全球PMI新订单和软数据总体上没有显示出任何改善的迹象。持续时间越长，瑞银的PMI模型就越倾向 于看空。对周期性股票(特别是在材料和消费者自由支配名称中)的谨慎可能是有必要的。 经合组织G20综合领先指数提供的宏观图景比采购经理人指数(PMI)或消费者调查更为乐观。瑞银的制 度模型变化不大，仍超配晚期周期性股票，低配晚期防御性股票。 瑞银表示，过去两个月的市场反弹，加上第一季度收益发布，主要(且负面地)影响了能源、科技和工业 的估值。目前，金融、公用事业和必需消费品仍是瑞银调整后的12个月远期市盈率模型中最便宜的行 业，而科技和医疗保健仍是最贵的行业。 智通财经APP获悉，瑞银的量化模型基于11个高性能指标，对全球股票进行筛选。报告指出，当前评分 最高的股票主要集中在通信服务、保险、媒体、交通和资本货物等行业。而评分最低的股票则多为半导 体、家用个人护理产品、消费者耐用消费品、医疗保健和材料类股票。 该行指出，投资者似乎正在远离能源和防御性股票，建立空头头寸，但尚未显得拥挤。然而，金融行业 （尤其是银行）的拥挤指标亮起红灯。房地产和中国仍分别是被低估的行业和地区。 从收益预期和动量的差异来看，公用事业股票在模 ...

Core Viewpoint - The market appears stable with minor fluctuations, but an increase in margin financing suggests underlying positive trends that may not be immediately visible [1][3]. Group 1: Market Dynamics - Margin financing has increased for five consecutive days, indicating that the market's apparent weakness may be misleading [3]. - The increase in margin financing is typically associated with a profit-making effect, despite the rapid switching of market hotspots [4]. - Key sectors such as new consumption, military industry, and innovative pharmaceuticals show an overall upward trend, contradicting the perception of a lack of opportunities [4]. Group 2: Retail Investor Challenges - Retail investors often struggle to navigate the market despite the presence of rising sectors due to difficulties in timing their trades [4]. - The inability to distinguish between "washing" and "topping" actions by institutional investors leads to confusion among retail investors [4]. Group 3: Institutional Insights - The maturity of quantitative models allows retail investors to analyze institutional trading behaviors, enhancing their ability to interpret market movements [6]. - Observing institutional "washing" actions can reveal significant trading patterns, such as initial selling pressure followed by a rebound [6]. - The "panoramic K-line" analysis can provide a comprehensive view of institutional activities, indicating whether institutions are actively participating in the market [8]. Group 4: Data Trends - Recent statistics show that institutional inventory data has reached over 2800, indicating significant activity and potential positive implications for the market's mid-term outlook [12].

Core Viewpoint - The article systematically categorizes A-share listed companies into four lifecycle stages: startup, growth, maturity, and consolidation, based on cash flow, and constructs corresponding optimal portfolios for each stage, achieving annualized excess returns of 14.0%, 15.0%, and 19.5% relative to benchmark indices since 2016 [1][3]. Group 1: Lifecycle Stages Characteristics - Startup companies typically have smaller market capitalizations, unstable profitability, and low dividend yields, but invest heavily in R&D [1]. - Growth companies show improved profitability with a balanced exposure across various factors [1]. - Mature companies are characterized by large market capitalizations, stable profitability, high dividend payout ratios, and healthier capital structures with lower debt ratios [1]. - Consolidation companies experience reduced scale, poorer profitability, lower dividend yields, and higher leverage with significant debt repayment pressures [1]. Group 2: Performance and Risk Characteristics - The buy-and-hold combinations across different lifecycle stages exhibit varying risk-return profiles, with mature companies showing the most stability and highest cumulative returns over time [2]. - Growth stock portfolios perform closely to market indices, while startup and consolidation stock portfolios exhibit higher volatility and lower returns [2]. - Factor performance varies across lifecycle stages, with low volatility and low turnover rates performing best in the riskier startup and consolidation phases [2]. Group 3: Optimal Portfolio Construction - The company constructs optimal portfolios for each lifecycle stage considering investment logic, factor effectiveness, and correlations, with the mature portfolio demonstrating the highest stability and an annualized return of 16.9% since 2016 [2]. - The mature portfolio has shown positive excess returns relative to common broad indices like the CSI All Share Index, CSI 300, and CSI 800 in most years, except for a 12% decline in 2018 [2].

