Company Overview - The report rates the company as "Buy" for the first time, indicating a positive outlook for investment [5] - The company, Blok, is a leading player in the building block toy sector, with significant growth potential [1] - Founded in 2014, Blok focuses on building block toys, with Ultraman as its core licensed IP, and is expanding its IP product matrix [1][14] Industry Insights - The "Guzi Economy," which encompasses the secondary economy around anime, games, and comics, is experiencing robust growth, providing ample market opportunities [2] - The building block toy market has seen a compound annual growth rate (CAGR) of 20.5%, growing from 13.2 billion RMB in 2019 to 27.8 billion RMB in 2023 [2] Core Competitiveness - Blok's competitive edge lies in its rich IP matrix, significant supply chain scale effects, and excellent channel marketing strategies [3] - The company has a diverse product matrix that caters to a wide age range, with rapid iteration speed and a standardized supply chain [3][17] - Blok's marketing strategy is driven by content, enhancing brand influence through a robust online and offline sales network [3][16] Financial Projections and Investment Recommendations - The company is expected to achieve a net profit of 1.188 billion RMB, 1.913 billion RMB, and 2.663 billion RMB from 2025 to 2027, representing year-on-year growth rates of 396.2%, 61.0%, and 39.3% respectively [4] - Revenue is projected to grow significantly, with estimates of 2.241 billion RMB in 2024 and 4.414 billion RMB in 2025, reflecting a year-on-year growth of 155.6% and 97.0% [4][28]

Investment Rating - The report maintains a "Buy" rating for the company, with a target market capitalization of 430 billion yuan, corresponding to a PE of 15 times for 2026, indicating an upside potential of over 20% from the current price [4][6]. Core Insights - The company is a leading player in the mass apparel market, particularly in men's clothing, with a robust main business and promising growth in new retail management initiatives such as JD Outlet and FCC [1][14]. - The main brand, HLA, is positioned in the mass market, focusing on quality and cost-effectiveness, with a projected revenue growth of 3% to 165.3 billion yuan from 2025 to 2027 [1][3]. - The company has successfully expanded its retail capabilities through innovative business models, particularly in the JD Outlet segment, which is expected to see rapid growth [2][15]. Summary by Sections Company Fundamentals - The company has transitioned from being primarily a men's clothing brand to a broader retail platform, with significant growth in new business areas [14][15]. - The main brand, HLA, has maintained a strong market position, with revenue expected to reach 153 billion yuan in 2024, despite a challenging consumer environment [20][23]. Men's Clothing Business - The men's clothing sector has seen a stabilization in demand, with the company increasing its market share due to improved competitive dynamics [22][23]. - HLA's product offerings emphasize high cost-performance ratios, appealing to a rational consumer base [24][27]. New Business Initiatives - The JD Outlet business is projected to expand significantly, with net profits expected to grow from 1.67 billion yuan in 2025 to 7.77 billion yuan in 2027 [2][3]. - The FCC business, which includes exclusive Adidas products, is also anticipated to contribute positively to the company's profitability, with net profits expected to reach 1.35 billion yuan by 2027 [3][15]. Financial Projections - The company is expected to achieve revenues of 222.7 billion yuan in 2025, growing to 264.6 billion yuan by 2027, with a compound annual growth rate of approximately 8.1% [3][4]. - The projected net profit for the parent company is expected to increase from 25.4 billion yuan in 2025 to 32.5 billion yuan in 2027, reflecting a strong growth trajectory [3][4]. Dividend Policy - The company has maintained a high dividend payout ratio of over 85% from 2021 to 2024, making it an attractive option for income-focused investors [3][14].

