Investment Rating - The report assigns a "Cautious Accumulate" rating to the company [1][24]. Core Insights - The AI ASIC server and Ethernet switch markets are experiencing high demand, positioning the company favorably for rapid revenue growth as projects enter mass production. The transition to ODM is expected to enhance profitability, with profit growth outpacing revenue growth [2][9]. Financial Summary - The company’s projected revenue for FY2023 to FY2027 is as follows: - FY2023: $7,961 million - FY2024: $9,646 million (+21%) - FY2025: $11,630 million (+21%) - FY2026: $14,568 million (+25%) - FY2027: $16,917 million (+16%) [4][16] - Adjusted net profit is projected to grow significantly, with estimates of $296 million in FY2023, $461 million in FY2024, $635 million in FY2025, $819 million in FY2026, and $940 million in FY2027 [4][16]. Business Segments - The company operates in two main segments: Connectivity & Cloud Solutions (CCS) and Advanced Technology Solutions (ATS). The CCS segment includes server and storage businesses, while ATS encompasses aerospace, defense, industrial, and medical technology [26][30]. - Revenue from the ATS segment is expected to grow steadily, while the CCS segment is anticipated to see rapid growth driven by AI demand, particularly in 400G and 800G switches [18][19]. Market Position - The company is a leading player in the EMS and ODM sectors, with a strong focus on high-value end markets. It has a robust project pipeline in AI ASIC and Ethernet switches, which are expected to drive future growth [26][30]. - The company has established a solid customer base, including major clients like Amazon, Dell, and Google, with a significant portion of revenue derived from top customers [30][35]. Valuation - The report employs a DCF valuation method, estimating a target price of $202 per share, corresponding to a market capitalization of $23.4 billion [24][25]. - The company’s PEG ratio is calculated at 1.4, reflecting its strong earnings growth relative to peers in the EMS and ODM industries [22][24].

Trading Activity - The average daily trading volume on the Beijing Stock Exchange (BSE) decreased by 5.30% to 23.773 billion yuan compared to the previous week[1] - The average turnover rate for the BSE was 26.75% during the week[7] - The BSE's trading volume accounted for 1.40% of the total market, remaining stable compared to the previous week[11] Market Indices - The North Exchange 50 Index rose by 1.56% during the week, continuing its narrow fluctuations since reaching a year-to-date high on May 21[14] - Other indices such as the Sci-Tech 50 and the CSI 1000 also saw increases of 0.65% and 2.51% respectively[13] Sector Performance - Among the 24 sectors on the BSE, 13 sectors, including petrochemicals, had a positive median increase, while 10 sectors, including transportation, had negative median changes[21] - The petrochemical sector led with a median increase of 5.01%, while the transportation sector had a median decrease of -3.55%[21] Individual Stock Performance - 51.85% of the 270 stocks listed on the BSE saw price increases, with Huami New Materials leading with a rise of 33.97%[28] - Conversely, *ST Guandao experienced a significant drop of -22.31%[28] New Listings and IPOs - Two new stocks were offered for subscription, and one stock was listed during the week[38] - The newly listed stock, Youli Intelligent, saw a first-day price increase of 271.09% compared to its issue price[41] New Third Board Activity - The trading volume on the New Third Board increased by 35.45% compared to the previous week, with a total of 6,026 listed companies[34] - The trading amounts for the innovation layer and basic layer were 1.411 billion yuan and 213 million yuan respectively, showing a decrease of 38.87% and 16.44%[35]

