Group 1 - The report highlights that recent geopolitical conflicts and changes in AI narratives may temporarily affect risk appetite, but the market tends to revert to its inherent trends in the medium term [1][11] - The National People's Congress (NPC) has set a positive and stable policy tone, with ongoing capital market reforms expected to support the market, indicating that post-NPC market trends are often policy-related [1][3] - Despite short-term fluctuations, the overall bullish market pattern for the year remains intact, with a focus on AI applications, strategic resources under security considerations, and traditional assets related to domestic demand [1][3][26] Group 2 - The "HALO" trading paradigm has emerged as a significant investment logic among foreign capital, reflecting a shift towards heavy asset sectors that are less likely to be disrupted by AI, while light asset sectors are facing outflows [2][16] - Historical data suggests that foreign trading trends tend to have continuity, with upcoming earnings reports serving as a critical observation window for the sustainability of the "HALO" trading narrative [2][16] - The report indicates that if internet companies or leading overseas software firms report strong fundamentals, along with a potential easing of geopolitical tensions, the narrative around foreign "HALO" trading may reverse [2][16] Group 3 - The NPC's policy framework for 2026 emphasizes a balance between domestic demand and technological advancement, aiming for qualitative improvements and reasonable growth [3][19] - The report notes that the government aims for a growth target of 4.5-5% for 2026, reflecting a shift from quantity-focused to quality-focused growth strategies [19][20] - The capital market is expected to see enhanced stability and improved institutional frameworks, with a focus on deepening reforms and protecting investors [3][20] Group 4 - The report identifies three key investment themes from the NPC's policies: technology, security, and domestic demand, aligning with previous insights on investment opportunities in AI, resource sectors, and traditional assets [27][30] - The "smart economy," driven by AI, is highlighted as a primary investment focus, with an emphasis on the development of new infrastructure and energy systems [30][31] - The report suggests that traditional assets related to domestic demand, such as real estate and consumer goods, may see a reversal in expectations due to supportive policies and improving fundamentals [31][32]

Investment Rating - The investment rating for Wuliangye (000858.SZ) is "Outperform the Market" (maintained) [1] Core Viewpoints - The sales performance during the 2026 Spring Festival showed resilience, reflecting the effectiveness of multiple reforms from the "1218 Conference" held on December 18, 2025 [2] - The company is actively addressing market concerns by enhancing dealer and terminal incentive policies, lowering payment prices, and respecting market demand to consolidate product and channel foundations [3][4] - The company expects revenue for 2025-2027 to be 758.2 billion, 735.8 billion, and 772.9 billion yuan respectively, with year-on-year changes of -15.0%, -3.0%, and +5.1% [3][9] - The projected net profit attributable to the parent company for the same period is 256.7 billion, 243.5 billion, and 262.8 billion yuan, with year-on-year changes of -19.4%, -5.1%, and +8.0% [3][9] Summary by Relevant Sections Sales Performance - The sales performance of Wuliangye during the 2026 Spring Festival was better than the industry average, with expectations of a small single-digit growth in sales volume compared to last year's Spring Festival [4] - The company has adapted to market conditions by dynamically adjusting shipments based on sales performance, maintaining stable prices for its products [4][8] 2025 Work Summary - In 2025, the company actively responded to market adjustments, consolidating product and channel foundations, and further marketizing its marketing system [5] - The company achieved over 30% growth in banquet occasions and opening rates for its products, while also expanding its channel structure [5] 2026 Work Deployment - The company has positioned 2026 as a "Year of Marketing Innovation," focusing on enhancing marketing reforms and execution capabilities to achieve high-quality market sales and increase market share [6][7] - The company aims to maintain the leading position of its flagship product at the 1,000 yuan price point while expanding its presence in high-end banquet scenarios [6][7] Financial Forecast and Valuation - The current stock price corresponds to a 16.3x PE ratio for 2026, with a cash dividend of 20 billion yuan corresponding to a 5.0% dividend yield, highlighting its dividend asset attributes [3][9] - The company maintains a solid brand advantage and is expected to improve its market position through proactive measures and respect for market dynamics [8]

