1. Report Industry Investment Rating - Not provided in the content 2. Core Viewpoints - Last week, the ChinaBond New Composite Index declined by 0.04% compared to before the Spring Festival; short - term pure - bond and medium - long - term pure - bond funds rose by 0.04% and remained flat respectively; the CSI AAA Sci - tech Innovation Bond Index and the SSE Benchmark Market - making Corporate Bond Index both rose by 0.05% [3] 3. Summary by Related Catalogs 3.1 Fund Flows - As of February 27, 2026, bond - type ETFs had a net outflow of 713 million yuan in the past week. Interest - rate, credit, and convertible - bond ETFs had net outflows of 520 million yuan, 1.466 billion yuan, and a net inflow of 1.273 billion yuan respectively. Among credit - type ETFs, short - term financing, corporate bonds, and urban investment bonds had net inflows of 1.837 billion yuan, 205 million yuan, and 94 million yuan respectively, while market - making credit bonds had a net outflow of 376 million yuan, and sci - tech innovation bonds had a net outflow of 3.225 billion yuan. Since 2025, interest - rate, credit, and convertible - bond ETFs have had cumulative net inflows of 56.529 billion yuan, 468.087 billion yuan, and 36.144 billion yuan respectively, with a total of 560.759 billion yuan [5] 3.2 Net Value Performance - Throughout the week, the net values of various types of bond ETF products generally rose. As of February 27, 2026, the 30 - year Treasury Bond ETF performed weakly, falling 0.67% for the week. The Treasury Bond ETF Dongcai and the National Development Bond ETF rose 0.04%. The Convertible Bond ETF and the SSE Convertible Bond ETF fell 0.23% and 0.48% respectively last week [6] 3.3 Performance of Credit Bond ETFs and Sci - tech Innovation Bond ETFs - As of February 27, 2026, the median unit net values of credit bond ETFs and sci - tech innovation bond ETFs were 1.0166 and 1.0043 respectively, rising 0.06% for the week. Among credit bond ETFs, Bosera Credit Bond ETF performed relatively well, rising 0.04% for the week. Among sci - tech innovation bond ETFs, Dacheng Sci - tech Innovation Bond ETF and Yongying Sci - tech Innovation Bond ETF performed relatively well. As of February 27, 2026, the median discount rate of credit bond ETFs was 19BP, and that of sci - tech innovation bond ETFs was 17BP [7] 3.4 Duration Tracking of Credit - type ETFs - As of February 27, 2026, the holding durations of short - term financing ETFs, corporate bond ETFs, and urban investment bond ETFs were 0.31 years, 1.92 years, and 2.01 years respectively. Among market - making credit bond ETFs, the median holding durations of products tracking the Shanghai Market - making Corporate Bond Index and the Shenzhen Market - making Corporate Bond Index were 3.49 years and 2.73 years respectively. Among sci - tech innovation bond ETFs, the median holding durations of products tracking the AAA Sci - tech Innovation Bond Index, the Shanghai AAA Sci - tech Innovation Bond Index, and the Shenzhen AAA Sci - tech Innovation Bond Index were 3.28 years, 3.20 years, and 3.09 years respectively [8]

