Core Insights - The index-enhanced funds have become one of the most prominent product lines in the public fund industry this year, showing significant improvement in scale expansion, issuance enthusiasm, and investor attention compared to last year [1][2] Group 1: Market Performance - As of December 5, the number of index-enhanced funds has increased to 459, with a management scale of 276.4 billion, up from 298 funds and 212.8 billion at the beginning of the year, indicating a notable growth in both product quantity and management funds [2][3] - Over 90% of index-enhanced products have achieved positive returns this year, with some products yielding over 50%, such as the Dongcai CSI Nonferrous Metals Index Enhanced A with a return of 74.93% [3] Group 2: Investor Sentiment - There has been a significant change in investor perception regarding index-enhanced funds, with increased recognition of their high allocation value, especially in the context of the current A-share market's excess return potential [4][5] - The positioning of index-enhanced products has shifted from being seen as "optional" to "necessary" within the overall investment strategy, as investors begin to focus more on long-term returns rather than short-term trading [6]

Group 1: Performance of Index Enhancement Portfolios - The CSI 300 index enhancement portfolio achieved an excess return of 0.68% this week and 18.98% year-to-date [8] - The CSI 500 index enhancement portfolio recorded an excess return of 0.13% this week and 7.30% year-to-date [8] - The CSI 1000 index enhancement portfolio had an excess return of 0.77% this week and 15.97% year-to-date [8] - The CSI A500 index enhancement portfolio reported an excess return of 0.87% this week and 9.47% year-to-date [8] Group 2: Factor Performance Tracking - In the CSI 300 component stocks, factors such as quarterly ROE, three-month institutional coverage, and EPTTM performed well [9] - In the CSI 500 component stocks, factors like BP, three-month turnover, and expected BP showed strong performance [12] - For the CSI 1000 component stocks, factors including quarterly EP, expected EPTTM, and EPTTM were notable [15] - In the CSI A500 index component stocks, factors such as quarterly ROE, three-month institutional coverage, and quarterly ROA performed well [18] Group 3: Public Fund Index Enhancement Products Performance - The CSI 300 index enhancement products had a maximum excess return of 1.01%, a minimum of -0.79%, and a median of 0.18% this week [24] - The CSI 500 index enhancement products achieved a maximum excess return of 1.26%, a minimum of -0.76%, and a median of 0.38% this week [27] - The CSI 1000 index enhancement products recorded a maximum excess return of 1.20%, a minimum of -0.85%, and a median of 0.54% this week [29] - The CSI A500 index enhancement products had a maximum excess return of 0.98%, a minimum of -1.14%, and a median of 0.16% this week [33] Group 4: Factor Performance in Public Fund Heavyweight Index - In the public fund heavyweight index, factors such as quarterly ROE, three-month institutional coverage, and quarterly ROA performed well recently [20] - Over the past month, three-month institutional coverage, three-month turnover, and one-month turnover showed strong performance [20] - Year-to-date, factors like quarterly ROE, DELTAROE, and quarterly revenue growth performed well [20]

- The report tracks the performance of Guosen's quantitative enhanced index portfolios and public fund enhanced index products, as well as the performance of common stock selection factors in different stock selection spaces[11][12][15] - Guosen's quantitative enhanced index portfolios are constructed based on multi-factor stock selection, targeting benchmarks such as CSI 300, CSI 500, CSI 1000, and CSI A500 indices, aiming to consistently outperform their respective benchmarks[11][12] - The construction process of Guosen's enhanced index portfolios includes three main components: return prediction, risk control, and portfolio optimization[12] - The MFE (Maximized Factor Exposure) portfolio is used to test the effectiveness of individual factors under real-world constraints, such as industry exposure, style exposure, stock weight deviation, and turnover rate. The optimization model maximizes single-factor exposure while adhering to these constraints[41][42][43] - The MFE optimization model is expressed as follows: $\begin{array}{ll}max&f^{T}\ w\\ s.t.&s_{l}\leq X(w-w_{b})\leq s_{h}\\ &h_{l}\leq H(w-w_{b})\leq h_{h}\\ &w_{l}\leq w-w_{b}\leq w_{h}\\ &b_{l}\leq B_{b}w\leq b_{h}\\ &\mathbf{0}\leq w\leq l\\ &\mathbf{1}^{T}\ w=1\end{array}$ where $f$ represents factor values, $w$ is the stock weight vector, and the constraints include limits on style factor exposure ($X$), industry exposure ($H$), stock weight deviation, and component stock weight proportions ($B_b$)[41][42][43] - The report also evaluates the performance of single-factor MFE portfolios across different stock selection spaces, including CSI 300, CSI 500, CSI 1000, CSI A500, and public fund heavy-holding indices[15][18][20][22][24][26] - The factor library includes over 30 factors categorized into valuation, reversal, growth, profitability, liquidity, volatility, corporate governance, and analyst-related dimensions. Examples include BP (Book-to-Price), single-quarter ROE, one-month reversal, and three-month turnover[16][17] - The public fund heavy-holding index is constructed using the holdings of ordinary stock funds and equity-biased hybrid funds. Stocks are selected based on cumulative weight reaching 90% of the average fund holdings[44] - The report tracks the excess returns of public fund enhanced index products for CSI 300, CSI 500, CSI 1000, and CSI A500 indices. For example, in the CSI 300 enhanced products, the highest weekly excess return was 1.01%, and the highest annual excess return was 11.97%[28][32][35][37][40]