Investment Rating - The report maintains a positive outlook on the construction materials industry, particularly in the context of infrastructure projects in the western regions and the recovery of the real estate market in Beijing [2][4][5]. Core Insights - The report highlights the increasing confidence in infrastructure projects in Xinjiang and Tibet following the commencement of the Yaxia Hydropower Station, with significant funding sources from state-owned enterprises and local governments [2][3][27]. - The real estate policies in Beijing are expected to catalyze a recovery in the consumption of building materials, with indicators suggesting that the market is nearing a bottom [4][5][19]. - The report emphasizes the potential for price stabilization and recovery in the cement industry due to supply-side adjustments and reduced competition among companies [6][30][31]. Summary by Sections Infrastructure and Cement - The establishment of the Xinjiang-Tibet Railway Company is expected to enhance the focus on infrastructure projects in these regions, which are characterized by strong internal demand and stable funding sources [2][3][27]. - Upcoming projects like the China-Kyrgyzstan-Uzbekistan Railway and others are anticipated to drive demand for cement, with companies in the region such as Qingsong Jianhua and Tibet Tianlu gaining attention [3][27]. - The report notes that the supply reduction in the cement industry, particularly in North China, is expected to improve the supply-demand balance and support price recovery [6][28][30]. Real Estate and Consumption Building Materials - Recent policy changes in Beijing are set to boost the real estate market, which is crucial for the consumption of building materials, indicating a potential recovery in sales and construction starts [4][5][19]. - The report suggests that the consumption building materials sector is nearing a recovery phase, with expectations of improved revenue performance starting in Q3 2025 [5][20]. - Companies like Dongfang Yuhong and Rabbit Baby are highlighted for their strong market positions and expected profitability improvements [21][22]. Glass and Other Materials - The report discusses the challenges faced by the float glass industry, including price declines and increased environmental regulations, which may lead to further consolidation and operational adjustments [37][38]. - The photovoltaic glass segment is experiencing a decline in inventory and a slight increase in new order prices, indicating a potential recovery in this market as well [45]. Individual Company Updates - Huaxin Cement is projected to achieve significant profit growth in 2025, driven by improved operational efficiency and market conditions [35]. - Xinyi Glass is expected to maintain a competitive edge in the automotive glass sector, with stable profit margins despite market fluctuations [40]. - The report also notes that companies like Qibin Group and Dongpeng Holdings are well-positioned to benefit from the anticipated recovery in the construction materials market [25][26].

风险偏好改善支撑全球权益配置价值 [Table_Authors] 方奕(分析师) 国泰海通资产配置月度方案（202508） 本报告导读： 我们认为市场后续表现将继续由风险偏好变化主导，当下风险资产具备更高的战术 性配置价值，8 月维持对 A 股和美股的战术性超配观点。 投资要点： 总量研究 /[Table_Date] 2025.08.11 | | 021-38031658 | | --- | --- | | | fangyi2@gtht.com | | 登记编号 | S0880520120005 | | | 李健(分析师) | | | 010-83939798 | | | lijian8@gtht.com | | 登记编号 | S0880525070013 | | | 王子翌(分析师) | | | 021-38038293 | | | wangziyi@gtht.com | | 登记编号 | S0880523050004 | [Table_Report] 相关报告 | 一页纸精读行业比较数据：3 月 2025.03.28 | | --- | | 行业比较-数据月报－价格链-25 年 3 月 | | 2025. ...

Investment Rating - The report maintains a "Buy" rating for the company [4][11]. Core Insights - The company demonstrated steady growth in Q2, with an increase in profit margins and an upgrade in AI capabilities enhancing the smart home product experience [1][11]. - Revenue for the first half of 2025 reached 2.827 billion yuan, a year-on-year increase of 9.45%, with net profit attributable to the parent company at 302 million yuan, up 7.38% year-on-year [11]. - The company is expected to achieve earnings per share (EPS) of 0.77, 0.98, and 1.21 yuan for 2025, 2026, and 2027 respectively, with growth rates of +10.4%, +12.1%, and +13.7% [11]. Financial Summary - Total revenue projections are as follows: - 2023A: 4.841 billion yuan - 2024A: 5.442 billion yuan - 2025E: 5.972 billion yuan - 2026E: 7.061 billion yuan - 2027E: 8.039 billion yuan - Net profit (attributable to the parent) is projected as: - 2023A: 563 million yuan - 2024A: 504 million yuan - 2025E: 610 million yuan - 2026E: 772 million yuan - 2027E: 951 million yuan [3][12]. Business Segmentation - In H1 2025, the smart home camera segment generated 1.547 billion yuan in revenue, a 7.2% increase, accounting for 55% of total revenue [11]. - The smart entry segment achieved 436 million yuan in revenue, a 33% increase, representing 16% of total revenue [11]. - The IoT cloud platform contributed 555 million yuan, growing 12% year-on-year, making up 19.7% of total revenue [11]. Market Position - The company’s overseas business saw a revenue growth of 25.42% in H1 2025, increasing its share of total revenue to 38% [11]. - The report anticipates that as the company continues its overseas expansion, the proportion of international revenue will keep rising [11].

