Investment Rating - The industry investment rating is "Positive (Maintain)" [5] Core Viewpoints - The report emphasizes the transformation and upgrading of the industry, highlighting the investment opportunities in companies with genuine brand strength [3][8] - The report notes that the gold jewelry sector is facing challenges due to rising gold prices and declining sales, with a significant drop in gold jewelry consumption [8] - Despite industry pressures, certain leading companies have seen stock price increases due to their differentiated transformation strategies and market expectations [8] Summary by Sections Investment Recommendations and Targets - The report recommends focusing on companies that have begun to establish a brand presence, including: - Chao Hong Ji (002345, Increase) - Lao Pu Gold (06181, Increase) - Chow Tai Fook (01929, Not Rated) - Lao Feng Xiang (600612, Buy) - Zhou Da Sheng (002867, Increase) [3] Industry Overview - The report indicates that gold jewelry consumption in China decreased by 3.54% year-on-year in the first half of 2025, with gold jewelry sales down by 26.00% [8] - The average gold price in China for the first half of 2025 was 725.28 yuan per gram, reflecting a year-on-year increase of 41.07% [8] - The report highlights a shift in consumer demand towards self-purchase and emotional consumption, particularly among younger consumers [8] Future Trends - The report anticipates a trend towards brandization and stratified development in the gold jewelry sector, with investment opportunities emerging from both high-end and light luxury fashion brands [8] - High-end brands are expected to focus on original design and craftsmanship, while light luxury brands will cater to younger consumers with affordable, stylish products [8]

Quantitative Models and Construction Methods 1. Model Name: Dividend Forecast Model - **Model Construction Idea**: The model aims to predict the impact of dividends on index futures pricing by estimating the dividend points for each index and calculating the theoretical cost of holding futures contracts until expiration[7][11][19] - **Model Construction Process**: 1. **Estimate Component Stocks' Net Profit**: Use annual reports, earnings forecasts, and other financial data to estimate the net profit of index component stocks[21][23] 2. **Calculate Pre-Tax Total Dividends**: Based on the estimated net profit and assuming a constant dividend payout ratio, calculate the total pre-tax dividends for each stock[21][24] 3. **Assess Dividend Impact on Index**: Using the latest market capitalization and weight of each stock, calculate the dividend impact on the index as follows: $$\text{w}_{it} = \frac{\text{w}_{i0} \times (1 + R)}{\sum_{1}^{n} \text{w}_{i0} \times (1 + R)}$$ where \( \text{w}_{i0} \) is the initial weight of stock \( i \), and \( R \) is the return over the period[24] 4. **Predict Dividend Impact on Futures Contracts**: Aggregate the dividend impact for all component stocks before the contract expiration date to estimate the total dividend points for each futures contract[25][28] - **Model Evaluation**: The model provides a systematic approach to quantify dividend impacts, but its accuracy depends on assumptions about dividend payout ratios and timing[19][28] 2. Model Name: Futures Pricing Model with Discrete Dividends - **Model Construction Idea**: This model calculates the theoretical price of index futures by incorporating discrete dividend distributions during the contract period[30] - **Model Construction Process**: 1. Assume the futures price \( F_t \), spot price \( S_t \), and the present value of dividends \( D \) over the period \( T-t \) 2. For \( m \) discrete dividend payments at times \( t_1, t_2, ..., t_m \), the present value of dividends is: $$D = \sum_{i=1}^{m} \frac{D_i}{(1 + r_i)}$$ where \( r_i \) is the risk-free rate for the period between \( t_i \) and \( t \) 3. The theoretical futures price is then: $$F_t = (S_t - D)(1 + r)$$ where \( r \) is the risk-free rate over the period \( T-t \)[30] - **Model Evaluation**: This model is effective for scenarios with discrete dividend distributions but may require adjustments for continuous dividend flows[30] 3. Model Name: Futures Pricing Model with Continuous Dividends - **Model Construction Idea**: This model simplifies the pricing of index futures by assuming continuous dividend distributions over the contract period[31] - **Model Construction Process**: 1. Assume the futures price \( F_t \), spot price \( S_t \), annualized dividend yield \( d \), and annualized risk-free rate \( r \) 2. The theoretical futures price is calculated as: $$F_t = S_t \cdot e^{(r-d)(T-t)}$$ where \( T-t \) is the time to maturity[31] - **Model Evaluation**: This model is suitable for markets with frequent and evenly distributed dividends, providing a more streamlined calculation compared to the discrete model[31] --- Model Backtesting Results 1. Dividend Forecast Model - **Annualized Hedging Costs (Excluding Dividends)**: - **IH (SSE 50)**: -1.56% for August contracts[7][11] - **IF (CSI 300)**: -0.19% for August contracts[7][11] - **IC (CSI 500)**: 8.55% for August contracts[7][11] - **IM (CSI 1000)**: 8.78% for August contracts[7][11] 2. Futures Pricing Model with Discrete Dividends - **Remaining Impact of Dividends on August Contracts**: - **IH (SSE 50)**: 0.09%[12] - **IF (CSI 300)**: 0.12%[13] - **IC (CSI 500)**: 0.12%[14] - **IM (CSI 1000)**: 0.07%[15] 3. Futures Pricing Model with Continuous Dividends - **Remaining Impact of Dividends on Futures Prices**: - **IH (SSE 50)**: 2.43 points for August contracts[7][11] - **IF (CSI 300)**: 4.81 points for August contracts[7][11] - **IC (CSI 500)**: 7.39 points for August contracts[7][11] - **IM (CSI 1000)**: 4.54 points for August contracts[7][11] --- Quantitative Factors and Construction Methods 1. Factor Name: Dividend Impact Factor - **Factor Construction Idea**: Quantify the impact of dividends on index futures pricing by calculating the dividend points and their contribution to the futures basis[7][11][19] - **Factor Construction Process**: 1. Estimate the dividend points for each index based on component stocks' dividend payouts and weights[21][24] 2. Incorporate the dividend points into the futures pricing model to adjust the theoretical basis[30][31] - **Factor Evaluation**: This factor effectively captures the influence of dividends on futures pricing, aiding in arbitrage and hedging strategies[19][28] --- Factor Backtesting Results 1. Dividend Impact Factor - **Dividend Points for August Contracts**: - **IH (SSE 50)**: 2.43[7][11] - **IF (CSI 300)**: 4.81[7][11] - **IC (CSI 500)**: 7.39[7][11] - **IM (CSI 1000)**: 4.54[7][11]

