1. Report Industry Investment Rating - The report does not mention the industry investment rating. 2. Core Viewpoints of the Report - Since 2025, in a low - interest - rate environment, the scale of fixed - income plus funds has expanded significantly. In Q4 2025, the total scale reached about 2.83 trillion yuan, with the growth mainly coming from secondary bond funds. The industry shows a trend of increasing concentration [7]. - There is a significant performance differentiation among fixed - income plus funds. The report analyzes the performance causes of high - performing fixed - income plus funds in Q4 2025 and long - term high - performing funds, providing references for investors [14]. - High - performing fixed - income plus funds in Q4 2025 generally use higher stock and convertible bond positions, have a relatively short average bond duration, and show characteristics such as heavy positions in high - growth cyclical sectors and low positions in falling sectors [27][46]. - Long - term high - performing fixed - income plus funds have high return - risk matching, stable equity positions, and a multi - strategy synergy model to enhance returns [76][81]. 3. Summary by Relevant Catalogs 3.1 Industry Overview - **Scale and Growth**: In a low - interest - rate environment, the scale of fixed - income plus funds has expanded. By the end of Q4 2025, the total scale was about 2.83 trillion yuan, a 3.2% increase from Q3 2025. The scale growth mainly came from secondary bond funds, while the scale of primary bond funds continued to decline [7]. - **Industry Concentration**: The industry shows a trend of increasing concentration. The proportion of the top ten fund companies in the fixed - income plus fund scale increased from 46.0% in Q3 2025 to 48.4% in Q4 2025 [10]. - **Leading Companies and Products**: As of the end of 2025, E Fund and Invesco Great Wall Fund were the only two companies with a "fixed - income plus" scale exceeding 20 billion yuan. Some leading products had large scales and better performance than the average [13]. 3.2 Performance Overview of Fixed - Income Plus Funds - **Overall Performance in Q4 2025**: The arithmetic average quarterly return of fixed - income plus funds was 0.42%. The average returns of partial - debt hybrid funds, primary bond funds, secondary bond funds, and convertible bond funds were 0.28%, 0.59%, 0.43%, and 0.88% respectively. The proportion of products with positive returns was 75.0%, a decrease from Q3 2025 [16]. - **Top - Performing Funds in Q4 2025**: In different types of funds, there were top - performing products. For example, Orient Minfeng Return Ying'an Hybrid led the partial - debt hybrid funds with a 15.95% return in Q4 2025 [18]. - **High - Performing Fixed - Income Plus Funds in Q4 2025**: The high - performing funds met certain conditions, with returns ranging from 0.88% - 7.36%. They had characteristics such as good returns, solid risk control, stable scale, and balanced allocation [21]. 3.3 Allocation Characteristics of High - Performing Fixed - Income Plus Funds - **Leverage and Investor Structure**: In Q4 2025, the average leverage levels of high - performing fixed - income plus funds and the whole market showed differentiation. The leverage of high - performing primary bond funds and partial - debt hybrid funds was slightly higher than the market average, while that of high - performing secondary bond funds and convertible bond funds was lower. The investor structure also showed category differentiation, with institutional funds being the main force in secondary bond funds, primary bond funds, and convertible bond funds, while partial - debt hybrid funds were mainly held by individuals [28][32]. - **Bond Allocation**: The bond allocation structures of fixed - income plus funds and high - performing fixed - income plus funds were similar, with financial bonds as the core holding. High - performing funds had a higher proportion of treasury bonds and convertible bonds and a lower proportion of corporate bonds and medium - term notes. The average duration of high - performing funds was relatively shorter [35][43]. - **Stock Allocation**: High - performing fixed - income plus funds in Q4 2025 had heavy positions in high - growth cyclical sectors and low positions in falling sectors. The top - performing stocks were concentrated in cyclical, technology, and financial blue - chip stocks, with high concentration [46][55]. - **Convertible Bond Allocation**: The convertible bond positions of high - performing fixed - income plus funds were similar to those of the whole market, with bank convertible bonds as the core bottom - position and high - elasticity individual bonds. The performance of individual bonds was significantly differentiated [62]. 3.4 Long - Term High - Performing Fixed - Income Plus Funds - **Selection and Basic Information**: Four fixed - income plus funds with performance ranking in the top 30% of their peers in each full year in the past five years were selected, including primary bond funds, secondary bond funds, and partial - debt hybrid funds. They had different scales and stable returns [65][67]. - **Common Allocation Characteristics**: These funds had high return - risk matching, stable equity positions, and a preference for high - grade bonds. They adopted a "bond as the base + X" multi - strategy synergy model to enhance returns [76][81].