Report Industry Investment Rating - Not provided in the content Core Viewpoints - After the Spring Festival, the overall sentiment in the A-share market has significantly warmed up, with the CSI 1000 and CSI 500 indexes rising by over 4% within the week. The technology and resource sectors have shown a dual-line market, driven by different logics. The policy tone during the Two Sessions is expected to be "structural optimization" rather than "strong stimulus" [5]. - The technology sector remains prosperous but shows continued differentiation. The computing infrastructure and commercial aerospace sectors have more solid fundamental support, while the AI application and large model concepts face short - term pressure. The allocation logic for resource products and public utilities is expected to strengthen next week [8]. Summary by Directory Market Observation - **Market Performance After the Spring Festival**: The overall sentiment in the A - share market has warmed up after the Spring Festival. The CSI 1000 and CSI 500 indexes have risen by over 4%. The computing power industry chain, power, commercial aerospace, and resource product cyclical sectors have been active, but the "AI swallowing applications" narrative has impacted sectors such as A - share software and Hang Seng Technology. The global HALO trading strategy has become the dominant direction for foreign capital, and the A - share market has resonated [5]. - **Driving Logic of the Dual - line Market of Technology and Resources**: The dual - line market of technology and resources is essentially two sides of the same market logic. The technology sector is driven by the industrial prosperity logic of "AI driving the expansion of computing power and power demand and accelerating domestic substitution", and the resource sector is driven by the cycle repair logic of "PPI recovery, anti - involution policy implementation, and global resource re - pricing" [5]. - **Policy Expectations During the Two Sessions**: The period from the Spring Festival to the Two Sessions is a time window with dense policy expectations and relatively high certainty of market rise. The current policy tone emphasizes "stabilizing expectations, preventing risks, and improving quality", and the policy combination is more inclined to "structural optimization" rather than "strong stimulus" [5]. - **Configuration Outlook**: The technology sector remains prosperous but shows continued differentiation. The computing infrastructure and commercial aerospace sectors have better risk - return ratios. The allocation logic for resource products and public utilities is expected to strengthen next week. The public utility sector has both substantial demand increments from AI computing power expansion and price mechanism reform expectations [8]. Market Review - **Market Performance**: Most major market indexes rose last week, with the CSI 1000 having the largest increase of 4.34%. The material and energy indexes performed relatively well, with weekly increases of 8.03% and 6.31% respectively, while the telecommunications service and financial indexes performed weakly, with decreases of 3.20% and 1.10% respectively. Among the 30 Shenwan primary industries, 24 industries rose, with steel, non - ferrous metals, and basic chemicals having relatively large increases of 12.27%, 9.77%, and 7.15% respectively, and media, commercial retail, and food and beverage having relatively large decreases of 5.10%, 1.64%, and 1.54% respectively [9][15][18]. - **Trading Heat**: The average daily trading volume of the Wind All - A index last week was 24402.93 billion yuan (the previous value was 21111.36 billion yuan), which is at a relatively high historical position (92.80% in the three - year historical quantile) [21]. - **Valuation Tracking**: As of February 27, 2026, the valuation (PE_TTM) of the Wind All - A index was 23.71, an increase of 0.24 from the previous week, and it is at the 99.90% quantile in the past 5 years. Among the 30 Shenwan primary industries, 23 industries' valuations (PE_TTM) have recovered [25]. Economic Calendar - **Domestic Economic Data**: The official manufacturing PMI for February will be released on March 4 [28]. - **Overseas Economic Data**: The US ISM manufacturing PMI for February, the US effective federal funds rate for February, the US ISM services PMI for February, and the initial jobless claims for the week ending February 28 will be released from March 2 to March 5 [28].

Investment Rating - The report maintains an "Overweight" rating for the real estate sector [1] Core Insights - The Shanghai government has relaxed housing purchase restrictions, which is expected to positively impact sales [8] - The real estate sector has shown signs of recovery, with both new and second-hand home sales experiencing a rebound compared to previous weeks [8] - The report emphasizes the importance of financially stable and well-performing leading real estate companies as key investment targets [8] Summary by Sections Weekly Market Review - The Shenwan Real Estate Index increased by 0.51%, while the CSI 300 Index rose by 1.08%, indicating underperformance of the real estate sector compared to the broader market [4][13] Industry Fundamentals - In the week of February 20-26, 2026, 7,098 new homes were sold across 38 key cities, reflecting a year-on-year decline of 72.9% but a month-on-month increase of 43.8% [23] - The total transaction area for new homes was 695,000 square meters, with a year-on-year decrease of 73.7% and a month-on-month increase of 39.9% [23] - For second-hand homes, 6,706 units were sold, showing a year-on-year decline of 68.3% but a month-on-month increase of 185.2% [37] Inventory Situation - The total inventory of commercial housing in 17 key cities was 186,786,000 square meters, with a slight month-on-month decrease of 0.1% and a depletion cycle of 174.1 weeks [50]

