- The non-bank financial sector confirmed an upward trend on the daily chart, while the retail sector experienced a downward trend on the daily chart[1][8][28] - The A-share prosperity index stood at 20.44 as of October 31, 2025, up 15.01 from the end of 2023, indicating an upward cycle[2][31] - The A-share sentiment index signals for bottom and top were both empty, with the overall signal being empty[2][39] - The CSI 500 enhanced portfolio underperformed the benchmark by 0.54%, while the CSI 300 enhanced portfolio outperformed the benchmark by 0.59%[2] - The Beta factor showed higher excess returns among style factors, while growth exhibited significant negative excess returns[2][58] - High-leverage stocks performed well recently, while factors such as residual volatility and non-linear market capitalization performed poorly[2][58] - The CSI 500 enhanced portfolio achieved a relative excess return of 51.82% since 2020, with a maximum drawdown of -5.73%[47] - The CSI 300 enhanced portfolio achieved a relative excess return of 39.01% since 2020, with a maximum drawdown of -5.86%[53] - The market's preference for high Beta stocks led to better performance in indices like CSI 500 and ChiNext, while indices like SSE Composite and SSE 50 performed poorly in style factors[65]

- The report tracks the performance of Barra style factors for October 2025, showing that the market capitalization factor recorded a return of -1.49%, the book-to-market ratio factor recorded a return of 0.39%, the growth factor recorded a return of -0.34%, and the earnings expectations factor recorded a return of 0.12%[4][14] - The report introduces a series of stock selection factors based on trading behavior, including the Ideal Reversal Factor, Smart Money Factor, APM Factor, and Ideal Amplitude Factor[5][15] - The Ideal Reversal Factor is constructed by segmenting the traditional reversal factor using W-shaped cuts, focusing on the average transaction amount per trade to identify the trading days with the strongest reversal attributes[41] - The Smart Money Factor is constructed by analyzing minute-level price and volume data to identify the involvement of institutional investors, using a specific formula to calculate the factor value[42][44] - The APM Factor measures the difference in stock price behavior between morning (or overnight) and afternoon trading sessions, using a regression model to calculate the residuals and then constructing a statistical measure to quantify the difference[43][45][46] - The Ideal Amplitude Factor measures the difference in amplitude information between high and low price states, calculating the average amplitude for the highest and lowest 25% of trading days and then taking the difference[48] - The historical performance of the Ideal Reversal Factor shows an IC mean of -0.050, rankIC mean of -0.061, IR of 2.48, and a long-short monthly win rate of 78.1%[6][16] - The historical performance of the Smart Money Factor shows an IC mean of -0.038, rankIC mean of -0.062, IR of 2.74, and a long-short monthly win rate of 81.2%[6][21] - The historical performance of the APM Factor shows an IC mean of 0.028, rankIC mean of 0.034, IR of 2.25, and a long-short monthly win rate of 76.5%[6][25] - The historical performance of the Ideal Amplitude Factor shows an IC mean of -0.054, rankIC mean of -0.074, IR of 3.03, and a long-short monthly win rate of 83.3%[6][28] - The historical performance of the composite trading behavior factor shows an IC mean of 0.067, rankIC mean of 0.093, IR of 3.33, and a long-short monthly win rate of 80.0%[6][32] - In October 2025, the Ideal Reversal Factor recorded a long-short return of 1.63% with a 12-month long-short monthly win rate of 66.7%[7][16] - In October 2025, the Smart Money Factor recorded a long-short return of 2.90% with a 12-month long-short monthly win rate of 83.3%[7][21] - In October 2025, the APM Factor recorded a long-short return of -1.13% with a 12-month long-short monthly win rate of 41.7%[7][25] - In October 2025, the Ideal Amplitude Factor recorded a long-short return of 3.33% with a 12-month long-short monthly win rate of 66.7%[7][28] - In October 2025, the composite trading behavior factor recorded a long-short return of 3.73% with a 12-month long-short monthly win rate of 75.0%[7][32]

