摩根士丹利基金总经理周文秱：打造公募界的纳帕谷“酒庄”，酿造经得起时间检验的“佳酿”

Core Viewpoint - Morgan Stanley Fund aims to create a "boutique winery" in the public fund industry, focusing on producing high-quality investment products that withstand the test of time [2][12][13]. Group 1: Company Overview - Morgan Stanley Fund officially became a wholly foreign-owned public fund company in July 2023, marking its second anniversary [2][8]. - Zhou Wenzhi joined Morgan Stanley Fund in October 2023 as Chief Investment Officer and became General Manager in May 2024, bringing extensive cross-market experience [4][6]. Group 2: Investment Research and Strategy - Investment research is considered the "ballast" and "first productivity" of the fund company, with a focus on diversifying and clarifying investment strategies [9][10]. - The company emphasizes a long-term performance assessment, aligning fund manager styles with product risk-return characteristics to avoid style drift [9][10]. - Morgan Stanley Fund has established a collaborative mechanism with global teams, enhancing local investment insights with international perspectives [10][11]. Group 3: Product Development and Market Positioning - The fund aims to develop a unique global multi-asset allocation strategy, focusing on competitive returns with manageable risks [14]. - The company is committed to long-term themes in sectors like AI and pharmaceuticals, ensuring resource allocation aligns with sustainable competitive advantages [14][15]. - The fixed income team has consistently ranked among the top in the industry, with a strong focus on risk and return balance [15]. Group 4: Market Outlook and Challenges - The public fund industry in China is undergoing a transformation, with opportunities arising from structural market characteristics [19][20]. - Zhou Wenzhi identifies three core challenges: rediscovering the value of active management, improving industry talent retention, and enhancing investor education [20][21]. - The company sees significant potential in the A-share market, emphasizing stock selection over index fluctuations, particularly in sectors like AI, consumer upgrades, and pharmaceutical innovation [21][22].