Group 1: Investment Rating of the Reported Industry - No information about the industry investment rating is provided in the report. Group 2: Core Viewpoints of the Report - Multiple - dimensional factors reflect the investment value of the CSI 300 Index, including high market attention, high - quality fundamentals, high dividend cost - effectiveness, and a low proportion of high - gain stocks among its components [2][7]. - CSI 300 index - enhanced funds are more difficult to manage compared to those tracking smaller - cap indices. However, the Guolianan CSI 300 Index - Enhanced Fund balances strong tracking performance and excess returns [2][24]. - The Guolianan CSI 300 Index - Enhanced Fund has low - deviation and flexible industry allocation, with a recent focus on growth and quality [2][39]. Group 3: Summary According to the Table of Contents 1. Multidimensional Factors Reflecting the Investment Value of the CSI 300 - The CSI 300 has high market attention, with its trading volume ratio rising since August 2025 and ranking first among representative broad - based indices as of November 7, 2025 [7]. - It is a high - quality broad - based index with strong profitability quality and stability, matching well with the "PB - ROE" stock - selection strategy [8][10]. - The dividend cost - effectiveness of the CSI 300 is becoming prominent. As of November 7, 2025, its 12 - month dividend rate is 2.54%, exceeding that of CSI 500, CSI 1000, and the 10 - year Treasury yield [17]. - The proportion of high - gain stocks among its components is low, with less than 35% of components having a year - to - date gain of over 20% as of November 7, 2025, and over 50% of components having a gain lower than the index's. Some high - quality stocks are still "waiting to rise" [20]. 2. Guolianan CSI 300 Index - Enhanced Fund: A Product Balancing Enhancement and Tracking Effects 2.1 CSI 300 Index - Enhanced Funds: Difficult to Manage - The difficulty of creating excess returns for index - enhanced funds is ranked as SSE 50 Index - Enhanced > CSI 300 Index - Enhanced > CSI 500 Index - Enhanced > CSI 1000 Index - Enhanced. Since 2020, the average annualized excess returns of SSE 50, CSI 300, CSI 500, and CSI 1000 index - enhanced funds are 0.50%, 1.64%, 2.77%, and 7.12% respectively [24]. - In the past three years, it has been difficult for mid - and large - cap indices represented by the CSI 300 and CSI 500 to create excess returns. The CSI 300 index - enhanced funds still have negative average excess returns this year [26]. 2.2 Guolianan CSI 300 Index - Enhanced Fund: Balancing Strong Tracking and Excess Performance - The fund has achieved positive excess returns this year, with a year - to - date cumulative return of 19.78% and an excess return of 5.06% compared to the CSI 300 Total Return Index. Its performance is relatively good among all CSI 300 index - enhanced funds [27]. - Focusing on tracking effects, it has achieved the highest excess return under a 3% tracking error this year and the lowest tracking error among products with over 3% excess returns. In the long - term, it has maintained a tracking error of less than 3% since its opening for redemptions, with an excellent excess information ratio [28][33]. - It can achieve positive returns in both favorable and unfavorable market conditions. Since its opening for redemptions on March 1, 2024, it has achieved a cumulative return of 2.69% in favorable market conditions while maintaining positive returns in unfavorable conditions [36]. 2.3 Portfolio Characteristics: Flexible Industry Allocation with Low Deviation, Recently Focusing on Growth and Quality - The industry under - or over - allocation amplitude of the fund is relatively low, with the proportion generally within 1%. In the first half of 2024, the industry deviation was significantly low, and it has increased since 2025. The allocation structure of its heavy - position stocks is highly similar to that of the index, with a proportion difference within 0.5% [39]. - Compared with similar products, the allocation deviation of the Guolianan CSI 300 Index - Enhanced Fund is significantly lower. Its individual - stock and industry allocation consistencies are in the top 25% and 15% of similar products respectively [45]. - The fund's factor exposure amplitude is relatively low. Its current portfolio attaches importance to growth, profitability, and analyst expectations, and has a moderate negative exposure in the market - value dimension [46].