据介绍,该产品成立于2022年10月,迄今运作时间超两年半,历经多个市场波动周期,自成立以来净值增长率 为10.33%,年化收益率达到3.80%,最大回撤仅-0.32%,其投资策略和业绩表现受到业界和客户的广泛认 可。 6月5日,由财视中国主办的第十八届"银行业·介甫奖评选"在上海举行。平安理财凭借专业精进的投研能 力、稳健优异的业绩表现等荣获"杰出银行理财子公司",旗下的启元策略(360天持有)1号获评"卓越创新 银行理财产品"。 作为在资管行业发展新格局大背景下成立的银行理财公司,平安理财以打造"国内品类最全的开放式理财 平台"为目标,持续提升专业投研、产品体系、渠道经营、运营服务、风险管理方面"五位一体"的能力,构 建多元化人才队伍和数据科技创新"双擎驱动"竞争优势,打造以"稳"为特色、聚焦绝对收益目标的产品 体系,致力于以更强的责任担当、更扎实的投研能力服务实体经济高质量发展,守护老百姓的钱袋子。 本届"介甫奖"评选中,平安理财旗下的启元策略(360天持有)1号固收类产品备受关注。"启元策略360天1 号A"是以绝对收益为目标的固收类理财产品,其以稳健资产打底、融入固收量化策略,基于机器学习和量 化模 ...

Macro - The global economic system is undergoing reconstruction due to changes in the trust foundation, leading to a gradual "de-dollarization" primarily driven by non-economic factors, particularly international relations [2] - The long-term bull market for gold is expected to be historical and significant, as the trend of declining trust among countries is unlikely to change [2] - In the short to medium term, attention should be paid to the potential decline in dollar credit and the risks of rising real interest rates and inflation expectations in the US [2][3] Strategy - The "transformation bull" market in China's stock market is becoming clearer, with a strategic outlook favoring 2025 [6] - Key drivers include the decline in risk-free rates and a systemic reduction in risk perception, which will help restore investor confidence [6] - Investment opportunities are emerging in sectors such as financials, emerging technologies, and cyclical consumption, with specific recommendations for stocks in these areas [7][8] Overseas Strategy - The Hang Seng Technology Index is expected to lead the market, driven by the AI industry cycle [11] - The fundamentals of Hong Kong's tech sector are improving, with strong growth in capital expenditure and cloud business revenues [12] - Despite uncertainties in the trade environment, domestic policy support is expected to drive fundamental recovery in the Hong Kong market [13] Fixed Income - The bond market is expected to experience a bull market due to supply-demand mismatches, with low interest rates driving demand for convertible bonds [34] - Strategies focusing on short-term interest rates are recommended, with an emphasis on maintaining duration without chasing long-term bonds [29] Real Estate - The real estate market is showing signs of recovery, with improving supply-demand dynamics in key cities and a narrowing of cumulative declines post-policy adjustments [41] - The industry is expected to benefit from a clearer policy direction and a supportive environment for first-time homebuyers [41] Construction Engineering - The construction sector is focusing on high-dividend central state-owned enterprises and technology transformation [48] - Significant growth is anticipated in sectors such as intelligent computing and low-altitude economy development [48][49] Utilities - The electricity market is expected to see a bottoming out of spot prices, with both valuation and performance improving [53] - The nuclear power sector is projected to grow significantly, with a forecast of 110 million kilowatts of installed capacity by 2030 [54] Transportation - The aviation industry is entering a low-growth supply era, with demand expected to drive ticket prices upward [57] - The highway sector is anticipated to maintain strong demand, with policies likely to enhance long-term investment value [60]

Group 1 - The international financial market experienced increased uncertainty following recent events, leading to a surge in gold prices, which rose by 2-3% to over $3,400 [1] - The A-share market showed resilience with the Shanghai Composite Index rising by 14 points on the first trading day after the holiday, despite a PMI reading of 49.5 in May, indicating economic contraction [1][3] - The real estate market's ongoing downturn is a significant factor, with sales from the top 100 real estate companies declining by 10.8% year-on-year from January to May, and a 17.3% drop in May alone [3] Group 2 - The market's upward movement is primarily driven by institutional investors, making it challenging for retail investors to benefit from the index rise [5] - The concentration of institutional control in the market means that retail investors have limited visibility into the underlying dynamics, akin to a card game where only the dealer sees all players' cards [5][7] - The emergence of quantitative models allows for better tracking of institutional trading behaviors, providing retail investors with insights into market movements [7][9] Group 3 - Special attention should be given to "strong recovery" and "strong sell-off" states, as they indicate potential turning points in trading dynamics [10] - The "instant inventory" data, which recently dropped to over 2,100 companies, serves as a warning signal; a drop below 2,000 would indicate a loss of institutional interest in over half of the stocks [13]

