Quantitative Models and Construction Methods 1. Model Name: "Risk Preference-Concentration-Turnover" Three-Dimensional Label Classification System - **Model Construction Idea**: The model aims to classify multi-asset fund advisory products based on three dimensions: risk preference, concentration, and turnover rate, to better understand their risk-return characteristics and performance differentiation[3][32] - **Model Construction Process**: - **Risk Preference**: Classified based on the proportion of income-generating assets and growth assets in the portfolio. If income-generating assets exceed 70%, it is classified as debt-oriented; if growth assets exceed 70%, it is equity-oriented; otherwise, it is balanced[34] - **Concentration**: Measured using the Herfindahl-Hirschman Index (HHI), calculated as $ \sum_{i} w_{i}^{2} $, where $w_{i}$ represents the weight of each asset class. Thresholds are set as follows: HHI > 0.5 is high concentration, HHI < 0.25 is low concentration, and values in between are medium concentration[34] - **Turnover Rate**: Measures the timing adjustment ability of multi-asset fund advisory products at the asset class level. Annualized one-sided turnover rate is used, with thresholds defined as follows: turnover rate > 2 is high turnover, < 1 is low turnover, and values in between are medium turnover[34] - **Model Evaluation**: The model effectively captures the heterogeneity in multi-asset fund advisory products and provides insights into their risk-return characteristics and strategic differences[3][34] --- Model Backtesting Results 1. "Risk Preference-Concentration-Turnover" Three-Dimensional Label Classification System - **Risk Preference**: - Equity-oriented products: 2025 annualized return 18.5%, 2024 annualized return 10.5%, 2023 annualized return -1.0%[37][39] - Debt-oriented products: 2025 annualized return 7.4%, 2024 annualized return 5.9%, 2023 annualized return 3.9%[37][39] - Balanced products: 2025 annualized return 15.7%, 2024 annualized return 8.8%, 2023 annualized return -4.7%[37][39] - **Concentration**: - Low concentration (HHI < 0.25): 2025 annualized return 17.7%, 2024 annualized return 8.2%, 2023 annualized return 0.4%[37][39] - Medium concentration (0.25 ≤ HHI ≤ 0.5): 2025 annualized return 13.0%, 2024 annualized return 6.9%, 2023 annualized return -4.0%[37][39] - High concentration (HHI > 0.5): 2025 annualized return 7.8%, 2024 annualized return 6.9%, 2023 annualized return 3.9%[37][39] - **Turnover Rate**: - Low turnover (< 1): 2025 annualized return 15.6%, 2024 annualized return 8.8%, 2023 annualized return 1.7%[37][39] - Medium turnover (1 ≤ turnover ≤ 2): 2025 annualized return 10.6%, 2024 annualized return 7.3%, 2023 annualized return 0.5%[37][39] - High turnover (> 2): 2025 annualized return 11.2%, 2024 annualized return 7.6%, 2023 annualized return -5.4%[37][39] --- Quantitative Factors and Construction Methods 1. Factor Name: Brinson Attribution Model - **Factor Construction Idea**: The model decomposes the excess return of multi-asset fund advisory products into two components: allocation return and selection return, to evaluate the sources of excess returns[42][46] - **Factor Construction Process**: - **Allocation Effect**: Measures the timing and allocation ability of fund managers across major asset classes. The formula is: $$ R_{allocation} = \sum_{i} (w_{i}^{actual} - w_{i}^{benchmark}) \times r_{i}^{asset} $$ where $w_{i}^{actual}$ is the actual weight of asset $i$, $w_{i}^{benchmark}$ is the benchmark weight, and $r_{i}^{asset}$ is the return of asset $i$[42][46] - **Selection Effect**: Reflects the ability to select superior funds within each asset class. The formula is: $$ R_{selection} = R_{excess} - R_{allocation} $$ where $R_{excess}$ is the total excess return relative to the benchmark[42][46] - **Factor Evaluation**: The model provides a clear decomposition of excess returns, helping to identify whether returns are driven by strategic asset allocation or fund selection[42][46] --- Factor Backtesting Results 1. Brinson Attribution Model - **Equity-Oriented Products**: - Example: "Guotai Global Allocation" achieved 2025 allocation return of 10.5% and selection return of 6.3%[48][49] - Example: "招商海外掘金" achieved 2025 allocation return of -0.8% and selection return of 14.5%[48][49] - **Debt-Oriented Products**: - Example: "嘉实百灵全天候策略" achieved 2025 allocation return of 3.8% and selection return of 0.5%[56][58] - Example: "全球固收+" achieved 2025 allocation return of 2.6% and selection return of 1.3%[56][58] - **Balanced Products**: - Example: "时光旅行者" achieved 2025 allocation return of 15.6% and selection return of -10.3%[65][66] - Example: "绘盈长投计划" achieved 2023 allocation return of 10.1%, providing a strong safety net during a bear market[65][66]