2025 年 10 月 31 日 中欧小盘成长: 广度优势+暴 控,打造高性价比小盘基 基金经理研究系列报告之八十五 申万宏源研究微信服务号 相关研究 证券分析师 白皓天 A0230525070001 baiht@swsresearch.com 奚佳诚 A0230523070004 xijc@swsresearch.com 蒋辛 A0230521080002 jiangxin@swsresearch.com 邓虎 A0230520070003 denghu@swsresearch.com 联系人 奚佳诚 (8621)23297818× xijc@swsresearch.com 请务必仔细阅读正文之后的各项信息披露与声明 小盘风格投资价值分析：量化舒适区，当下估值分位数与盈利预期相对占优 ○ 0 多维成长、内涵丰富，相比大盘估值或具备盈利预期与估值上的双重优势：1）行业结构: 年内收益靠前的行业多具备成长属性，而小盘指数成长属性更为突出；年内收益表现靠后 的行业在小盘指数中占比较少，如银行、食品饮料等；2）年内热点主题反映小盘具备丰富 内涵：提取了规模增长的非宽基、非港股指数，三只指数成分股均普遍由中小盘股票构 ...

Core Viewpoint - Shenzhen has become a significant hub for quantitative private equity, with a total of 125 firms and an average return of 24.43% in the first three quarters of the year [2]. Group 1: Overview of Quantitative Private Equity in Shenzhen - Shenzhen is one of China's four first-tier cities and a frontier for opening up, attracting world-class financial, professional services, and technology companies [2]. - The city has a solid policy and industrial foundation for the development of quantitative private equity [2]. Group 2: Distribution of Quantitative Private Equity Firms - The majority of quantitative private equity firms are located in Futian District (59 firms) and Nanshan District (53 firms), accounting for nearly 90% of the total [4]. - Futian District is identified as the traditional financial center, while Nanshan is recognized as the technology center of Shenzhen [4]. Group 3: Top Firms in Futian District - The leading firms in Futian District include Chao Quantum Fund and Chengqi Asset, both managing over 10 billion [7]. - The top firms in terms of employee count include Youmeili Investment, Chao Quantum Fund, and Qianhai Guoen Capital, each with over 30 employees [7]. Group 4: Performance of Top Firms - Chengqi Asset achieved the highest average return among its products, with a management scale of over 100 billion [9]. - Chao Quantum Fund, established in 2015, focuses on stock quantitative strategies and has also reached a management scale of over 100 billion [10]. Group 5: Overview of Nanshan District - In Nanshan District, the top firms include Hanrong Investment and Dadao Investment, with the latter being a newly established firm managing over 100 billion [11][14]. - The firms in Nanshan are also characterized by a strong focus on quantitative strategies and advanced technology [11]. Group 6: Performance of Top Firms in Nanshan - Hanrong Investment leads in performance with an average return from its products, while Dadao Investment has also shown strong results since its establishment [13][14]. - The firms in Nanshan are noted for their innovative approaches, including the use of machine learning and advanced statistical methods [13]. Group 7: Other Districts - Other districts such as Longgang, Luohu, Baoan, and Yantian collectively host 13 small-scale quantitative private equity firms, all managing between 0-5 billion [15]. - These firms primarily focus on niche strategies and have smaller employee counts compared to those in Futian and Nanshan [15].