Group 1: Investment Strategy and Market Analysis - The report emphasizes the investment value of the Bank of China CSI All-Index Free Cash Flow ETF (563760), highlighting its large scale and liquidity advantages in the market [1][6][9] - It discusses the current economic environment characterized by a Kondratiev wave downturn, suggesting that cash flow assets are superior "safe assets" during this period [6][7] - The report predicts that 2026 will be a "value investment year" in China, with cash flow assets expected to undergo systematic revaluation due to improved cash flow generation capabilities of Chinese companies [7] Group 2: Company Overview - Jiu Li Special Materials (002318.SZ) - Jiu Li Special Materials is pursuing a strategy focused on high-end products, international expansion, and platform development, which is expected to drive growth in various sectors including nuclear power and aerospace [2][10][11] - The company is projected to achieve net profits of 1.789 billion, 1.999 billion, and 2.228 billion CNY from 2025 to 2027, with corresponding EPS of 1.83, 2.05, and 2.28 CNY [10] - The report assigns a target price of 42.85 CNY per share for 2026, based on a PE ratio of 23, and initiates coverage with a "buy" rating [2][10] Group 3: Company Overview - Far East Horizon (03360.HK) - Far East Horizon reported total revenue and net profit of 35.785 billion and 3.889 billion CNY for 2025, reflecting a year-over-year change of -5.20% and +0.67% respectively [14][15] - The company has optimized its liability structure, resulting in a significant increase in net interest margin, with a net interest margin of 4.39% for 2025, up by 0.39 percentage points year-over-year [15] - The report maintains a "buy" rating, forecasting net profits of 4.061 billion, 4.254 billion, and 4.367 billion CNY for 2026 to 2028, indicating a positive growth outlook [14][15]

Core Viewpoint - The article emphasizes the emergence of fund managers who prioritize shareholder returns and sustainable excess returns over mere performance rankings, indicating a shift towards high-quality development in public funds [1]. Group 1: Fund Manager Selection - The annual selection of active equity and fixed-income fund managers aims to identify those who can outperform the market in the future rather than just listing past winners [2]. - In a volatile market, investors are particularly focused on investment experience, leading to an analysis of balanced-style fund managers [2]. Group 2: Zhang Jing's Investment Philosophy - Zhang Jing, a prominent fund manager, focuses on absolute return-oriented investment, aiming to enhance shareholder experience by reducing volatility while pursuing returns [4]. - His investment framework is built on the premise that high volatility in the A-share market hinders investors from making profits, leading him to prioritize lower volatility alongside higher excess returns [4][5]. Group 3: Investment Framework - Zhang Jing's approach includes three main aspects: 1. Utilizing stock selection as the primary source of excess returns, diversifying across sectors to mitigate high volatility [5]. 2. Focusing on identifying fundamental turning points in companies, allowing for rapid realization of alpha when market data aligns with company performance [5]. 3. Emphasizing the replicability of valuation space, aiming to buy companies at relatively low prices to minimize volatility [6]. Group 4: Balanced Investment Style - Zhang Jing's balanced investment style is characterized by adaptability to various market conditions, having successfully navigated different market cycles without relying on a single style or sector [8]. - His portfolio spans multiple sectors, ensuring low correlation among industries to maintain balance [8]. Group 5: Team and Company Philosophy - Anxin Fund has a total public fund scale of approximately 105.7 billion, with 57% of its non-cash scale in equity and mixed products, highlighting its focus on active equity investment [11]. - The company fosters a research-oriented culture, allowing fund managers to develop their unique styles while adhering to a core value of long-term wealth preservation for shareholders [12][14]. Group 6: Common Traits Among Fund Managers - Anxin Fund managers share common traits such as a strong value-oriented philosophy, a focus on volatility control, and a commitment to long-term returns, with many having over 10 years of industry experience [13]. - The emphasis on fundamental research and stock selection as the main source of alpha is a defining characteristic of the fund managers at Anxin [13]. Group 7: Market Outlook - The year 2025 is expected to present concentrated structural opportunities, with significant performance differences across industries, indicating that sector selection will greatly impact returns [16]. - As market styles become more balanced, Zhang Jing's investment approach may find better opportunities for performance [16].