证券研究报告 | 宏观研究 gszqdatemark 2025 06 19 年 月 日 宏观点评 增量信息有限——美联储 6 月议息会议点评 事件：北京时间 6 月 19 日凌晨 2 点，美联储公布 6 月议息会议决议。 核心结论：美联储如期维持利率不变，下调经济预测、上调通胀预测，点 阵图显示年内降息次数维持 2 次不变，明年降息从 2 次减少至 1 次。会议 过后，市场降息预期变化不大，仍维持全年降 2 次、首次在 9 月。继续提 示：未来两个月将是重要的窗口期，关注贸易谈判结果、特朗普财政法案 落地情况、伊朗-以色列局势演化。美联储下次会议是 7/31，届时这些事 件均有望尘埃落定，因此下次会议可能释放更多政策信号。 1、美联储如期按兵不动，下调经济预测，点阵图显示降息空间减少。 >会议决议：美联储维持联邦基金利率 4.25-4.5%不变，符合市场预期。 会议声明有两处明显变化：（1）对经济前景不确定性的表述从"进一步加 剧"改为"有所下降，但依然很高"；（2）删掉了"委员会判断失业率和通 胀上升的风险已经增加"。 >点阵图：本次更新的利率点阵图与 3 月相比，美联储官员对年内降息的 预期维持 2 次不 ...

Group 1: Retail Sector Insights - In May, the retail sales year-on-year growth was 6.4%, slightly exceeding expectations, indicating a stable recovery in the retail sector since 2025, with some sub-sectors showing marginal improvement [3][5] - New consumption trends are thriving, with key companies such as Gu Ming, Cha Bai Dao, and others being highlighted as potential investment opportunities [3] - The retail adjustment continues, with companies like Yonghui Supermarket and Chongqing Department Store identified as key players in this ongoing transformation [3] Group 2: Electronics Sector Insights - BOE Technology Group announced plans to acquire a 30% stake in Rainbow Optoelectronics for a base price of 4.849 billion yuan, which is expected to enhance BOE's display business significantly [5] - The acquisition is projected to strengthen BOE's technical capabilities and market share, potentially increasing its market share to over 30% in the display panel sector [5] - Revenue forecasts for BOE are optimistic, with expected revenues of 215.996 billion yuan, 239.566 billion yuan, and 264.058 billion yuan for 2025, 2026, and 2027 respectively [5] Group 3: Social Services Sector Insights - Meituan is recognized as a leading local life service provider in China, with strong scale and operational efficiency, showing resilience and growth potential amid macroeconomic recovery [8] - Profit forecasts for Meituan indicate a net profit of 41.83 billion yuan, 53.46 billion yuan, and 63.86 billion yuan for 2025, 2026, and 2027 respectively, with adjusted net profits expected to be 49.98 billion yuan, 61.61 billion yuan, and 72.01 billion yuan [8]

Investment Rating - The report maintains a "Buy" rating for Meituan-W (03690.HK) [4][6]. Core Views - The company is actively investing to strengthen its ecosystem and is optimistic about its long-term competitive advantages [1]. - The core local business has shown healthy growth with a significant investment of 100 billion RMB to support merchants, leading to a 17.8% year-on-year increase in revenue for Q1 2025 [2]. - New business segments are improving losses and expanding overseas, with a 19.2% increase in revenue for Q1 2025 [3]. Summary by Sections Financial Performance - In Q1 2025, Meituan achieved revenue of 865.6 billion RMB, a year-on-year increase of 15.92%, and a net profit of 100.57 billion RMB, up 87.33% year-on-year [1]. - The core local business generated revenue of 643 billion RMB, with an operating profit of 135 billion RMB, reflecting a 39.1% increase year-on-year [2]. - The new business segment reported revenue of 222 billion RMB, with operating losses narrowing to 23 billion RMB, a 17.5% year-on-year improvement [3]. Business Segments - The food delivery segment is experiencing healthy growth through refined operations, with a focus on high-quality products and services [2]. - The flash purchase segment continues to grow strongly, with an increase in the number of flash warehouses and order proportions [2]. - The company launched a "Meituan Membership" program to enhance cross-selling and transaction frequency in lower-tier markets [2]. Financial Metrics and Projections - The report projects net profits of 418.3 billion RMB, 534.6 billion RMB, and 638.6 billion RMB for 2025, 2026, and 2027 respectively [4]. - Adjusted net profits are expected to be 499.8 billion RMB, 616.1 billion RMB, and 720.1 billion RMB for the same years, with corresponding valuations of 15.9, 12.9, and 11.0 times [4]. - The company’s gross margin improved to 37.45% in Q1 2025, with a decrease in sales and management expense ratios [3].