Core Insights - The number of index funds in the market is approaching 3000, with a total scale of 6.72 trillion yuan as of Q3 2025, and the number of newly established ETFs has reached a historical high of 328, with a new issuance scale exceeding 250 billion yuan [1] - The index investment sector is facing intensified competition characterized by "issuance wars, fee wars, and scale wars," leading to compressed profit margins for fund companies and decision-making difficulties for investors [1] - Tianhong Fund has differentiated itself by evolving from "tool provider" to "comprehensive solution provider," focusing on unique layouts, stable excess returns, and full-cycle support [1] Differentiated Product Line - Tianhong Fund has adopted a differentiated approach by avoiding the saturated broad-based index market and instead focusing on "forward-looking segmentation + comprehensive core" strategies [2] - The fund has launched products targeting "new productivity" sectors, such as the Tianhong CSI Hong Kong-Shenzhen Cloud Computing Industry Index ETF, which includes both Hong Kong cloud service providers and domestic hardware suppliers [2] - As of Q3 2025, Tianhong's index funds in the photovoltaic industry have nearly 10 billion yuan in scale, with its computer ETF at 2.555 billion yuan and biopharmaceutical ETF at 3.315 billion yuan, leading in their respective categories [2] Index Enhancement Strategy - Tianhong Fund has positioned index enhancement as a core competitive advantage, aiming to create sustainable excess returns for investors [3] - As of Q3 2025, the number of Tianhong's index enhancement funds has reached 19, with a management scale exceeding 12.084 billion yuan, making it one of the few "hundred billion-level index enhancement teams" in the industry [3] - The fund's strategies focus on high-quality risk-adjusted returns, with significant excess returns over peers, such as 19.01% for Tianhong CSI 500 Index Enhancement A over the past five years [3][4] Technology and Investor Support - Tianhong Fund leverages technology to enhance investor services, providing practical tools and full-cycle support to improve decision-making and holding experiences [5] - The fund has introduced a systematic investment plan for the ChiNext index, optimizing investment timing through specific triggers for stopping investments and taking profits [5] - Additionally, Tianhong has developed various grid trading tools to convert professional strategies into tangible returns for investors [6] Market Position and Future Outlook - Tianhong Fund's quantitative and technology teams have created an index analysis module to assist investors in comparing indices effectively [8] - The fund has established a strong presence in the market, with 12.8118 million holders of domestic equity index products, leading the industry [8] - The current phase of index investment in China is shifting towards high-quality development, with a focus on customer value creation, positioning Tianhong Fund to lead in this new stage of "detailed value, strong return quality, and deep customer engagement" [9]

Core Insights - The index fund market is rapidly growing, with nearly 3,000 funds and a total scale of 6.72 trillion yuan by the end of Q3 2025, alongside a record 328 new ETFs launched this year, exceeding 250 billion yuan in new issuance [1] - The industry is facing intensified competition characterized by "issuance wars, fee wars, and scale wars," leading to compressed profit margins for fund companies and decision-making challenges for investors [1] - Tianhong Fund is leveraging its internet-based approach and extensive experience to transition from "tool provision" to "comprehensive solution" offerings, highlighting its unique characteristics in the large index business [1] Differentiated Product Line - Tianhong Fund is avoiding the saturated broad-based index market by adopting a "forward-looking segmentation + comprehensive core" differentiation strategy [2] - The fund has launched products targeting "new productivity" sectors, such as the Tianhong CSI Hong Kong-Shenzhen Cloud Computing Industry Index ETF, which integrates both Hong Kong and domestic computing hardware providers [2] - As of Q3 2025, Tianhong's index products in the photovoltaic industry and other sectors have achieved significant scale, with the Tianhong CSI Photovoltaic Industry ETF nearing 10 billion yuan [2] Index Enhancement Strategy - Tianhong Fund is focusing on index enhancement as a core competitive