Investment Rating - The report maintains an "Outperform" rating for the banking wealth management industry, indicating expected performance exceeding the market benchmark by over 10% [39]. Core Insights - The wealth management scale is gradually recovering, with a slight month-on-month increase in February, reaching a total of 31.7 trillion yuan, indicating a positive growth trend [1][11]. - Regulatory measures have been implemented to address the "ranking" phenomenon in wealth management products, which previously distorted market order by artificially inflating short-term high-yield products. This shift is expected to lead to a more stable and sustainable operating environment in the long term [2][3]. - The downward trend in baseline yields for wealth management products is prompting a shift towards enhanced yield strategies, with recent interest in equity and gold strategies. For instance, a certain wealth management product achieved over 7% annual net value growth through diversified asset allocation [3][10]. Summary by Sections Wealth Management Scale - In February, the wealth management product stock scale slightly increased by 0.1 trillion yuan, with cash management and fixed-income products remaining the dominant categories [11][10]. New Product Issuance - The initial fundraising scale for newly issued products in February was 299.5 billion yuan, primarily consisting of fixed-income products. The average performance benchmark for new products showed a slight rebound to 2.35% [18][10]. Product Performance - Most products that matured in February met their performance benchmarks, with 1,434 closed-end wealth management products reaching expected returns [27][10].

Investment Rating - The report maintains an "Outperform" rating for the banking sector [4][5]. Core Insights - The banking sector is expected to transition from a policy bottom to an earnings bottom, with high-quality stocks leading the value reassessment [1]. - The economic environment in 2026 is anticipated to resemble the second half of 2016, with a strong expectation for a bottoming out of the banking sector's fundamentals, although no clear upward momentum is seen yet [2]. - The pricing power of bank stocks is expected to gradually shift from insurance capital and central Huijin to public and foreign funds in 2026 [3]. Summary by Sections Historical Context - The banking sector has experienced two significant market cycles: 2016-2017 driven by a fundamental upturn and 2023-2025 characterized by defensive strategies led by insurance and ETF investments [11][12]. Fundamental Outlook - The banking sector's fundamentals are expected to stabilize, with a projected annual earnings growth of 3.0% for 2026 [8][52]. - The net interest margin has been under pressure, with a decline from approximately 2.09% in early 2022 to 1.41% in the first three quarters of 2025 [54]. Funding Outlook - Insurance capital remains the most stable and sustainable core allocation in the banking sector, although marginal growth is slowing [3]. - Central Huijin's strategy has shifted from aggressively increasing ETF holdings to a more neutral approach, while public funds are expected to adopt a structural allocation strategy [3][58]. Investment Recommendations - The report suggests selecting stocks with recovery potential, emphasizing the importance of high-dividend, stable stocks while maintaining a focus on quality recovery stocks [3][4]. - Key recommendations include China Merchants Bank, Ningbo Bank, Changsha Bank, and Chongqing Rural Commercial Bank, with a focus on Jiangsu Bank, Chengdu Bank, and Industrial Bank as stable core holdings [3][4].

证券研究报告 | 2026年02月28日 2026年03月01日 2026年03月07日 农产品研究跟踪系列报告（196） 优于大市 肉牛价格淡季不淡，生猪产能节后有望持续去化 周度农产品跟踪：年内肉奶周期有望共振反转，反内卷支撑中长期生猪价格。 生猪：反内卷有望支撑猪价中长期表现。2 月 28 日生猪价格 10.79 元/公斤， 周环比-7.78%；7kg 仔猪价格约 356.19 元/头，周环比-0.27%。 白鸡：供给小幅增加，关注旺季消费修复。2 月 28 日鸡苗价格 2.72 元/羽， 周环比+10.57%，同比+3.30%；毛鸡价格 7.14 元/公斤，周环比-2.46%。 黄鸡：供给维持底部，有望率先受益内需改善。2 月 27 日浙江快大三黄鸡/ 青脚麻鸡/雪山草鸡斤价为5.1/4.6/6.3元，周环比+8.51%/+4.55%/+12.50%。 鸡蛋：在产父母代存栏处于高位，中期供给压力较大。2 月 28 日，鸡蛋主产 区价格 3.34 元/斤，周环比-4.57%，同比+18.86%。 肉牛：新一轮牛价上涨开启，看好牛周期反转上行。2 月 28 日，国内育肥公 牛出栏价为 25.20 元/kg ...

