[Table_Page] 金融工程|量化投资专题 2026 年 3 月 3 日 证券研究报告 [Table_Title] 港股通成分股调入调出效应与预测 [Table_Summary] 报告摘要： | [分析师： Table_Author]陈原文 | | --- | | SAC 执证号：S0260517080003 | | 0755-82797057 | | chenyuanwen@gf.com.cn | | 分析师： 安宁宁 | | SAC 执证号：S0260512020003 | | SFC CE No. BNW179 | | 0755-23948352 | | anningning@gf.com.cn | | 请注意，陈原文并非香港证券及期货事务监察委员会的注 | | 册持牌人，不可在香港从事受监管活动。 | [Table_ 相关研究： DocReport] | 金融工程:成长质量选股探讨 | 2026-02-13 | | --- | --- | | 基于卷积神经网络的指数轮 | 2026-02-13 | | 动策略:行业主题轮动研究报 | | | 告 | | | 业绩预告与行业表现呈现分 | 2026 ...

Core Viewpoint - Hedge funds achieved their highest overall returns in at least five years in 2025, driven by significant gains in the U.S. stock market, particularly in the AI sector, and volatility in the bond and currency markets due to trade tensions [1][3]. Performance Highlights - Bridgewater's flagship fund, Pure Alpha II, recorded a historic return of 34%, marking a significant recovery from annual returns below 3% from 2012 to 2024 [1][2]. - The Melqart Opportunities Fund led the performance with a return of 45.1%, while other notable funds included Bridgewater's Asian Macro Fund at 37% and the All Weather Fund at 20% [4][6]. - D.E. Shaw's flagship multi-strategy fund, D.E. Shaw Composite, achieved an 18.5% return, and its Oculus fund reached 28.2% [2][10]. Strategy Analysis - The strong performance of hedge funds is attributed to the flexibility of event-driven strategies, which capitalize on corporate mergers and restructurings amid increasing trade policy uncertainties [7]. - Multi-strategy funds showed varied performance, with Dymon achieving 18.1% and ExodusPoint at 18.04%, while industry giant Millennium only managed a 10.5% return [12]. - In the long/short equity strategy category, Soroban Opportunities delivered a robust 25% return, significantly outperforming the market [13]. Market Context - The U.S. stock indices recorded double-digit annual gains for the third consecutive year, a trend not seen since 2019-2021, with 14 out of 25 major hedge funds outperforming the S&P 500's 16.7% increase [3][5]. - Bridgewater's assets under management reached approximately $92 billion, reflecting its strategic shift towards AI-driven investment decisions [6][11].

Core Insights - The hedge fund industry is expected to achieve its strongest performance in at least five years in 2025, driven by market volatility from the Trump administration's trade war, which has created lucrative opportunities for traders [1][2] - Bridgewater Associates' flagship fund, Pure Alpha II, recorded a historic return of 34%, marking a significant recovery from the previous years' returns of less than 3% [1][4] - The overall performance of hedge funds in 2025 is characterized by a mix of strategies, with event-driven funds leading the pack [5][6] Performance Summary - **Top Performing Funds**: - Melqart Opportunities Fund achieved a return of 45.1%, the highest among major hedge funds [5] - Bridgewater's Asian fund recorded a return of 37%, while both Pure Alpha II and Bridgewater China achieved 34% [4] - D.E. Shaw's Oculus fund returned 28.2%, and its Composite fund achieved 18.5% [6] - **Market Context**: - The strong performance of hedge funds is attributed to significant gains in the U.S. stock market, particularly driven by artificial intelligence themes, and the volatility in bond and currency markets due to trade tensions [2] - In 2025, the three major U.S. stock indices recorded double-digit annual gains for the third consecutive year, a trend not seen since 2019-2021 [2] Strategy Performance - **Event-Driven Funds**: - Event-driven strategies have shown flexibility and adaptability, with Melqart Opportunities leading at 45.1% and Kite Lake Special Opportunities at 17.9% [5] - **Multi-Strategy Funds**: - D.E. Shaw's flagship funds outperformed market benchmarks, with Oculus achieving a return of 28.2% and Composite at 18.5% [6] - Other multi-strategy funds displayed varied performance, with Dymon at 18.1% and Millennium at 10.5%, which did not outperform the S&P 500 [6][8] - **Equity Strategies**: - Equity long/short strategies showed significant divergence, with Soroban Opportunities at 25% and Anson Investments Master at 21.2% [7] - Other equity funds like Schonfeld's Fundamental Equity and Marshall Wace's Eureka recorded returns of 16.5% and 11.6%, respectively [7] Quantitative Strategies - **Quantitative Funds**: - Winton's multi-strategy fund had the lowest return at 7.4%, while AQR Capital Management's Apex Strategy achieved a 19.6% increase [8]