Group 1 - The article discusses the lesser-known topic of bond index funds and offers a free course on investment methods for these funds [2] Group 2 - The article analyzes the performance of technology indices in the A-share and Hong Kong markets, noting that bull markets often experience corrections and typically follow a pattern of "three up, one down" or "three up, two down" [6] - It highlights that the growth in technology indices is closely linked to the earnings growth of the underlying listed companies, with significant increases in earnings leading to substantial index gains [6] - For instance, in the first half of 2025, Hong Kong technology stocks are expected to see a year-on-year doubling of earnings, which would drive the technology index upward in the first three quarters of 2025 [6] - However, since the fourth quarter of 2025, the growth rate of earnings for technology indices in both A-share and Hong Kong markets has slowed down [6]

Group 1 - The core concept of the article revolves around the emergence of HALO trading, which stands for Heavy Assets, Low Obsolescence, indicating a shift in investment logic on Wall Street since 2026 [4][5]. - HALO trading emphasizes investing in heavy asset companies that are less likely to be replaced by technological advancements, particularly in the context of rapid AI development [5][22]. - The performance of HALO asset portfolios has significantly outperformed light asset industries since 2025, highlighting a renewed focus on real assets in the AI era [5][22]. Group 2 - HALO investment fundamentally seeks long-term cash flow assets, characterized by stable and sustainable free cash flow [6][9]. - Heavy asset industries typically have high entry barriers, making them difficult to replicate quickly, thus ensuring a stable cash flow once established [7][8]. - The market is increasingly valuing companies with stable cash flow capabilities due to the uncertainties introduced by AI technologies [9]. Group 3 - For ordinary investors, systematically screening for HALO assets can be challenging; utilizing a free cash flow index can provide a more efficient method for identifying quality assets [10][11]. - The Guozheng Free Cash Flow Index focuses on free cash flow capability, stability, profitability quality, and asset quality to identify companies that generate long-term cash flow [11][12]. - The index's performance aligns well with the current HALO investment philosophy, indicating its effectiveness in identifying quality investments [12]. Group 4 - Investors interested in HALO logic can consider passive index funds like the Huaxia Guozheng Free Cash Flow ETF, which diversifies investments across companies with stable cash flow [16][18]. - This ETF approach helps mitigate industry-specific risks and focuses on companies with strong profitability and cash flow stability [16][18]. - In the rapidly changing AI landscape, companies with real assets and stable cash flows are likely to become core assets of long-term market interest [18]. Group 5 - The article suggests that asset pricing may be returning to "real value" as the market reassesses which assets are truly irreplaceable in light of rapid AI advancements [22]. - The emergence of HALO trading reflects a new investment trend where capital is shifting back to real assets and cash flow itself [22]. - For investors seeking long-term asset allocation strategies in uncertain environments, focusing on companies with stable cash flow capabilities is recommended [22].