Group 1 - The report indicates a sustained "wide monetary + wide credit" environment, with China's new social financing in January reaching 72,208 billion yuan, exceeding expectations, and new RMB loans at 47,100 billion yuan, also above forecasts, suggesting a low risk of tightening funds [1][13] - The asset price outlook suggests a convergence of styles, with a focus on low valuation and high-performance stocks as external uncertainties rise, indicating a shift from high-risk trading to assets with higher safety margins [2][19] - The report highlights the performance of various asset classes in February, with the stock market showing differentiation, the bond market strengthening, and commodities experiencing volatility, while the RMB appreciated against the USD [30][41] Group 2 - The report provides quantitative asset allocation recommendations, suggesting an aggressive allocation of 10% in stocks, 45% in bonds, 15% in oil, and 30% in gold under an optimistic scenario, while a conservative scenario suggests 10% in stocks, 85% in bonds, 1.7% in oil, and 3.3% in gold [5][22] - The report notes that the stock-bond valuation ratio has decreased, indicating a reduced attractiveness of stocks relative to bonds, with the stock risk premium showing a historical low [44][47] - The report emphasizes the importance of monitoring macroeconomic indicators and market sentiment through various indices, which can help investors make informed decisions regarding asset allocation [53][55]

Investment Rating - The report maintains an "Outperform" rating for the banking wealth management industry, indicating expected performance above the market benchmark by over 10% [39]. Core Insights - The wealth management scale is gradually recovering, with a slight month-on-month increase in February, reaching a total scale of 31.7 trillion yuan [1][11]. - Regulatory measures have been implemented to address the "ranking" phenomenon in wealth management products, which has led to a downward adjustment in yield levels. This shift is expected to guide the industry towards long-term stable operations rather than short-term scale pursuits [2][3]. - The long-term trend indicates a decline in benchmark yields for wealth management products, prompting a shift towards strategies that enhance returns, particularly in equities and gold [3]. Summary by Sections Wealth Management Scale - In February, the wealth management product scale saw a slight increase, with a total of 31.7 trillion yuan, reflecting a recovery trend [1][11]. Regulatory Environment - Recent regulatory actions have targeted the "ranking" practices that mislead investors and create unhealthy competition. These measures include penalties for institutions and a push for industry self-regulation [2]. Product Performance - The average annualized yield for banking wealth management products in February was 1.70%, a decrease of 192 basis points from the previous month. Cash management products yielded 1.28%, while pure bond products yielded 2.30% [10]. - New product issuance in February reached 299.5 billion yuan, with a slight rebound in performance benchmarks to an average of 2.35% [18]. Asset Allocation Strategies - Wealth management products are increasingly adopting diversified strategies, with a focus on equities and gold to enhance returns in a low-interest, high-volatility environment. For instance, a specific product achieved over 7% annual net value growth while maintaining a maximum drawdown of under 1% [3].

Group 1: A-Share Market - The recent week saw an estimated net outflow of 9.2 billion yuan in northbound funds, compared to a net inflow of 2.1 billion yuan in the previous week [10] - Flexible foreign capital experienced a net outflow of 5 billion yuan, while the previous week had a net inflow of 10 billion yuan [10] - The top active stocks in the northbound trading included Ningde Times with a total transaction amount of 18.4 billion yuan, accounting for 18% of the stock's weekly trading volume [10] Group 2: Hong Kong Market - In the recent week, a total of 22.5 billion HKD flowed into the Hong Kong stock market, with stable foreign capital outflow of 11.9 billion HKD and flexible foreign capital outflow of 0.6 billion HKD [12] - The Hong Kong Stock Connect saw an inflow of 24.8 billion HKD, while local funds from Hong Kong or mainland China contributed 10.9 billion HKD [12] - Foreign capital was notably active in sectors such as non-bank financials, pharmaceuticals, and non-ferrous metals [12][14] Group 3: Asia-Pacific Market - In the Asia-Pacific region, there was a net inflow of 745.4 billion JPY into the Japanese stock market during the latest week, up from 523.4 billion JPY in the previous week, with a cumulative net inflow of 14.6 trillion JPY since the beginning of 2023 [18] - In February, overseas institutional investors saw a net inflow of 2.5 billion USD into the Indian stock market, reversing a net outflow of 3.98 billion USD in the previous month, with a cumulative net inflow of 10.8 billion USD since 2020 [18] Group 4: US and European Markets - In January, global mutual funds recorded a net inflow of 32.2 billion USD into the US equity market, compared to a net inflow of 29.8 billion USD in the previous month, with a cumulative net inflow of 753.5 billion USD since 2020 [19][21] - European equity markets saw net inflows of 3.67 billion USD, 3.59 billion USD, and 4.27 billion USD into the UK, Germany, and France respectively, with increases from the previous month's inflows [21]