Core Viewpoint - The explosive growth of AI has significantly boosted the popularity of actively managed quantitative funds, which have shown the ability to outperform the market while reducing volatility risk [2][3]. Group 1: Market Trends - The total share of actively managed quantitative funds reached 80.5 billion units by the end of Q3 2025, marking a 27% increase from the previous year [2]. - Institutional investors hold 46.5 billion units of these funds, accounting for over 70% of the total shares [3]. Group 2: Fund Performance - The "Huaan Event-Driven Quantitative Strategy A" fund has outperformed the CSI 300 index for six consecutive years, with a significant lead in 2025 [6]. - In 2025, the fund achieved a return of 35.77%, compared to 14.04% for its benchmark and 17.20% for the CSI 300 [8]. - The fund's risk-return profile is strong, with annualized returns of 33.02% and a maximum drawdown of -9.96%, outperforming peers in all six key metrics [10]. Group 3: Fund Management - The success of the "Huaan Event-Driven" fund is attributed to its manager, Zhang Xu, who employs a multi-faceted strategy that includes industry rotation and event-driven factors [13][18]. - The "Guojin Quantitative Multi-Factor A" fund, managed by Ma Fang, has also shown resilience, achieving positive returns in 2022 and 2023 despite market downturns [26][29]. Group 4: Investment Strategies - Actively managed quantitative funds are increasingly favored for their ability to adapt to market conditions, utilizing diverse strategies to capture excess returns [18][29]. - The focus on risk-adjusted returns and the ability to navigate different market environments are key factors driving institutional interest in these funds [22][23].

Market Review - The equity market showed mixed performance last week, with the North Certificate 50 index rising the most by 2.79%, while the Shanghai Composite Index fell by 0.34% [5][6] - The bond market saw a collective decline in both short and long-term interest rates, with the 10-year government bond yield decreasing by 0.84 basis points to 1.840% [10][13] - The fund market reflected the equity market's influence, with the equity fund index increasing by 0.71% and the secondary bond fund index rising by 0.06% [16] Equity Product Allocation Strategy Event-Driven Strategy - The joint announcement by three departments to boost consumption suggests a focus on consumer-related funds such as Jiashi New Consumption A and Industrial Bank New Generation Consumption [18] - The release of the "Action Plan for Enhancing Elderly Care Service Capacity" indicates potential investment in the healthcare sector, with funds like Jiashi Mutual Selection A and Penghua Medical Innovation A being highlighted [19] - The opening of the "Robot World" emphasizes investment opportunities in AI and robotics, with funds like Huaxia Intelligent Manufacturing Upgrade A and Jiashi Frontier Innovation being recommended [20] Asset Allocation Strategy - The overall strategy suggests a balanced core plus a barbell approach, focusing on dividend and technology sectors, with recommended funds including Anxin Dividend Selection A and Jiashi Hong Kong Internet Core Assets [21][26] - The dividend assets are highlighted for their value in a low-interest-rate environment, supported by national policies encouraging regular dividends from companies [21] - The technology growth direction is emphasized due to government support and the global trend towards AI development, making tech companies increasingly attractive [22][23] Stable Product Allocation Strategy - The analysis indicates a continued net injection by the central bank, maintaining a loose monetary environment, which is favorable for the bond market [27] - Recent CPI and PPI data show a slight increase in consumer prices, while the Federal Reserve's recent rate cut aligns with expectations for a supportive monetary policy [28] - Recommended products include short-term bond funds like Nord Short Bond A and Guotai Lianan Medium and Short Bond A, with a focus on maintaining a conservative risk profile [33]

