Quantitative Models and Construction Methods Model Name: Index Component Adjustment Impact Model - **Model Construction Idea**: The model aims to measure the impact of index component adjustments on stock prices, considering the scale of passive products tracking the index and the average trading volume of the stocks[7][8][9]. - **Detailed Construction Process**: - The model calculates the impact of index adjustments using the following formula: $$ \mathrm{effect}_{s} = \frac{\sum_{i}^{m} wt_{in} * index_{-}scale_{i} - \sum_{i}^{n} wt_{out} * index_{-}scale_{i}}{avg_{-}amt_{s}} $$ where: - \( wt_{in} \) represents the buy weight of the stock in the index - \( wt_{out} \) represents the sell weight of the stock in the index - \( index_{-}scale_{i} \) represents the total scale of passive products tracking the index - \( avg_{-}amt_{s} \) represents the average daily trading volume of the stock over the past two weeks[7][8][9]. - **Model Evaluation**: The model effectively quantifies the potential trading impact on stocks due to index adjustments, providing valuable insights for identifying trading opportunities[7][8][9]. Model Backtesting Results - **Index Component Adjustment Impact Model**: - **Net Buy Scale**: - Shenghong Technology: 48.65 billion CNY[10] - Dongshan Precision: 47.91 billion CNY[10] - Guangqi Technology: 34.87 billion CNY[10] - **Impact Coefficient**: - Shenghong Technology: 0.57[10] - Dongshan Precision: 1.31[10] - Guangqi Technology: 3.37[10] Quantitative Factors and Construction Methods Factor Name: Impact Coefficient - **Factor Construction Idea**: The impact coefficient measures the potential impact on a stock's price due to changes in its index weight, considering the net adjustment scale and the stock's average trading volume[9][10][11]. - **Detailed Construction Process**: - The impact coefficient is calculated using the formula: $$ \text{Impact Coefficient} = \frac{\text{Net Adjustment Scale}}{\text{Average Daily Trading Volume}} $$ where: - Net Adjustment Scale is the net buy or sell scale of the stock due to index adjustments - Average Daily Trading Volume is the stock's average trading volume over the past two weeks[9][10][11]. - **Factor Evaluation**: The impact coefficient provides a clear measure of the potential price impact on stocks due to index adjustments, helping investors identify stocks that may experience significant price movements[9][10][11]. Factor Backtesting Results - **Impact Coefficient**: - **Stocks with Impact Coefficient > 2**: - Tower Group: 8.69[12] - Jiangzhong Pharmaceutical: 8.44[12] - Shanxi Drum Power: 6.99[12] - **Stocks with Impact Coefficient < -2**: - Deep Expressway: -15.65[14] - Wanhe Electric: -13.30[14] - Tianyoude Wine: -10.52[14]

Report Industry Investment Rating No information provided in the content. Core Viewpoints of the Report - Last week, the A-share market rebounded continuously. Vanke's debt extension once dragged down bond market sentiment. On Friday, it was reported that the six major banks stopped selling five-year large - denomination certificates of deposit and lowered the interest rates of three - year deposit products, which increased the expectation of domestic interest rate cuts and led to a slight rebound in the bond market. Overall, the bond market first declined and then rebounded, while ultra - long bonds continued to fall. The trading activity of ultra - long bonds remained stable and was very active. The term spread of ultra - long bonds remained flat, and the variety spread narrowed [1][11][37]. - The current bond market is more likely to fluctuate at a low level. The economic stabilization since last Q4 mainly comes from the central government's leverage increase. Considering the low probability of additional treasury bond issuance in Q4 this year, the growth rate of government bond financing is expected to continue to decline, and the domestic economy in Q4 remains under pressure. Also, the absolute level of interest rates is low, the market is desensitized to positive factors, and investor sentiment has recently weakened [2][3][12][13]. Summary by Relevant Catalog Weekly Review Ultra - long Bond Review - The A - share market rebounded continuously last week. Vanke's debt extension affected bond market sentiment. On Friday, news of interest rate adjustments increased the expectation of interest rate cuts, causing a slight rebound in the bond market. Overall, ultra - long bonds fell, trading activity was stable and active, the term spread remained flat, and the variety spread narrowed [1][11][37]. Ultra - long Bond Investment Outlook - **30 - year Treasury Bonds**: As of November 30, the spread between 30 - year and 10 - year treasury bonds was 34BP, at a historically low level. In October, the economic downward pressure increased, with GDP growth estimated at about 4.2% year - on - year, a 1.1% decline from September. CPI was 0.2%, and PPI was - 2.1%, indicating deflation risk. The bond market is likely to fluctuate at a low level, and the