Quantitative Models and Construction Methods 1. Model Name: Maximized Factor Exposure Portfolio (MFE) - **Model Construction Idea**: The MFE portfolio is designed to maximize the exposure of a single factor while controlling for various constraints such as industry exposure, style exposure, stock weight deviation, and turnover rate. This approach ensures that the factor's predictive power is tested under realistic portfolio constraints, making it more applicable to actual investment scenarios [39][40]. - **Model Construction Process**: - The optimization model is formulated as follows: $$ \begin{array}{ll} \text{max} & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T}w = 1 \end{array} $$ - **Objective Function**: Maximize the single-factor exposure, where \(f\) represents the factor values, \(f^T w\) is the weighted exposure of the portfolio to the factor, and \(w\) is the weight vector of stocks [40]. - **Constraints**: 1. **Style Exposure**: \(X\) is the factor exposure matrix for style factors, and \(s_l\) and \(s_h\) are the lower and upper bounds for style factor deviations [40]. 2. **Industry Exposure**: \(H\) is the industry exposure matrix, and \(h_l\) and \(h_h\) are the lower and upper bounds for industry deviations [40]. 3. **Stock Weight Deviation**: \(w_l\) and \(w_h\) are the lower and upper bounds for individual stock weight deviations relative to the benchmark [40]. 4. **Constituent Stock Weight**: \(B_b\) is a binary vector indicating whether a stock is a benchmark constituent, and \(b_l\) and \(b_h\) are the lower and upper bounds for constituent stock weights [40]. 5. **No Short Selling**: Ensures non-negative weights and limits individual stock weights to a maximum of \(l\) [40]. 6. **Full Investment**: Ensures the portfolio is fully invested, with the sum of weights equal to 1 [41]. - The MFE portfolio is constructed monthly, and historical returns are calculated after accounting for transaction costs (0.3% on both sides) [43]. - **Model Evaluation**: The MFE portfolio approach is effective in testing factor performance under realistic constraints, making it a robust method for evaluating factor predictability in practical investment scenarios [39][40]. --- Quantitative Factors and Construction Methods 1. Factor Name: EPTTM (Earnings-to-Price Trailing Twelve Months) - **Factor Construction Idea**: Measures the profitability of a company relative to its market valuation, using trailing twelve months (TTM) earnings [16]. - **Factor Construction Process**: - Formula: \( \text{EPTTM} = \frac{\text{Net Income (TTM)}}{\text{Market Capitalization}} \) [16]. - **Factor Evaluation**: Demonstrates strong performance across multiple sample spaces, particularly in the short term, indicating its effectiveness as a valuation factor [18][19][21]. 2. Factor Name: Pre-Expected EPTTM - **Factor Construction Idea**: Similar to EPTTM but uses consensus analyst forecasts for earnings instead of historical data [16]. - **Factor Construction Process**: - Formula: \( \text{Pre-Expected EPTTM} = \frac{\text{Consensus Forecasted Net Income (TTM)}}{\text{Market Capitalization}} \) [16]. - **Factor Evaluation**: Consistently ranks among the top-performing factors, highlighting its predictive power in various market conditions [18][19][21]. 3. Factor Name: BP (Book-to-Price Ratio) - **Factor Construction Idea**: Represents the ratio of a company's book value to its market value, often used as a valuation metric [16]. - **Factor Construction Process**: - Formula: \( \text{BP} = \frac{\text{Book Value}}{\text{Market Capitalization}} \) [16]. - **Factor Evaluation**: Exhibits strong performance in mid-cap and small-cap sample spaces, making it a reliable valuation factor [19][21][24]. 4. Factor Name: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: Measures the deviation of actual earnings from expected earnings, standardized by the standard deviation of forecast errors [16]. - **Factor Construction Process**: - Formula: \( \text{SUE} = \frac{\text{Actual Quarterly Net Income} - \text{Expected Quarterly Net Income}}{\text{Standard Deviation of Forecast Errors}} \) [16]. - **Factor Evaluation**: Effective in capturing earnings surprises, particularly in growth-oriented sample spaces [16]. --- Factor Backtesting Results 1. EPTTM - **Recent Week**: 1.46% (HS300), 1.66% (Public Fund Index) [18][26] - **Recent Month**: 0.97% (HS300), 2.47% (Public Fund Index) [18][26] - **Year-to-Date**: 1.55% (HS300), 0.62% (Public Fund Index) [18][26] 2. Pre-Expected EPTTM - **Recent Week**: 1.44% (HS300), 1.66% (Public Fund Index) [18][26] - **Recent Month**: 0.66% (HS300), 1.78% (Public Fund Index) [18][26] - **Year-to-Date**: 1.14% (HS300), -0.51% (Public Fund Index) [18][26] 3. BP - **Recent Week**: 0.55% (HS300), 0.85% (Public Fund Index) [18][26] - **Recent Month**: 0.09% (HS300), 1.90% (Public Fund Index) [18][26] - **Year-to-Date**: 0.42% (HS300), 1.79% (Public Fund Index) [18][26] 4. SUE - **Recent Week**: -0.07% (HS300) [18] - **Recent Month**: -0.24% (HS300) [18] - **Year-to-Date**: 0.06% (HS300) [18]