Investment Rating - The report maintains a "Buy" rating for the company [6] Core Views - The acquisition of a 30% stake in Rainbow Optoelectronics is expected to enhance BOE's display business by improving product technology, increasing scale in large-size panels, and expanding market share [3][4] - The competitive landscape in the panel industry is anticipated to rebalance, with top manufacturers gaining more market power, potentially increasing their market share to over 70% [4] Summary by Sections Acquisition Details - BOE plans to acquire a 30% stake in Rainbow Optoelectronics for a base price of 4.849 billion yuan, which will reduce Rainbow's stake to 69.79% while still maintaining control [1] Company Operations - Rainbow Optoelectronics operates a G8.6 LCD panel production line with a monthly capacity of 120K glass substrates, focusing on high-resolution and large-size panels [2] - The company is set to enhance its production capacity for large-size panels from 30K/month to 60K/month by March 2025, aiming for full production by 2026 [2] Market Position and Strategy - The acquisition is expected to strengthen BOE's VA technology capabilities and enhance its competitive position in the 50-inch and larger panel segments [3] - The market share of BOE is projected to exceed 30%, solidifying its leadership in the 32-inch to 50-inch and large-size panel markets [3] Financial Projections - Revenue forecasts for 2025, 2026, and 2027 are 215.996 billion yuan, 239.566 billion yuan, and 264.058 billion yuan, respectively, with corresponding net profits of 9.415 billion yuan, 13.410 billion yuan, and 15.513 billion yuan [4][5] - The company's price-to-book (PB) ratio is estimated to be around 1.0 for 2025, indicating a favorable valuation [4]

Investment Rating - The report maintains an "Accumulate" rating for the retail sector [5] Core Insights - In May 2025, the total retail sales of consumer goods reached 41,326 billion yuan, with a year-on-year growth of 6.4%, slightly exceeding expectations [1][9] - The retail sales excluding automobiles amounted to 37,316 billion yuan, with a year-on-year increase of 7.0% [1][9] - The overall retail sales from January to May 2025 totaled 203,171 billion yuan, reflecting a year-on-year growth of 5.0% [1][9] Summary by Sections Retail Sales Performance - In May 2025, the retail sales of essential goods showed positive growth across all categories, with food and oil products experiencing significant changes [2][14] - Essential goods such as grain and oil, food, beverages, and daily necessities saw year-on-year increases of 14.6%, 0.1%, 11.2%, and 8.0% respectively [2][14] - The retail sales of discretionary items, except for petroleum products, also showed growth, with home appliances and communication equipment experiencing accelerated growth [2][14] Regional and Channel Analysis - Urban retail sales in May reached 36,057 billion yuan, growing by 6.5% year-on-year, while rural retail sales were 5,269 billion yuan, growing by 5.4% [3][28] - Online retail sales of physical goods from January to May 2025 reached 49,878 billion yuan, accounting for 24.5% of total retail sales, with food, clothing, and daily necessities showing year-on-year growth of 14.5%, 1.2%, and 6.1% respectively [3][30] Investment Recommendations - The report highlights a stable recovery in the retail sector since 2025, with certain sub-sectors showing marginal improvements and policy support expected to drive future growth [4][34] - Key investment targets include companies in new consumption, retail transformation, cross-border e-commerce, and tourism sectors [4][34]