Core Viewpoint - The stock market is experiencing rapid fluctuations due to conflicting news, particularly regarding U.S. tariff policies and interest rate changes, creating uncertainty for investors [1] Group 1: Market Trends - The current stock market appears stagnant, but there is an underlying potential for growth, likened to a calm before a storm [1] - A significant trend is anticipated with the potential for the Federal Reserve to lower interest rates, which could lead to substantial changes in the financial market [1][4] Group 2: Capital Movement - The disparity in interest rates between China and the U.S. has led to a phenomenon of "carry trade," where Chinese manufacturers are holding onto their dollar earnings instead of converting them to RMB [2] - Once the U.S. lowers interest rates, it is expected that these funds will return to China, providing a significant boost to the stock market [4] Group 3: Institutional Behavior - Institutional investors are actively manipulating stock prices through tactics like "shakeout," which involves driving prices down to eliminate weak hands before accumulating shares [6][8] - The use of quantitative models is becoming more prevalent, allowing for better identification of institutional trading patterns, particularly in recognizing "institutional shakeouts" [6][8] Group 4: Market Sentiment - Despite current market declines, there is an increase in stocks being held in "lock-up zones," indicating institutional confidence and a positive outlook for future market performance [11]

Summary of Conference Call Records Industry or Company Involved - The discussion primarily revolves around the fixed income and equity markets, with a focus on investment strategies for 2025, including sectors like banking, AI, robotics, and new consumption. Core Points and Arguments 1. **Fixed Income + Strategy Performance**: The fixed income + strategy has shown better performance compared to pure bond funds in the first half of 2025, with overall returns exceeding the median of pure bond funds [2][1] 2. **Economic Conditions**: The current economic momentum is insufficient, leading to a preference for longer duration bonds and a buy-on-dip strategy. Equity markets are expected to experience wide fluctuations and structural trends [1][4] 3. **Sector Rotation**: 2025 has seen accelerated sector rotation, with significant rebounds in small-cap stocks and new consumption since April. Robotics and deep learning have led the growth trend earlier in the year [1][6] 4. **Banking Sector Stability**: The banking sector remains attractive due to improved asset quality from national debt management, with dividend yields still appealing compared to deposits. Insurance funds favor dividend stocks, supporting bank stock performance [1][7] 5. **Extreme Asset Allocation**: There is a noticeable trend towards extreme asset allocation in 2025, with a focus on dividend stocks like banks and growth assets in AI and robotics. New consumption sectors are also gaining traction [1][8] 6. **Quantitative Models**: Quantitative models are crucial for controlling drawdowns and optimizing investment strategies, allowing for effective management of equity and bond positions [4][5] 7. **Market Dynamics**: The bond market is less risky, and the pricing efficiency of bonds is faster than that of stocks, leading to a reduced stock-bond seesaw effect [12][11] 8. **Investor Behavior**: Changes in investor structure, such as the entry of insurance and social security funds, can elevate stock market valuations, indicating a potential bullish trend for 2025 [17][18] 9. **Future Predictions**: The outlook for the Chinese economy and financial markets remains stable, with no significant risks anticipated in the near term. The focus will be on maintaining high positions in bonds and rotating sectors in equities [29][28] Other Important but Possibly Overlooked Content 1. **Absolute Return Philosophy**: The absolute return philosophy emphasizes stable and continuous growth in net asset value, aiming for a Sharpe ratio of at least 1.5 to 2, with maximum drawdown being about twice the annual return [3][10] 2. **Challenges in Hedging**: Domestic public funds face challenges in using government bond futures for hedging due to regulatory constraints and market capacity issues [21][22] 3. **Sector Opportunities**: Current investment opportunities include the banking sector, small-cap stocks, AI applications, and new consumption trends like pet economy and trendy toys, with potential rebounds in these areas [23][24] 4. **Impact of US-China Tariff Discussions**: Positive developments in US-China tariff discussions could enhance the performance of stable cash flow stocks, particularly in the banking sector [25][26] 5. **Monetary Policy Effects**: The Chinese central bank's recent policies, including rate cuts, are expected to support the bond market, while the US Federal Reserve's actions will significantly influence market dynamics [27][28]