Core Viewpoint - The FOF market is expected to experience a strong recovery in 2025, with over 80 new funds launched and a total fundraising scale of 800 billion yuan, highlighting the increasing importance of multi-asset allocation for clients [1] Multi-Asset Allocation Core - Multi-asset allocation emphasizes diversification across various asset types, including global equity markets and flexible fixed income investments, as well as commodities and alternative investments [3] - The core of multi-asset allocation lies in understanding macroeconomic and industry cycles, along with risk control capabilities, which are dynamic rather than static [3][5] Multi-Strategy Approach - Multi-strategy provides another dimension to multi-asset allocation, with common strategies including CPPI, risk parity, and macro allocation strategies [4] - The essence of multi-asset allocation is to seek heterogeneous returns and risk sources to reduce volatility and risk [5] Sources of Returns in Multi-Asset Allocation - Returns from multi-asset allocation can be broken down into two core dimensions: the ability to grasp trends in individual asset categories and top-down macro allocation capabilities [8] - For equities, understanding industry trends and cycles is crucial, while fixed income requires a comprehensive assessment of macro variables like interest rate risk and economic growth [8] Effective Multi-Asset Allocation - Effective multi-asset allocation should focus on diversifying into heterogeneous assets like bonds and gold to lower portfolio volatility and risk [12] - It is essential to conduct sector rebalancing based on different industry and economic cycle characteristics, as well as asset price-performance ratios [12]

Core Viewpoint - Investment is the realization of cognition, and excess returns come from being ahead of market recognition. Huashan Fund has consistently aligned with the direction of China's industrial rise, leading the market in growth investment through various industry transformations since 2013 [1]. Group 1: Huashan Fund's Investment Strategy - Huashan Fund has developed a global perspective on the comparison between China and the US, being sensitive to overseas technological innovations and changes [1][3]. - The fund has established a learning-oriented research platform that encourages collaboration among researchers from different fields to tackle the complexities of emerging industries [5]. - Huashan Fund emphasizes building a high-quality research foundation, hiring researchers with industry backgrounds to quickly identify changes in the Chinese economy [5][6]. Group 2: Performance of Fund Managers - Fund manager Sang Xiangyu has shown significant performance, achieving a 58.19% growth in the pharmaceutical sector and an 85.56% net value increase in the Huashan Huihong Select fund over the past year [1][19]. - Sang's investment framework combines top-down industry analysis with bottom-up stock selection, focusing on the resonance between industry beta and stock alpha for optimal investment efficiency [11][12]. Group 3: Emerging Industry Focus - Huashan Fund has proactively invested in emerging industries, including 5G, electric vehicles, and artificial intelligence, demonstrating a strong ability to capture new opportunities [3][4]. - The fund's research covers both traditional and emerging sectors, ensuring no industry is overlooked, which has allowed for rapid adaptation to industry changes [6]. Group 4: Future Investment Directions - Sang Xiangyu has identified two long-term investment directions: "going out" and "rolling out," categorizing industries into three priority levels based on their competitiveness and growth potential [14][15]. - The focus on AI investment is structured into three layers: hardware, energy, and resource investments, indicating a comprehensive approach to capitalizing on technological advancements [15][16]. Group 5: Product Offering - The new product, Huashan Innovation Momentum, features a floating fee structure that aligns the interests of the fund with its investors, showcasing a commitment to performance-based management [19]. - The product's performance benchmark is designed to reflect a balanced growth index, allowing for investment in both domestic and Hong Kong stocks [19]. Group 6: Research Foundation - Huashan Fund's robust research foundation is crucial for generating excess returns, moving away from individual heroism to a team-based approach in investment management [20].

