东方证券研报指出，具身智能场景应用浪潮加速，永创智能机器人有望加速推进。人形机器人场景应用 正在加速，饮料/包装/分拣领域需求大，有望成为重要应用。此前市场更多关注工厂内搬运场景，而该 行认为饮料包装和分拣领域也有望成为人形机器人的重要落地场景，因为饮料食品快递包装的分拣工作 对人工数量需求大、劳动强度高，但任务简单且重复性高，可能更快催化机器人应用落地。永创是饮料 包装自动化设备的龙头供应商，更懂行业需求。市场认为初创人形机器人企业可能最早推出适配产品， 但该行认为具有行业积淀的设备企业具备优势，有望更快推进机器人落地。2025年来，公司重视人形机 器人研发，已经注册部分人形机器人专利，并分别成立多家子公司进行布局，我们认为永创有望较快推 进人形机器人产品落地。参考可比公司估值，给予2025年的34倍PE，对应目标价为13.26元，维持"买 入"评级。 ...

Group 1 - The company, Boshi Co., Ltd. (SZ 002698), announced that it will participate in a research meeting organized by Dongfang Securities Asset Management Co., Ltd. on August 1, 2025 [2] - The company's director and board secretary, Chen Bo, will be involved in the meeting and will respond to questions from investors [2]

Investment Rating - The report maintains an "Outperform" rating for the industry [3][5]. Core Insights - The overseas investment banks are increasingly participating in digital finance, with emerging models continuously surfacing. The focus is on the issuance and trading of digital assets, particularly Real World Assets (RWA), which signify a transformation of traditional investment banking into the digital finance realm. The RWA market has grown from approximately $5 billion in 2022 to about $25.2 billion by July 2025, indicating a shift from experimental stages to large-scale promotion [1][12]. - The RWA market is projected to reach $16 trillion by 2030, accounting for about 10% of global GDP, driven by factors such as rising global interest rates, institutional involvement in crypto assets, and improving regulatory policies [1][17]. Summary by Sections RWA: Bridging On-chain Funds and Real Assets - RWA represents tangible or traditional financial assets on blockchain networks, enhancing liquidity and enabling fractional ownership, thus democratizing access to previously high-barrier investments [12][16]. - The RWA market has seen rapid growth, with a total market size reaching $25.4 billion by mid-2025, driven by technological advancements and traditional financial institutions' involvement [12][13]. RWA Token Types and Development Momentum - The RWA token landscape includes various types, with U.S. Treasury tokens being a significant category due to their low-risk profile and established legal framework. The market for tokenized U.S. Treasuries grew from $100 million in January 2023 to $6.74 billion by July 2025 [22][23]. - Private credit tokens have emerged as the largest segment within RWA, with a market size of $15 billion as of July 2025, driven by their high yield and low correlation with other asset classes [27][28]. - Commodity tokens, particularly gold tokens, dominate the commodity tokenization market, which reached $1.75 billion by July 2025 [31][32]. Stock Tokens: Comparison of Tokenization Models - Stock tokenization is rapidly evolving, with platforms like Robinhood and xStocks offering different models. Robinhood's model is based on derivative contracts, while xStocks provides direct ownership representation through compliant third-party custodians [39][50]. - The largest stock token, EXOD, represents a company specializing in crypto wallets, with a market cap of approximately $277.1 million [41]. Investment Recommendations - The report suggests that Robinhood's approach to virtual asset-related business could serve as a reference for Chinese brokerage firms entering this space. The rapid development of RWA may catalyze further market activity in the brokerage sector, indicating potential for significant returns [3][4].

Investment Rating - The report maintains a positive outlook on the non-bank financial sector, indicating an "Overweight" rating for the insurance sector and a favorable view on the brokerage sector [1][2][59]. Core Insights - The insurance sector is expected to benefit from a decrease in new liability costs, an increase in the value of dividend insurance options, and a stabilization of long-term interest rates, leading to a positive performance outlook [2][3]. - The brokerage sector is facing intense competition, particularly in brokerage and investment banking services, but there is potential for improved profitability if fee competition stabilizes [2][3]. Summary by Sections Market Review - The Shanghai Composite Index closed at 4,054.93 with a decline of 1.8% during the week of July 28 to August 1, 2025. The non-bank index closed at 1,941.35, down 2.4% [5][11]. - The brokerage sector index fell by 3.2%, while the insurance sector index saw a slight decline of 0.1% [5][11]. Non-Bank Financial Insights - As of August 1, 2025, the 10-year government bond yield was 1.71%, showing a decrease of 0.87 basis points, while the credit spread for corporate bonds was 0.31% [11][14]. - The average daily trading volume in the stock market was 18,099.28 billion, reflecting a decrease of 2.11% week-on-week [14][33]. Key Company Announcements - China Pacific Insurance announced a capital increase of up to HKD 1.5 billion for its wholly-owned subsidiary in Hong Kong [20]. - New China Life Insurance plans to distribute a cash dividend of RMB 1.99 per share, totaling approximately RMB 6.21 billion [24]. Investment Analysis - The report recommends several stocks in the insurance sector, including China Life, China Pacific, and New China Life, based on their expected performance [2][3]. - For the brokerage sector, it suggests focusing on leading firms with strong competitive positions, such as GF Securities and CITIC Securities, as well as those with significant international business capabilities [2][3].