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[64][65] - **Model Construction Process**: - The optimization model is formulated as follows: $$ \begin{array}{ll} \max & f^{T}w \\ \text{s.t.} & s_{l} \leq X(w-w_{b}) \leq s_{h} \\ & h_{l} \leq H(w-w_{b}) \leq h_{h} \\ & w_{l} \leq w-w_{b} \leq w_{h} \\ & b_{l} \leq B_{b}w \leq b_{h} \\ & 0 \leq w \leq l \\ & 1^{T}w = 1 \\ & \Sigma|w-w_{0}| \leq to_{h} \end{array} $$ - **Explanation of Parameters**: - \( f^{T}w \): Weighted exposure of the portfolio to the factor - \( w \): Portfolio weight vector - \( w_{b} \): Benchmark weight vector - \( X, H, B_{b} \): Matrices representing factor, industry, and benchmark exposures - \( s_{l}, s_{h}, h_{l}, h_{h}, w_{l}, w_{h}, b_{l}, b_{h}, to_{h} \): Constraints on factor exposure, industry exposure, stock weight deviation, and turnover rate - Constraints include: - Limiting style and industry deviations relative to the benchmark - Controlling stock weight deviations and turnover rates - Ensuring full investment (weights sum to 1) and no short selling[64][65][67] - The portfolio is rebalanced monthly, and historical returns are calculated after deducting transaction costs to evaluate factor effectiveness[68] - **Model Evaluation**: The MFE model effectively isolates the impact of individual factors while adhering to practical constraints, making it a robust tool for factor evaluation[64][65] --- Quantitative Factors and Construction Methods 1. Factor Name: Trend - **Factor Construction Idea**: Captures the momentum of stock price trends over different time horizons[16] - **Factor Construction Process**: - Two variations: - **Trend_120**: \( \text{EWMA}(\text{halflife}=20) / \text{EWMA}(\text{halflife}=120) \) - **Trend_240**: \( \text{EWMA}(\text{halflife}=20) / \text{EWMA}(\text{halflife}=240) \) - \( \text{EWMA} \): Exponentially Weighted Moving Average[16] - **Factor Evaluation**: Demonstrates strong performance in capturing price continuation patterns, particularly in volatile markets[11][13] 2. Factor Name: Volatility - **Factor Construction Idea**: Measures the variability of stock returns over a specified period[16] - **Factor Construction Process**: - Variants include: - **Stdvol**: Standard deviation of daily returns over the past 243 days - **Ivff**: Fama-French 3-factor idiosyncratic volatility over the past 243 days - **Range**: \( \text{High Price}/\text{Low Price} - 1 \) over the past 243 days - **MaxRet_6**: Average of the six highest daily returns over the past 243 days - **MinRet_6**: Average of the six lowest daily returns over the past 243 days[16] - **Factor Evaluation**: Effective in identifying high-risk stocks, though performance may vary across market conditions[11][13] 3. Factor Name: BP (Book-to-Price Ratio) - **Factor Construction Idea**: Represents the valuation of a stock relative to its book value[20] - **Factor Construction Process**: - Formula: \( \text{BP} = \text{Net Assets} / \text{Market Capitalization} \)[20] - **Factor Evaluation**: Consistently performs well in value-oriented strategies, particularly in markets favoring undervalued stocks[42][43] 4. Factor Name: Three-Month Institutional Coverage - **Factor Construction Idea**: Measures the level of analyst coverage over the past three months[20] - **Factor Construction Process**: - Formula: Count of research reports published by institutions over the past three months[20] - **Factor Evaluation**: Strongly correlated with market sentiment and stock visibility, often leading to positive price momentum[8][46] --- Factor Backtesting Results 1. Trend Factor - **Recent Weekly Return**: 2.39% - **Recent Monthly Return**: 5.57% - **Year-to-Date Return**: -0.70% - **Annualized Return (1 Year)**: 24.36% - **Annualized Return (10 Years)**: 14.25%[11][13] 2. Volatility Factor - **Recent Weekly Return**: -1.75% - **Recent Monthly Return**: -3.95% - **Year-to-Date Return**: 4.10% - **Annualized Return (1 Year)**: 24.26% - **Annualized Return (10 Years)**: -13.16%[11][13] 3. BP Factor - **Recent Weekly Return**: 0.68% - **Recent Monthly Return**: 0.06% - **Year-to-Date Return**: -4.33% - **Annualized Return (1 Year)**: -1.51% - **Annualized Return (10 Years)**: -0.61%[42][43] 4. Three-Month Institutional Coverage Factor - **Recent Weekly Return**: 1.70% - **Recent Monthly Return**: 1.29% - **Year-to-Date Return**: 4.96% - **Annualized Return (1 Year)**: 1.66% - **Annualized Return (10 Years)**: 4.39%[46][48]