Market Overview - As of March 6, 2026, the total market size of ETFs reached 5.30 trillion yuan, a decrease of 0.72 trillion yuan since the beginning of the year, with the number of listed ETFs increasing to 1,445, adding 45 new listings [2][22] - The stock-type ETFs accounted for 3.09 trillion yuan, while bond-type ETFs totaled 737.49 billion yuan, and commodity-type ETFs increased by 106.15 billion yuan to 356.61 billion yuan, driven by strong demand for gold as a safe haven [2][22] Performance Disparity - Last week, leading military industry ETFs and dividend ETFs had PE percentiles close to 100, while the Hang Seng Technology ETF (15.57), pharmaceutical ETF (32.73), and electric power ETF (44.71) remained at historical low valuations, indicating potential investment opportunities [2][12][18] - The performance of various sectors showed significant divergence, with cyclical manufacturing ETFs like oil rising by 8.20%, while broader indices like the CSI 300 and CSI 500 experienced declines of 1.23% and 3.62%, respectively [12][16] Fund Flows - Overall, funds showed a defensive tendency last week, with broad-based ETFs experiencing net outflows, while commodity (gold) and fixed-income ETFs attracted capital, with SGE gold seeing a net inflow of 877.57 billion yuan year-to-date [3][20] - The main inflow channels were thematic ETFs (+2,016 billion yuan) and cyclical manufacturing ETFs (+1,443 billion yuan), indicating a clear trend of capital migrating from broad-based ETFs to thematic and cyclical sectors [3][33] Issuance Dynamics - The issuance of ETFs accelerated last week, with 77 ETFs in the process of being issued (up 48% week-on-week), and 12 new funds established (up 140%) [4][52] - New products primarily focused on energy sectors, with electric grid equipment, electric power, and photovoltaic ETFs dominating the new listings, reflecting current market trends [4][52] Trading Activity - The total trading volume of ETFs was approximately 2.9 trillion yuan last week, with bond-type ETFs leading the increase, followed by stock-type ETFs [39] - The short-term bond ETF from Hai Fu Tong had a weekly trading volume of 2,991.97 billion yuan, indicating high liquidity in the bond market [41] Valuation Insights - The valuation structure showed that core broad-based ETFs remained relatively stable, while growth and small-cap valuations were more volatile, reflecting a higher sensitivity to market fluctuations [12][18] - The Hang Seng Technology ETF and other low-valuation sectors like pharmaceuticals are attracting attention for potential long-term investments due to their historical low PE percentiles [18][20]

Core Insights - The report highlights a significant shift in fund allocation preferences, with traditional pure bond funds losing dominance as "fixed income +" funds and index bond funds expand in size and popularity [3][14][33] - The "fixed income +" funds are seen as more attractive due to their ability to provide both bond base and equity flexibility, especially in a low-interest-rate environment where the appeal of pure bond funds diminishes [19][23][32] Fund Allocation Behavior Analysis - In 2025, pure bond funds experienced negative growth, while "fixed income +" funds and index bond funds saw substantial growth, indicating a market preference for diversified and tool-based products [3][14][33] - The allocation preferences have shifted, with "fixed income +" funds increasing their market share from 14% in Q4 2024 to 23% in Q4 2025, while pure bond funds decreased from 76% to 61% during the same period [14][33] - The report identifies that the marginal changes in bond allocation preferences within "fixed income +" products can influence market liquidity and credit spreads, providing valuable insights for bond fund managers and investors [33] Market Structure and Trends - The overall market for "fixed income +" funds saw a net increase of 86 products and a scale increase of 10,443 billion yuan in 2025, contrasting with a decline of 1,901 billion yuan in the previous year [46] - The report notes that the mixed secondary bond funds are leading in both product count and scale growth, with a significant increase in their market presence [46] - The asset allocation overview indicates a rebalancing towards interest rate bonds and equities, while reducing exposure to credit bonds and convertible bonds [52][56] Risk-Return Assessment - The report assesses that the return elasticity of "fixed income +" funds has improved, with defensive attributes being enhanced, while pure bond funds have seen a decline in return rates and increased volatility [23][26] - The performance of various fund types in 2025 shows a divergence in risk-return profiles, with stock and mixed funds performing better compared to pure bond funds, which have struggled in a low-interest-rate environment [23][26]

