专题：资本市场大咖2026新春献词：骏马踏春来 驭势稳行启新程 编者按：辞旧迎新，金马贺岁。值此新春佳节，新浪财经特邀公私募领域数十位领军人物，通过镜头与 文字，为投资者送来马年新春祝福。信心如磐，笃行致远。愿这一声声真挚寄语，伴您策马扬鞭，共赴 投资长路。 因诺（上海）资产管理有限公司创始人、投资总监徐书楠送来新春祝福。他表示，展望2026年，因诺将 继续坚持长期稳健的底色，依托十年AI积淀，推动大模型更深度地服务投研体系，将前沿能力沉淀为 更扎实的研究与实盘能力，持续打造多策略体系，力争为投资者带来更稳健、更可持续的长期体验与回 报。新的一年，愿大家行稳致远、马到功成。 专题：资本市场大咖2026新春献词：骏马踏春来 驭势稳行启新程 编者按：辞旧迎新，金马贺岁。值此新春佳节，新浪财经特邀公私募领域数十位领军人物，通过镜头与 文字，为投资者送来马年新春祝福。信心如磐，笃行致远。愿这一声声真挚寄语，伴您策马扬鞭，共赴 投资长路。 因诺（上海）资产管理有限公司创始人、投资总监徐书楠送来新春祝福。他表示，展望2026年，因诺将 继续坚持长期稳健的底色，依托十年AI积淀，推动大模型更深度地服务投研体系，将前沿能力沉 ...

Core Insights - The core viewpoint of the article highlights the performance of various investment strategies in 2025, particularly the growth-oriented selected portfolio which achieved a cumulative return of 84.1%, significantly outperforming the 885001 index by 50.9% [1]. Group 1: Performance Analysis - In 2025, the growth-oriented selected portfolio showed the best performance among active quantitative portfolios, with a net cumulative return of 84.1%, surpassing the cumulative excess returns of the CSI 800 and 885001 indices by 63.2% and 50.9% respectively [1]. - The small-cap style portfolio also performed well, significantly outperforming the CSI 2000 index, while the high-dividend style portfolio had a weaker performance with a cumulative return of 15.0%, underperforming the CSI 800 index but exceeding the corresponding CSI dividend index [1]. Group 2: Strategy Enhancement - The monthly rebalancing index-enhanced portfolio constructed based on a linear multi-factor model showed that the ICIR weighted method significantly outperformed the IC mean weighted method in 2025 [2]. - Under the IC mean weighted method, the excess returns for the CSI 300, CSI 500, CSI 1000, and CSI A500 index enhancement strategies relative to their benchmark indices were 6.8%, 3.1%, 5.1%, and 4.8% respectively, while the ICIR weighted method yielded excess returns of 10.7%, 9.5%, 10.2%, and 13.2% [2]. - To improve the performance of index-enhanced portfolios in a challenging excess return environment, a multi-strategy approach was proposed, consisting of a basic index enhancement strategy (60% weight), an intra-domain satellite strategy focusing on momentum and fundamental factors (30% weight), and an extra-domain satellite strategy targeting small-cap high-growth stocks (10% weight), resulting in an annualized return improvement of 3.6% compared to the basic strategy [2].

