Core Viewpoint - The article discusses how AI empowerment in public quantitative funds can effectively navigate market cycles to achieve excess returns [2] Group 1: AI Empowerment in Quantitative Funds - AI technology is increasingly being integrated into public quantitative funds, enhancing their ability to analyze data and make investment decisions [2] - The article emphasizes the importance of adapting AI strategies to different market conditions to maintain performance [2] - Historical data shows that funds utilizing AI have outperformed traditional investment strategies during volatile periods [2] Group 2: Market Trends and Performance - Recent trends indicate a growing interest in AI-driven investment solutions, with significant capital inflows into these funds [2] - The performance metrics of AI-enabled funds demonstrate a consistent increase in returns, with some funds reporting up to a 20% higher return compared to their non-AI counterparts [2] - The article highlights the necessity for continuous innovation in AI algorithms to keep pace with changing market dynamics [2]

Group 1 - The core concept emphasizes the importance of foundational knowledge in investment and fund selection, suggesting that solid fundamentals are essential for successful investing [2] - The article distinguishes between absolute and relative returns, defining absolute return as the actual profit after fees, while relative return refers to excess returns compared to a benchmark [3]

Market Overview - The A-share market experienced a collective decline, with the Shanghai Composite Index down 0.40%, Shenzhen Component down 0.76%, and ChiNext down 1.12%, while the Northbound 50 fell by 1.00%. The total trading volume was 1.72 trillion yuan, a decrease of 20 billion yuan from the previous day, with over 3,850 stocks declining [1] Reasons for Market Adjustment - The first reason for the market adjustment is profit-locking by institutional investors, as November is recognized as a settlement month for public funds and a critical period for annual performance assessment. Institutions tend to shift from seeking excess returns to locking in profits, leading to active portfolio adjustments [2] - The second reason is the uncertainty surrounding the Federal Reserve's interest rate cuts, which has impacted global liquidity. Recent reports suggest that the Fed may not lower interest rates in the first half of next year, disrupting expectations for liquidity easing and causing capital outflows from the Asia-Pacific region, including A-shares [3] - The third reason is the rising tensions in Sino-Japanese relations, which have raised market concerns. Recent remarks from the Japanese Prime Minister and subsequent countermeasures from China, such as travel warnings and import restrictions, have created uncertainty in economic and trade prospects between the two countries, affecting market sentiment [4] Long-term Market Outlook - Despite the current adjustment, the underlying logic supporting the bull market remains intact. China's rapid advancements in technology and military capabilities, along with ongoing policies aimed at boosting economic development and industrial upgrades, are expected to provide key support for the capital market [4] - The market is anticipated to undergo a period of consolidation, which may help digest profit-taking and repair valuation structures, ultimately paving the way for a return to an upward trajectory towards new highs [4] Investment Strategy - Given the recent market corrections, several risk signals have emerged, including the breaking of key moving averages and a decline in trading volume to around 1.7 trillion yuan. If trading volume does not rebound above 2 trillion yuan quickly, the index may struggle to achieve upward momentum in the short term [5] - Investors are advised to adopt a balanced allocation strategy, avoiding heavy bets on high-priced technology stocks and instead diversifying into lower-priced sectors such as AI applications, consumer goods, pharmaceuticals, and dividend assets. This approach allows for both offensive and defensive positioning in response to upcoming market conditions [5][7]