Investment Rating - The report assigns an "Accumulate" rating for the humanoid robot industry [4]. Core Viewpoints - The 2025 World Robot Expo has significantly improved in scale and product quality compared to previous years, marking a critical turning point for the commercialization of the humanoid robot industry [2][4]. - Short-term focus should be on industry sentiment fluctuations driven by events, while long-term attention should be on high-quality companies with certainty in the supply chain, recommending companies such as Xinquan Co., Ningbo Huaxiang, Top Group, Zhaomin Technology, and Junsheng Electronics [4]. Summary by Sections - **Event Overview**: The 2025 World Robot Conference opened in Beijing, featuring over 200 domestic and international robot companies with more than 1,500 exhibits, including over 100 new product launches [2][4]. - **Exhibition Insights**: The number of humanoid robot manufacturers participating reached a record high, showcasing a variety of humanoid robots and robotic dogs, indicating a maturation of the industry [4]. - **Product Pricing**: Many manufacturers began to display product prices ranging from tens of thousands to millions of yuan, reflecting increased confidence in product competitiveness and a response to intensified price competition [4]. - **Price Trends**: The pricing structure shows a clear gradient from industrial to commercial to research modification robots, with examples such as the SA02 robot priced at 38,500 yuan and the Walker S1 at 1 million yuan, indicating a trend towards lower prices as commercialization scales up [4]. - **Company Performance Forecasts**: The report includes performance forecasts and financial valuations for several companies, all rated as "Accumulate," with projected EPS and PE ratios indicating growth potential [5].