spread repair is expected to end [2][12]. - **20 - year CDB Bonds**: As of November 30, the spread between 20 - year CDB bonds and 20 - year treasury bonds was 12BP, at a historically extremely low level. The economic situation in October was similar to that for 30 - year bonds. The bond market is likely to fluctuate at a low level, and the variety spread of 20 - year CDB bonds is expected to have narrow - range fluctuations [3][13]. Ultra - long Bond Basic Overview - The balance of outstanding ultra - long bonds is 24.3 trillion. As of November 30, the total amount of ultra - long bonds with a remaining maturity of over 14 years was 243,416 billion (excluding asset - backed securities and project revenue notes), accounting for 15.1% of all bonds. Local government bonds and treasury bonds are the main varieties [14]. - By variety, treasury bonds account for 26.8% (65,243 billion), local government bonds account for 67.8% (165,015 billion), and other varieties account for a small proportion [14]. - By remaining maturity, the 30 - year variety accounts for the highest proportion. The amount in the 14 - 18 - year range is 60,963 billion (25.0%), 18 - 25 - year is 70,852 billion (29.1%), 25 - 35 - year is 97,548 billion (40.1%), and over 35 - year is 14,055 billion (5.8%) [14]. Primary Market Weekly Issuance - Last week (November 24 - 28, 2025), the issuance of ultra - long bonds increased sharply, with a total issuance of 1,735 billion yuan. Compared with the previous week, the total issuance increased significantly [19]. - By variety, local government bonds issued 1,732 billion yuan, and corporate bonds issued 3 billion yuan, while other varieties issued 0 billion yuan [19]. - By term, 15 - year bonds issued 482 billion yuan, 20 - year bonds issued 367 billion yuan, 30 - year bonds issued 887 billion yuan, and 50 - year bonds issued 0 billion yuan [19]. This Week's Scheduled Issuance - The announced issuance plan for ultra - long bonds this week is 558 billion yuan. Among them, ultra - long treasury bonds are 270 billion yuan, and ultra - long local government bonds are 288 billion yuan [25]. Secondary Market Trading Volume - Last week, the trading of ultra - long bonds was very active, with a trading volume of 9,136 billion yuan, accounting for 11.3% of all bond trading volume. By variety, ultra - long treasury bonds accounted for 33.9% of all treasury bond trading volume, ultra - long local bonds accounted for 50.3% of all local bond trading volume, ultra - long policy - financial bonds accounted for 0.2% of all policy - financial bond trading volume, and ultra - long government agency bonds accounted for 24.4% of all government agency bond trading volume [27]. - Compared with the previous week, the trading volume of ultra - long bonds decreased by 125 billion yuan, with the proportion remaining unchanged. The trading volume of ultra - long treasury bonds increased by 385 billion yuan, the proportion decreased by 1.8%; the trading volume of ultra - long local bonds decreased by 470 billion yuan, the proportion decreased by 3.4%; the trading volume of ultra - long policy - financial bonds increased by 14 billion yuan, the proportion increased by 0.1%; the trading volume of ultra - long government agency bonds increased by 2 billion yuan, the proportion increased by 11.7% [27]. Yield - Last week, the bond market first declined and then rebounded, and ultra - long bonds continued to fall. For treasury bonds, the yields of 15 - year, 20 - year, 30 - year, and 50 - year bonds changed by 3BP, 4BP, 3BP, and 5BP to 2.09%, 2.20%, 2.19%, and 2.36% respectively. For CDB bonds, the corresponding yields changed by 3BP, 3BP, 2BP, and 5BP to 2.21%, 2.32%, 2.32%, and 2.49% respectively. For local bonds, the yields of 15 - year, 20 - year, and 30 - year bonds changed by 5BP, 7BP, and 7BP to 2.33%, 2.41%, and 2.41% respectively. For railway bonds, the yields of 15 - year, 20 - year, and 30 - year bonds changed by 3BP, 4BP, and 4BP to 2.29%, 2.37%, and 2.42% respectively [37]. Spread Analysis - **Term Spread**: Last week, the term spread of ultra - long bonds remained flat, with an absolute low level. The spread between 30 - year and 10 - year treasury bonds was 34BP, unchanged from the previous week, at the 15th percentile since 2010 [48]. - **Variety Spread**: Last week, the variety spread of ultra - long bonds narrowed, with an absolute low level. The spread between 20 - year CDB bonds and treasury bonds was 12BP, and the spread between 20 - year railway bonds and treasury bonds was 18BP, changing by - 1BP and 0BP respectively from the previous week, at the 10th and 13th percentiles since 2010 [49]. 30 - year Treasury Bond Futures - Last week, the main contract of 30 - year treasury bond futures, TL2603, closed at 114.46 yuan, a decrease of 0.81%. The total trading volume was 92,500 lots (17,365 lots), and the open interest was 147,400 lots (38,082 lots). The trading volume and open interest increased significantly compared with the previous week [54].

