Investment Rating - The report maintains a "Recommendation" rating for the automotive industry, indicating a positive outlook for the sector [5]. Core Insights - The automotive industry experienced an overall increase of 2.6% from June 22 to June 28, with significant developments in electric vehicles and autonomous driving technology [1][11]. - Xiaomi's YU7 model exceeded expectations with over 200,000 pre-orders within 3 minutes of launch, and 240,000 orders within 18 hours, highlighting strong consumer interest [23][24]. - Tesla achieved a milestone by delivering a Model Y autonomously for the first time, showcasing advancements in self-driving technology [29]. Market Performance Overview - The automotive sector's secondary segments saw comprehensive growth, with automotive parts and services rising by 4.6% and 4.3% respectively [11]. - Notable individual stock performances included Construction Industry (+35.9%), Haitai Technology (+35.7%), and Patel (+31.3%) [3][14]. Recent Industry Developments - The report highlights several key industry events, including the launch of the Wanjie M8 model, which achieved over 30,000 deliveries in 58 days, and the introduction of a strategic investment of 5 billion RMB in Seris Automotive [21][27]. - The establishment of new companies, such as Yipai Automotive by Dongfeng Motor, aims to enhance the company's capabilities in the electric and intelligent vehicle sectors [22]. Investment Recommendations - The report suggests focusing on companies with strong sales performance or potential blockbuster vehicles, including BYD, Seris, Great Wall Motors, and Jianghuai Automotive [5]. - For commercial vehicles, it recommends Yutong Bus, China National Heavy Duty Truck, and Weichai Power, while highlighting quality enterprises in parts manufacturing such as Fuyao Glass and Top Group [5].

Investment Rating - The report maintains a strong buy rating for the company, with a target valuation not specified [5]. Core Views - The company is expected to achieve high-quality growth in FY25, with a projected revenue increase of 11.6% and a net profit increase of 14.3%, demonstrating strong operational resilience amid a warm winter [1][11]. - The company is focusing on the "fashion functional technology apparel" segment while optimizing its product categories and channel quality [11]. Revenue and Profitability - For FY25, the company's total revenue reached 25.9 billion RMB, with a significant increase in operating profit by 12.9% to 4.97 billion RMB and a net profit attributable to shareholders of 3.51 billion RMB, reflecting a 14.3% year-on-year growth [11][10]. - The gross margin for the brand's down jackets decreased by 2.3 percentage points to 57.3%, while the net profit margin increased by 0.4 percentage points to 13.6% due to expense optimization [4][11]. Brand Performance - The brand's down jacket revenue grew by 11.0% to 21.67 billion RMB, with the main brand contributing 85.3% of total down jacket revenue [10][2]. - Online and offline sales for the brand's down jackets were 7.48 billion RMB (+9.4%) and 14.19 billion RMB (+11.9%), respectively [2]. Channel and Retail Expansion - The company added 253 retail outlets, bringing the total to 3,470, with a significant presence in first and second-tier cities [2]. - The self-operated and wholesale channels generated revenues of 15.09 billion RMB (+5.2%) and 5.72 billion RMB (+24.3%), respectively [2]. Financial Health - The company maintains healthy cash flow and inventory turnover, with a cash flow net amount of 3.98 billion RMB, which is 1.13 times the net profit [11]. - The asset-liability ratio stands at 37.9%, indicating a solid financial position [5][14]. Future Projections - The company forecasts net profits of 3.91 billion RMB, 4.34 billion RMB, and 4.76 billion RMB for FY26, FY27, and FY28, respectively, with corresponding growth rates of 11% [11][10]. - Revenue projections for FY26, FY27, and FY28 are 28.5 billion RMB, 31.3 billion RMB, and 34.2 billion RMB, with growth rates of 10%, 10%, and 9% [11][10].

Group 1: Geopolitical Developments - Iran and Israel announced a ceasefire, with concerns about the potential for renewed military action if negotiations fail[5] - NATO summit agreed to increase defense spending to 5% of GDP by 2035, with 3.5% for core defense and 1.5% for broader measures[10] - Ongoing U.S. trade negotiations with multiple countries, including China, Japan, and South Korea, with a focus on tariffs and trade barriers[13] Group 2: Trade and Economic Policies - U.S. tariffs on various goods remain a critical issue, with a focus on semiconductor and pharmaceutical investigations initiated in April[16] - The U.S. is considering extending tariff suspension for countries participating in trade negotiations until July 9[16] - The potential for a shift in U.S. trade policy towards more strategic protectionism, particularly in key supply chains[16] Group 3: Risks and Future Outlook - Risks include unexpected changes in U.S. policy and international relations, particularly regarding Iran and trade negotiations[4] - The geopolitical landscape is shifting, with a focus on balancing relations between major powers, including the U.S., Russia, and China[19] - Long-term uncertainties may arise from internal U.S. political dynamics affecting foreign policy and trade strategies[20]