Group 1: Report Overview - The report is a weekly update on public - offering funds and ETF strategy indices, covering the week ending May 16, 2025 [1][11] Group 2: ETF Strategy Indices Introduction 2.1 General Introduction - The report presents several ETF strategy indices, aiming to convert quantitative models or subjective views into practical investment strategies and track their performance and holdings weekly [11] 2.2 Specific Indices 2.2.1 Huabao Research Large - Small Cap Rotation ETF Strategy Index - 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. It outputs weekly signals to determine positions and gain excess returns. As of May 16, 2025, the excess return since 2024 is 16.17%, the excess return in the past month is - 0.28%, and the excess return in the past week is - 0.93% [3][13] 2.2.2 Huabao Research SmartBeta Enhanced ETF Strategy Index - It uses price - volume indicators to time self - built Barra factors and maps timing signals to ETFs based on their exposure to 9 Barra factors. It selects mainstream broad - based index ETFs and some style and strategy ETFs. As of May 16, 2025, the excess return since 2024 is 16.94%, the excess return in the past month is - 0.30%, and the excess return in the past week is - 0.43% [3][17] 2.2.3 Huabao Research Quantitative Windmill ETF Strategy Index - 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. As of May 16, 2025, the excess return since 2024 is 1.55%, the excess return in the past month is 0.40%, and the excess return in the past week is - 0.02% [4][21] 2.2.4 Huabao Research Quantitative Balance Technique ETF Strategy Index - 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 judgment. It also predicts the market's large - and small - cap styles to adjust equity market positions. As of May 16, 2025, the excess return since 2024 is 0.20%, the excess return in the past month is - 2.03%, and the excess return in the past week is - 0.89% [4][25] 2.2.5 Huabao Research Hot - Spot Tracking ETF Strategy Index - 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. It constructs an ETF portfolio to capture market hot - spots and assist investors in making decisions. As of May 16, 2025, the excess return in the past month is - 1.57%, and the excess return in the past week is - 0.11% [5][29] 2.2.6 Huabao Research Bond ETF Duration Strategy Index - 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 to improve long - term returns and control drawdowns. As of May 16, 2025, the excess return in the past month is 0.15%, and the excess return in the past week is 0.05% [5][32] Group 3: Index Performance Comparison 3.1 Last Week's Performance | Index Name | Last Week's Index Return | Comparison Benchmark | Last Week's Benchmark Return | Excess Return | | --- | --- | --- | --- | --- | | Huabao Research Large - Small Cap Rotation ETF Strategy Index | - 0.13% | CSI 800 | 0.80% | - 0.93% | | Huabao Research Quantitative Windmill ETF Strategy Index | 0.78% | CSI 800 | 0.80% | - 0.02% | | Huabao Research Quantitative Balance Technique ETF Strategy Index | 0.22% | SSE 50 | 1.12% | - 0.89% | | Huabao Research SmartBeta Enhanced ETF Strategy Index | 0.38% | CSI 800 | 0.80% | - 0.43% | | Huabao Research Hot - Spot Tracking ETF Strategy Index | 0.56% | CSI All - Share | 0.67% | - 0.11% | | Huabao Research Bond ETF Duration Strategy Index | - 0.35% | ChinaBond Aggregate Index | - 0.40% | 0.05% | [12] 3.2 Other Periods' Performance - For each index, the report also provides performance data for the past month and since 2024, as well as the corresponding excess returns compared to the benchmarks [14][17][18][23][28][31][35] Group 4: Index Holdings - Each index has its specific holdings and corresponding weights as of May 16, 2025, which are detailed in the report [17][23][25][29][35][37]