advantage, aiming to create sustainable excess returns for investors [3] - The fund has 19 index enhancement funds with a total management scale exceeding 12.08 billion yuan, positioning it among the few "hundred billion-level index enhancement teams" in the industry [3] - Performance metrics show that Tianhong's index enhancement products have consistently outperformed industry averages, with notable excess returns over the past several years [3][4] Technology and Investor Engagement - Tianhong Fund is utilizing technology to enhance investor services, addressing common pain points such as "zombie investment" and "difficulty in profit-taking" through innovative investment plans [5] - The fund has introduced improved grid trading tools and developed an index analysis module to assist investors in comparing indices effectively [6][8] - By integrating professional education and deep insights from fund managers, Tianhong Fund has built strong user engagement, leading to a significant number of account holders in its equity index products [8] Market Positioning and Future Outlook - The shift in domestic index investment towards high-quality development emphasizes customer value creation over mere scale competition [9] - Tianhong Fund's model, centered on customer needs, technology, and solution delivery, is expected to lead the index investment sector into a new phase focused on segmentation, quality returns, and deep customer engagement [9]

Group 1 - The performance of the HuShen 300 index enhanced portfolio achieved an excess return of 0.64% this week and 17.85% year-to-date [5][17] - The performance of the Zhongzheng 500 index enhanced portfolio recorded an excess return of 0.00% this week and 7.07% year-to-date [5][17] - The Zhongzheng 1000 index enhanced portfolio had an excess return of 0.21% this week and 14.89% year-to-date [5][17] - The Zhongzheng A500 index enhanced portfolio achieved an excess return of 0.44% this week and 8.26% year-to-date [5][17] Group 2 - In the HuShen 300 constituent stocks, factors such as three-month institutional coverage, one-year momentum, and single-quarter ROE performed well [6][8] - In the Zhongzheng 500 constituent stocks, factors like one-year momentum, expected net profit month-on-month, and DELTAROE showed strong performance [6][8] - For Zhongzheng 1000 constituent stocks, factors such as single-quarter revenue year-on-year growth, DELTAROA, and standardized expected external income performed well [6][8] - In the Zhongzheng A500 index constituent stocks, one-year momentum, standardized expected external profit, and standardized expected external income were strong factors [6][8] Group 3 - The HuShen 300 index enhanced products had a maximum excess return of 2.01%, a minimum of -0.78%, and a median of 0.19% this week [21] - The Zhongzheng 500 index enhanced products recorded a maximum excess return of 0.93%, a minimum of -2.16%, and a median of 0.05% this week [22] - The Zhongzheng 1000 index enhanced products achieved a maximum excess return of 1.47%, a minimum of -0.59%, and a median of 0.39% this week [23] - The Zhongzheng A500 index enhanced products had a maximum excess return of 1.47%, a minimum of -0.59%, and a median of 0.39% this week [24]

Quantitative Models and Construction Methods 1. Model Name: Maximized Factor Exposure Portfolio (MFE) - **Model Construction Idea**: The MFE portfolio is designed to test the effectiveness of single factors under real-world constraints, such as industry exposure, style exposure, stock weight limits, and turnover constraints. This approach ensures that factors deemed effective can genuinely contribute to return prediction in the final portfolio[41][42]. - **Model Construction Process**: - The optimization model aims to maximize single-factor exposure while adhering to various constraints: $$ \begin{array}{ll} \text{max} & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T}w = 1 \end{array} $$ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, \( f^{T}w \) is the weighted exposure of the portfolio to the factor, and \( w \) is the stock weight vector[42]. - **Constraints**: - **Style Exposure**: \( X \) is the factor exposure matrix for stocks, \( w_b \) is the benchmark weight vector, and \( s_l, s_h \) are the lower and upper bounds for style factor exposure[42]. - **Industry Exposure**: \( H \) is the industry exposure matrix, and \( h_l, h_h \) are the lower and upper bounds for industry deviations[42]. - **Stock Weight Deviation**: \( w_l, w_h \) are the lower and upper bounds for individual stock weight deviations from the benchmark[42]. - **Constituent Stock Weight**: \( B_b \) is a 0-1 vector indicating whether a stock is a benchmark constituent, and \( b_l, b_h \) are the lower and upper bounds for constituent stock weights[42]. - **No Short Selling**: Ensures non-negative weights and limits individual stock weights to \( l \)[42]. - **Full Investment**: Ensures the portfolio is fully invested with \( \mathbf{1}^{T}w = 1 \)[43]. - The MFE portfolio is constructed monthly, and historical returns are calculated after accounting for transaction costs of 0.3% on both sides[45]. - **Model Evaluation**: The MFE portfolio effectively tests factor performance under realistic constraints, making it a robust tool for evaluating factor predictability in practical scenarios[41][42]. --- Factor Construction and Methods 1. Factor Name: Momentum (1-Year Momentum) - **Factor Construction Idea**: Measures the momentum effect by capturing the price trend over the past year, excluding the most recent month[18]. - **Factor Construction Process**: - Formula: \( \text{1-Year Momentum} = \text{Cumulative Return over the past 12 months (excluding the last month)} \)[18]. - **Factor Evaluation**: Momentum factors generally perform well in capturing price trends, as evidenced by their positive performance in multiple sample spaces[20][22][24]. 2. Factor Name: DELTAROE - **Factor Construction Idea**: Measures the change in return on equity (ROE) compared to the same quarter in the previous year, reflecting profitability improvement[18]. - **Factor Construction Process**: - Formula: \( \text{DELTAROE} = \text{Current Quarter ROE} - \text{ROE of the Same Quarter Last Year} \)[18]. - **Factor Evaluation**: DELTAROE is effective in identifying companies with improving profitability, as shown by its strong performance in various sample spaces[22][24][26]. 3. Factor Name: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: Measures the deviation of actual earnings from expected earnings, standardized by the standard deviation of expected earnings, to capture earnings surprises[18]. - **Factor Construction Process**: - Formula: \( \text{SUE} = \frac{\text{Actual Quarterly Net Profit} - \text{Expected Net Profit}}{\text{Standard Deviation of Expected Net Profit}} \)[18]. - **Factor Evaluation**: SUE is a reliable indicator of earnings surprises and is particularly effective in growth-oriented sample spaces[18][24]. --- Factor Backtesting Results 1. 1-Year Momentum - **Performance in Different Sample Spaces**: - **CSI 300**: Positive performance in the past week but underperformed in the past month and year-to-date[20]. - **CSI 500**: Strong performance in the past week and year-to-date, with weaker results in the past month[22]. - **CSI 1000**: Underperformed year-to-date but showed strong weekly performance[24]. - **CSI A500**: Mixed results, with strong weekly performance but weaker year-to-date performance[26]. - **Public Fund Heavyweight Index**: Positive weekly performance but underperformed year-to-date[28]. 2. DELTAROE - **Performance in Different Sample Spaces**: - **CSI 300**: Strong year-to-date performance, with mixed results in the past week and month[20]. - **CSI 500**: Positive weekly and year-to-date performance, with weaker results in the past month[22]. - **CSI 1000**: Strong weekly and year-to-date performance, with weaker results in the past month[24]. - **CSI A500**: Positive weekly and year-to-date performance, with weaker results in the past month[26]. - **Public Fund Heavyweight Index**: Positive weekly and year-to-date performance, with weaker results in the past month[28]. 3. SUE - **Performance in Different Sample Spaces**: - **CSI 300**: Not explicitly mentioned in the report[18]. - **CSI 500**: Not explicitly mentioned in the report[18]. - **CSI 1000**: Not explicitly mentioned in the report[18]. - **CSI A500**: Not explicitly mentioned in the report[18]. - **Public Fund Heavyweight Index**: Not explicitly mentioned in the report[18]. --- Quantitative Model Backtesting Results 1. MFE Portfolio - **Performance in Different Sample Spaces**: - **CSI 300**: Weekly excess return of 0.64%, year-to-date excess return of 17.85%[15]. - **CSI 500**: Weekly excess return of 0.00%, year-to-date excess return of 7.07%[15]. - **CSI 1000**: Weekly excess return of 0.21%, year-to-date excess return of 14.89%[15]. - **CSI A500**: Weekly excess return of 0.44%, year-to-date excess return of 8.26%[15].