Core Viewpoint - The current market conditions suggest that the A-share market may be entering a bullish phase, with the 4000-point level on the Shanghai Composite Index being a significant milestone for potential upward movement [4][10]. Private Equity Market - Recent trends indicate a recovery in quantitative strategies within the private equity market, with various strategies such as index enhancement and small-cap index enhancement showing strong performance due to favorable market conditions [7][9]. - The market has shifted towards a more balanced and rotational rhythm, alleviating previous concentrated investments in technology stocks, which is conducive for quantitative strategies to identify excess returns [8]. - Small-cap stocks, previously under pressure, are becoming more active, providing opportunities for quantitative strategies to accumulate excess returns [8]. Investment Strategy - Investors holding quantitative strategies are encouraged to maintain patience and confidence, while those observing the market may find this a valuable window for investment [9]. - Concerns exist regarding the challenges of further upward movement beyond the 4000-point mark, as well as uncertainties in the market environment for quantitative excess return extraction [10]. - A shift in investment approach from timing to allocation is suggested, emphasizing the importance of diversified asset allocation to mitigate risks and enhance returns [11]. Strategy Performance - A specific quantitative strategy has demonstrated resilience during market downturns, maintaining stable performance through a diversified approach that includes equities, convertible bonds, and cash management [13]. - The strategy's success is attributed to its multi-asset allocation, which balances risks and smooths overall volatility, as well as its focus on undervalued assets to enhance safety margins and potential returns [14][15]. - The multi-strategy approach allows for adaptability to market changes, with various sub-strategies catering to different market conditions, thereby improving the overall risk-return profile [14]. Conclusion - The improvement in market conditions has brought quantitative strategies back into focus, presenting a favorable time for investment consideration. Multi-asset strategies centered on quantitative equity may provide a more secure investment avenue amidst market uncertainties [16].

Core Viewpoint - Quantitative investment is transitioning from a marginal role to a mainstream strategy in the volatile A-share market, with Shenzhen Liangdao Investment leveraging its strong quantitative technology foundation and systematic strategy framework to advance in the competitive asset management industry [2]. Company Overview - Shenzhen Liangdao Investment was established in April 2015, with a founding team that has been dedicated to quantitative investment and algorithmic trading since 2010. The company has research centers in Xiamen, Beijing, and Shanghai, and its core personnel have over 10 years of experience in quantitative strategy research and risk control [2]. - The name "Liangdao" signifies the "path of quantitative investment," reflecting a deep understanding of the essence of investment—finding the optimal solution between returns and risks [2]. Performance Highlights - Liangdao Investment's quantitative stock and CTA (Commodity Trading Advisor) products have shown outstanding performance this year. As of September 30, 2025, its "Liangdao Shunfeng No. 1 A-class share" and "Liangdao Chengfeng No. 1 A-class share" ranked in the top 10 for excess returns among similar-sized institutions in their respective strategies [3]. - The "Liangdao CTA Selected No. 17 A-class" product achieved a return of ***%, ranking 4th among private equity firms with over 5 billion in assets [3]. Differentiation Strategies - The company attributes its performance to four key differentiating features: 1. Low correlation with the market, achieved through an independent research system and various machine learning models, resulting in an average correlation of 0.40 with excess returns [8]. 2. Utilization of GNN (Graph Neural Network) technology to uncover hidden style rotation opportunities through dynamic relationships between stocks [8]. 3. A unique alternative database that enhances the robustness and stability of price-volume factors in event-driven markets [8]. 4. A specialized risk control system that combines the Barra system with A-share characteristics, such as additional controls for dividends and micro-cap stocks [8]. AI Model Optimization - Liangdao Investment has made significant improvements to its AI models, focusing on input layer optimization and dynamic graph structure construction, which sets it apart from traditional models [10]. - The company employs AI and machine learning algorithms to explore non-linear relationships between factors and returns, enhancing the ability to capture hidden signals from unstructured data [10]. Risk Control Mechanisms - The company's risk control strategy encompasses pre-trade, in-trade, and post-trade measures, ensuring comprehensive oversight throughout the investment process [12]. - Pre-trade controls involve constraints on major style factors and market characteristics, while in-trade controls utilize third-party systems to monitor trading activities [13][14]. - Post-trade controls are implemented through a self-built system that analyzes account holdings and ensures consistency with investment strategies [15]. Market Adaptation Strategies - To adapt to the rapidly changing styles and themes in the A-share market, Liangdao Investment has developed a "multi-dimensional, multi-model" investment system that allows for quick responses to market changes [16]. - The company regularly updates its factor versions and model training to incorporate the latest market characteristics, ensuring its strategies remain relevant [16]. Future AI Strategy - Liangdao Investment's future AI strategy focuses on four main areas: enhancing AI applications in strategy development, strengthening data mining and analysis capabilities, optimizing risk control systems, and cultivating AI talent [21].