Investment Rating - The report does not explicitly state an investment rating for the insurance industry, but it emphasizes the importance of risk resolution for small and medium-sized insurance companies as a key regulatory task for 2026 [4][27]. Core Insights - The risk resolution of small and medium-sized insurance institutions is a significant regulatory focus during the "14th Five-Year Plan" period, with a particular emphasis on market-oriented solutions for existing risks [4][32]. - The report highlights that 19 life insurance companies are currently unable to disclose their solvency reports, with recognized liabilities totaling approximately 4.31 trillion yuan, accounting for about 11.4% of the industry [4][17]. - The report discusses the transition from a "single fund guarantee" model for the insurance guarantee fund to a more diversified market-oriented risk resolution approach [4][32]. Summary by Sections 1. Introduction - The report outlines the challenges faced by small and medium-sized insurance institutions in a persistently low interest rate environment, which has led to operational difficulties and increased risk exposure [10][14]. 2. Observations and Thoughts on Risk Resolution - The current risk resolution approach for small insurance companies involves customized strategies rather than reducing the number of licensed institutions, contrasting with the banking sector [4][35]. - The report compares the current situation to Japan's 1990s insurance crisis, noting that the resolution of risks has not yet broken the "guaranteed return" constraint [4][38]. - It emphasizes the need to find market participants willing and capable of taking over the business of troubled institutions as a priority for risk resolution [4][4]. 3. Key Processes in Risk Resolution for Life Insurance Institutions - The report details various models for risk resolution, including state-led initiatives and the involvement of large insurance funds [6][23]. - It highlights specific cases of life insurance companies undergoing restructuring and the methods employed, such as new entity establishment and asset transfer [6][23]. 4. Key Processes in Risk Resolution for Property Insurance Institutions - The report notes that property insurance companies have a relatively lighter burden due to their asset-liability characteristics, allowing for quicker risk resolution [4][4]. - It outlines diverse methods for property insurance companies, including bankruptcy restructuring and new entity establishment [6][23]. 5. Investment Recommendations - The report suggests that accelerating the risk resolution process for small problem insurance companies is essential for transitioning the market from "quantity expansion" to "quality improvement," fostering a healthier competitive environment [4][4].

Investment Rating - The report does not explicitly provide an investment rating for the insurance industry, but it emphasizes the importance of addressing risks in small and medium-sized insurance companies as a key regulatory task for 2026 [4][32]. Core Insights - The risk resolution of small and medium-sized insurance institutions is a significant regulatory focus during the "14th Five-Year Plan" period, with a particular emphasis on market-oriented solutions for existing risks [4][32]. - The report highlights that 19 life insurance companies are currently unable to disclose their solvency reports, with recognized liabilities totaling approximately 4.31 trillion yuan, accounting for about 11.4% of the industry [4][17]. - The report discusses the transition from a "single fund guarantee" model for the insurance guarantee fund to a more diversified market-oriented risk resolution approach [4][32]. Summary by Sections Introduction - The report outlines the challenges faced by small and medium-sized insurance institutions in a persistently low interest rate environment, which has led to operational difficulties and increased risk exposure [10][14]. Current Situation of Small and Medium-Sized Insurance Institutions - The report categorizes the 19 life insurance companies unable to disclose solvency reports into three stages: newly established companies, those undergoing risk resolution, and those with slow progress in risk resolution [22][24]. - It notes that the current risk resolution approach in the insurance sector is characterized by "one company, one policy," allowing new entities to take over business without reducing the total number of insurance licenses [33][35]. Comparison with Historical Events - The report draws parallels between the current situation in China's insurance industry and the insurance crisis in Japan during the 1990s, noting that the current environment has not yet broken the "guaranteed return" constraint [4][38]. Changes in Risk Resolution Models - The report indicates that the insurance guarantee fund's model will shift from a single fund to a multi-faceted market-oriented resolution strategy, highlighting the need for capable market participants to assist in risk resolution [4][32]. Investment Recommendations - The report suggests that accelerating the risk resolution process for small problem insurance companies is essential for promoting a healthier competitive ecosystem in the industry, transitioning from quantity expansion to quality improvement [4][32].

Investment Rating - The report maintains a "Buy" rating for several companies including WuXi Biologics, Tigermed, and others, indicating a positive outlook for the sector [3][12][17]. Core Insights - The report emphasizes the importance of focusing on Q1 performance expectations and actively seizing thematic opportunities, particularly in areas like brain-computer interfaces, surgical robots, and AI healthcare [6][15]. - The surgical robot market in China is projected to grow rapidly, with a potential market size exceeding 100 billion yuan by 2033, driven by policy support and increasing clinical demand [10][30]. - The report highlights a strategic focus on the raw material drug sector, which is expected to see a turnaround due to rising prices and the introduction of new business lines such as small nucleic acids and ADCs [7][15]. Summary by Sections Market Performance - In February 2026, the pharmaceutical sector experienced a slight decline of 0.2%, underperforming compared to the Shanghai Composite Index, which rose by 0.1% [6][11]. - The report notes that various sub-sectors within pharmaceuticals, such as traditional Chinese medicine and medical devices, showed positive performance, with increases of 1.49% and 0.93% respectively [6][15]. Surgical Robots - The surgical robot market is on track to reach a scale of 1020.19 billion yuan by 2033, with a compound annual growth rate (CAGR) of 34.3% from 2024 to 2033 [10][23]. - The report discusses the establishment of a unified pricing framework for surgical robots, which is expected to enhance procurement willingness among hospitals [30][31]. Thematic Opportunities - The report suggests focusing on thematic opportunities in brain-computer interfaces, surgical robots, and AI healthcare, particularly as catalysts are expected to materialize soon [6][15]. - Companies such as Innovent Biologics and others are highlighted as key players in the biotech and biopharma sectors, with potential for significant growth [9][16]. Raw Material Drugs - The raw material drug sector is identified as being at a turning point, with expectations of price improvements following several years of decline [7][15]. - Companies like Pro Pharma and others are recommended for their strong business fundamentals and potential for growth in this sector [7][15].