Investment Rating - The investment rating for the company is "Outperform the Market" (maintained) [2] Core Viewpoints - The company has steadily developed into a leading chain pharmacy enterprise in China over the past 20 years, with a strong market presence in Central South, East China, and South China regions, and a total of over 14,666 stores by September 2025, serving 110 million members [3][4] - The retail pharmacy industry is undergoing a transformation from scale expansion to quality competition, with a market size of 929.3 billion yuan in 2023, growing by 6.5% year-on-year, but showing signs of slowing growth [3][46] - The company has shown slight revenue growth and strong profit growth in the first three quarters of 2025, with operating income of 17.286 billion yuan (up 0.4% year-on-year) and net profit of 1.225 billion yuan (up 10.3% year-on-year) [20][21] - The company is expected to maintain growth through refined operations and the development of a new retail system, with projected revenues of 24.546 billion yuan, 27.292 billion yuan, and 30.444 billion yuan for 2025-2027, representing year-on-year growth rates of 2.0%, 11.2%, and 11.5% respectively [3][20] Summary by Sections Company Overview - The company has expanded its operational regions and has a strong financing and acquisition capability, establishing itself as a leading chain pharmacy since its founding in 2001 [5] - The company has a clear shareholding structure, with the controlling shareholder being Chairman Gao Yi, who holds 11.67% of the shares directly [8] Industry Status - The retail pharmacy market is experiencing a decline in growth rates, with the number of retail pharmacies decreasing from 706,000 in Q3 2024 to 699,000 in Q1 2025 due to industry slowdown and online competition [3][46] - The industry is expected to see increased concentration and chain rates, with larger chain enterprises likely to gain competitive advantages over smaller pharmacies [3][46] Operational Effectiveness - The company has implemented a "fleet-type" store network strategy, enhancing customer repurchase rates through a membership system and digitalization [3][29] - The company has issued convertible bonds to raise 1.797 billion yuan for projects aimed at improving operational efficiency and logistics capabilities [18] Performance Review - The company has maintained stable expense ratios, with a gross margin of 40.4% and a net margin of 7.6% in the first three quarters of 2025 [29] - The retail business remains the primary revenue source, while the franchise and distribution business has shown significant growth, with a 17.5% increase in revenue [32] Future Outlook - The company is expected to benefit from the trend of prescription drug outflow, which is anticipated to provide new growth opportunities in the retail pharmacy market [57][62] - The company is focusing on expanding its new retail system, enhancing its O2O and B2C channels, and leveraging its large member base to drive sales [93]

证券研究报告 | 2025年11月30日 美元债双周报（25 年第 47 周） 弱于大市 经济数据陆续发布，降息预期大幅抬升 新美联储主席人选或在圣诞前宣布，热门候选人主张 12 月降息。11 月 25 日，美国财政部长斯科特·贝森特表示，美国总统特朗普极有可能在今 年圣诞节前，提名美联储主席鲍威尔的继任者。鲍威尔当前任期将于 2026年 5月结束，但特朗普此前已多次公开批评其货币政策并要求辞职。 而下一届联储主席热门候选人沃勒表示，他主张在 12 月降息。他指出， 最新数据显示劳动力市场依然疲软，不过一旦明年 1 月收到大量经济数 据后，美联储大概可以采取"逐次会议"决定的方式。与此同时，旧金 山联储主席戴利也表示支持美联储在下月会议上降息，理由是她认为就 业市场突然恶化的可能性更大，且比通胀飙升更难管理。 美国 9 月 PPI 核心通胀继续放缓。11 月 25 日周二，美国劳工统计局公布 因政府停摆而延迟的的报告，数据显示显示核心通胀持续放缓。9 月 PPI 环比上涨 0.3%符合预期，主要受能源和食品价格推动；但剔除这两项的 核心 PPI 环比仅涨 0.1%，不及预期的 0.2%。同比方面，核心 PPI ...