Core Viewpoint - The article emphasizes the importance of systematic investment and long-term strategies to achieve stable excess returns for investors, despite short-term market fluctuations [1][3]. Investment Philosophy - The investment philosophy of the company is centered around systematic investment, focusing on long-term strategies rather than being swayed by short-term market movements [1][3]. - The company aims to create a robust and efficient index enhancement system to continuously generate stable excess returns for investors [1][3]. Product Offering - The company has launched the CICC CSI All Share Index Enhanced Fund, which provides comprehensive coverage of the A-share market, serving as a "one-stop" investment tool for capturing systematic opportunities in the equity market [1][8]. - The index enhancement products are a core offering of the company's quantitative investment strategy, with a focus on major broad-based indices such as CSI 300, CSI 500, and CSI 1000 [8]. Investment Strategy - The quantitative team employs a dual-driven strategy combining fundamental quantitative strategies and algorithm-driven strategies, aiming to construct Alpha strategies that pursue stable performance [5]. - The team has developed and applied domain-specific nonlinear models to address challenges posed by traditional linear models in the evolving market [5]. Performance Metrics - The CICC CSI 500 Index Enhanced A Fund has achieved a cumulative net value growth rate of 123.32% since its inception, outperforming its benchmark by 109.18% [7]. - The CICC CSI 300 Index Enhanced A Fund has a cumulative net value growth rate of 102.90%, exceeding its benchmark by 59.76% since inception [7]. Market Outlook - The company anticipates that the A-share market is entering a phase of short-term consolidation and a long-term upward trend following significant gains in the third quarter [9]. - The company believes that the "14th Five-Year Plan" will provide fundamental support for the long-term development of the A-share market [9]. Investor Guidance - The company suggests that investors should select index enhancement products that align with their risk tolerance and hold them long-term to accumulate excess returns relative to the index [10]. - The index enhancement products are suitable for investors with a certain level of understanding of the capital market and a longer investment horizon [10]. Future Development - The company plans to continue developing diverse strategies and expanding its range of equity products to meet the growing investment needs of various investors [11].

Core Insights - The recent surge in interest around Meta's smart glasses and the significant rise of Industrial Fulian's stock by 280% this year highlights the volatility and potential opportunities in the market [1] Market Trends - The global market size for consumer electronics is projected to grow from $919.5 billion in 2018 to $1,176.7 billion by 2028, indicating a steady recovery and growth trajectory [2] - The AI high-end market is driving a structural recovery in consumer electronics, with a notable 4.1% growth in 2023 after a decline of 4.4% in 2022 [2] Stock Performance Analysis - Luxshare Precision has shown significant volatility with 17 instances of daily fluctuations exceeding 5% in the past three months, while Zhaoyi Innovation experienced eight consecutive days of upward movement with long upper shadows, suggesting institutional trading activity [2] - Historical data indicates that stocks can maintain high institutional inventory levels even during price corrections, as seen in a consumer electronics leader that rose over 90% after a period of sell signals from traditional indicators [5] Behavioral Insights - Behavioral economics suggests that investors experience loss aversion, feeling twice the pain from losses compared to the joy from gains, which institutions exploit to create panic at critical price levels [7] - The transition from hardware competition to ecosystem competition in the industry is expected to increase market volatility, necessitating tools to discern long-term trends amidst short-term fluctuations [9] Future Projections - Statista predicts that the global consumer electronics market will reach $1.15 trillion by 2030, emphasizing that significant investment opportunities often lie within the most volatile market movements [9]

