活动背景 在瞬息万变的金融市场中，准确及时的宏观经济情报与微观交易数据正成为卖方研究与投资决 策的关键驱动力。宏观层面，LSEG 与 XTech 联合推出的预测模型，通过前沿指标提前洞察全 球经济趋势，为研究机构和投资者提供可操作的市场信号。微观层面，借助分钟级别的股票交 易数据和机器学习算法，投资者能够实时识别"聪明资金"何时建仓或减仓，从而在制定入场与 退出策略时获得关键优势。 LSEG 的解决方案将宏观经济预测与市场微观结构分析相结合，帮助卖方研究人员和投资专业 人士在海量信息中精准识别"信号"，有效规避"噪音"，提升研究效率与投资回报。 我们诚挚邀请您参加由伦敦证券交易所集团（LSEG）主办的量化专题活动——" 从微观交易到 宏观经济：LSEG量化洞察上海交流会 "，与基金、量化、研究机构及咨询公司的专业人士，共 话量化洞察与数据驱动的投资未来。 徐晓波 ，锐天投资创始人、投资部负责人 李怡康 ，FFT Investment 合伙人/COO Arman Sahovic博士 , LSEG亚太区Front Office解决方案总监 活动时间 活动议程 16:30 - 17:00 签到与交流 17:00 - ...

"量化投资的本质是人才、技术的积累和迭代。我们的目标是最终实现工程化的胜利，每个模块不断打 磨，做深做细，做到极致，最后无缝拼接。"蒙玺投资创始人兼总经理李骧说。 李骧称，公司未来将持续迭代策略和技术，打造"严格控制风格的全频段Alpha"，成为具有国际视野的 稳健型量化投资机构。 低延迟、中心化和非线性模型 笃定三大关键打造核心竞争力 李骧是一位典型的理工科背景的量化私募掌门人，学生时代参加各种科学竞赛，本科考入了中国科学技 术大学，学化学物理专业，后来出国留学，获得美国布朗大学理论化学硕士。 他对股市兴趣浓厚，2008年开始研发美股量化策略，2010年中国股指期货推出后，专注期货策略研究， 并在低延迟领域持续深耕；2016年他创立了蒙玺投资，经过九年发展，公司管理资产规模逾150亿元。 回顾公司创立至今，李骧表示，蒙玺投资发展的每一步都围绕"长期主义"展开，而三个关键决策则打造 了公司在量化投资领域的核心竞争力。 首先，创立之初，公司就非常笃定要拥有很强的低延迟技术。"因为量化策略每个时刻下单，某种意义 上来说都要与同行竞争，所以技术层面一定要有优势。"李骧说，低延迟的IT是量化投资的必要不充分 条件，技 ...

李骧称，公司未来将持续迭代策略和技术，打造"严格控制风格的全频段Alpha"，成为具有国际视野的稳健型量化投资机构。 低延迟、中心化和非线性模型 笃定三大关键打造核心竞争力 "量化投资的本质是人才、技术的积累和迭代。我们的目标是最终实现工程化的胜利，每个模块不断打磨，做深做细，做到极致，最后无缝 拼接。"蒙玺投资创始人兼总经理李骧说。 在英雄辈出的私募江湖，蒙玺投资给自己的定位是一家"业绩至上、技术至上"的量化投资机构。从早期聚焦低延迟交易的量化新兵，到如 今覆盖多策略、多品种、多频段的百亿机构，蒙玺投资的成长轨迹堪称中国量化行业"精细化发展"的缩影。 再者，投研团队架构采用"中心化"大组模式而非多PM制。李骧表示，蒙玺投资的投研团队是模块化运作，通过分工合作，使研究成果成为 统一集合，避免重复研究，类似汽车制造商的"流水线的工业化生产模式"。"我们内部沟通交流比较顺畅，大家乐于分享，共同成长，都是 站在别人的肩膀上研究，而不是跑马模式，一群人做一样的事，资源浪费。"他说。 第三，2020年全面拥抱"非线性模型"，也就是AI技术。他称，最开始是树模型，现在是深度模型，"在运用AI非线性模型后，预测能力大幅 提 ...

