Core Insights - The article highlights the career journey of Hu Di, who has developed a unique perspective on quantitative investment strategies through her experiences in both international and domestic markets [1][5] - Hu Di emphasizes the importance of continuous innovation in quantitative investment, focusing on refining models and exploring new data sources and algorithms to adapt to changing market conditions [1][2] Investment Strategy - Hu Di leads a team at Morgan Asset Management (China) that focuses on a "Core Beta + Enhanced Alpha" framework, aiming to create a product system that balances efficiency and resilience while pursuing long-term risk premiums and stable excess returns [1][5] - The team has identified around 200 commonly used factors, with 40% being fundamental factors, 40% price-volume factors, and the remaining 20% derived from machine learning and alternative factor systems [2][3] Factor Analysis - The team employs a multi-dimensional approach to factor analysis, enhancing traditional methods to capture excess returns more effectively by considering various dimensions of factors like reversal [3][4] - Machine learning techniques are integrated into the factor generation process, leading to a "logic-driven + data-enhanced" paradigm that spans factor discovery, return prediction, and portfolio optimization [3][4] Market Adaptation - Hu Di notes that the impact of U.S. tariff policies on China has diminished over time, and the focus has shifted to diversifying export markets and mitigating external shocks through policy measures [5][6] - The introduction of the Morgan CSI A500 Enhanced Strategy ETF is positioned as a response to current market conditions, prioritizing leading companies in emerging industries while reducing exposure to traditional sectors [6][7] Risk Management - The investment strategy emphasizes strict control over industry and style risks, ensuring that the sources of returns remain independent and minimizing excessive exposure [4][8] - Hu Di advocates for a "core + satellite" asset allocation approach, where core positions are based on stable beta assets adjusted for volatility, while satellite positions target growth or policy-driven assets [8][9] Product Development - The timing of product launches is critical, with successful ETFs launched in 2023 and 2024 showing significant growth in scale, indicating effective market entry strategies [9] - The company prioritizes investor education alongside product offerings, aiming to provide tailored asset allocation solutions based on individual risk preferences and return expectations [9]

超额（相对）收益与绝对收益真的是不可兼得的鱼和熊掌吗？长期主义者会给出不一样的答案——可持续 的超额（相对）收益本质上是绝对收益的时间积分形态。 物理学家费曼说："量子力学之所以难以理解，是因为我们总用经典世界的语言描述它。"资本市场同样如 此——当投资者用线性思维理解非线性的收益获得机制，必然陷入认知困境，如粒子位置与动量不可同时 精确测定一样。 在投资领域同样存在"风险、收益、可持续性"的不确定性三角 ： ★ 宣称高绝对收益者，往往承受隐性尾部风险（长期资本管理公司的陨落）； ★ 标榜可持续性者，常以牺牲收益锐度为代价（固定收益类产品的平庸回报)； ★ 追求超额收益者，难逃时间维度的均值回归（连续跑赢市场的主动管理基金数量了了）。 对投资者而言，就像一场在迷雾中前行的冒险，收益的测不准性让投资领域充满了悬念与变数，许多投资 者陷入"超额（相对）收益与绝对收益对立"的思维困境。 这并非文字游戏，而是数学规律的必然。当某组合每年以2%的幅度持续跑赢标普500指数，30年后的累计 超额收益将高达81.1%，相当于在美股百年长牛的贝塔地基上，用阿尔法的复利魔法建造出一座收益金字 塔。 历史反复验证：当管理人以长期 ...