Quantitative Models and Construction Methods 1. Model Name: Risk Parity Strategy - **Model Construction Idea**: The model aims to allocate risk equally across asset classes, ensuring that no single asset class dominates the portfolio's risk exposure[4][59]. - **Model Construction Process**: - Identify risk factors such as growth, inflation, interest rates, and liquidity[59]. - Allocate capital to asset classes (e.g., equities, bonds, commodities) based on their risk contribution rather than nominal weights. - Use derivatives to adjust exposures and maintain risk parity across the portfolio[59]. - **Model Evaluation**: Demonstrates strong performance in diversified portfolios, particularly in volatile markets, by balancing risk exposure across asset classes[59]. 2. Model Name: Multi-Factor Framework (Mixed Strategy) - **Model Construction Idea**: Combines quantitative frameworks with subjective judgment to adjust asset allocation based on macroeconomic and fundamental indicators[58][59]. - **Model Construction Process**: - Use macroeconomic data (e.g., GDP, inflation, employment) and alternative data (e.g., climate change, central bank meetings) to generate signals through natural language processing[58]. - Incorporate fundamental indicators such as bond yields, credit risk, earnings growth, and valuation levels for specific asset classes[58]. - Adjust baseline quantitative weights based on subjective views to capture short-term opportunities[58]. - **Model Evaluation**: Provides flexibility to adapt to changing market conditions while maintaining a systematic foundation, offering a balance between stability and opportunism[58]. 3. Model Name: Covered Call Strategy (Income Strategy) - **Model Construction Idea**: Focuses on generating stable cash flows by combining equity holdings with options strategies[58]. - **Model Construction Process**: - Invest in high-dividend stocks to capture equity beta returns. - Sell call options on the underlying stocks to generate premium income. - Maintain a balance between equity exposure and option coverage to optimize risk-adjusted returns[58]. - **Model Evaluation**: Suitable for investors seeking stability and income, with lower volatility compared to pure equity strategies[58]. --- Model Backtesting Results 1. Risk Parity Strategy - **Fidelity Risk Parity Fund**: - 1-month return: -0.09% - 3-month return: 5.20% - 6-month return: 11.51% - YTD return: 4.72% - 1-year return: 21.37% - 1-year volatility: 11.55% - 1-year max drawdown: 3.46% - Return/volatility: 1.85 - Return/max drawdown: 2.29[68] - **Invesco Balanced-Risk Allocation Fund**: - 1-month return: 6.61% - 3-month return: 12.35% - 6-month return: 17.22% - YTD return: 12.62% - 1-year return: 19.20% - 1-year volatility: 8.91% - 1-year max drawdown: 3.74% - Return/volatility: 2.15 - Return/max drawdown: 2.49[68] 2. Multi-Factor Framework (Mixed Strategy) - **PIMCO Global Core Asset Allocation Fund**: - 1-month return: -0.77% - 3-month return: 5.68% - 6-month return: 11.56% - YTD return: 3.68% - 1-year return: 21.30% - 1-year volatility: 9.20% - 1-year max drawdown: 3.58% - Return/volatility: 2.32 - Return/max drawdown: 2.34[68] - **Blackrock Tactical Opportunities Fund**: - 1-month return: 1.69% - 3-month return: 3.38% - 6-month return: 1.19% - YTD return: 2.59% - 1-year return: 7.20% - 1-year volatility: 6.37% - 1-year max drawdown: 2.56% - Return/volatility: 1.13 - Return/max drawdown: 1.27[68] 3. Covered Call Strategy (Income Strategy) - **PIMCO Dividend and Income Fund**: - 1-month return: 0.13% - 3-month return: 5.70% - 6-month return: 10.28% - YTD return: 4.60% - 1-year return: 19.11% - 1-year volatility: 7.56% - 1-year max drawdown: 2.66% - Return/volatility: 2.53 - Return/max drawdown: 2.75[68] --- Quantitative Factors and Construction Methods 1. Factor Name: Growth - **Factor Construction Idea**: Measures economic expansion through GDP growth and corporate earnings[59]. - **Factor Construction Process**: - Collect macroeconomic data on GDP and corporate earnings. - Normalize data to account for seasonal and cyclical variations. - Use the factor to overweight equities and commodities during periods of strong growth[59]. 2. Factor Name: Inflation - **Factor Construction Idea**: Captures the impact of rising prices on asset classes such as bonds and commodities[59]. - **Factor Construction Process**: - Track inflation indicators such as CPI and PPI. - Adjust bond and commodity exposures based on inflation trends. - Hedge inflation risk using TIPS or commodity futures[59]. 3. Factor Name: Liquidity - **Factor Construction Idea**: Assesses market liquidity conditions to optimize asset allocation[59]. - **Factor Construction Process**: - Monitor central bank policies, interest rates, and money supply. - Increase exposure to liquid assets during tightening cycles. - Use derivatives to manage liquidity risk[59]. --- Factor Backtesting Results 1. Growth Factor - Positive correlation with equity and commodity returns during periods of economic expansion[59]. 2. Inflation Factor - Strong performance in inflationary environments, particularly for TIPS and commodities[59]. 3. Liquidity Factor - Effective in managing drawdowns during periods of market stress by increasing exposure to liquid assets[59].