1. Report Industry Investment Rating No relevant content provided. 2. Core View of the Report - As of October 31, 2025, Tianhong Fund has 18 index - enhanced products with a total management scale of 11.947 billion yuan. The product line comprehensively covers broad - based and industry indices, with a leading number of products in the market [2][5]. - Tianhong Fund's index - enhanced products have shown excellent long - term historical performance and outstanding performance this year. The company's unified quantitative system supports a high - consistency performance output ability [18][23]. - Tianhong Fund has a continuously iterative investment framework, a new paradigm of index - enhanced investment with high AI content, and is building a research - investment integrated platform TIRD to improve investment and research efficiency [30][32]. - The fund managers have rich quantitative industry and investment experience, contributing to stable excess returns [33]. 3. Summary According to the Catalog 3.1 Tianhong Fund's Index - Enhanced Product Line: Comprehensive Coverage of Broad - Based and Industry Indices, Leading in the Number of Products in the Market - **Overall Situation**: Tianhong Fund's index - enhanced business started in the second half of 2019. As of October 31, 2025, there are 18 index - enhanced products (only counting main - code funds), with a total management scale of 11.947 billion yuan. Among them, there are 12 broad - based index - enhanced products (including 2 enhanced - strategy ETFs) with a scale of about 10.7 billion yuan, and 6 industry - themed index - enhanced products with a scale of about 1.2 billion yuan [2][5]. - **Broad - Based Index Coverage**: The product line fully covers major broad - based indices in the market, spanning different market - value styles from CSI 300 to SSE 2000, covering large, medium, and small market - value dimensions. It also has multiple broad - based index - enhanced products in the main board, GEM, and STAR Market. In addition to comprehensive index coverage, Tianhong Fund has innovated in product forms, providing both off - exchange ordinary index - enhanced funds and on - exchange index - enhanced ETFs, creating an "on - and off - exchange linked, well - equipped" product ecosystem [7][9]. - **Industry Index - Enhanced Product Layout**: Tianhong Fund actively explores niche industry tracks, building a competitive industry index - enhanced product line, which is different from most peers focusing on broad - based indices. It ranks second in the market for industry index - enhanced funds, showing forward - looking product layout capabilities. It has systematically deployed index - enhanced products in five key areas: technology, consumption, medicine, advanced manufacturing, and new energy, helping investors capture structural opportunities [11][15]. 3.2 Long - Term Historical Performance is Outstanding, and Product Performance is Comprehensive and Prominent - **High - Consistency Systematized Ability**: As of October 31, 2025, 4 broad - based index - enhanced products of Tianhong Fund have been in operation for more than three years. In the past three years, these four products have shown excellent and highly consistent excess - return capabilities in the same - type benchmark index - enhanced funds, with their excess - return rankings all in the top 40% and an average ranking percentile of 31.89%. They also show a scientific return - risk allocation level, with their information - ratio rankings all in the top 40% and an average ranking percentile of 28.57%. All products' information - ratio rankings are not inferior to their excess - return rankings, indicating reasonable risk control [18][19]. - **Outstanding Long - Term Historical Performance - A Replicable and Expandable Investment Paradigm**: Tianhong Fund's operation mode for long - term stable excess performance can be replicated and expanded in industry index - enhanced products. Five index - enhanced fund products were established between 2020 - 2022, and their excess - return rates compared to the benchmark since their establishment range from 3% to 28%, showing better performance than the benchmark, especially in elastic industries such as advanced manufacturing and technology TMT [21]. - **Excellent Performance This Year**: As of October 31, 2025, Tianhong Fund's index - enhanced products have shown excellent performance in the overall upward market this year. Three products, including the SSE 2000 Index - Enhanced, CSI 1000 Enhanced Strategy ETF, and CSI 1000 Index - Enhanced, have an excess - return rate of more than 10% compared to the benchmark. Except for the SSE STAR Market 100 Index - Enhanced, which slightly underperformed the benchmark, the rest of the products achieved varying degrees of excess returns. Most of the index - enhanced products achieved an excess return of more than 5% compared to the benchmark this year [23][26]. 