Core Viewpoint - The article emphasizes the importance of excess return (Alpha) in quantitative investment, highlighting the need for thorough analysis and attribution of performance to understand the sources of excess returns and evaluate the effectiveness of quantitative strategies [2][3]. Group 1: Excess Return and Its Calculation - Excess return (Alpha) is defined as the return of an investment portfolio relative to a benchmark, reflecting the ability to outperform passive benchmarks through active management [3]. - The calculation of excess return varies based on the chosen strategy and benchmark, with a core formula being: Excess Return = Portfolio Return - Benchmark Return [3]. - An example illustrates that if a quantitative strategy has a return of 25% while the benchmark (e.g., CSI 300) returns 10%, the simple excess return is 15% [3]. Group 2: Sources of Excess Return - Excess return can be categorized into three components: Pure Alpha, Smart Beta, and Beta, each with different characteristics and risk profiles [3]. - The performance of excess return is influenced by external market factors and the comprehensive investment capabilities of the institution, which are critical for assessing a fund's sustainability of returns [3]. Group 3: Brinson Attribution Model - The Brinson attribution model is a widely used method for performance attribution, breaking down excess return into allocation effect, selection effect, and interaction effect [4]. - The model requires detailed portfolio holding data to accurately assess the contributions of asset allocation and stock selection to excess returns [4]. Group 4: Performance Attribution Example - An example using the Brinson model shows a fund outperforming the CSI 300 by 4.2%, with contributions from asset allocation and stock selection analyzed to determine the sources of excess return [9]. - The analysis reveals that stock selection contributes significantly to excess return, indicating a strong capability in identifying high-performing stocks [9]. Group 5: Barra Risk Model - The Barra risk model is utilized for post-performance analysis, helping to identify risk exposures and optimize investment strategies [10][11]. - The model decomposes risk into various factors, allowing for a detailed understanding of how different risk factors contribute to overall portfolio volatility [13]. Group 6: Risk Management and Optimization - The article discusses the importance of managing risk while maintaining return potential, with specific strategies for adjusting factor exposures to enhance performance [15][16]. - It highlights the need for continuous strategy iteration and adaptation to market conditions to mitigate risks associated with excess returns [17].

□本报记者 王雪青 2025年，量化持续成为市场"关键词"。伴随着A股市场震荡上行，单日两万亿元成交额已成常态，量化 产品备案数量同比翻倍，私募江湖风起云涌。平方和投资成立已有十周年，这十年历程，既是行业风雨 的缩影，也是其自身穿越周期的注脚。 回望2015年成立之初，外界对量化投资是否适合中国市场仍存疑问；十年来，平方和投资不仅在策略上 实现了"策略十年、十年长青"，更在业绩方面交出了扎实的成绩单，率先验证了量化方法论在中国市场 的长期有效性。 近日，中国证券报记者专访了平方和投资创始人、总经理吕杰勇。在他位于中关村的办公室，这位亲历 中国量化从萌芽到壮大的资深投资者，分享了他一路走来的成长与感悟。 初心如磐：深耕中国市场 一切的起点源于1999年。这一年，吕杰勇考入北京大学数学科学学院。在这里，他不仅被数学的纯粹与 理性深深吸引，更从知名量化投资者詹姆斯·西蒙斯的实践中获得启发：数学不仅能在公式推导中展现 优势，也可以成为优化金融市场效率的工具。一颗量化投资的种子，就此在他心中扎根。 "我始终觉得，量化投资是科学的价值发现方法论，能让市场更有效率，而且衍生品工具在中国市场肯 定是未来的大方向。"站在公司十 ...