1. Report Industry Investment Rating - No information provided regarding the report industry investment rating. 2. Core Viewpoints of the Report - The report presents several ETF strategy indices developed by Huabao Research, aiming to provide investors with strategies to obtain excess returns relative to the market. These indices are tracked weekly for performance and holdings [13]. 3. Summary by Relevant Catalog 1. ETF Strategy Index Tracking - **Overall Performance Table**: The table shows the performance of different ETF strategy indices in the last week, including their returns, benchmark returns, and excess returns. For example, the Huabao Research Small - Large Cap Rotation ETF Strategy Index had a last - week return of - 1.06%, with a benchmark (CSI 800) return of - 1.13% and an excess return of 0.07% [14]. 1.1. Huabao Research Small - Large Cap Rotation ETF Strategy Index - **Strategy**: It uses multi - dimensional technical indicator factors and a machine - learning model to predict the return difference between the Shenwan Large - Cap Index and the Shenwan Small - Cap Index. The model outputs signals weekly to determine holdings [15]. - **Performance**: As of 2025/11/14, the excess return since 2024 was 20.08%, the excess return in the last month was - 0.02%, and the excess return in the last week was 0.07%. The index's last - week return was - 1.06%, compared to the CSI 800's - 1.13% [15][18]. - **Holdings**: As of 2025/11/14, it held 100% of the Shanghai - Shenzhen 300ETF [20]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: It uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on their exposure to 9 major Barra factors [20]. - **Performance**: As of 2025/11/14, the excess return since 2024 was 18.92%, the excess return in the last month was 2.02%, and the excess return in the last week was 1.63%. The index's last - week return was 0.50%, compared to the CSI 800's - 1.13% [20][23]. - **Holdings**: As of 2025/11/14, it held multiple ETFs, such as the 512890.SH Dividend Low - Volatility ETF with a 25.15% weight [24]. 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: It starts from a multi - factor perspective, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behavior. It uses valuation and crowding signals to indicate industry risks and digs out potential sectors [24]. - **Performance**: As of 2025/11/14, the excess return since 2024 was 37.09%, the excess return in the last month was 6.32%, and the excess return in the last week was 1.25%. The index's last - week return was 0.12%, compared to the CSI 800's - 1.13% [24][26]. - **Holdings**: As of 2025/11/14, it held ETFs like the 516160.SH New Energy ETF with a 20.47% weight [28]. 1.4. Huabao Research Quantitative Balancing Act ETF Strategy Index - **Strategy**: It uses a multi - factor system including economic fundamentals, liquidity, technical aspects, and investor behavior to build a quantitative timing system for equity market trend analysis. It also predicts the market's large - and small - cap styles to adjust equity market positions [28]. - **Performance**: As of 2025/11/14, the excess return since 2024 was - 11.12%, the excess return in the last month was - 1.10%, and the excess return in the last week was 0.77%. The index's last - week return was - 0.31%, compared to the Shanghai - Shenzhen 300's - 1.08% [28][29]. - **Holdings**: As of 2025/11/14, it held the 511260.SH 10 - Year Treasury Bond ETF with a 9.23% weight [31]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: It tracks and mines hot - spot index target products through market sentiment analysis, industry event tracking, investor sentiment, professional views, policy changes, and historical analysis to build an ETF portfolio that can capture market hot - spots [31]. - **Performance**: As of 2025/11/14, the excess return in the last month was 0.51%, and the excess return in the last week was 2.99%. The index's last - week return was 2.46%, compared to the CSI All - Share Index's - 0.53% [31][34]. - **Holdings**: As of 2025/11/14, it held the 159652.SZ Non - Ferrous Metals 50ETF with a 36.05% weight [35]. 1.6. Huabao Research Bond ETF Duration Strategy Index - **Strategy**: It uses bond market liquidity and price - volume indicators to select effective timing factors and predicts bond yields through machine learning. When the expected yield is below a certain threshold, it reduces the long - duration positions in the bond portfolio [35]. - **Performance**: As of 2025/11/14, the excess return in the last month was - 0.05%, and the excess return in the last week was - 0.01%. The index's last - week return was 0.04%, compared to the ChinaBond Aggregate Index's 0.05% [35][36]. - **Holdings**: As of 2025/11/14, it held the 511260.SH 10 - Year Treasury Bond ETF with a 50.00% weight [38].

Core Insights - As of November 14, 2023, 19 public funds have doubled their performance this year, all of which are actively managed funds, indicating the unique advantages of active investment strategies in capturing excess returns [1][2] Fund Performance and Strategy - The majority of these funds saw a significant increase in net asset value starting from the second quarter, largely due to heavy investments in strong sectors such as optical modules, PCB, innovative pharmaceuticals, and storage [1][4] - Many funds exhibited a notable increase in concentration, with over 60% of their net asset value held in the top ten stocks by the end of the second and third quarters [1][2] Notable Fund Examples - The top-performing fund, Yongying Technology Smart Selection, achieved a return rate exceeding 180% this year, with its manager, Ren Jie, having a background as a TMT researcher [1][2] - This fund underwent significant portfolio adjustments, completely changing its top ten holdings multiple times within the year, reflecting Ren Jie's preference for concentrated holdings [2][3] Sector Focus - The top holdings of the funds are heavily concentrated in the optical communication, PCB, and cloud computing sectors, with the top three stocks in the optical module sector accounting for nearly 30% of the fund's net asset value [3][4] - The performance of these top holdings has been impressive, with seven stocks doubling in value during the third quarter, including Industrial Fulian, which saw a rise of over 200% [3][4] Common Trends Among High-Performing Funds - A significant trend among the 19 funds is the heavy investment in optical module stocks, with nearly 70% of the funds having optical module stocks as their top holdings by the end of the second quarter [4] - Other sectors contributing to the strong performance include PCB and innovative pharmaceuticals, with specific funds like Yongying Technology Smart Selection and Hengyue Advantage Select showing substantial gains from these sectors [4][5]

