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 Insights - The A-share market and global asset rotation have revitalized the fund advisory industry in 2025, with notable performance from star advisory combinations achieving average returns of 27.27% and 18.45% respectively [1][4] Group 1: A-share Market Performance - In October 2025, the A-share market showed positive performance, with the Shanghai Composite Index surpassing 4000 points and a monthly increase of 1.85%. Net inflows into stock ETFs exceeded 100 billion [2] - All 16 star fund advisory combinations focused on A-shares achieved positive returns in the first ten months of 2025, with an average return of 27.27%. The top performer was the China Europe Wealth's China Europe Super Stock All-Star with a return of 35.52% [2][3] - The top three combinations have made recent adjustments in their portfolios, focusing on sectors benefiting from global liquidity improvements and increasing allocations in areas like pharmaceuticals, electronics, and new consumption [2] Group 2: Global Asset Performance - A total of 26 global asset allocation fund advisory combinations reported positive returns in the first ten months of 2025, with an average net value increase of 18.45%. The top performer was the Guotai Fund's Guotai Progress Global Allocation with a return of 34.37% [4] - The global asset combinations have been expanding since 2023, with some achieving over 60% returns since inception, demonstrating the sustained advantages of global multi-asset strategies [4] Group 3: Dual Advisory Model - The dual advisory model, a collaboration between fund companies and brokerages, is gaining traction in 2025, allowing for a division of responsibilities where fund companies provide strategies and brokerages handle client outreach and sales [5][6] - This model is particularly appealing to small and medium-sized brokerages, enabling them to quickly adopt established strategies without incurring high research and development costs [6] - Despite the advantages, challenges exist, such as increased communication costs and the need for brokerages to make strategic decisions regarding reliance on external strategies versus developing their own [6][7]