Group 1 - The core view of the report indicates that the Sci-Tech Innovation Board is expected to accelerate its rise, with a shift in leading sectors towards technology. The index is anticipated to continue its upward trend without significant resistance, as evidenced by the recent increases in major indices: Shanghai Composite Index up 1.67%, ChiNext Index up 2.76%, and Sci-Tech 50 Index up 4.63% [2][13]. - There is an imminent change in the leading structure of industries and themes. Last week, the leading sectors included construction materials (up 8.2%), coal (up 8.0%), steel (up 7.7%), and non-ferrous metals (up 6.7%), driven by themes such as "anti-involution" and hydropower station developments. However, the report suggests that the current phase of rapid price increases may be nearing its end, and market expectations for policy announcements may not exceed optimistic forecasts [3][14]. - The technology sector is expected to become the main focus of attention as the rapid rise of cyclical sectors comes to an end. The report emphasizes that technology will be the main line of the upcoming market trends [4][15]. Group 2 - The report maintains a positive outlook on artificial intelligence (AI) as a key theme, predicting significant marginal changes in the AI industry over the next 1-2 months. The release of new models, such as OpenAI's GPT-5, is expected to stimulate competition and drive growth in the sector [5][16]. - Within the AI theme, the report highlights strong potential in domestic computing power, AI applications, PCB-related sectors, and robotics. It argues that domestic computing power is crucial for national development and will likely receive continued policy support. AI applications are expected to gain traction as new models are released, while the PCB sector remains in an upward trend. Robotics, as a significant application of AI, is also projected to follow the growth of the AI sector [6][17][18].