Core Insights - The recent performance of active equity funds has been under scrutiny, with over 38% of these funds still in losses over the past five years despite a significant number achieving positive returns since 2025 [1][2][3] - Key factors contributing to the underperformance include high-level accumulation, frequent trading, and reliance on specific sectors, which have eroded fund values [1][5][7] Performance Overview - As of November 10, 2025, the Shanghai Composite Index has risen by 19.42%, while 97.45% of active equity funds reported positive returns [2][3] - However, 1019 active equity funds remain in losses, with 38% of the total, indicating a stark contrast in performance for investors who entered the market earlier [1][2] Fund Performance Analysis - Among the 2695 active equity funds with over five years of existence, 1676 have achieved positive returns, with six funds reporting over 200% returns [3] - Conversely, nearly 40% of active equity funds have not turned a profit in five years, with some funds experiencing maximum drawdowns starting in 2021 [3][4] Underperforming Funds - Notable underperformers include funds managed by well-known managers, with losses exceeding 30% over five years [4] - Specific funds like Tianzhi New Consumption and Fangzheng Fubang Innovation Power have reported losses of -65.25% and -62.32%, respectively [3][4] Trading Behavior - High average stock positions during market peaks have been linked to poor long-term performance, with funds showing an average stock position of 84.22% during critical periods [5][6] - Frequent trading has also negatively impacted fund performance, with an average turnover rate of 460.71% across all active equity funds, rising to 508.45% for those with over 30% losses [7][8] Sector Reliance - Many funds have shown over-reliance on traditional sectors, leading to underperformance despite being labeled as "new" or "growth" funds [8][9] - Funds like Tianzhi New Consumption and Invesco Great Wall New Growth have shifted their holdings but still struggle to achieve positive returns [8][9] Market Outlook - The active equity fund market is seeing a resurgence, with 1354 new funds launched in 2025, indicating renewed investor interest [11] - Fund managers are advised to focus on sectors with long-term growth potential, such as high-end manufacturing and new consumption, while being cautious of market volatility [12]

Core Insights - The article emphasizes the stability and long-term performance of the fixed income team at ICBC Credit Suisse Asset Management, highlighting the rarity of fund managers who maintain consistent performance over a decade or more [1][5][13] Group 1: Investment Strategy - The fixed income investment approach is likened to a marathon, focusing on long-term rhythm and endurance rather than short-term speed [1] - The company has developed a mature system to continuously seek excess returns in a low-yield, high-volatility environment, emphasizing the importance of macroeconomic foresight and institutional behavior tracking [2][3] - Asset pricing dynamics are crucial for identifying investment opportunities, with the company considering various valuation indicators to inform its "fixed income+" product strategies [3] Group 2: Team and Talent - The fixed income team at ICBC Credit Suisse has grown to 46 members, with a structured growth path for team members to ensure the continuity of research capabilities [7] - The presence of experienced fund managers, such as Ouyang Kai and He Xiuhong, who have managed funds for over a decade, contributes to the company's stability and performance [6][5] Group 3: Product Offering - The company has established a comprehensive "fixed income super shelf" with a diverse range of products tailored to different investor needs, including short-term, medium-term, and various types of bond funds [8][10] - The "fixed income+" products are categorized into three tiers based on equity positions and risk-return characteristics, catering to different market cycles and investor risk appetites [9] Group 4: Historical Development - The development of ICBC Credit Suisse's fixed income business has been marked by significant milestones, including the launch of the first money market fund in 2006 and the establishment of a robust investment research framework [10][11] - The company has achieved substantial growth, with its fixed income business scale surpassing 670 billion yuan by 2024, reflecting a successful transition to high-quality development [12] Group 5: Future Outlook - The company aims to enhance its investment capabilities and continue innovating in product offerings, particularly in response to the evolving market environment and investor needs [13]

Core Viewpoint - The first batch of new floating-rate funds has shown uneven performance, with some funds excelling in the AI sector while others lagged due to conservative investments in sectors like liquor and banking [1][3]. Performance Analysis - As of October 27, the average increase of the first 26 floating-rate funds is approximately 14.3%, but performance varies significantly due to different investment strategies [3]. - Notable performers include Huashang Zhiyuan Return with a return of 53.58%, followed by Jiashi Growth Win at 47.57%, and Yifangda Growth Progress at around 40% [3][4]. - Conversely, several funds have underperformed, with some showing returns below 5% [5]. Investment Strategy - Leading funds have heavily invested in the booming AI sector, with top holdings including stocks like Zhongji Xuchuang and Dongshan Precision [5][6]. - Funds with average performance predominantly invested in the liquor and banking sectors, which did not perform well in the recent tech-driven market [6]. Benchmark Comparison - Out of the 26 funds, only 9 have outperformed their benchmarks, which include indices like the CSI 300 and CSI 800 [9]. - The design of the floating-rate fund management fee structure ties fees to performance relative to benchmarks, incentivizing fund managers to achieve excess returns [9][10]. Future Outlook - The performance of the first batch of floating-rate funds is expected to positively influence the fundraising and operation of the second batch [12]. - The second batch of funds is diversifying into industry-specific themes, such as high-end equipment and healthcare, indicating a shift from broad market selection to targeted strategies [12][13].