Quantitative Factors and Models Summary Quantitative Factors and Construction Process - **Factor Name**: Intraday Skewness Factor **Construction Idea**: This factor captures the skewness of intraday stock returns, reflecting the asymmetry in return distribution[13][16][18] **Construction Process**: The factor is calculated based on the third moment of intraday return distribution, normalized by the cube of standard deviation. The detailed methodology is referenced in the report "Stock Selection Factor Series Research (19) - High-Frequency Factors on Stock Return Distribution Characteristics"[13][16][18] - **Factor Name**: Downside Volatility Proportion Factor **Construction Idea**: This factor measures the proportion of downside volatility in the total realized volatility of a stock[18][19][20] **Construction Process**: The factor is derived by decomposing realized volatility into upside and downside components. The methodology is detailed in the report "Stock Selection Factor Series Research (25) - High-Frequency Factors on Realized Volatility Decomposition"[18][19][20] - **Factor Name**: Post-Open Buying Intention Proportion Factor **Construction Idea**: This factor quantifies the proportion of buying intention in the early trading period after market open[22][23][24] **Construction Process**: The factor is constructed using high-frequency data to identify and aggregate buying signals in the post-open period. The methodology is detailed in the report "Stock Selection Factor Series Research (64) - Low-Frequency Applications of High-Frequency Data Based on Intuitive Logic and Machine Learning"[22][23][24] - **Factor Name**: Post-Open Buying Intensity Factor **Construction Idea**: This factor measures the intensity of buying activity in the early trading period after market open[27][28][29] **Construction Process**: Similar to the proportion factor, this factor aggregates the magnitude of buying signals during the post-open period, normalized by trading volume[27][28][29] - **Factor Name**: Post-Open Large Order Net Buying Proportion Factor **Construction Idea**: This factor captures the proportion of large order net buying in the early trading period after market open[32][34][35] **Construction Process**: The factor is calculated by summing the net buying of large orders during the post-open period and dividing by total trading volume[32][34][35] - **Factor Name**: Post-Open Large Order Net Buying Intensity Factor **Construction Idea**: This factor measures the intensity of large order net buying in the early trading period after market open[37][39][40] **Construction Process**: The factor aggregates the net buying of large orders during the post-open period, normalized by the total number of large orders[37][39][40] - **Factor Name**: Improved Reversal Factor **Construction Idea**: This factor captures the reversal effect in stock returns, adjusted for high-frequency data characteristics[40][43][44] **Construction Process**: The factor is constructed by identifying stocks with extreme short-term returns and measuring their subsequent reversal performance[40][43][44] - **Factor Name**: Deep Learning Factor (Improved GRU(50,2)+NN(10)) **Construction Idea**: This factor leverages a deep learning model combining GRU and neural networks to predict stock returns[63][65][66] **Construction Process**: The model uses 50 GRU units and 10 neural network layers, trained on historical high-frequency data to predict short-term stock returns[63][65][66] - **Factor Name**: Deep Learning Factor (Residual Attention LSTM(48,2)+NN(10)) **Construction Idea**: This factor employs an LSTM model with residual attention mechanisms to enhance prediction accuracy[65][66][68] **Construction Process**: The model uses 48 LSTM units and 10 neural network layers, incorporating residual connections to capture long-term dependencies in high-frequency data[65][66][68] - **Factor Name**: Multi-Granularity Model Factor (5-Day Label) **Construction Idea**: This factor predicts stock returns over a 5-day horizon using a multi-granularity deep learning model[68][69][70] **Construction Process**: The model is trained using bidirectional AGRU (Attention-Gated Recurrent Unit) to capture multi-scale temporal patterns in stock data[68][69][70] - **Factor Name**: Multi-Granularity Model Factor (10-Day Label) **Construction Idea**: Similar to the 5-day label factor, this factor predicts stock returns over a 10-day horizon[69][70][71] **Construction Process**: The model uses the same AGRU architecture as the 5-day label factor but is trained with a 10-day prediction horizon[69][70][71] Factor Backtesting Results - **Intraday Skewness Factor**: - IC: 0.024 (2025), 0.019 (historical) - e^(-RankMAE): 0.327 (2025), 0.324 (historical) - Long-Short Return: 16.90% (2025 YTD), -0.66% (last week) - Long-Only Excess Return: 1.84% (2025 YTD), -0.79% (last week)[9][10][13] - **Downside Volatility Proportion Factor**: - IC: 0.020 (2025), 0.016 (historical) - e^(-RankMAE): 0.325 (2025), 0.323 (historical) - Long-Short Return: 12.93% (2025 YTD), -1.19% (last week) - Long-Only Excess Return: -0.12% (2025 YTD), -1.07% (last week)[9][10][18] - **Post-Open Buying Intention Proportion Factor**: - IC: 0.026 (2025), 0.026 (historical) - e^(-RankMAE): 0.322 (2025), 0.321 (historical) - Long-Short Return: 13.98% (2025 YTD), 0.27% (last week) - Long-Only Excess Return: 7.20% (2025 YTD), 0.28% (last week)[9][10][22] - **Post-Open Buying Intensity Factor**: - IC: 0.029 (2025), 0.030 (historical) - e^(-RankMAE): 0.327 (2025), 0.326 (historical) - Long-Short Return: 18.53% (2025 YTD), 0.05% (last week) - Long-Only Excess Return: 7.09% (2025 YTD), 0.43% (last week)[9][10][27] - **Post-Open Large Order Net Buying Proportion Factor**: - IC: 0.027 (2025), 0.036 (historical) - e^(-RankMAE): 0.319 (2025), 0.322 (historical) - Long-Short Return: 18.25% (2025 YTD), 0.31% (last week) - Long-Only Excess Return: 9.48% (2025 YTD), 0.43% (last week)[9][10][32] - **Post-Open Large Order Net Buying Intensity Factor**: - IC: 0.019 (2025), 0.025 (historical) - e^(-RankMAE): 0.318 (2025), 0.321 (historical) - Long-Short Return: 10.50% (2025 YTD), 0.31% (last week) - Long-Only Excess Return: 7.08% (2025 YTD), 0.24% (last week)[9][10][37] - **Improved Reversal Factor**: - IC: 0.025 (2025), 0.031 (historical) - e^(-RankMAE): 0.331 (2025), 0.330 (historical) - Long-Short Return: 17.44% (2025 YTD), 0.12% (last week) - Long-Only Excess Return: 6.14% (2025 YTD), 0.33% (last week)[9][10][40] - **Deep Learning Factor (Improved GRU(50,2)+NN(10))**: - IC: 0.045 (2025), 0.066 (historical) - e^(-RankMAE): 0.335 (2025), 0.336 (historical) - Long-Short Return: 28.86% (2025 YTD), 1.36% (last week) - Long-Only Excess Return: 2.19% (2025 YTD), 0.06% (last week)[9][10][63] - **Deep Learning Factor (Residual