Core Viewpoint - The traditional model of relying on individual and star fund managers in public fund management is facing significant challenges as the asset management industry transitions into a more systematic and disciplined "industrialized" era [1][2] Group 1: Transition to FOF 2.0 Era - The FOF investment approach is evolving from a focus on selecting individual fund managers (1.0 era) to a diversified asset and strategy allocation (2.0 era) [2] - The new phase emphasizes providing clients with a one-stop asset allocation solution rather than merely achieving relative rankings [2][3] - A systematic investment philosophy is being developed, which is not just a simple combination of macro, strategy, and industry research but a set of rules and processes aimed at achieving performance that is historically explainable, currently replicable, and future-optimizable [2][3] Group 2: Investment Framework - The investment framework consists of four steps: 1. Identifying investable tools by including a wide range of global assets and strategies, analyzing their win rates, odds, and functional roles [3] 2. Strategic allocation based on clear quantitative rules to determine long-term weightings for various assets [3] 3. Tactical allocation using objective timing and position management models to adjust initial weights for enhanced returns [3] 4. Real-time attribution monitoring to dissect the sources of returns and risks daily, ensuring adherence to the initial investment goals [3] Group 3: Risk Management Philosophy - The core investment philosophy emphasizes "risk management first, then asset allocation," focusing on managing risks before predicting asset performance [4] - The aim is to avoid significant mistakes and then enhance portfolio returns, differentiating from traditional stock and bond products [4][5] Group 4: Role of FOF - FOF is viewed not just as a product but as a service that bridges asset management institutions and sales channels, enhancing client experience [6] - Internally, FOF teams provide valuable insights for strategic planning and product development based on their market understanding [6] - Externally, FOF serves as a key link between asset management and wealth management institutions, especially as banks transition to client-centered asset allocation services [6]

Core Viewpoint - The traditional model of relying on individual and star fund managers in public fund management is facing significant challenges as the asset management industry transitions into a more systematic and disciplined "industrialized" era [1][2] Group 1: Transition to FOF 2.0 Era - The FOF investment approach is evolving from a focus on selecting individual fund managers (1.0 era) to a diversified asset and strategy allocation (2.0 era) [2] - The new phase emphasizes providing clients with a one-stop asset allocation solution rather than merely achieving relative rankings [2][3] Group 2: Investment Philosophy and Strategy - The investment framework consists of four steps: 1. Identifying investable tools by including a wide range of global assets and strategies, analyzing their win rates and roles in the portfolio [3] 2. Strategic allocation based on clear quantitative rules to minimize risk [3] 3. Tactical allocation using objective timing and position management models to enhance portfolio returns [3] 4. Real-time attribution monitoring to dissect sources of returns and risks, ensuring adherence to initial investment goals [3] - The philosophy is rooted in a "weakness mindset," acknowledging the difficulty of accurately predicting asset movements, thus favoring low-correlation asset allocation [3] Group 3: Risk Management Focus - The primary investment goal is to achieve stable absolute returns and a reassuring holding experience for both institutional and retail clients [4] - The emphasis is on managing risks first, as indicated by the focus on the Sharpe ratio, which requires controlling risks before enhancing returns [4][5] Group 4: Role of FOF in Asset Management - FOF is viewed as a service that bridges asset management institutions and sales channels, enhancing client experience [5] - Internally, FOF teams provide valuable insights for strategic planning and product development, while externally, they connect asset management and wealth management institutions [5][6] Group 5: Expectations for FOF Fund Managers - FOF fund managers are expected to adopt a systematic approach in research and investment while also focusing on effective communication to enhance client experience [6]