Core Viewpoint - The market is inherently volatile, and a systematic investment approach is essential to navigate short-term fluctuations while focusing on long-term strategies to generate stable excess returns for investors [1][2]. Investment Philosophy - The investment philosophy emphasizes systematic investment, avoiding distractions from short-term market movements, and building a robust index enhancement system to create long-term excess returns [1][2]. - The quantitative team at CICC has launched the CICC CSI All Share Index Enhanced Fund, which aims to provide comprehensive exposure to the A-share market [1][2]. Quantitative Investment Strategy - The quantitative team employs a dual-driven strategy combining fundamental quantitative strategies and algorithm-driven approaches, integrating top-down and bottom-up methods to construct Alpha strategies [3]. - The team has developed and applied domain-specific nonlinear models to address challenges posed by traditional linear models in the evolving A-share market [3]. Team Collaboration and Performance - The ultimate goal of team collaboration is to achieve long-term, stable, and explainable excess returns rather than seeking short-term high returns [4]. - The CICC-managed index enhancement funds, such as the CICC CSI 500 Index Enhanced Fund, have consistently outperformed their benchmarks, with a cumulative net value growth rate of 123.32% since inception [4][5]. Product Features and Market Position - The index enhancement products are a core offering of CICC's quantitative team, with a focus on comprehensive coverage of major broad-based indices [5]. - The CICC CSI All Share Index Enhanced Fund is characterized by its broad coverage of the A-share market, balanced exposure to growth and value styles, and significant stock selection opportunities [5][6]. Market Outlook - The A-share market is expected to experience short-term fluctuations and a positive long-term trend, driven by China's high-quality economic development and ongoing reforms [6]. - The index enhancement products are suitable for investors with a long-term perspective who seek to accumulate excess returns relative to the index [6][7]. Industry Trends - The public quantitative fund market is gaining recognition, with index enhancement funds becoming the most prevalent product type due to their stable excess returns and lower fee structures [7]. - The regulatory environment, including the recent guidelines from the CSRC, is expected to create opportunities for the development of index enhancement strategies [7].

Core Viewpoint - The convertible bond market has shown strong performance in 2023, with the China Convertible Bond Index rising by 17.14% year-to-date and total trading volume reaching 13.46 trillion yuan, a year-on-year increase of 37.75%. This has led to increased interest in quantitative investment strategies that leverage the unique characteristics of convertible bonds, which offer both offensive and defensive capabilities [1]. Group 1: Why Choose Convertible Bonds? - Convertible bonds are considered high-quality beta assets, with the China Convertible Bond Index significantly outperforming major broad-based indices since 2017. For instance, during the market downturn in 2018, the index only fell by 1.16%, while the CSI 300 and CSI 500 indices dropped by 25.31% and 33.32%, respectively. Conversely, in 2019, the index rose by 25.15%, demonstrating its ability to provide both growth and protection [3][4]. Group 2: Characteristics and Pricing Factors of Convertible Bonds - The core factor influencing the pricing of convertible bonds is the underlying stock price, which directly affects their conversion value. The bonds exhibit a T+0 trading mechanism, allowing for good liquidity and turnover [8][9]. - Convertible bonds have unique contractual advantages, such as downwards adjustment and redemption clauses, which protect investor interests. Issuers typically have a strong incentive to convert bonds into stock, aligning the interests of both issuers and investors [8]. - The embedded bond value of convertible bonds is influenced by the interest rate environment. A decrease in market interest rates enhances the attractiveness of convertible bonds as fixed-income assets, thereby supporting their price [10]. - The supply-demand dynamics in the convertible bond market are crucial. The issuance pace and scale of convertible bonds directly affect market supply, while institutional investors significantly influence demand [11]. Group 3: Common Quantitative Strategies for Convertible Bonds - Quantitative strategies for investing in convertible bonds involve using computer models to systematically identify and execute investment opportunities, minimizing emotional decision-making. Common strategies include: - **Dual Low Strategy**: Focuses on bonds with low prices and low conversion premiums to balance safety and upside potential [12]. - **Low Premium Strategy**: Targets bonds with very low or negative conversion premiums, capitalizing on strong stock performance [12]. - **High YTM Strategy**: Treats convertible bonds as fixed-income securities to secure stable interest income, particularly in bearish or volatile markets [12]. - **Event-Driven Strategy**: Monitors events that may cause price fluctuations, such as earnings announcements or proposed adjustments to conversion prices [12].