and strict risk control to address the challenges of investing in the "Double Innovation" sector, enhancing the probability of capturing quality growth stocks while minimizing non-systematic risks [5][6]. - Unlike traditional actively managed funds, the quantitative fund relies on model-driven strategies and comprehensive market coverage rather than deep fundamental research [5][6]. Group 4: Team and Technology - The Guojin Fund has a well-established quantitative research team with a strong background in mathematics and investment, having built its quantitative investment framework since 2013 [7]. - The team utilizes a wide range of data sources, including research reports and trading data, to construct dynamic predictive models that identify market opportunities that traditional strategies may overlook [7].

Core Insights - The article emphasizes that technological innovation and industrial upgrading are key drivers of high-quality economic development in China, with the Sci-Tech Innovation Board and the Growth Enterprise Market as primary platforms supporting this innovation [1][2] Investment Focus - The newly launched Guojin Sci-Tech Innovation and Entrepreneurship Quantitative Stock Fund aims to leverage active quantitative investment strategies, focusing on "hard technology" and "new growth" sectors to capitalize on economic growth and industrial transformation [1][2] - The fund will invest at least 80% of its non-cash assets in the Sci-Tech Innovation Board and the Growth Enterprise Market, allowing for diversified allocation across sectors and market capitalizations [1][2] Sector Characteristics - The "double innovation" sector is characterized by information explosion, high specialization, and strong volatility, making stock selection challenging due to rapid technological changes and varying company quality [3] - Companies in this sector exhibit high R&D investment, leading to performance growth that significantly outpaces market averages, as evidenced by the Wind Double Innovation Index outperforming major indices like CSI 300 and CSI 500 since 2020 [2][3] Quantitative Investment Strategy - The Guojin fund employs a systematic quantitative investment approach, which includes broad stock selection through technical models, strict risk control, and optimization of portfolios to achieve smoother long-term excess returns [3][4] - Unlike traditional actively managed funds, the quantitative fund relies on model-driven strategies and comprehensive market coverage rather than deep fundamental research [3][4] Team and Technology - Guojin Fund has a strong quantitative research team with extensive experience and a solid mathematical background, having established its quantitative investment framework since 2013 [4][5] - The team utilizes a wide range of data sources, including research reports and trading data, to build dynamic predictive models and enhance strategy effectiveness [4][5]