Quantitative Models and Construction Methods 1. Model Name: Daily Frequency "High/Low Volume" Signal - **Model Construction Idea**: Define "high volume at high price" and "high volume at low price" events using daily frequency data to identify event signals and construct a capital channel strategy [1][13] - **Model Construction Process**: 1. Define "low volume" events: - Closing price is in the bottom 10% percentile of the past 120 trading days - Trading volume exceeds the average of the past 120 trading days by 1.5 standard deviations 2. Define "high volume" events: - Closing price is in the top 90% percentile of the past 120 trading days - Trading volume exceeds the average of the past 120 trading days by 1.5 standard deviations [13] 3. Construct a capital channel strategy: - Set up 4 capital channels, each with a holding period of 20 trading days - At the beginning of each week, review the past 5 trading days and identify stocks that triggered high/low volume signals - Equally allocate funds to the identified stocks at the beginning of the week and hold for 20 trading days - Calculate the net value of the capital channel portfolio by summing the net values of the 4 channels [18] - **Model Evaluation**: The daily frequency "high/low volume" signals showed that the average excess return peaked around 20-25 trading days after the signal was triggered, but the returns were volatile and did not provide stable incremental returns [1][13][18] 2. Model Name: High-Frequency "High/Low Volume" Event Cluster - **Model Construction Idea**: Use high-frequency micro-level price and volume data to construct more stable "high/low volume" event clusters, which are less correlated and more effective [2][25] - **Model Construction Process**: 1. **Event Identification**: - Define "high/low price" using minute-level closing price data - Define "high/low volume" using minute-level trading volume data, considering factors such as "who's volume," "direction of volume," and "type of volume" [26][29][32] 2. **Signal Definition**: - Combine "high/low price" and "high/low volume" using two methods: - "Price first, volume second": Identify high/low price points first, then check if volume is high - "Volume first, price second": Identify high volume points first, then check if price is high/low [42][43] 3. **Signal Screening and Synthesis**: - Produce thousands of event signals by combining different identification methods - Evaluate the effectiveness and correlation of each signal - Retain effective and low-correlation signals to form "high volume event cluster" and "low volume event cluster" - Synthesize signals to construct comprehensive "high volume" and "low volume" signals [26][44][45] - **Model Evaluation**: The high-frequency "low volume" comprehensive signal provided stable positive excess returns, while the "high volume" comprehensive signal demonstrated strong negative selection effects [50][57] 3. Model Name: Combined "High/Low Volume" Signal - **Model Construction Idea**: Combine the positive selection effect of the "low volume" signal with the negative selection effect of the "high volume" signal to enhance the performance of the capital channel strategy [3][58] - **Model Construction Process**: 1. Use the "low volume" comprehensive signal to pre-screen the stock pool 2. Exclude stocks that triggered the "high volume" comprehensive signal in the past 5 trading days 3. Construct a capital channel strategy: - Set up 4 capital channels, each with a holding period of 20 trading days - At the beginning of each week, review the past 5 trading days and identify stocks that meet the combined signal criteria - Equally allocate funds to the identified stocks at the beginning of the week and hold for 20 trading days - Calculate the net value of the capital channel portfolio by summing the net values of the 4 channels [58] - **Model Evaluation**: The combination of the two signals improved the performance