Quantitative Models and Construction Quantitative Models and Construction Process 1. **Model Name**: Linear Multi-Factor Model for Index Enhancement - **Construction Idea**: The model is based on a linear multi-factor framework, incorporating style, price-volume, and fundamental factors to construct monthly rebalanced index enhancement portfolios for major indices like CSI 300, CSI 500, CSI 1000, and CSI A500[41][42] - **Construction Process**: - Factors used include size, mid-cap, reversal, volatility, turnover, PB, ROE, SUE, R&D ratio, adjusted net profit expectations, analyst coverage, and others[41] - Risk control constraints include limits on size, valuation, individual stock, and industry deviations[42] - Two weighting methods are tested: IC mean weighting and ICIR weighting. ICIR weighting considers factor volatility, aiming for more stable performance[42][57] - **Evaluation**: ICIR weighting outperforms IC mean weighting, especially in recent years when factor returns have declined, and volatility has increased[57][44] 2. **Model Name**: Composite Strategy for CSI 300 Index Enhancement - **Construction Idea**: Combines multiple strategies to improve performance by allocating weights to different sub-strategies[60][53] - **Construction Process**: - The composite strategy consists of three components: 1. **Base Index Enhancement Strategy** (60% weight) 2. **In-Scope Satellite Strategy** (30% weight), focusing on momentum and fundamental factors 3. **Out-of-Scope Satellite Strategy** (10% weight), targeting small-cap, high-growth stocks[60][53] - Monthly rebalancing is applied to the portfolio[60] - **Evaluation**: The composite strategy improves annualized returns by 3.6% compared to the base strategy, with higher stability across years. However, relative drawdowns may increase in certain years[55][60] --- Model Backtesting Results Linear Multi-Factor Model for Index Enhancement 1. **CSI 300 Index**: - IC Mean Weighting: Annualized excess return 10.0%, tracking error 5.1%, IR 1.85[45] - ICIR Weighting: Annualized excess return 11.1%, tracking error 5.2%, IR 2.01[45] - 2025 Results: IC Mean Weighting excess return 6.8%, ICIR Weighting excess return 10.7%[57][45] 2. **CSI 500 Index**: - IC Mean Weighting: Annualized excess return 11.0%, tracking error 5.1%, IR 2.08[46] - ICIR Weighting: Annualized excess return 12.3%, tracking error 4.7%, IR 2.53[46] - 2025 Results: IC Mean Weighting excess return 3.1%, ICIR Weighting excess return 9.5%[57][46] 3. **CSI 1000 Index**: - IC Mean Weighting: Annualized excess return 14.8%, tracking error 5.4%, IR 2.67[47] - ICIR Weighting: Annualized excess return 17.4%, tracking error 5.0%, IR 3.39[47] - 2025 Results: IC Mean Weighting excess return 5.1%, ICIR Weighting excess return 10.2%[57][47] 4. **CSI A500 Index**: - IC Mean Weighting: Annualized excess return 7.7%, tracking error 4.5%, IR 1.67[49] - ICIR Weighting: Annualized excess return 10.3%, tracking error 4.5%, IR 2.21[49] - 2025 Results: IC Mean Weighting excess return 4.8%, ICIR Weighting excess return 13.2%[57][49] Composite Strategy for CSI 300 Index Enhancement 1. Annualized excess return: 12.2%, compared to 8.6% for the base strategy[55] 2. Information ratio: Improved from 1.56 (base strategy) to 1.93 (composite strategy)[55] 3. 2025 Results: The composite strategy mitigated drawdowns during periods of small-cap and low-valuation factor underperformance, outperforming the base strategy[56][60] --- Quantitative Factors and Construction Quantitative Factors and Construction Process 1. **Factor Name**: Small-Cap Factor - **Construction Idea**: Captures the performance of small-cap stocks relative to the market[50] - **Construction Process**: - Exposure to small-cap stocks is measured and incorporated into the portfolio construction process - The factor contributed 3.7% to the excess return of the CSI 300 enhancement strategy in 2025[50][57] 2. **Factor Name**: SUE (Standardized Unexpected Earnings) - **Construction Idea**: Measures earnings surprises to identify stocks with positive earnings momentum[50] - **Construction Process**: - SUE is calculated and used as a factor in the multi-factor model - Higher exposure to SUE contributed positively to the ICIR-weighted portfolio in 2025[50][57] 3. **Factor Name**: R&D Ratio - **Construction Idea**: Reflects the intensity of research and development investment as a proxy for innovation[50] - **Construction Process**: - R&D ratio is calculated and included in the factor set - The factor contributed positively to the ICIR-weighted portfolio in 2025[50][57] --- Factor Backtesting Results 1. **Small-Cap Factor**: Contributed 3.7% to the excess return of the CSI 300 enhancement strategy in 2025[50][57] 2. **SUE Factor**: Contributed 2.75% to the excess return of the ICIR-weighted portfolio in 2025[50][57] 3. **R&D Ratio Factor**: Contributed 0.88% to the excess return of the ICIR-weighted portfolio in 2025[50][57]

Group 1 - The report highlights the limitations of traditional multi-factor models, which face inherent path dependency and structural mismatches, leading to a dilution of returns and an inability to capture high elasticity styles [2][25][26] - The report proposes a dual-driven solution based on XGBoost non-linear prediction and high elasticity alpha extraction, achieving an annualized excess return of 20.0% across ten market segments with an information ratio of 3.78 [3][4] - The integration of high elasticity strategies significantly enhances the performance of traditional index-enhanced models, with annualized excess returns improving by 2.1% to 4.7% compared to single strategies [4][12][19] Group 2 - The report discusses the challenges faced by traditional multi-factor models, particularly their reliance on historical data and the inability to adapt to changing market structures, which can lead to systematic failures during specific market conditions [21][22][25] - It emphasizes the non-normal distribution of returns in the market, where excess returns are often concentrated in a few stocks, contradicting the diversification philosophy of traditional models [26][28][29] - The analysis reveals that the performance of quantitative strategies is closely tied to specific style factors, indicating a path dependency that can hinder adaptability in dynamic market environments [32][34][37]