Core Viewpoint - The article emphasizes the strategy of investing in small-cap stocks to uncover hidden value and generate sustainable long-term returns through deep research and a focus on fundamental analysis [1][2]. Group 1: Investment Strategy - The company aims to identify undervalued small-cap stocks in a liquidity-rich environment, which inherently possess higher uncertainty and potential for greater returns [1][2]. - The approach involves a defensive strategy that prioritizes safety by selecting high-quality assets based on fundamental research, which helps in controlling drawdowns while maximizing upside potential [2][3]. Group 2: Market Conditions - The current A-share market exhibits significant structural differentiation, with concentrated trading in sectors like AI, semiconductors, and robotics, leading to relative weakness in small-cap stocks [4][5]. - Historical patterns suggest that extreme market structures are often unsustainable, indicating that investment opportunities may become more diversified in the near future [5]. Group 3: Valuation Insights - As of October 22, the Wind data shows that the micro-cap stock index has a price-to-book (PB) ratio of 2.49, lower than the 2.81 of the CSI 2000, highlighting a relative valuation gap for small-cap assets [5]. - The current market sentiment may shift, providing accumulation opportunities for small-cap stocks that have solid fundamentals, low previous gains, and are aligned with industrial policy but not yet fully recognized by the market [5].

Report Title - Which Active Equity Funds are Suitable for Core Portfolio Allocation? - Weekly Insights on Financial Products 20251025 [1] Core Viewpoints - From the allocation needs of core funds, the report sets the characteristics that core funds should possess, aiming to provide basic excess returns, improve the holding experience, and effectively respond to the volatile market environment. It proposes three strategies to find suitable core funds: high win - rate relative to the equity - focused fund index, good holding experience, and wide distribution of the ability circle [3]. Summary by Sections Strategy 1: High Win - Rate Relative to the Equity - Focused Fund Index (Active & Quantitative) - **Difficulty of Outperforming the Index**: It is not easy for active equity funds to outperform the equity - focused fund index (885001) in the long term. Only 2 products (Huashang New Trend Optimization, Anxin Advantage Growth) have outperformed 885001 every year in the past 10 years. The proportion of products that outperform 885001 in different time intervals is shown in relevant tables [3][10][12]. - **Investment Style Analysis of Anxin Advantage Growth**: Since being managed by Nie Shilin, it has outperformed 885001 every year. The product has a balanced and flexible industry distribution, with a certain proportion of allocation in multiple major active equity sectors, and the industry distribution is flexibly adjusted. It has relatively concentrated holdings to obtain excess returns through concentrated stock selection [15]. - **Excess Return Analysis**: In terms of the relationship between annualized excess and annualized tracking error, for funds with a tracking error within 10%, 8 products have an annualized excess of over 10%; for those within 8%, 1 product has an annualized excess of over 8%. Only 63 products (2.69% of the total) can generate excess returns in both rising and falling environments of 885001 [20]. - **Selection of High - Win - Rate Funds**: 20 active equity funds are selected based on positive cumulative excess returns in both rising and falling daily environments of 885001 in the past five years and ranked by information ratio. Some products have their current fund managers managing them for a full five - year period, and some products have high quarterly and annual win - rates [23]. - **Screening Framework and List**: The report screens high - win - rate active equity funds by calculating four indicators, setting time intervals, and eliminating certain types of funds. The final list includes more balanced funds like Bodao Shengyan and funds with greater elasticity like Huaxia Innovation Frontier [26][27] Strategy 2: Good Holding Experience (Low Volatility & High Sharpe Ratio) - **Characteristics of Funds with Good Holding Experience**: These funds are close to the efficient frontier (low volatility and outstanding long - term performance) and have a high number of record - high days. Some examples are given according to different quantile criteria [46]. - **Screening Process and Results**: The report screens funds by calculating two indicators, eliminating certain types of funds, and finally selects 30 funds with better comprehensive capabilities. Representative products selected over the past three years and two years are also provided [48] Strategy 3: Wide Distribution of the Ability Circle (Individual Ability vs. Platform System) - **Requirement of the Ability Circle**: To effectively respond to the volatile market environment, fund managers need a wide ability circle, with both the ability to allocate in multiple tracks and the ability to select stocks deeply within tracks [3] - **Analysis of Fund Managers' Investment Styles**: The investment styles of several fund managers such as Zhou Yun, Hu Song, Chen Wen, Qiao Qian, and Zhang Jiansheng are analyzed, including their investment concepts, stock - selection methods, and portfolio adjustment strategies [30]