of the capital channel strategy, enhancing both returns and stability [58][60] --- Model Backtesting Results 1. Daily Frequency "High/Low Volume" Signal - **Low Volume Signal**: - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] - **High Volume Signal**: - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57] 2. High-Frequency "High/Low Volume" Event Cluster - **Low Volume Comprehensive Signal**: - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] - **High Volume Comprehensive Signal**: - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57] 3. Combined "High/Low Volume" Signal - **Combined Signal**: - Annualized excess return: 9.14% - IR: 2.42 - Maximum drawdown: 3.70% [60] --- Quantitative Factors and Construction Methods 1. Factor Name: Low Volume Signal - **Factor Construction Idea**: Identify stocks with low prices and high trading volumes as potential candidates for positive returns [13] - **Factor Construction Process**: 1. Define "low price" as the closing price in the bottom 10% percentile of the past 120 trading days 2. Define "high volume" as trading volume exceeding the average of the past 120 trading days by 1.5 standard deviations 3. Combine the two conditions to identify "low volume" events [13] - **Factor Evaluation**: The low volume signal showed positive returns, peaking around 20-25 trading days after the signal was triggered, but the returns were volatile [1][13] 2. Factor Name: High Volume Signal - **Factor Construction Idea**: Identify stocks with high prices and high trading volumes as potential candidates for negative returns [13] - **Factor Construction Process**: 1. Define "high price" as the closing price in the top 90% percentile of the past 120 trading days 2. Define "high volume" as trading volume exceeding the average of the past 120 trading days by 1.5 standard deviations 3. Combine the two conditions to identify "high volume" events [13] - **Factor Evaluation**: The high volume signal showed negative returns, with stocks underperforming after the signal was triggered [15][18] --- Factor Backtesting Results 1. Low Volume Signal - Annualized excess return: 7.67% - IR: 2.22 - Maximum drawdown: 4.68% [50][51] 2. High Volume Signal - Annualized excess return: -10.16% - IR: -0.44 - Maximum drawdown: 8.47% [57]

Group 1 - The core viewpoint of the article emphasizes the characteristics and trading behaviors of convertible bonds, particularly focusing on the phenomenon of abnormal trading in this market segment [1][7]. - Abnormal convertible bonds are influenced by factors such as T+0 trading, relaxed price limits, and lower transaction costs, making them more susceptible to speculative trading [8][10]. - The article categorizes abnormal trading in convertible bonds based on special clause triggers, significant price fluctuations, and high turnover rates [2][12]. Group 2 - The performance statistics after significant price fluctuations indicate that if a convertible bond experiences a daily price swing exceeding 10% and closes up by more than 5%, its future performance tends to be weak unless it is in a redemption counting period [3][28]. - Conversely, if a convertible bond closes down by more than 5% after a significant price drop, it shows potential for excess returns, especially if it is in a down-adjustment or repurchase counting period [4][37]. Group 3 - The article outlines event-driven strategies, suggesting a sell strategy for convertible bonds that experience significant price increases after abnormal trading, which has yielded excess returns of 69.5% since 2017 [5][56]. - A buy strategy is proposed for convertible bonds that decline significantly after abnormal trading, particularly those in down-adjustment counting periods, although caution is advised due to high concentration risks [6][61]. Group 4 - The characteristics of abnormal convertible bonds include small market capitalization, low ratings, high valuations, and strong stock characteristics [7][73]. - The analysis reveals that abnormal trading convertible bonds tend to have lower average remaining scales and ratings compared to the overall sample, indicating a distinct profile for these securities [69][70].