证券研究报告 | 行业定期报告 2025 年 06 月 29 日 基本面宏观面共振 铜向上突破 金属行业周报 周期/金属及材料 宏观和地缘局势缓和，市场风险偏好回升。下半年，我们预计金属市场步入全 球宽松和金属价格受益进入上行通道。当前风险因素依然较多。美国和中国之 外关税 90 天豁免临近结束，仍需关注。铜基本面很强，一方面消费韧性，另 外美国 232 带来的大量铜蜂拥至美国，导致非美地区供应吃紧。预计近期随着 LME 逼仓，国内库存重回下降，基本面走强，但是需要警惕 232 消息的扰动。 黄金价格近期调整，但是长期看涨逻辑未变，我们继续看多。此外，关注自主 可控相关以及时间友好的科技、机器人、可控核聚变等相关材料标的。 推荐（维持） 行业规模 | | | 占比% | | --- | --- | --- | | 股票家数（只） | 235 | 4.6 | | 总市值（十亿元） | 4242.0 | 4.8 | | 流通市值（十亿元） | 3944.2 | 4.9 | 行业指数 % 1m 6m 12m 绝对表现 7.7 13.0 32.6 相对表现 5.5 14.5 19.1 资料来源：公司数据、招商证券 - ...

Investment Rating - The industry is rated as "Recommended" based on the positive outlook for the digital asset sector and its expected growth due to regulatory advancements [2][32]. Core Insights - The digital asset market is poised for accelerated growth as regulatory frameworks are established, with Hong Kong aiming to become a global innovation hub for digital assets [5][16]. - The release of the "Hong Kong Digital Asset Development Policy Declaration 2.0" emphasizes the LEAP framework, which focuses on legal and regulatory optimization, expanding tokenized product categories, promoting application scenarios, and developing talent and partnerships [16][17]. - The approval of 41 institutions for license upgrades indicates a growing acceptance and integration of virtual asset services within traditional financial frameworks [10][13]. Summary by Sections 1. Hong Kong Digital Asset Regulatory Legislation - Guotai Junan International has become the first Hong Kong-based Chinese broker to offer comprehensive virtual asset trading services after upgrading its license [9]. - A total of 41 institutions have received license upgrades, including 38 brokers, 1 bank, and 1 internet company, indicating a significant shift towards virtual asset services [10][13]. 2. Artificial Intelligence Industry Chain Update - Multiple domestic companies are accelerating their deployment in the AI agent sector, transitioning from technical exploration to practical applications across various industries [20][24]. - Intel plans to outsource marketing positions to Accenture, aiming to enhance operational efficiency and digital capabilities through AI [20]. 3. Market Performance Review - The computer sector saw a 7.71% increase in the fourth week of June 2025, with notable performers including Tianli Technology and ST Guangdao [25].