Quantitative Models and Construction Methods 1. Model Name: Maximized Factor Exposure Portfolio (MFE) - **Model Construction Idea**: The MFE portfolio is designed to test the effectiveness of single factors under real-world constraints, such as industry exposure, style exposure, stock weight limits, and turnover constraints. This approach ensures that factors deemed effective can genuinely contribute to return prediction in the final portfolio[41][42]. - **Model Construction Process**: - The optimization model aims to maximize single-factor exposure while adhering to various constraints: $$ \begin{array}{ll} \text{max} & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T}w = 1 \end{array} $$ - **Objective Function**: Maximize single-factor exposure, where \( f \) represents factor values, \( f^{T}w \) is the weighted exposure of the portfolio to the factor, and \( w \) is the stock weight vector[42]. - **Constraints**: - **Style Exposure**: \( X \) is the factor exposure matrix for stocks, \( w_b \) is the benchmark weight vector, and \( s_l, s_h \) are the lower and upper bounds for style factor exposure[42]. - **Industry Exposure**: \( H \) is the industry exposure matrix, and \( h_l, h_h \) are the lower and upper bounds for industry deviations[42]. - **Stock Weight Deviation**: \( w_l, w_h \) are the lower and upper bounds for individual stock weight deviations from the benchmark[42]. - **Constituent Stock Weight**: \( B_b \) is a 0-1 vector indicating whether a stock is a benchmark constituent, and \( b_l, b_h \) are the lower and upper bounds for constituent stock weights[42]. - **No Short Selling**: Ensures non-negative weights and limits individual stock weights to \( l \)[42]. - **Full Investment**: Ensures the portfolio is fully invested with \( \mathbf{1}^{T}w = 1 \)[43]. - The MFE portfolio is constructed monthly, and historical returns are calculated after accounting for transaction costs of 0.3% on both sides[45]. - **Model Evaluation**: The MFE portfolio effectively tests factor performance under realistic constraints, making it a robust tool for evaluating factor predictability in practical scenarios[41][42]. --- Factor Construction and Methods 1. Factor Name: Momentum (1-Year Momentum) - **Factor Construction Idea**: Measures the momentum effect by capturing the price trend over the past year, excluding the most recent month[18]. - **Factor Construction Process**: - Formula: \( \text{1-Year Momentum} = \text{Cumulative Return over the past 12 months (excluding the last month)} \)[18]. - **Factor Evaluation**: Momentum factors generally perform well in capturing price trends, as evidenced by their positive performance in multiple sample spaces[20][22][24]. 2. Factor Name: DELTAROE - **Factor Construction Idea**: Measures the change in return on equity (ROE) compared to the same quarter in the previous year, reflecting profitability improvement[18]. - **Factor Construction Process**: - Formula: \( \text{DELTAROE} = \text{Current Quarter ROE} - \text{ROE of the Same Quarter Last Year} \)[18]. - **Factor Evaluation**: DELTAROE is effective in identifying companies with improving profitability, as shown by its strong performance in various sample spaces[22][24][26]. 3. Factor Name: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: Measures the deviation of actual earnings from expected earnings, standardized by the standard deviation of expected earnings, to capture earnings surprises[18]. - **Factor Construction Process**: - Formula: \( \text{SUE} = \frac{\text{Actual Quarterly Net Profit} - \text{Expected Net Profit}}{\text{Standard Deviation of Expected Net Profit}} \)[18]. - **Factor Evaluation**: SUE is a reliable indicator of earnings surprises and is particularly effective in growth-oriented sample spaces[18][24]. --- Factor Backtesting Results 1. 1-Year Momentum - **Performance in Different Sample Spaces**: - **CSI 300**: Positive performance in the past week but underperformed in the past month and year-to-date[20]. - **CSI 500**: Strong performance in the past week and year-to-date, with weaker results in the past month[22]. - **CSI 1000**: Underperformed year-to-date but showed strong weekly performance[24]. - **CSI A500**: Mixed results, with strong weekly performance but weaker year-to-date performance[26]. - **Public Fund Heavyweight Index**: Positive weekly performance but underperformed year-to-date[28]. 2. DELTAROE - **Performance in Different Sample Spaces**: - **CSI 300**: Strong year-to-date performance, with mixed results in the past week and month[20]. - **CSI 500**: Positive weekly and year-to-date performance, with weaker results in the past month[22]. - **CSI 1000**: Strong weekly and year-to-date performance, with weaker results in the past month[24]. - **CSI A500**: Positive weekly and year-to-date performance, with weaker results in the past month[26]. - **Public Fund Heavyweight Index**: Positive weekly and year-to-date performance, with weaker results in the past month[28]. 3. SUE - **Performance in Different Sample Spaces**: - **CSI 300**: Not explicitly mentioned in the report[18]. - **CSI 500**: Not explicitly mentioned in the report[18]. - **CSI 1000**: Not explicitly mentioned in the report[18]. - **CSI A500**: Not explicitly mentioned in the report[18]. - **Public Fund Heavyweight Index**: Not explicitly mentioned in the report[18]. --- Quantitative Model Backtesting Results 1. MFE Portfolio - **Performance in Different Sample Spaces**: - **CSI 300**: Weekly excess return of 0.64%, year-to-date excess return of 17.85%[15]. - **CSI 500**: Weekly excess return of 0.00%, year-to-date excess return of 7.07%[15]. - **CSI 1000**: Weekly excess return of 0.21%, year-to-date excess return of 14.89%[15]. - **CSI A500**: Weekly excess return of 0.44%, year-to-date excess return of 8.26%[15].