3.3 Continuously Iterative Investment Framework, a New Paradigm of Index - Enhanced Investment with High AI Content - **Investment Strategy Framework**: Tianhong's index - enhanced product series aims to obtain stable excess returns. It relies on a rich Alpha - factor system, a complete risk - control system, and diversified portfolio - construction strategies. The company has deep - rooted in the traditional fundamental multi - factor system and actively deployed AI technology in recent years, introducing machine - learning methods. It has developed and applied multiple algorithm models in real - time, using diverse feature factors constructed from mixed - frequency data [30]. - **Research - Investment Integrated Platform TIRD**: To address the problems in the traditional public - fund research - investment platform, Tianhong Fund is building the TIRD platform. This platform can ensure the accumulation and clarity of research, quantifiable assessment, iterative strategy accumulation, and interpretable performance evaluation. It transforms from a distributed platform to a collaborative one, achieving complete knowledge retention, timely sharing, smooth strategy generation, and clear team incentives [32]. 3.4 Team Members - Rich Quantitative Industry and Investment Experience - Fund manager Yang Chao has a master's degree in mathematics and financial computing from the University of Wales, Swansea. He has 15 years of securities industry experience and 10 years of index - enhanced and quantitative fund management experience. He has a mature index - enhanced investment strategy and has contributed stable excess returns. He has worked in multiple fund companies and is currently the general manager of the Index and Quantitative Investment Department at Tianhong Fund, managing multiple index - enhanced products [33].

Quantitative Models and Construction Methods 1. Model Name: Guosen Quantitative Index Enhanced Portfolio - **Model Construction Idea**: The model aims to construct enhanced portfolios benchmarked against indices such as CSI 300, CSI 500, CSI 1000, and CSI A500, with the goal of consistently outperforming their respective benchmarks [10][11]. - **Model Construction Process**: 1. **Revenue Prediction**: Predict stock returns using multiple factors. 2. **Risk Control**: Apply constraints on industry exposure, style exposure, stock weight deviation, and turnover rate. 3. **Portfolio Optimization**: Optimize the portfolio to maximize single-factor exposure while adhering to constraints. The optimization model is as follows: $ \begin{array}{ll} max & f^{T} w \\ s.t. & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T} w = 1 \end{array} $ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, \( w \) is the stock weight vector, and \( f^{T}w \) is the weighted exposure to the factor. - **Constraints**: - **Style Exposure**: \( X \) is the factor exposure matrix, \( w_b \) is the benchmark weight vector, and \( s_l, s_h \) are the lower and upper bounds for style exposure. - **Industry Exposure**: \( H \) is the industry exposure matrix, and \( h_l, h_h \) are the lower and upper bounds for industry deviation. - **Stock Weight Deviation**: \( w_l, w_h \) are the lower and upper bounds for stock weight deviation. - **Component Stock Weight**: \( B_b \) is a 0-1 vector indicating whether a stock is a benchmark component, and \( b_l, b_h \) are the lower and upper bounds for component stock weight. - **No Short Selling**: Ensure non-negative weights and limit individual stock weights. - **Full Investment**: Ensure the portfolio is fully invested with weights summing to 1 [40][41][42]. 4. **Backtesting**: Rebalance the portfolio monthly, calculate historical returns, and evaluate performance metrics such as excess returns and risk statistics [44]. 