基金经理研究系列报告之七十：民生加银杨林：持续迭代维持竞争力，多维因子+AI技术增厚收益

1. Report Industry Investment Rating There is no information provided regarding the industry investment rating in the given content. 2. Core Viewpoints of the Report - The report focuses on the analysis of fund manager Yang Lin from Minsheng Jiachen Fund. Yang Lin has over 13 years of experience in the securities industry and about 1.6 years as an investment manager. His investment framework is a multi - dimensional AI quantitative investment framework that continuously iterates and evolves. He makes full use of various information, constructs factors through both manual and machine - learning methods, and applies AI technology in multiple dimensions [3][7][9]. - The representative product, Minsheng Jiachen Smart Selection Growth, has shown excellent performance in the active equity category. Since its establishment until June 27, 2025, it has achieved a return of 27.94%, ranking in the top 20% of active equity products. It also has a relatively low volatility and a high return - risk ratio [3][29]. - The product has distinct investment characteristics. Its overall position is similar to the combination of CSI 500 and CSI 1000, with low individual - stock concentration, small industry over - or under - weighting, and a focus on small - and medium - cap stocks without micro - cap stocks. Trading turnover may be the main source of its income [3][43][53]. 3. Summary Based on the Table of Contents 3.1 Fund Manager Overview - Yang Lin is a CFA, with a bachelor's degree in finance from Xi'an Jiaotong University and a master's degree in financial mathematics from the University of Warwick. He has held various positions in different financial institutions and joined Minsheng Jiachen Fund in October 2019. Currently, he manages one product. His fund manager index lagged slightly behind the CSI 300 before September 2024 due to the small - cap style of the products he managed but has significantly outperformed the CSI 300 since then [3][7]. 3.2 Investment Framework: A Continuously Iterating and Evolving Multi - dimensional AI Quantitative Investment Framework - Yang Lin uses multiple dimensions of information to create effective investment factors. He constructs factors through both manual and machine - learning methods. Manual factors include fundamental (about 20%) and price - volume factors (about 40%), mainly for longer - term factors, while machine - learning processes relatively short - term price - volume factors (about 40%). The ratio of long/medium/short/ultra - short - term factors is about 2:2:3:3 [9][11]. - AI technology is applied in multiple dimensions of his investment framework, such as in ultra - short - term factor construction, manual stock - selection, and comprehensive data processing [11]. - Yang Lin believes that continuous iteration is crucial for maintaining competitiveness. He iterates his models in three dimensions: data, model, and training. He has iterated his quantitative strategies multiple times in the past few years, with an optimization frequency of 1 - 2 times a year, and only implements new strategies in real - time after verifying their superiority [14][15]. 3.3 Representative Product: Minsheng Jiachen Smart Selection Growth - The product was established in June 2024, managed by Cai Xiao and Yang Lin. Its goal is to use a quantitative investment model to achieve long - term stable appreciation of fund assets while controlling risks. It has a management fee rate of 1.20% and a custody fee rate of 0.20% [18]. - In actual operation, it uses a stock strategy of "50% weight of CSI 500 - like all - market enhancement + 50% weight of CSI 1000 - like all - market enhancement". Its holdings are consistent with this positioning, with about half of the holdings being CSI 500 component stocks and about 40% being CSI 1000 component stocks [20]. - Due to the adoption of the high - order PB - ROE framework, the product shows a significant low - PB characteristic in its holdings. Its weighted average PB in 24H2 full - position and 25Q1 heavy - position stocks is in the lower 9.1% and 1.8% levels respectively among active equity products, while ROE is around the 20% quantile [21]. 3.4 Performance Analysis of Minsheng Jiachen Smart Selection Growth - Performance in the Same Category: The product's return since its establishment (as of June 27, 2025) is 27.94%, ranking in the top 20% of active equity products. Its annualized volatility is 24.80%, in the lower - middle level among active equity products. Its annualized Sharpe ratio is 1.18, and the Calmar ratio is 2.40, both ranking around the top 10% [29]. - Relative Performance: Compared with the composite index of "45% CSI 500 + 45% CSI 1000+10% ChinaBond New Composite Wealth (Total Value)", the product has significantly outperformed the composite index since November 2024. From October 2024 to June 2025, its monthly winning rate is 77.8%, and the average monthly excess return is 0.34% [33][37]. 3.5 Investment Characteristic Analysis of Minsheng Jiachen Smart Selection Growth - Positioning Characteristics: The product has a highly diversified individual - stock position. The proportion of the top ten stocks in 24H2 full - position is only about 6%, and the top thirty is about 17%. It focuses on small - and medium - cap stocks without micro - cap stocks, strictly controlling non - linear market - value exposure [43][48]. - Industry Distribution: Compared with the industry distribution of CSI 500 and CSI 1000, the product slightly over - weights industries such as basic chemicals, machinery, and environmental protection, and slightly under - weights industries such as electronics, power equipment, and media, with a small overall over - or under - weighting range [49]. - Income Source: Using the Brinson model to split the fund's income, trading has made a significant contribution to the product's excess return since its management, while other income sources contribute less. The product's relatively high turnover rate suggests that trading turnover may be the main reason for its leading performance. The product's absolute income comes from various sectors, with financial real - estate and technological innovation contributing more, and it also has a strong ability to obtain relative income in these sectors [51][53].