证券研究报告 | 2025年11月30日 美股市场速览 弱于大市 价格快速修复，业绩预期平稳 价格走势：多数行业与全风格显著修复 本周，标普 500 涨 3.7%，纳斯达克涨 4.9%。 风格：小盘成长（罗素 2000 成长+6.3%）＞小盘价值（罗素 2000 价值+4.7%） ＞大盘成长（罗素 1000 成长+4.2%）＞大盘价值（罗素 1000 价值+3.4%）。 22 个行业上涨，1 个行业下跌，1 个基本持平。上涨的主要有：汽车与汽车 零部件（+9.3%）、媒体与娱乐（+6.5%）、半导体产品与设备（+6.2%）、 耐用消费品与服装（+4.8%）、零售业（+4.7%）；下跌的主要有：家庭与个 人用品（-0.4%）。 资金流向：多数行业带动资金显著回流 本周，标普 500 成分股估算资金流（涨跌额 x 成交量）为+214.0（亿美元， 下同），上周为-154.0，近 4 周为-133.6，近 13 周为+492.3。 22 个行业资金流入，2 个行业资金流出。资金流入的主要有：半导体产品与 设备（+46.3）、媒体与娱乐（+43.0）、汽车与汽车零部件（+33.5）、综 合金融（+17.4）、技术硬件 ...

Investment Rating - The report maintains an "Outperform" rating for the Hong Kong stock market [4] Core Viewpoints - The price recovery across the market is evident, with significant differentiation in fundamentals among various sectors [1] - The Hang Seng Index and Hang Seng Composite Index have shown positive performance, with increases of 2.5% and 3.8% respectively [1] - Small-cap stocks outperformed mid and large-cap stocks, indicating a shift in market dynamics [1] Summary by Sections Market Performance - The Hang Seng Index rose by 2.5%, while the Hang Seng Composite Index increased by 3.8% [1] - The performance of different market segments showed that small-cap stocks (Hang Seng Small Cap +3.0%) outperformed mid-cap (Hang Seng Mid Cap +2.6%) and large-cap stocks (Hang Seng Large Cap +2.5%) [1] - Notable sector performances included the Hang Seng Innovation Drug Index (+6.1%) and the Hang Seng Automobile Index (+4.5%) [1] Valuation Levels - The valuation of the Hang Seng Index increased by 1.6% to 11.8x, while the Hang Seng Composite Index rose by 1.8% to 11.7x [2] - Significant valuation increases were observed in the Hang Seng Automobile Index (+5.3% to 13.8x) [2] - Among 30 sectors, 22 saw valuation increases, with notable rises in Light Industry Manufacturing (+6.7%) and Automotive (+5.7%) [2] Earnings Expectations - The earnings per share (EPS) for the Hang Seng Index increased by 0.4%, while the Hang Seng Composite Index saw a 0.5% rise [3] - The earnings expectations showed a mixed trend, with the Hang Seng Biotechnology Index up by 1.3% and the Hang Seng Automobile Index down by 0.7% [3] - A total of 19 sectors experienced upward revisions in EPS, with Steel (+11.6%) and Non-ferrous Metals (+3.6%) leading the increases [3]

Group 1: Economic Structure and Trends - The service and manufacturing sectors are not in opposition but rather have a symbiotic relationship, as evidenced by the increase of over 7 percentage points in the service sector's share of global GDP from 1980 to 1996, while manufacturing remained stable[1] - From 2002 to 2019, both sectors exhibited a synchronized trend of rise and fall, indicating their interdependence rather than a zero-sum game[1] - Manufacturing acts as an incubator for service industries, with many productive services like logistics and R&D initially emerging from within manufacturing firms[1] Group 2: Support and Demand Dynamics - The large service sector constitutes the core consumer base for manufacturing products, creating significant demand for items ranging from medical equipment to educational materials[2] - Services play a crucial role in enhancing human capital, which is essential for the quality of manufacturing inputs, thereby supporting innovation and breakthroughs in the manufacturing sector[2] - The current economic transition in China highlights the need for high-quality development in manufacturing to create more opportunities for productive services like R&D and digital services[2] Group 3: Current Economic Indicators - Fixed asset investment has decreased by 1.70% year-on-year, indicating a contraction in investment activities[4] - Retail sales have shown a modest increase of 2.90% year-on-year, reflecting some resilience in consumer spending[4] - Exports have declined by 1.10% year-on-year, suggesting pressure on external demand[4] - The M2 money supply has grown by 8.21%, indicating a continued expansionary monetary policy[4]