Summary of Key Points from Conference Call Industry Overview - The conference call discusses the **offshore bond market**, specifically focusing on **Chinese dollar bonds** and **dim sum bonds**. The former is denominated in USD, while the latter is denominated in offshore RMB and is primarily issued in Hong Kong [1][2]. Core Insights and Arguments - **Market Dynamics**: The offshore bond market has seen a contraction since 2021 due to the Federal Reserve's interest rate hikes and real estate risks. However, a rebound in issuance is expected in 2024 with anticipated rate cuts, although net financing remains negative [1][12]. - **Dim Sum Bonds Growth**: The dim sum bond market has been expanding, benefiting from the advantages of RMB financing and the Southbound Trading initiative, with a notable increase in the proportion of municipal investment bonds [1][12][13]. - **Pricing Factors**: The pricing of Chinese dollar bonds is influenced by historical returns, yield spreads, and credit ratings. High-yield bonds exhibit significant volatility and are closely tied to credit risk. Dim sum bonds are priced based on offshore RMB government bond rates, affected by liquidity in both onshore and offshore RMB markets [1][14][15]. Important but Overlooked Content - **Investment Strategies**: Various investment strategies are discussed, including curve trading, event-driven trading, and swing trading, each with its own advantages and requiring market environment adjustments [2][23][24][25]. - **Regulatory Environment**: The regulatory framework for offshore bond issuance is relatively lenient, with different disclosure requirements based on the type of issuance (e.g., SEC 144A, Reg S). Most Chinese issuers prefer Reg S due to lower compliance costs [5][8][18]. - **Default Resolution**: Common default resolution strategies include bond swaps, debt-to-equity conversions, bankruptcy liquidation/restructuring, and discounted buybacks/extensions. The effectiveness of these strategies largely depends on the underlying company's value performance [27][28]. Market Characteristics - **Issuance Structures**: The most common issuance structure in both markets is direct issuance, followed by guaranteed structures and maintenance agreements. The Chinese dollar bond market has a higher proportion of guaranteed structures compared to the dim sum market [7][12]. - **Investor Behavior**: Investors are increasingly focused on short-term liquidity rather than long-term value, reflecting a shift in risk appetite and market conditions [2][28]. Conclusion - The offshore bond market, particularly Chinese dollar and dim sum bonds, is influenced by macroeconomic factors, regulatory environments, and investor behavior. The anticipated changes in interest rates and market dynamics will play a crucial role in shaping future investment opportunities and risks in this sector [1][12][19].

Core Insights - The Galaxy CSI 800 Index Enhanced Securities Investment Fund will be launched on November 10, aiming to provide investors with a pathway to participate in China's long-term economic development while pursuing excess returns [1][2] - The CSI 800 Index is a representative index in the A-share market, established as a "pillar" since its release at the end of 2004, reflecting the achievements of economic structural adjustments [1] Fund Strategy - The fund manager, Luo Bo, employs a "multi-factor stock selection + event-driven strategy" combined with a rigorous risk model for comprehensive management [2] - The multi-factor model evaluates constituent stocks based on growth, valuation, and profitability, dynamically adjusting factor weights to adapt to changing market conditions [2] - The event-driven strategy focuses on identifying assets that may yield excess returns for individual stocks, aiming to enhance overall portfolio performance [2] Risk Management - The fund aims to maintain an annualized tracking error within 7.75% and an average absolute tracking deviation of no more than 0.5%, closely aligning with the CSI 800 Index to prevent style drift [1]

Report Industry Investment Rating - Not provided in the content Core Viewpoints of the Report - In 2025, quantitative strategies are recommended over subjective ones in private securities investment institutions [1] - The private securities investment fund industry in China is characterized by increasing industry concentration with significant advantages for leading institutions, and an enhanced trend of diversified and international investment strategies [23][24] Summary by Relevant Catalogs Market Background - Affected by geopolitical conflicts and US tariff policies, the global stock market rose in the first half of 2025. A-shares showed an "N-shaped" trend, Hong Kong stocks performed better, and US stocks achieved a "V-shaped reversal". By the end of June 2025, the number of A-share listed companies reached 5,420, an increase of 37 from the end of 2024, and the total market value exceeded 100.02 trillion yuan, hitting a record high. The Beizheng 50 Index soared 39.45% in the first half of the year, leading the world in terms of gains. Industries such as non-ferrous metals (17.93%) and enterprise services (16.85%) led the rise, while industries such as coal (-10.02%) and real estate (-6.52%) faced pressure [4] - Chinese private securities investment funds are privately raised from qualified investors and mainly invest in publicly traded financial assets. They have more flexible investment strategies compared to public funds, lower liquidity, and can achieve differentiated returns through personalized strategies. Their operation must meet strict standards for qualified investors and emphasize the principle of self-risk assumption [5] - The development of Chinese private securities investment funds has evolved from disorderly exploration to standardization and specialization. Since 2025, driven by structural opportunities in the A-share market and excess returns from quantitative strategies, the issuance of private securities funds has recovered. In the first half of the year, over 5,400 new products were filed, with the filing scale increasing by 75% year-on-year [6] Market Status - As of the end of August 2025, the outstanding scale of Chinese private securities investment funds reached 5.56 trillion yuan, accounting for 27.4% of the total scale of private funds, a 6.5% increase from 5.24 trillion yuan at the beginning of 2025. Stock strategies dominate, and diversified strategies such as quantitative hedging and macro strategies are also developing rapidly. In July 2025, 1,313 new private securities funds were filed, with a scale of 79.281 billion yuan, a record high for the year. In the first half of the year, a total of 5,461 new filings were made, a 53.6% increase year-on-year, reflecting a significant trend of funds "entering the market through funds" [7][8] - As of the end of August 2025, there were 7,722 private securities fund managers, 385 fewer than at the end of 2024, mainly due to regulatory cleanup of "fake private funds". Geographically, Shanghai, Beijing, and Shenzhen account for over 50% of the total number of managers, and their management scales account for 25.2%, 23.2%, and 9.7% respectively [9] - The market demand for private securities funds shows a trend of diversification and stratification. The number of qualified investors has continued to expand, covering high-net-worth individuals, insurance funds, pensions, and foreign institutions. Insurance funds are accelerating the allocation of equity assets through pilot programs, and foreign institutions are also increasing their layout in the A-share market. Investor demand is significantly differentiated, with conservative funds preferring low-volatility products such as quantitative hedging and macro strategies, and aggressive funds focusing on stock long strategies. Market structural opportunities and policy guidance also affect the flow of funds and drive the continuous iteration of private securities fund strategies [10] Market Competition - The selection of the top ten private securities investment institutions follows a multi-dimensional quantitative evaluation model, with core indicators including management scale and stability, historical performance, and excess return ability [11] - The current industry competition shows a pattern of "siphoning by leading players" and "strategy differentiation". Leading quantitative private funds dominate with technical barriers and excess return ability. In 2025, the number of 10-billion-yuan quantitative private funds reached 41, exceeding that of 10-billion-yuan subjective private funds (40) for the first time. In the first half of the year, the average yield of quantitative private funds was 13.54%, significantly higher than that of subjective private funds (5.51%). Quantitative strategies perform well in volatile markets, while subjective strategies face challenges [12] - Ten institutions, including Gao Yi Asset, Orient Harbor, and Ningbo Magic Square Quantitative, are introduced, each with its own characteristics in terms of management scale, investment strategy, and core team [13][14][15] Development Trends - The Chinese private securities investment fund industry shows a significant "Matthew effect", with leading institutions having significant advantages in terms of funds, talent, technology, data, and trading systems. The number of 10-billion-yuan private fund managers has exceeded 100, and their share of the total industry management scale continues to rise. Small and medium-sized private funds face survival pressure, and foreign private funds are accelerating their localization layout, intensifying industry competition and promoting the concentration of resources to leading institutions [23] - With the deepening of China's capital market reform and the enrichment of financial derivative tools, private securities investment strategies are developing in a diversified direction from traditional stock long to quantitative hedging, macro strategies, event-driven, and cross-border investment. Regulatory authorities encourage private funds to serve the real economy and introduce long-term funds, and the cooperation between private funds and financial institutions such as securities firms and banks is deepening. In the future, strategy innovation and international layout will become core competitiveness [24]