Investment Rating - The report maintains a "Positive" investment rating for the defense and military industry [5]. Core Viewpoints - The integrated combat system of China is expected to rapidly open up the market, with military trade likely to continue increasing [16][17]. - In Q2 2025, active funds have significantly increased their overweight position in the military sector, with expectations for further increases focusing on military trade and new combat directions [21]. - The current market position remains optimistic for the military sector, with upstream components and key materials expected to benefit from demand amplification effects [22]. Summary by Sections 1.1 Military Trade and Equipment Strength - The Weapon Industry Group showcased China's military trade capabilities in unmanned and counter-unmanned systems, indicating a growing demand for military trade [9][16]. - The demonstration included various advanced equipment such as the BZK-005E drone and the Tianlong 100 air defense missile system, highlighting the capabilities of China's integrated combat system [17][18]. 1.2 Fund Allocation Trends - In Q2 2025, the overweight position of active funds in the military sector increased to 0.92 percentage points, up from 0.57 percentage points in Q1 2025, indicating a growing confidence in military trade and new combat technologies [21][22]. - The report suggests that the market's understanding of the marginal elasticity of military trade is still insufficient, with potential for performance releases to strengthen military trade logic [21]. 1.3 Current Market Outlook - The military sector has shown positive performance since July, with many sub-sectors still at low levels, suggesting significant configuration value [22]. - The report emphasizes the importance of upstream components and key materials in weapon development and production, which are expected to benefit from increased demand [22]. Appendix: Market Performance and News - The defense and military industry index rose by 1.28% but underperformed compared to the broader market indices [24]. - Key military companies have reported significant growth in their half-year earnings, with many companies showing rapid increases in net profits [44].

Investment Rating - The report maintains a "Positive" outlook for the pharmaceutical and biotechnology industry in China [6]. Core Insights - Small nucleic acid drugs are expected to become the third major class of drugs after small molecules and antibodies, with unique advantages such as broad targets, strong specificity, high development efficiency, and long dosing intervals [9][38]. - The commercialization of rare diseases is maturing, and the long-term advantages for chronic diseases are becoming evident, with significant sales growth for products like Spinraza and Leqivo [9][60]. - There is a notable increase in business development (BD) activities, highlighting the potential of early-stage chronic disease pipelines [9]. Summary by Sections 1. Small Nucleic Acids: Potential as a New Drug Class - Small nucleic acid drugs, including ASO, siRNA, and Aptamer, interact with mRNA to regulate gene expression, offering a new technological pathway for drug development [13]. - The global market for small nucleic acid drugs has grown from $1.04 billion in 2017 to $5.09 billion in 2024, with a CAGR of 25.5% [60]. 2. Milestones in Overseas and Domestic Markets - In the overseas market, significant developments are expected in the TTR field and cardiovascular diseases, with drugs like Vutrisiran and Pelacarsen showing promise [9]. - In China, new therapies for chronic hepatitis B and competitive advancements in cardiovascular drugs are emerging, with several companies making progress in their pipelines [9][60]. 3. Investment Recommendations and Targets - The report suggests focusing on high-quality domestic companies involved in the development of small nucleic acid drugs targeting chronic hepatitis B and cardiovascular diseases, such as HengRui Medicine, China National Pharmaceutical Group, and others [9].

Investment Rating - The industry investment rating is maintained at "Neutral" [7] Core Insights - The issuance of new operational licenses for L4 level autonomous driving in Shanghai is expected to accelerate the commercialization of Robotaxi services, benefiting companies in the related supply chain [2][4] - The first batch of eight companies authorized for operation includes major players such as Baidu and SAIC, indicating a significant step towards the integration of autonomous vehicles into urban transportation [2][4] - The report highlights that the successful rollout of Tesla's Robotaxi service in the U.S. is likely to create a positive ripple effect in the domestic Robotaxi market, potentially speeding up its development [7] Summary by Sections Industry Overview - The report discusses the recent developments in the autonomous driving sector, particularly focusing on the issuance of operational licenses in Shanghai for L4 level autonomous vehicles [2][4] - It emphasizes the collaboration between intelligent driving companies and traditional taxi services to facilitate the integration of Robotaxi into existing transportation systems [7] Investment Recommendations - Recommended stocks for investment include: - Automakers: SAIC Motor (600104, Buy), Changan Automobile (000625, Buy) - Parts suppliers: Huayu Automotive (600741, Buy), Desay SV (002920, Buy) [4] - The report suggests that companies receiving operational licenses will be direct beneficiaries, and the overall automotive intelligence process is expected to accelerate [4] Market Expectations - The report notes that market expectations for domestic Robotaxi services are currently low, but advancements in technology and regulatory frameworks are anticipated to enhance commercialization efforts [7] - It predicts that by 2027, Shanghai aims to achieve significant milestones in L4 level autonomous driving, including over 6 million passenger trips and 80,000 TEU of cargo [7]