Quantitative Models and Construction Methods 1. Model Name: Hong Kong Stock Selection Portfolio - **Model Construction Idea**: The model is based on a dual-layer selection process combining fundamental and technical analysis to identify outperforming stocks with both fundamental support and technical resonance [14][15] - **Model Construction Process**: 1. **Analyst Recommendation Pool**: Constructed using three analyst recommendation events: upward earnings forecast revisions, initial analyst coverage, and research report titles with unexpected positive events [15] 2. **Dual-Layer Selection**: - **Fundamental Dimension**: Stocks with strong fundamental support are selected - **Technical Dimension**: Stocks with technical resonance are identified 3. **Backtesting**: The backtesting period is from January 1, 2010, to December 31, 2025, considering full investment and transaction costs [15] 4. **Annualized Return**: The portfolio achieved an annualized return of 19.08%, with an excess return of 18.06% relative to the Hang Seng Index [15] --- 2. Model Name: Stable New High Stock Screening - **Model Construction Idea**: The model leverages momentum and trend-following strategies, focusing on stocks that have recently reached new highs and exhibit stable price paths. This approach is supported by research indicating that stocks near their 52-week highs tend to outperform [20][22] - **Model Construction Process**: 1. **250-Day New High Distance Calculation**: - Formula: $ 250 \text{ Day New High Distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ - $\text{Close}_{t}$: Latest closing price - $\text{ts\_max(Close, 250)}$: Maximum closing price over the past 250 trading days - If the latest closing price reaches a new high, the distance is 0; otherwise, it is a positive value indicating the degree of fallback [22] 2. **Screening Criteria**: - Stocks must have reached a 250-day high in the past 20 trading days - Analyst attention: At least five "Buy" or "Overweight" ratings in the past six months - Relative strength: Top 20% in 250-day returns within the sample pool - Stability: Evaluated using price path smoothness and new high persistence metrics over the past 120 days [22][23] 3. **Final Selection**: Top 50 stocks based on trend continuation metrics over the past five days [23] --- Model Backtesting Results 1. Hong Kong Stock Selection Portfolio - **Absolute Return**: -8.24% (weekly), -0.92% (year-to-date) [17] - **Excess Return**: -4.96% (weekly), -1.41% (year-to-date) [17] - **Annualized Return**: 19.08% (full sample) [15] - **Excess Return**: 18.06% (full sample) [15] - **Information Ratio (IR)**: 1.19 (full sample) [19] - **Maximum Drawdown**: 23.73% (full sample) [19] 2. Stable New High Stock Screening - **Selected Stocks**: Examples include PetroChina (0857.HK), COSCO Shipping Energy (1138.HK), and WuXi AppTec (2359.HK) [22][28] - **Sector Distribution**: - Cyclical: 6 stocks - Manufacturing: 5 stocks - Technology: 4 stocks - Consumer: 3 stocks - Healthcare: 2 stocks [22][28] --- Factor Construction and Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the proximity of a stock's latest closing price to its 250-day high, capturing momentum and trend-following characteristics [22] - **Factor Construction Process**: - Formula: $ 250 \text{ Day New High Distance} = 1 - \frac{\text{Close}_{t}}{\text{ts\_max(Close, 250)}} $ - $\text{Close}_{t}$: Latest closing price - $\text{ts\_max(Close, 250)}$: Maximum closing price over the past 250 trading days - Interpretation: A lower value indicates stronger momentum, while a higher value suggests a fallback from the peak [22] --- Factor Backtesting Results 1. 250-Day New High Distance - **Selected Stocks**: Examples include PetroChina (0857.HK) with a 250-day new high distance of 0.3% and WuXi AppTec (2359.HK) with a distance of 12.2% [28] - **Sector Performance**: - Cyclical: 6 stocks - Manufacturing: 5 stocks - Technology: 4 stocks - Consumer: 3 stocks - Healthcare: 2 stocks [22][28]