2. Model Name: Public Fund Heavyweight Index - **Model Construction Idea**: Construct an index based on the holdings of public funds to evaluate factor performance under "institutional style" [42][43]. - **Model Construction Process**: 1. **Sample Selection**: Include ordinary equity funds and partial equity hybrid funds with a minimum size of 50 million RMB and at least six months of listing history. Exclude recently transformed funds or those with insufficient data. 2. **Data Collection**: Use fund periodic reports (annual, semi-annual, or quarterly) to gather holding information. 3. **Weight Calculation**: Average the stock weights across eligible funds. 4. **Index Construction**: Sort stocks by weight in descending order and select those accounting for 90% of cumulative weight to form the index [43]. --- Model Backtesting Results 1. Guosen Quantitative Index Enhanced Portfolio - **CSI 300 Enhanced Portfolio**: - Weekly excess return: -0.71% - Year-to-date excess return: 16.74% [13] - **CSI 500 Enhanced Portfolio**: - Weekly excess return: 0.12% - Year-to-date excess return: 6.85% [13] - **CSI 1000 Enhanced Portfolio**: - Weekly excess return: -0.94% - Year-to-date excess return: 14.08% [13] - **CSI A500 Enhanced Portfolio**: - Weekly excess return: -1.37% - Year-to-date excess return: 7.55% [13] 2. Public Fund Heavyweight Index - **CSI 300 Index Enhanced Products**: - Weekly excess return: Max 0.70%, Min -1.26%, Median 0.09% - Year-to-date excess return: Max 9.92%, Min -4.53%, Median 2.58% [31] - **CSI 500 Index Enhanced Products**: - Weekly excess return: Max 1.17%, Min -1.13%, Median 0.11% - Year-to-date excess return: Max 13.14%, Min -9.17%, Median 3.94% [33] - **CSI 1000 Index Enhanced Products**: - Weekly excess return: Max 0.89%, Min -1.38%, Median -0.05% - Year-to-date excess return: Max 19.12%, Min -1.84%, Median 8.24% [36] - **CSI A500 Index Enhanced Products**: - Weekly excess return: Max 0.71%, Min -0.86%, Median -0.04% - Year-to-date excess return: Max 2.67%, Min -4.14%, Median -0.76% [39] --- Quantitative Factors and Construction Methods 1. Factor Name: Maximized Factor Exposure (MFE) - **Factor Construction Idea**: Evaluate factor effectiveness under real-world constraints by maximizing single-factor exposure in a portfolio [40][41]. - **Factor Construction Process**: 1. Define constraints for style exposure, industry exposure, stock weight deviation, and component stock weight. 2. Optimize the portfolio to maximize single-factor exposure while adhering to constraints. 3. Rebalance monthly and calculate historical returns [40][41][44]. 2. Factor Name: Public Fund Heavyweight Factors - **Factor Construction Idea**: Test factor performance in the public fund heavyweight index to reflect institutional preferences [42][43]. - **Factor Construction Process**: 1. Use public fund holdings to construct the index. 2. Evaluate factor performance within this index using metrics such as excess returns and risk-adjusted returns [42][43]. --- Factor Backtesting Results 1. Maximized Factor Exposure (MFE) - **CSI 300 Sample Space**: - Best-performing factors (weekly): One-month volatility (0.83%), one-month turnover (0.68%), three-month volatility (0.65%) - Worst-performing factors (weekly): Single-quarter profit growth (-0.26%), three-month institutional coverage (-0.24%), one-year momentum (-0.24%) [18] - **CSI 500 Sample Space**: - Best-performing factors (weekly): Three-month institutional coverage (1.09%), one-month reversal (1.01%), three-month reversal (0.99%) - Worst-performing factors (weekly): Standardized unexpected earnings (-1.00%), DELTAROA (-0.81%), DELTAROE (-0.81%) [20] - **CSI 1000 Sample Space**: - Best-performing factors (weekly): One-month turnover (1.08%), three-month institutional coverage (1.06%), single-quarter ROA (1.04%) - Worst-performing factors (weekly): Single-quarter SP (-1.29%), expected PEG (-1.25%), SPTTM (-1.22%) [22] - **CSI A500 Sample Space**: - Best-performing factors (weekly): One-month turnover (0.82%), three-month turnover (0.75%), one-month volatility (0.74%) - Worst-performing factors (weekly): Expected net profit QoQ (-0.91%), single-quarter net profit growth (-0.61%), expected PEG (-0.41%) [24] - **Public Fund Heavyweight Index**: - Best-performing factors (weekly): One-month volatility (1.32%), one-month turnover (1.23%), three-month turnover (0.89%) - Worst-performing factors (weekly): Single-quarter revenue growth (-0.89%), single-quarter profit growth (-0.88%), single-quarter ROE (-0.81%) [26]