1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report The report analyzes the primary and secondary market conditions of local government bonds in the week of June 29, 2025, and predicts the issuance plan for the third quarter of 2025. It shows that the issuance volume and net financing of local government bonds in the primary market have increased, the proportion of long - term issuance has risen, and the issuance spread has widened. In the secondary market, the secondary spreads of 3Y, 15Y, and 30Y local government bonds are advantageous, and the turnover rates of local government bonds in Fujian, Sichuan, and Shandong are relatively high. 3. Summary According to the Directory 3.1 Primary Market Issuance Situation - **Net Financing**: This week, local government bonds issued a total of 641.6 billion yuan, with a repayment of 81.3 billion yuan and a net financing of 560.4 billion yuan. The issuance volume and net financing increased [1]. - **Issuance Term**: The issuance proportion of 10Y local government bonds was the highest this week (27%), and the proportion of 10Y and above issuance was 73%, showing an increase compared with last week. The issuance proportion of 7Y local government bonds decreased significantly, with a month - on - month decrease of about 10 percentage points [1][12]. - **Debt - Resolution - Related Local Government Bonds**: This week, special refinancing bonds issued a total of 5.97 billion yuan. In 2025, 33 regions have disclosed plans to issue special bonds to replace hidden debts, with a total of 179.59 billion yuan. Among them, Jiangsu, Sichuan, Shandong, and Yunnan plan to issue 25.11 billion yuan, 11.48 billion yuan, 11.13 billion yuan, and 8.78 billion yuan respectively [15][16]. - **Issuance Spread**: The weighted average issuance spread of local government bonds this week was 11.9bp, which widened compared with last week. The weighted average issuance spread of 30Y local government bonds was the highest, reaching 18.8bp. Except for the 5Y, 10Y, and 20Y local government bonds, the weighted average issuance spreads of other terms narrowed [1][24]. - **Raised Funds Allocation**: As of the end of this week, the main allocation directions of newly - added special bond funds in 2025 were cold - chain logistics, municipal and industrial park infrastructure construction (30%), transportation infrastructure (20%), affordable housing projects (13%), and social undertakings (12%). The proportion of land reserve allocation increased by 10.9% compared with 2024, while the proportion of cold - chain logistics, municipal and industrial park infrastructure construction decreased by 6.9% [2][28]. - **Issuance Plan**: As of the end of this week, 30 regions have disclosed the local government bond issuance plan for the third quarter of 2025, with a total of 2.56 trillion yuan. Among them, the planned issuance in July is 128.1 billion yuan. In addition, the planned issuance of new bonds and refinancing bonds in the third quarter is 161.23 billion yuan and 94.7 billion yuan respectively. Next week, the planned issuance of local government bonds is 6.14 billion yuan, with a repayment of 5.05 billion yuan and a net financing of 1.09 billion yuan, a month - on - month decrease of 54.94 billion yuan [3][30]. 3.2 Secondary Market Situation - **Secondary Spread**: This week, the secondary spreads of 3Y, 15Y, and 30Y local government bonds were advantageous, and the widening amplitudes of the secondary spreads of 3Y and 30Y local government bonds were relatively large. The secondary spreads of 3Y, 15Y, and 30Y local government bonds were relatively high, reaching 17.2bp, 18.5bp, and 18.3bp respectively. From the perspective of the historical quantile in the past three years, the historical quantile of the secondary spread of 30Y local government bonds was relatively high, reaching 77%. Regionally, the secondary spreads of local government bonds over 20Y in various types of regions were relatively high, and the secondary spreads of 10 - 20Y local government bonds in medium - level regions were also relatively high [5][35]. - **Trading Volume**: This week, the trading volume and turnover rate of local government bonds basically remained at the same level as last week. The turnover rates of local government bonds in Fujian, Sichuan, and Shandong were relatively high. The trading volume of local government bonds this week reached 520.6 billion yuan, with a turnover rate of 1.01%. Among them, the trading volumes of local government bonds in Shandong and Jiangsu were large, reaching 5.05 billion yuan and 4.86 billion yuan respectively; the turnover rates in Fujian, Sichuan, Shandong and other places were all higher than 1.6% [5][39].

Domestic Insights - In the last week of June, production data continued to show seasonal weakness, with expected further decline in production growth for June[2] - Summer consumption has become a structural highlight, with a rebound in consumption data and improved travel flow[2] - The real estate market remains weak, with transaction volumes in 30 cities in June showing a larger gap compared to the same period last year[2] - The recent "strong US stocks + weak dollar" pattern is boosting non-US equity risk appetite and liquidity, with expectations for improved domestic equity risk appetite in July[2] Overseas Insights - Trade policy is likely to evolve towards overall easing with localized tightening, as the July tariff exemption period is expected to be extended[2] - The latest version of the OBBB Act is estimated to increase the total deficit by $3.5-4.2 trillion, significantly higher than the House's $2.9 trillion estimate[2] - The Federal Reserve's recent statements show a slight easing in tone, but most officials still oppose a rate cut in July[2] - The US Senate is expected to pass a new budget coordination bill by Q3, with a potential deadline before the X-Date in August-September[2]