Quantitative Models and Construction 1. Model Name: Portfolio Optimization with 10-Year Treasury Bonds - **Model Construction Idea**: Incorporating 10-year Treasury bonds into a portfolio to optimize the risk-return profile by leveraging their low correlation with other asset classes and high Sharpe ratio[10][13][14] - **Model Construction Process**: 1. Calculate the correlation matrix between 10-year Treasury bonds and other asset classes such as A-shares, U.S. equities, and gold[13] 2. Evaluate historical performance metrics, including annualized return, volatility, maximum drawdown, Sharpe ratio, and Calmar ratio for each asset[14] 3. Add 10-year Treasury bonds to a portfolio consisting of equities and short-term bonds (e.g., CSI 300, ChiNext, 1-3 year Treasury bonds) 4. Optimize the portfolio's efficient frontier by maximizing the Sharpe ratio[15] - **Model Evaluation**: The inclusion of 10-year Treasury bonds significantly improves the portfolio's efficient frontier, enhancing the risk-return tradeoff[10][15] --- Quantitative Factors and Construction 1. Factor Name: Macro Cycle-Based Bond Performance Factor - **Factor Construction Idea**: Assessing the performance of 10-year Treasury bonds under different macroeconomic cycles to identify favorable investment periods[16][18] - **Factor Construction Process**: 1. Divide the macroeconomic environment into six stages based on monetary, credit, and growth factors[16] 2. Calculate the annualized return of 10-year Treasury bonds in each macroeconomic stage[18] 3. Use a macroeconomic scoring card to evaluate the bond's performance probability in the current stage[18] - **Factor Evaluation**: The factor indicates that 10-year Treasury bonds perform best during the late stages of economic downturns, with a recent macroeconomic probability score of 40%[16][18] --- Backtesting Results of Models and Factors 1. Portfolio Optimization with 10-Year Treasury Bonds - **Annualized Return**: 4.51%[14] - **Annualized Volatility**: 2.31%[14] - **Maximum Drawdown**: 6.86%[14] - **Sharpe Ratio**: 1.95[14] - **Calmar Ratio**: 0.66[14] 2. Macro Cycle-Based Bond Performance Factor - **Recent Macro Probability Score**: 40%[18]

Core Insights - The current ten-year government bonds have high investment value, optimizing risk-return performance in portfolios and showing low correlation with other assets like stocks and gold [2][3] - The macroeconomic environment is favorable for ten-year bonds, with a loose monetary policy and weak credit demand, leading to better performance compared to other assets during this phase [2][3] Ten-Year Government Bond Historical Analysis - The long-term trend indicates a downward shift in interest rates, primarily driven by declining real returns, with expectations of lower financing costs due to weakening prices [3] - Financial institutions are experiencing a downward trend in earnings, with deposit and investment product yields decreasing further from the beginning of the year [3] - Supply-demand dynamics and central bank liquidity support are expected to drive interest rates lower, with a potential asset shortage emerging as bond supply slows [3] Ten-Year Government Bond Advantages - Interest rates are anticipated to reach new lows, with expectations of the ten-year bond yield dropping to 1.4%-1.5% within the year [4] - The ten-year bond serves as a crucial benchmark rate, balancing long and short-term funding needs and is a key reference for pricing other financial products [4] - The 国泰上证 10-year government bond ETF is the only ETF tracking the ten-year bond index, utilizing an optimized sampling method to enhance liquidity and reduce trading costs [4][5] ETF Characteristics - The 国债 ETF operates on a T+0 trading mechanism, allowing for same-day buying and selling, which facilitates multiple trading opportunities within a single day [5] - The ETF maintains transparency in holdings, with daily disclosures, making it suitable for conservative long-term investors [5] - The ETF has low fees, high liquidity, and a strong historical performance, managed by experienced fund managers [5] Industry Performance Overview - The steel industry saw a 6.9% year-on-year decline in crude steel production in May, indicating a need for further observation regarding production strength [14] - The coal industry experienced a continued decline in imports, with a slight increase in thermal power generation, suggesting a potential rebound in demand [15]