谁都不会想到，那个无数人用来种草护肤品、寻找旅游攻略的小红书，竟会埋藏着一桩惊天金融案的导火索。 2023年的某一天，时年34岁的清华学霸吴舰，在平台上发布了一篇看似普通的炫耀帖——"不敢发朋友圈，自己心 态还是太年轻，想找个没人认识的地方偷偷炫耀下……" 轻描淡写的几句话背后，是一张令人瞠目结舌的薪酬截图：2350万美元，折合人民币约1.67亿元。 这个数字是什么概念？ 甚至相当于顶级对冲基金高管年薪的数倍，或超过了知名投资银行CEO的薪酬水平。 相比吴舰往年的收入水平，2022年的这笔报酬出现了难以解释的倍数级增长。在量化投资这个讲究平稳回报的行 业，这样的薪酬波动就是一个巨大的警报。 很快，这篇帖子在量化金融圈内流传。 业内人士的疑惑与质疑声渐起。 它相当于一个普通北上广深白领工作上千年的总收入；足以买下一整栋豪华公寓楼；甚至超过了某些上市公司一 整年的净利润。 即便在遍地富豪的华尔街，这也是一个令人侧目的数字。 一个年仅34岁的量化研究员，即便再优秀，何以能获得如此惊人的报酬？ 是做出了革命性的模型突破？还是管理了异常成功的基金产品？ 抑或是……另有隐情？ 这些疑问后来终是传到了Two Sigma高管 ...

谁都不会想到，那个无数人用来种草护肤品、寻找旅游攻略的小红书，竟会埋藏着一桩惊天金融案的导火索。 2023年的某一天，时年34岁的清华学霸吴舰，在平台上发布了一篇看似普通的炫耀帖——"不敢发朋友圈，自己心 态还是太年轻，想找个没人认识的地方偷偷炫耀下……" 轻描淡写的几句话背后，是一张令人瞠目结舌的薪酬截图：2350万美元，折合人民币约1.67亿元。 吴舰分享在网络上的照片 这个数字是什么概念？ 它相当于一个普通北上广深白领工作上千年的总收入；足以买下一整栋豪华公寓楼；甚至超过了某些上市公司一 整年的净利润。 即便在遍地富豪的华尔街，这也是一个令人侧目的数字。 甚至相当于顶级对冲基金高管年薪的数倍，或超过了知名投资银行CEO的薪酬水平。 相比吴舰往年的收入水平，2022年的这笔报酬出现了难以解释的倍数级增长。在量化投资这个讲究平稳回报的行 业，这样的薪酬波动就是一个巨大的警报。 很快，这篇帖子在量化金融圈内流传。 业内人士的疑惑与质疑声渐起。 一个年仅34岁的量化研究员，即便再优秀，何以能获得如此惊人的报酬？ 是做出了革命性的模型突破？还是管理了异常成功的基金产品？ 抑或是……另有隐情？ 这些疑问后来终是传到 ...

Core Insights - In 2025, quantitative investment has become a key term in the capital market, with a significant increase in trading volume and the number of registered quantitative products doubling year-on-year [1] - Square and Investment celebrates its tenth anniversary, marking a decade of growth and resilience in the quantitative investment sector in China [1][6] - The founder, Lv Jieyong, emphasizes the effectiveness of quantitative methodologies in the Chinese market, showcasing the company's solid performance over the years [1][6] Company Development - Square and Investment was established in 2015 amidst skepticism about the suitability of quantitative investment for the Chinese market, but has since proven its long-term effectiveness [1][6] - The company has maintained a consistent strategy framework while continuously iterating and evolving its investment strategies over the past decade [10][11] - The firm currently manages around 10 billion yuan, benefiting from scale effects and focusing on mid-to-low frequency strategies [12][14] Industry Context - The quantitative investment industry has faced several crises, which have also presented opportunities for growth, as seen in the company's ability to thrive during market downturns [8][9] - The firm has adapted to regulatory changes, emphasizing the importance of solid alpha generation capabilities as arbitrage opportunities diminish [14][15] - The introduction of new regulations in July 2025 is expected to enhance the standardization of quantitative private equity management, aligning with the company's long-term strategy [14] Future Outlook - The company aims to become a leading player in the global quantitative investment landscape, aspiring to be "China's Renaissance" in this field [6][13] - The recent addition of partner Fang Zhuangxi is expected to enhance the firm's research capabilities and drive further innovation in factor and portfolio optimization [13][14] - Square and Investment is committed to maintaining a focus on steady and sustainable growth while leveraging its decade-long experience in the A-share market to navigate future challenges [15]