Quantitative Models and Construction Methods - **Model Name**: Multi-period interest rate timing strategy **Model Construction Idea**: The model uses multi-period resonance strategies to capture interest rate trends and generate timing signals based on shape recognition algorithms[10][22] **Model Construction Process**: 1. **Signal Generation**: Utilize kernel regression algorithms to identify support and resistance lines of interest rate data. Analyze the breakthrough patterns of interest rate trends across long, medium, and short cycles[10][22] 2. **Portfolio Construction**: - If at least two cycles show downward breakthroughs and the trend is not upward, allocate fully to long-duration bonds - If at least two cycles show downward breakthroughs but the trend is upward, allocate 50% to medium-duration bonds and 50% to long-duration bonds - If at least two cycles show upward breakthroughs and the trend is not downward, allocate fully to short-duration bonds - If at least two cycles show upward breakthroughs but the trend is downward, allocate 50% to medium-duration bonds and 50% to short-duration bonds - In other cases, allocate equally across short, medium, and long durations - Stop-loss mechanism: Adjust holdings to equal-weighted allocation if daily excess returns fall below -0.5%[22] **Model Evaluation**: The strategy demonstrates strong performance with consistent positive returns and high excess return ratios over the long term[22][23] Model Backtesting Results - **Multi-period interest rate timing strategy**: - **Short-term annualized return**: 7.27%[4][22] - **Short-term maximum drawdown**: 1.56%[4][22] - **Short-term return-to-drawdown ratio**: 6.23[4][22] - **Short-term excess return**: 2.2%[4][23] - **Long-term annualized return**: 6.17%[22] - **Long-term maximum drawdown**: 1.52%[22] - **Long-term return-to-drawdown ratio**: 2.26[22] - **Long-term excess return**: 1.66%[22] - **Excess return-to-drawdown ratio**: 1.18[22] - **Annual absolute return win rate**: 100%[23] - **Annual excess return win rate**: 100%[23] Quantitative Factors and Construction Methods - **Factor Name**: Interest rate structure indicators (level, term, convexity) **Factor Construction Idea**: Transform yield-to-maturity (YTM) data of 1-10 year government bonds into structural indicators to analyze market trends from a mean-reversion perspective[7][9] **Factor Construction Process**: 1. Calculate the level structure indicator as the average YTM across maturities 2. Compute the term structure indicator as the difference between long-term and short-term YTM 3. Derive the convexity structure indicator based on the curvature of the yield curve[7][9] **Factor Evaluation**: The indicators provide insights into the current state of the interest rate market, showing low levels across all three structures[7][9] - **Factor Name**: Multi-period interest rate timing signals **Factor Construction Idea**: Use kernel regression algorithms to identify interest rate trends and generate timing signals based on breakthroughs across long, medium, and short cycles[10] **Factor Construction Process**: 1. Apply kernel regression to identify support and resistance lines for interest rate data 2. Analyze breakthrough patterns across different cycles (monthly for long-term, bi-weekly for medium-term, weekly for short-term)[10] **Factor Evaluation**: The signals are effective in capturing market trends, with the latest signals indicating a neutral-to-bearish stance[10] Factor Backtesting Results - **Interest rate structure indicators**: - **Level structure**: Current reading is 1.51%, positioned at 6%, 4%, and 2% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Term structure**: Current reading is 0.3%, positioned at 13%, 8%, and 10% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Convexity structure**: Current reading is 0.02%, positioned at 18%, 11%, and 11% percentiles for 3, 5, and 10-year historical perspectives, respectively[9] - **Multi-period interest rate timing signals**: - **Long-term signal**: Upward breakthrough[10] - **Medium-term signal**: No signal[10] - **Short-term signal**: Downward breakthrough[10] - **Overall signal**: Neutral-to-bearish[10]

Investment Rating - The report maintains a "Strong Buy" rating for Luzhou Laojiao [1][3]. Core Views - The company is actively embracing new consumption trends in the industry, with a focus on product innovation and channel transformation [1][6]. - The management has a clear understanding of the industry landscape and is strategically planning to adapt to changes, particularly in consumer preferences towards lower-alcohol products [1][6]. - The company aims to improve inventory control and maintain pricing stability for its Guojiao series products, leveraging digital marketing for channel expansion [1][6]. Financial Data and Valuation - The projected EPS for 2025-2027 is 9.47, 10.00, and 10.83, respectively, with a corresponding PE of 12X for 2025 [1][3]. - Total revenue is expected to grow from 30,233 million in 2023 to 35,708 million in 2027, reflecting a compound annual growth rate [2][12]. - The company’s net profit is projected to increase from 13,246 million in 2023 to 15,935 million in 2027, indicating a steady growth trajectory [7][12]. Market Strategy - The company is focusing on penetrating lower-tier markets, aiming to reach four million terminals in the next five years [1][6]. - Digital marketing initiatives are being implemented to enhance direct channel capabilities and meet emerging consumer demands [1][6]. - The company is committed to developing low-alcohol products, with successful innovations like the 28-degree Guojiao 1573 and ongoing research for other low-alcohol variants [1][6]. Financial Ratios - The return on equity (ROE) is projected to be 26.9% for the trailing twelve months, indicating strong profitability [3][13]. - The asset-liability ratio is expected to decrease from 34.4% in 2023 to 22.6% in 2027, reflecting improved financial stability [13]. - The company maintains a high gross margin of approximately 87.4% to 88.3% over the forecast period, showcasing its pricing power [13].