Quantitative Models and Construction Methods 1. Model Name: CCBA Pricing Model - **Model Construction Idea**: The CCBA pricing model is used to calculate the pricing deviation of convertible bonds, defined as the difference between the market price and the model price, adjusted for redemption probability[6][24] - **Model Construction Process**: - The pricing deviation is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCBA\ Model\ Price} - 1 $ - Here, the "Convertible Bond Price" represents the market price of the bond, and the "CCBA Model Price" is derived from the CCBA pricing model[6][24] - The model incorporates historical volatility as a central parameter to determine the deviation level[7] - **Model Evaluation**: The model effectively identifies valuation ranges for convertible bonds, providing insights into their relative attractiveness[6] 2. Model Name: CCB_out Pricing Model - **Model Construction Idea**: This model builds upon the CCBA model by incorporating delisting risk to refine the pricing deviation calculation[24] - **Model Construction Process**: - The pricing deviation is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCB\_out\ Model\ Price} - 1 $ - The "CCB_out Model Price" adjusts the CCBA model price by accounting for delisting probabilities[24] - Convertible bonds are categorized into three domains: debt-biased, balanced, and equity-biased, with the lowest deviation bonds selected for each domain[24] - **Model Evaluation**: The model demonstrates strong stability and adaptability, achieving consistent returns even in volatile market conditions[24] 3. Model Name: Return Decomposition Model - **Model Construction Idea**: This model decomposes the returns of convertible bonds into three components: bond floor returns, equity-driven returns, and valuation-driven returns[17] - **Model Construction Process**: - The model uses historical data to separate the total return of convertible bonds into: - Bond floor returns, representing the fixed-income component - Equity-driven returns, reflecting the impact of the underlying stock's performance - Valuation-driven returns, capturing changes in the bond's relative pricing[17][21] - **Model Evaluation**: The model provides a detailed understanding of the drivers of convertible bond performance, aiding in strategy optimization[17] --- Quantitative Factors and Construction Methods 1. Factor Name: Pricing Deviation Factor (CCB_out) - **Factor Construction Idea**: Measures the relative valuation of convertible bonds by comparing market prices to model-derived prices[24] - **Factor Construction Process**: - The factor is calculated as: $ Pricing\ Deviation = \frac{Convertible\ Bond\ Price}{CCB\_out\ Model\ Price} - 1 $ - Bonds with the lowest deviation are selected for further analysis[24] - **Factor Evaluation**: The factor effectively identifies undervalued bonds, contributing to the success of valuation-based strategies[24] 2. Factor Name: Momentum Factor - **Factor Construction Idea**: Captures the price momentum of the underlying stock over different time horizons[29] - **Factor Construction Process**: - Momentum scores are calculated based on the stock's returns over the past 1, 3, and 6 months, with equal weighting applied to each period[29] - **Factor Evaluation**: The factor enhances the responsiveness of valuation-based strategies, improving their adaptability to market trends[29] 3. Factor Name: Turnover Factor - **Factor Construction Idea**: Measures the trading activity of convertible bonds to identify liquidity and investor interest[33] - **Factor Construction Process**: - The factor is derived from: - Bond turnover rates over 5-day and 21-day periods - The ratio of bond turnover to stock turnover over the same periods[33] - **Factor Evaluation**: The factor effectively identifies actively traded bonds, improving the liquidity profile of selected portfolios[33] --- Backtesting Results of Models 1. CCBA Pricing Model - **Annualized Return**: 8.6% - **Annualized Volatility**: 11.6% - **Maximum Drawdown**: 19.9% - **Information Ratio (IR)**: Not explicitly provided[6] 2. CCB_out Pricing Model - **Annualized Return**: 21.8% - **Annualized Volatility**: 13.6% - **Maximum Drawdown**: 15.6% - **Information Ratio (IR)**: 2.10[27] 3. Return Decomposition Model - **Annualized Return**: Not explicitly provided - **Annualized Volatility**: Not explicitly provided - **Maximum Drawdown**: Not explicitly provided - **Information Ratio (IR)**: Not explicitly provided[17] --- Backtesting Results of Factors 1. Pricing Deviation Factor (CCB_out) - **Annualized Return**: 21.8% - **Annualized Volatility**: 13.6% - **Maximum Drawdown**: 15.6% - **Information Ratio (IR)**: 2.10[27] 2. Momentum Factor - **Annualized Return**: 24.5% - **Annualized Volatility**: 14.3% - **Maximum Drawdown**: 11.9% - **Information Ratio (IR)**: 2.39[31] 3. Turnover Factor - **Annualized Return**: 23.4% - **Annualized Volatility**: 15.4% - **Maximum Drawdown**: 15.9% - **Information Ratio (IR)**: 2.15[35]