Report Industry Investment Rating - No information provided in the report. Core Viewpoints - The report presents several ETF strategy indices constructed using ETFs, and tracks the performance and holdings of these indices on a weekly basis. These indices aim to obtain excess returns relative to the market through different strategies [11]. Summary by Relevant Catalogs 1. ETF Strategy Index Tracking - **Overall Performance**: The table shows the performance of various ETF strategy indices last week, including index returns, benchmark returns, and excess returns. For example, the Huabao Research Size Rotation ETF Strategy Index had a last - week index return of 0.61%, a benchmark (CSI 800) return of 0.29%, and an excess return of 0.32% [12]. 1.1. Huabao Research Size Rotation ETF Strategy Index - **Strategy**: Utilizes 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. It outputs weekly signals to determine holdings and obtain excess returns [13]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.87%, the recent one - month excess return was 1.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.61%, recent one - month return was - 2.35%, and since 2024 was 25.11%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [13][14]. - **Holdings**: As of April 30, 2025, it held 50% of CSI 500ETF (159922.SZ) and 50% of CSI 1000ETF (512100.SH) [16]. 1.2. Huabao Research SmartBeta Enhanced ETF Strategy Index - **Strategy**: 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 to achieve market - outperforming returns. It selects mainstream broad - based index ETFs and some style and strategy ETFs [15]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 16.49%, the recent one - month excess return was 1.48%, and the recent one - week excess return was - 1.51%. The index's recent one - week return was - 1.22%, recent one - month return was - 1.91%, and since 2024 was 24.73%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [16][17]. - **Holdings**: As of April 30, 2025, it held 100% of Dividend Low - Volatility ETF (512890.SH) [23]. 1.3. Huabao Research Quantitative Fire - Wheel ETF Strategy Index - **Strategy**: Adopts a multi - factor approach, including long - and medium - term fundamental analysis, short - term market trend tracking, and analysis of market participants' behaviors. It uses valuation and crowding signals to indicate industry risks and multi - dimensionally digs out potential sectors to obtain excess returns [20]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 0.53%, the recent one - month excess return was 0.93%, and the recent one - week excess return was - 0.03%. The index's recent one - week return was 0.26%, recent one - month return was - 2.45%, and since 2024 was 8.78%, compared to the CSI 800's 0.29%, - 3.38%, and 8.24% respectively [20][23]. - **Holdings**: As of April 30, 2025, it held 20.93% of Bank ETF (512800.SH), 20.88% of Agriculture ETF (159825.SZ), 19.59% of Military Industry ETF (512660.SH), etc. [24]. 1.4. Huabao Research Quantitative Balancing Act ETF Strategy Index - **Strategy**: Employs a multi - factor system covering economic fundamentals, liquidity, technical aspects, and investor behavior. It constructs a quantitative timing system to judge the equity market trend, builds a prediction model for market large - and small - cap styles to adjust equity market position distribution, and comprehensively obtains excess returns through timing and rotation [24]. - **Performance**: As of April 30, 2025, the excess return since 2024 was 2.46%, the recent one - month excess return was 2.04%, and the recent one - week excess return was 0.32%. The index's recent one - week return was 0.27%, recent one - month return was - 0.97%, and since 2024 was 12.35%, compared to the SSE 300's - 0.05%, - 3.01%, and 9.89% respectively [24][26]. - **Holdings**: As of April 30, 2025, it held 5.09% of CSI 1000ETF (512100.SH), 4.98% of 500ETF Enhanced (159610.SZ), 29.13% of 300 Enhanced ETF (561300.SH), etc. [28]. 1.5. Huabao Research Hot - Spot Tracking ETF Strategy Index - **Strategy**: Based on strategies such as market sentiment analysis, industry event tracking, investor sentiment and professional opinions, policy and regulatory changes, and historical deduction, it tracks and mines hot - spot index target products in a timely manner to construct an ETF portfolio that can capture market hot - spots, providing short - term market trend references for investors [28]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 2.06%, and the recent one - week excess return was 0.11%. The index's recent one - week return was 1.19%, compared to the CSI All - Share's 1.08% [28][31]. - **Holdings**: As of April 30, 2025, it held 4.15% of Real Estate ETF (515060.SH), 27.03% of Hong Kong Stock Consumption ETF (513230.SH), etc. [32]. 1.6. Huabao Research Bond ETF Duration Strategy Index - **Strategy**: Uses bond market liquidity and price - volume indicators to screen effective timing factors and predicts bond yields through machine - learning methods. When the expected yield is below a certain threshold, it reduces the long - duration position in the bond investment portfolio to improve long - term returns and drawdown control ability [32]. - **Performance**: As of April 30, 2025, the recent one - month excess return was 0.20%, and the recent one - week excess return was 0.02%. The index's recent one - week return was 0.19%, recent one - month return was 1.20%, since 2024 was 9.32%, and since inception was 14.47%, compared to the ChinaBond Aggregate Index's 0.17%, 1.00%, 4.97%, and 6.91% respectively [32][33]. - **Holdings**: As of April 30, 2025, it held 50.01% of 10 - Year Treasury Bond ETF (511260.SH), 25.00% of Policy Financial Bond ETF (511520.SH), etc. [36].