Core Insights - In 2025, quantitative investment has become a key term in the capital market, with A-shares experiencing significant fluctuations and a transaction volume reaching trillions, leading to a doubling of the number of registered quantitative products compared to the previous year [1] - Square and Investment celebrates its tenth anniversary, marking a decade of growth and resilience in the quantitative investment sector, demonstrating the long-term effectiveness of quantitative methodologies in the Chinese market [1][3] Company Development - Square and Investment was founded in 2015 amidst skepticism about the suitability of quantitative investment for the Chinese market, but has since proven its strategies and delivered solid performance [1][3] - The company has maintained a consistent strategy framework while continuously iterating and evolving its methodologies, which has allowed it to create stable returns for investors [6][7] - The firm has experienced significant growth during market crises, leveraging its strategies and rigorous risk management to navigate challenges effectively [4][5] Strategy and Performance - The company primarily employs mid-to-low frequency strategies, with a current management scale of around 10 billion yuan, optimizing its capacity for returns [2][7] - Square and Investment has enhanced its computational power by approximately 2.3 times this year, enabling efficient testing of investment ideas and supporting robust research capabilities [7] - The firm emphasizes the importance of a solid risk management framework, which has evolved to include multi-dimensional risk assessments and a self-developed Bsim system for trade execution [6][9] Future Outlook - Looking ahead, Square and Investment aims to not only become a leader in China's quantitative investment space but also to establish itself globally [7][8] - The company is adapting to regulatory changes in the industry, focusing on sustainable alpha generation and reducing reliance on high-leverage strategies [8][9] - With the addition of new talent and a commitment to enhancing its research capabilities, Square and Investment is poised to navigate the evolving competitive landscape effectively [7][9]

Core Insights - SNOW Quantitative has initiated a nationwide experience center strategy, marking a significant shift in the quantitative investment industry towards offline services, allowing ordinary investors to experience professional quantitative investment services face-to-face [1] Group 1: Experience Center Strategic Planning - The first flagship experience centers will be established in major cities such as Beijing, Shanghai, Guangzhou, and Shenzhen, with plans to expand to all provincial capitals by 2024 and key prefecture-level cities by 2025 [3] - The experience centers will feature various functional areas, including strategy experience zones, educational lecture areas, VIP consultation rooms, and technology display zones [3] - Technical support will include cloud synchronization for real-time data updates, VR technology for strategy demonstrations, and self-service terminals for 24-hour assistance [3] Group 2: User Experience Enhancement - Services will be upgraded to include face-to-face consultations with professional investment advisors, hands-on guidance for quantitative investment operations, and real-time answers to investment queries [4] - Educational initiatives will involve weekly investment knowledge lectures, master classes with industry experts, and a simulated trading environment for practice [4] - Social features will include investor salons for networking, strategy sharing sessions, and the establishment of localized investment communities [4] Group 3: Strategic Value Analysis - The experience centers will enhance user trust through physical locations, increase conversion rates via personal experiences, and promote word-of-mouth marketing through offline events [4] - Brand building will be supported by physical displays that enhance brand image, reinforce professional reliability, and deepen market penetration [4] - The centers will offer personalized services, deeper customer engagement, and foster long-term client relationships [4] Group 4: Technological Innovation and Integration - The integration of online and offline services will ensure seamless data connectivity and consistent service experiences [5] - Smart technologies will be applied, including facial recognition for VIP clients, intelligent recommendations based on user profiles, and remote assistance from experts [5] - Data security measures will include local encryption, multiple layers of network security, and strict privacy protection protocols [5] Group 5: Industry Development Impact - The initiative will innovate service models in the quantitative investment sector, establish new industry service standards, and redefine competitive dynamics [5] - Enhanced operational transparency through physical locations will facilitate regulatory compliance and promote industry standardization [5] - The experience centers will drive related industry development, create new job opportunities, and stimulate regional economic growth [5] Group 6: Future Development Plans - Future upgrades will include the deployment of AI investment advisor assistants, deeper applications of big data analytics, and the use of IoT technologies to enhance user experiences [5] - Plans for service expansion include establishing overseas experience centers and deep collaborations with financial institutions [5] - The initiative aims to promote investor education, enhance financial inclusivity, and drive overall industry progress [5] Conclusion - The SNOW Quantitative experience center strategy represents a milestone in the development of the quantitative investment industry, breaking down barriers and making quantitative investment more accessible to ordinary investors, thus promoting the democratization of investment [5]