Investment Rating - The report maintains a "Buy" rating for the company with a target price of 39.36 CNY [5][2] Core Views - The company has completed a share buyback, indicating confidence in future growth prospects, with a total of 3.9865 million shares repurchased, accounting for 0.47% of total shares, at a total cost of 100 million CNY [9] - The company aims to enhance the value of its robotic joint module products, expecting to replicate the growth path seen in its new energy thermal management segment [9] - The overseas business is projected to continue growing, with Q1 2025 foreign sales accounting for over 25% of total revenue, and efforts to achieve profitability in European operations [9] Financial Forecasts and Investment Recommendations - Adjusted EPS forecasts for 2025-2027 are 1.23 CNY, 1.63 CNY, and 2.04 CNY respectively, with a comparable company PE average of 32 times for 2025 [2] - Revenue projections for 2023A to 2027E are 11,018 million CNY, 12,702 million CNY, 15,278 million CNY, 18,143 million CNY, and 21,502 million CNY, reflecting a growth rate of 29.9%, 15.3%, 20.3%, 18.8%, and 18.5% respectively [4] - Operating profit is expected to grow from 816 million CNY in 2023A to 2,201 million CNY in 2027E, with corresponding growth rates of 67.7%, 23.6%, 31.2%, 32.6%, and 25.4% [4] - The net profit attributable to the parent company is forecasted to increase from 612 million CNY in 2023A to 1,704 million CNY in 2027E, with growth rates of 59.7%, 28.0%, 30.7%, 32.6%, and 25.4% [4]

Investment Rating - The industry investment rating is "Positive (Maintain)" [5] Core Insights - AI applications are gradually entering the implementation phase, with the commercialization of AI Agent applications expected to accelerate across various fields [3] - The collective rise of domestic models in China is effectively boosting investor confidence, as recent developments show significant advancements in open-source models [8] - The core focus of model iterations is on programming and Agent capabilities, which are crucial for the practical application of AI [8] - The acceleration of AI application commercialization is evident, with major internet companies and enterprise service providers enhancing their core products with AI [8] Summary by Sections Industry Overview - The report highlights the rapid development of domestic AI models, with notable achievements in open-source rankings [8] - Key players in the AI space are focusing on enhancing programming and Agent capabilities, which are essential for future AI applications [8] Market Trends - The report notes a significant increase in AI-related activities, with companies like Google and ByteDance reporting substantial growth in their AI services [8] - The domestic AI application cycle is slightly lagging behind the US, but the iteration of domestic models is expected to accelerate the rollout of various Agent applications [8] Investment Recommendations - Recommended companies in the enterprise service sector include Dingjie Zhizhi, Tax Friend Co., and Fanwei Network, among others [8] - Companies with strong advantages in vertical industry applications include Tuolisi, iFlytek, and Jiao Dian Technology [8] - For AI tool applications, companies such as Zhuoyi Information and Hongsoft Technology are highlighted as potential investment opportunities [8]

Investment Rating - The report maintains a "Positive" investment rating for the non-ferrous and steel industry [5] Core Viewpoints - The report argues that the value reassessment of the strategic metals sector has just begun, contrary to some investors' belief that the recent rapid price increases indicate an impending peak [8][14] - It highlights three dimensions supporting this view: policy measures against strategic mineral smuggling, a tight supply-demand balance driving product prices up, and an increase in risk appetite due to political policy risk premiums [8][14][17] Summary by Sections Strategic Metals - Some investors believe the recent surge in strategic metals prices is unsustainable and may soon peak [8][13] - The report counters this by stating that the value reassessment of strategic metals is just beginning, driven by macroeconomic inflation, tight supply-demand dynamics, and political risk premiums [14][17] - Policy measures to combat strategic mineral smuggling are expected to be reinforced, particularly for rare earths and other strategic metals [15] - The supply-demand balance remains tight, with increasing demand from sectors like new energy vehicles and offshore wind power, leading to rising prices for rare earths [16] - Political policy risk premiums are expected to rise, enhancing the attractiveness of the strategic metals sector [17] Steel Industry - Steel prices are anticipated to continue rising due to production cut expectations [18] - Steel demand and production have decreased, but a dynamic balance in supply and demand is expected [18][25] - Inventory levels are showing differentiation among various steel products, with total inventory likely to decline further [25] - Cost increases in raw materials are pushing steel prices up, with profits for steel mills expected to recover [28] - The overall steel price index has seen a slight increase, with specific products like hot-rolled steel showing notable price rises [35] New Energy Metals - Lithium production in June 2025 saw a significant year-on-year increase of 20.95%, indicating strong supply growth [40] - The demand for new energy vehicles remains robust, with production and sales in June 2025 showing substantial growth [44] - Prices for lithium and cobalt have generally risen, while nickel prices have seen a decline [49][50] Industrial Metals - Global refined copper production has increased, with supply slightly better than expected [57] - The demand outlook is improving, with manufacturing activity expected to continue recovering [69]