Group 1: Event Overview - On February 28, 2026, the U.S. and Israel launched a military strike against Iran, which was followed by Iran's retaliation. On March 1, reports indicated the death of Iran's Supreme Leader Khamenei[3] - The military action aims to push for a regime change in Iran, indicating high conditions for conflict resolution and a risk of escalation in retaliatory actions[4] Group 2: Market Implications - If the conflict is perceived to end quickly, there may be a temporary rise in non-ferrous metals and energy sectors, followed by a potential pullback[2] - A sustained Iranian retaliation could lead to a re-evaluation of Middle Eastern risk premiums, creating new opportunities in precious metals, non-ferrous, and energy sectors[2] Group 3: Political and Strategic Dynamics - The death of Khamenei complicates Iran's political landscape but does not guarantee a quick de-escalation of the conflict; the regime's resilience is expected to maintain control in the short term[4] - The ongoing conflict may increase political pressure on the U.S. government, especially if casualties rise, impacting future strategic decisions[4] Group 4: Investment Recommendations - Investors are advised to monitor the intensity and duration of Iranian retaliation, as well as diplomatic interactions between Iran and the U.S.[2] - Focus on sectors such as commercial aerospace, semiconductor equipment, and AI applications, which may benefit from increased demand for high-end computing and information systems due to geopolitical tensions[5]

Investment Rating - The industry investment rating is "Increase" with an expectation of a relative increase of over 10% compared to the benchmark index in the next 6 to 12 months [17]. Core Insights - The market is currently in an upward trend, with the core observation variable being the change in profit effect, which is at 1.91%, indicating a potential for continued market growth [5][8]. - The upcoming Two Sessions (Lianghui) period is expected to drive short-term policy focus, historically associated with stable market performance [5][8]. - The market has shown resilience despite geopolitical tensions in the Middle East, which may suppress risk appetite [5][8]. Summary by Sections Market Overview - The overall market (WIND All A Index) has shown an increase of 2.75% and reached a new high, with small-cap stocks (CSI 1000) rising by 4.34% and mid-cap stocks (CSI 500) by 4.32% [2][7]. - The steel sector has performed particularly well, with an increase of 11.8%, while the media sector has declined by 4.44% [2][7]. Timing System Analysis - The distance between the 20-day and 120-day moving averages is 6.28%, indicating a positive market trend, with the short-term average above the long-term average [2][5]. - The market trend line is positioned around 6812 points, suggesting a favorable environment for continued investment [5][8]. Sector Allocation - The industry trend configuration model suggests waiting for a reversal signal in the real estate chain (Construction Materials ETF code 159745.SZ) during the Two Sessions window, which may present short-term opportunities [6][15]. - The TWO BETA model continues to recommend the technology sector, particularly focusing on commercial aerospace (Satellite ETF code 563230.SH) for rebound opportunities [6][15]. - The performance trend model highlights the importance of focusing on the computing-related industry chain (Semiconductor Equipment ETF code 159516.SZ, Communication ETF code 515880.SH) as well as non-ferrous metals (Industrial Non-ferrous ETF code 560860.SH, Rare Earth ETF code 516150.SH) and chemicals (Chemical ETF code 159870.SZ) [6][15]. Valuation Metrics - The PE ratio of the WIND All A Index is near the 90th percentile, indicating a high valuation level, while the PB ratio is at the 50th percentile, suggesting a moderate valuation level [9][11]. - Based on the short-term trend assessment, an 80% allocation in absolute return products based on the WIND All A Index is recommended [9].