- The reversal factor performed relatively well, with the GARP portfolio achieving a weekly return of 3.28% from August 1, 2025, to August 8, 2025[1] - The cumulative return of the GARP portfolio in 2025 was 28.2%[1] - The PB-profit combination had a weekly return of 2.86%, with a cumulative return of 20.53% in 2025[5][9] - The small-cap growth portfolio had a weekly return of 4.87%, with a cumulative return of 56.37% in 2025[5][9] - The small-cap value preferred portfolio 1 had a weekly return of 3.67%, with a cumulative return of 48.10% in 2025[5][9] - The small-cap value preferred portfolio 2 had a weekly return of 5.00%, with a cumulative return of 56.61% in 2025[5][9] - The performance of the multi-factor portfolios showed that the aggressive portfolio and the balanced portfolio had weekly returns of 3.37% and 3.19%, respectively[10][11] - The aggressive portfolio and the balanced portfolio had cumulative returns of 61.10% and 49.08% in 2025, respectively[11] - The enhanced CSI 300 portfolio had a weekly return of 1.43%, with a cumulative return of 11.18% in 2025[14][15] - The enhanced CSI 500 portfolio had a weekly return of 2.17%, with a cumulative return of 14.96% in 2025[14][15] - The enhanced CSI 1000 portfolio had a weekly return of 2.01%, with a cumulative return of 22.07% in 2025[14][15] - The performance of the style factors showed that small-cap stocks outperformed large-cap stocks, and high-valuation stocks outperformed low-valuation stocks[5][43] - The performance of the technical factors showed that the reversal factor contributed positive returns, with a weekly long-short return of 0.98%[5][46][48] - The performance of the fundamental factors showed that the SUE factor and the expected net profit adjustment factor contributed positive returns, with weekly long-short returns of 0.51% and 0.34%, respectively[5][50][52]

Group 1: Current State of Long-term Funds in China - China's long-term funds, including social security and pension funds, have a significantly lower equity investment ratio compared to developed markets, with actual equity investment at only 12.8% against a policy cap of 25% for insurance funds[4] - The investment ratio of pension funds and enterprise annuities in equity assets is around 10%, well below the international average of 30%-50%[4] - The proportion of index-based investments, such as ETFs, in institutional portfolios is less than 15%, compared to 60% in the United States[4] Group 2: Policy Recommendations and Market Potential - The implementation of long-term assessment cycles and relaxation of investment restrictions could significantly increase the equity investment ratio of long-term funds in China[3] - The "Implementation Plan for Promoting Long-term Funds to Enter the Market" aims for public funds to increase their A-share holdings by at least 10% annually over the next three years, potentially adding over 100 billion yuan in long-term funds each year[15] - The report suggests enhancing product innovation and asset allocation systems to attract long-term funds, alongside tax incentives to encourage market entry[8] Group 3: Comparative Analysis with Developed Markets - In the U.S., long-term funds, particularly pension funds, have an equity investment ratio exceeding 80%, with a significant portion allocated to diversified assets like stocks and mutual funds[8] - European pension funds are increasing their equity allocations, focusing on long-term returns through diversified investments and strict regulations[8] - Japan's pension system, led by the Government Pension Investment Fund (GPIF), has become the largest public pension fund globally, emphasizing diversified and international investments[8]

Group 1 - The report indicates a potential small net inflow of northbound funds, estimating a net inflow of 3.3 billion yuan during the week of August 4-8, 2025, compared to a net outflow of 12.1 billion yuan the previous week [11] - The report highlights that the top active stocks in the northbound trading include Ningde Times with a total transaction amount of 9.4 billion yuan, accounting for 19% of the stock's trading volume for the week [11] - The report notes that flexible foreign capital estimated a net inflow of 1.8 billion yuan during the recent week, contrasting with a net outflow of 8.5 billion yuan the week before [11] Group 2 - The report states that a total of 14.8 billion Hong Kong dollars flowed into the Hong Kong stock market during the week of July 30 to August 5, 2025, with stable foreign capital outflow of 29.8 billion Hong Kong dollars and flexible foreign capital outflow of 3.2 billion Hong Kong dollars [18] - It mentions that the main inflows from southbound funds were observed in software and services, as well as retail sectors [23] - The report indicates that stable foreign capital primarily flowed into pharmaceuticals, biotechnology, and life sciences, while flexible foreign capital saw significant inflows into banks and materials [23] Group 3 - The report highlights that foreign capital saw a net outflow from the Japanese stock market amounting to 198 billion yen during the week ending July 28, 2025, compared to a net inflow of 688.9 billion yen the previous week [30] - It also notes that in July, overseas institutional investors withdrew 2.1 billion dollars from the Indian stock market, contrasting with a net inflow of 1.7 billion dollars the previous month [30] - The report states that since 2023, the cumulative net inflow into the Japanese stock market has reached 7.7 trillion yen [30] Group 4 - The report indicates that in the US stock market, global mutual funds saw a net inflow of 6.8 billion dollars in June 2025, reversing a net outflow of 13.3 billion dollars the previous month [37] - It mentions that in Europe, global mutual funds recorded net inflows into the equity markets of the UK, Germany, and France, amounting to 0.2 billion dollars, 19.8 billion dollars, and 17.8 billion dollars respectively [37] - The report highlights that since 2020, the cumulative net inflow into the US equity market has reached 730.9 billion dollars [37]