Investment Rating - The investment rating for the company is "Outperform the Market" [6] Core Views - The company reported a 42.5% year-on-year growth in net profit attributable to shareholders for the first half of the fiscal year 2026, driven by product and store efficiency optimization, as well as an increase in gross margin [1][3] - Same-store sales continued to show double-digit growth from October 1 to November 21, indicating a sustained positive trend [1] - The company announced an interim dividend of HKD 0.55 per share, with a payout ratio of 52% [1] Summary by Sections Financial Performance - For the first half of the fiscal year 2026, the company achieved revenue of HKD 6.843 billion, a year-on-year increase of 25.6%, and a net profit of HKD 619 million, reflecting a growth of 42.5% [1] - The gross margin improved by 2 percentage points to 34.7%, reaching a historical high, benefiting from rising gold prices and an increased proportion of high-margin priced jewelry [2] - The retail business revenue grew by 12.8%, accounting for 76.8% of total revenue, while wholesale business revenue surged by 190.6%, making up 16.3% of total revenue [2] Business Segmentation - The revenue from weight-based products increased by 11%, while fixed-price products saw a growth of 67.9%, with the latter's share rising by 8.8 percentage points to 35.7%, and the proportion of priced gold is expected to reach around 25% [2] - The revenue from the mainland China market grew by 54.2%, accounting for 43.6% of total revenue, while revenue from Hong Kong, Macau, and overseas markets increased by 9.9%, making up 56.4% [2] Future Outlook - The company is expected to continue benefiting from product innovation, channel optimization, and accelerated overseas development, with projected net profits of HKD 1.501 billion, HKD 1.787 billion, and HKD 2.028 billion for fiscal years 2026, 2027, and 2028, respectively [3][4] - The price-to-earnings ratio (PE) is projected to be 9.5, 8.0, and 7.1 for the fiscal years 2026, 2027, and 2028, indicating a favorable valuation [3][4]

Investment Rating - The report maintains an "Outperform the Market" rating for the company [6]. Core Insights - The company demonstrated a significant acceleration in revenue growth in Q3, achieving a revenue of 5.797 billion, a year-on-year increase of 28.2%, surpassing previous guidance [2]. - The adjusted operating profit for Q3 was 1.022 billion, up 14.8% year-on-year, while the adjusted net profit reached 767 million, reflecting an 11.7% increase [2]. - The company expects Q4 revenue growth to be between 25% and 30%, with double-digit same-store sales growth anticipated in both China and the U.S. [2]. - The domestic business is benefiting from a large store strategy and refined operations, with same-store sales showing a positive trend [4]. - The overseas business is expanding rapidly, with a net addition of 117 stores in Q3, bringing the total overseas store count to 3,424 [2]. Financial Performance Summary - Q3 revenue for the brand was 5.222 billion, a year-on-year increase of 22.9%, with domestic revenue at 2.909 billion, up 19.3% [2]. - The company forecasts a full-year revenue growth of 25%, with adjusted operating profit expected to be between 3.65 billion and 3.85 billion [4]. - The financial projections for 2023 to 2027 indicate a steady increase in revenue and net profit, with 2023 revenue projected at 13.839 billion, growing to 28.578 billion by 2027 [5]. - The adjusted net profit for 2023 is estimated at 2.253 billion, with a projected increase to 3.257 billion by 2027 [5].