- The report introduces a comprehensive impact coefficient model to measure the influence of index rebalancing on individual stocks, particularly focusing on the March 2026 adjustments for key indices such as STAR 50, STAR-ChiNext 50, STAR 100, Dividend Low Volatility 100, and Beijing Stock Exchange 50[9][11][14] - The comprehensive impact coefficient is defined as follows: $ effect\_total_{s}=\sum_{i=1}^{n}\frac{wt\_chg_{s_{i}}\times fund\_size_{i}}{amount\_avg_{s_{i}}20} $ where: - $ wt\_chg_{s_{i}} $ represents the weight change of stock $ s $ in index $ i $ - $ fund\_size_{i} $ is the tracking scale of index $ i $ - $ amount\_avg_{s_{i}}20 $ is the average trading volume of stock $ s $ over the past 20 days[11] - The model evaluates the impact of passive trading caused by index rebalancing, emphasizing that larger indices with higher tracking scales (e.g., STAR 50 with 1489 billion RMB) generate more significant passive trading effects, creating potential investment opportunities for stocks added to these indices[13][14] - The report provides detailed calculations of the comprehensive impact coefficients for stocks with significant adjustments, identifying stocks like Jikang Technology (impact coefficient: 5.95), Zhongke Feice (impact coefficient: 1.73), and Taoli Bread (impact coefficient: 1.55) as having notable positive impacts due to their inclusion in indices such as Beijing Stock Exchange 50 and STAR 50[14][17] - Stocks removed from indices also exhibit negative impact coefficients, such as Weida Optoelectronics (-2.95), Jike Shares (-2.65), and Junshi Biosciences (-1.73), reflecting the adverse effects of exclusion from key indices[17]

Quantitative Models and Construction Methods 1. Model Name: Timing System Signal - **Model Construction Idea**: The model uses the distance between the short-term and long-term moving averages of the WIND All A Index to determine market trends and timing signals [2][7][13] - **Model Construction Process**: 1. Define the short-term moving average (20-day) and long-term moving average (120-day) of the WIND All A Index 2. Calculate the distance between the two moving averages: $ Distance = \frac{Short\text{-}term\ MA - Long\text{-}term\ MA}{Long\text{-}term\ MA} $ 3. If the absolute value of the distance is greater than 3%, it indicates a significant trend signal [2][7][13] - **Model Evaluation**: The model effectively identifies market trends and provides actionable timing signals [2][7][13] 2. Model Name: Industry Trend Allocation Model - **Model Construction Idea**: This model identifies industry allocation opportunities based on medium-term reversal expectations and performance trends [6][8][15] - **Model Construction Process**: 1. Monitor medium-term reversal signals for specific industries, such as the real estate chain 2. Use performance trend analysis to identify industries with strong growth potential, such as technology, semiconductors, and chemicals 3. Recommend ETF products corresponding to these industries for allocation [6][8][15] - **Model Evaluation**: The model provides clear industry allocation guidance and captures sectoral opportunities effectively [6][8][15] 3. Model Name: Position Management Model - **Model Construction Idea**: This model determines the recommended equity allocation ratio based on valuation levels and market trends [9] - **Model Construction Process**: 1. Assess the PE and PB valuation levels of the WIND All A Index 2. Combine valuation levels with short-term market trends to determine the recommended equity allocation ratio 3. For example, with the current PE at the 90th percentile and PB at the 50th percentile, the model suggests an 80% equity allocation [9] - **Model Evaluation**: The model provides a systematic approach to position management, balancing valuation and trend considerations [9] --- Model Backtesting Results 1. Timing System Signal - Moving average distance: 6.28% (absolute value > 3%) - Market trend line: 6812 points - Profitability effect: 1.91% (significantly > 0) [2][7][13] 2. Industry Trend Allocation Model - Recommended sectors: - Real estate chain (e.g., Building Materials ETF: 159745.SZ) - Technology (e.g., Satellite ETF: 563230.SH) - Semiconductors and communication (e.g., Semiconductor Equipment ETF: 159516.SZ, Communication ETF: 515880.SH) - Metals and chemicals (e.g., Industrial Metals ETF: 560860.SH, Rare Earth ETF: 516150.SH, Chemical ETF: 159870.SZ) [6][8][15] 3. Position Management Model - Recommended equity allocation: 80% [9] --- Quantitative Factors and Construction Methods 1. Factor Name: Profitability Effect - **Factor Construction Idea**: Measures the market's profitability to assess upward momentum [2][7][13] - **Factor Construction Process**: 1. Calculate the profitability effect as a percentage of profitable stocks in the market 2. A positive profitability effect indicates upward momentum [2][7][13] - **Factor Evaluation**: The factor effectively captures market sentiment and momentum [2][7][13] --- Factor Backtesting Results 1. Profitability Effect - Current value: 1.91% (significantly > 0) [2][7][13]