- Model Name: Short-term Quantitative Timing Model; Model Construction Idea: The model is based on market sentiment indicators, valuation, macro liquidity, and macro fundamentals to generate timing signals; Model Construction Process: The model uses various indicators such as manufacturing PMI, long-term loan balance growth rate, M1 growth rate, PE and PB valuation percentiles, Beta dispersion, volume sentiment score, volatility, monetary rate, exchange rate expectation, and net financing amount to generate signals. For example, the formula for the volume sentiment score is: $$ \text{Volume Sentiment Score} = \frac{\text{Current Volume} - \text{Mean Volume}}{\text{Standard Deviation of Volume}} $$ where the current volume is the trading volume of the current period, the mean volume is the average trading volume over a specified period, and the standard deviation of volume is the standard deviation of trading volumes over the same period. The model evaluates these indicators to determine the overall market sentiment and generates a timing signal accordingly[9][14][15]; Model Evaluation: The model is highly sensitive to market sentiment indicators, which can lead to frequent signal changes[9] - Model Name: Growth-Value Style Rotation Model; Model Construction Idea: The model uses economic cycle analysis to determine the allocation between growth and value styles; Model Construction Process: The model evaluates the slope of the profit cycle, the level of the interest rate cycle, and the changes in the credit cycle. For example, the formula for the profit cycle slope is: $$ \text{Profit Cycle Slope} = \frac{\text{Current Profit} - \text{Previous Profit}}{\text{Previous Profit}} $$ where the current profit is the profit of the current period, and the previous profit is the profit of the previous period. The model also considers PE and PB valuation differences and turnover and volatility differences between growth and value styles to generate allocation signals[25][26]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[25][26] - Model Name: Small-Cap vs. Large-Cap Style Rotation Model; Model Construction Idea: The model uses economic cycle analysis to determine the allocation between small-cap and large-cap styles; Model Construction Process: The model evaluates the slope of the profit cycle, the level of the interest rate cycle, and the changes in the credit cycle. For example, the formula for the interest rate cycle level is: $$ \text{Interest Rate Cycle Level} = \frac{\text{Current Interest Rate} - \text{Mean Interest Rate}}{\text{Standard Deviation of Interest Rate}} $$ where the current interest rate is the interest rate of the current period, the mean interest rate is the average interest rate over a specified period, and the standard deviation of interest rate is the standard deviation of interest rates over the same period. The model also considers PE and PB valuation differences and turnover and volatility differences between small-cap and large-cap styles to generate allocation signals[30][31][32]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[30][31][32] - Model Name: Four-Style Rotation Model; Model Construction Idea: The model combines the conclusions of the growth-value and small-cap vs. large-cap rotation models to determine the allocation among four styles: small-cap growth, small-cap value, large-cap growth, and large-cap value; Model Construction Process: The model uses the signals generated by the growth-value and small-cap vs. large-cap rotation models to allocate the portfolio among the four styles. For example, if the growth-value model suggests overweighting value and the small-cap vs. large-cap model suggests overweighting large-cap, the allocation would be adjusted accordingly[33][34]; Model Evaluation: The model provides significant improvement over the benchmark in terms of annualized returns and Sharpe ratio[33][34] Model Backtest Results - Short-term Quantitative Timing Model: Annualized Return 16.24%, Annualized Volatility 14.70%, Maximum Drawdown 27.70%, Sharpe Ratio 0.9613, IR 0.5862, Monthly Win Rate 68.21%, Quarterly Win Rate 68.63%, Annual Win Rate 85.71%[16][19][22] - Growth-Value Style Rotation Model: Annualized Return 11.51%, Annualized Volatility 20.85%, Maximum Drawdown 43.07%, Sharpe Ratio 0.5316, IR 0.2672, Monthly Win Rate 58.00%, Quarterly Win Rate 60.00%, Annual Win Rate 85.71%[27][29] - Small-Cap vs. Large-Cap Style Rotation Model: Annualized Return 11.92%, Annualized Volatility 22.75%, Maximum Drawdown 50.65%, Sharpe Ratio 0.5283, IR 0.2386, Monthly Win Rate 60.67%, Quarterly Win Rate 56.00%, Annual Win Rate 85.71%[32] - Four-Style Rotation Model: Annualized Return 13.03%, Annualized Volatility 21.60%, Maximum Drawdown 47.91%, Sharpe Ratio 0.5834, IR 0.2719, Monthly Win Rate 59.33%, Quarterly Win Rate 62.00%, Annual Win Rate 85.71%[34][35]