Quantitative Factors and Models Summary Quantitative Factors and Their Construction - **Factor Name**: Standardized Unexpected Revenue (SUR) - **Construction Idea**: Measures the deviation of actual revenue from analysts' expectations, standardized by the standard deviation of expected revenue[20][27][31] - **Construction Process**: $ SUR = \frac{Actual\ Revenue - Expected\ Revenue}{Standard\ Deviation\ of\ Expected\ Revenue} $ - The numerator represents the difference between actual and expected revenue - The denominator is the standard deviation of expected revenue, ensuring comparability across stocks[20][27][31] - **Evaluation**: Demonstrated strong performance across multiple indices, indicating its effectiveness in capturing unexpected revenue trends[8][27][31] - **Factor Name**: Delta ROA - **Construction Idea**: Tracks the year-over-year change in Return on Assets (ROA) to capture profitability trends[20][31][39] - **Construction Process**: $ \Delta ROA = ROA_{Current\ Quarter} - ROA_{Same\ Quarter\ Last\ Year} $ - ROA is calculated as $ \frac{Net\ Income}{Total\ Assets} $ - The factor highlights improvements or deteriorations in asset efficiency[20][31][39] - **Evaluation**: Consistently strong performance, particularly in small-cap indices like the CSI 1000 and CSI 2000, suggesting its relevance in growth-oriented stocks[8][39][43] - **Factor Name**: Standardized Unexpected Earnings (SUE) - **Construction Idea**: Similar to SUR, measures the deviation of actual earnings from analysts' expectations, standardized by the standard deviation of expected earnings[20][31][39] - **Construction Process**: $ SUE = \frac{Actual\ Earnings - Expected\ Earnings}{Standard\ Deviation\ of\ Expected\ Earnings} $ - The numerator captures the earnings surprise - The denominator ensures standardization for comparability[20][31][39] - **Evaluation**: Strong performance in indices like CSI 500 and CSI 800, indicating its ability to capture earnings surprises effectively[8][27][31] - **Factor Name**: Delta ROE - **Construction Idea**: Measures the year-over-year change in Return on Equity (ROE) to identify shifts in shareholder profitability[20][31][39] - **Construction Process**: $ \Delta ROE = ROE_{Current\ Quarter} - ROE_{Same\ Quarter\ Last\ Year} $ - ROE is calculated as $ \frac{Net\ Income}{Shareholders'\ Equity} $ - Highlights changes in equity efficiency over time[20][31][39] - **Evaluation**: Demonstrated strong performance in growth-oriented indices, particularly the CSI 1000 and Growth Enterprise Market (GEM) indices[8][39][43] Factor Backtesting Results - **Standardized Unexpected Revenue (SUR)** - CSI 500: Weekly return 1.43%, monthly return 1.66%, annualized return 12.83%[27] - CSI 800: Weekly return 1.36%, monthly return 2.61%, annualized return 4.26%[31] - CSI All Share: Weekly return 1.37%, monthly return 1.95%, annualized return 6.91%[47] - **Delta ROA** - CSI 1000: Weekly return 0.56%, monthly return 1.67%, annualized return 11.51%[35] - CSI 2000: Weekly return 1.90%, monthly return 1.90%, annualized return 27.67%[39] - CSI All Share: Weekly return 1.10%, monthly return 2.33%, annualized return 7.78%[47] - **Standardized Unexpected Earnings (SUE)** - CSI 500: Weekly return 1.39%, monthly return 2.75%, annualized return 7.19%[27] - CSI 800: Weekly return 0.52%, monthly return 1.33%, annualized return 3.04%[31] - CSI All Share: Weekly return 1.09%, monthly return 2.46%, annualized return 0.72%[47] - **Delta ROE** - CSI 1000: Weekly return 0.30%, monthly return 1.59%, annualized return 8.89%[35] - CSI 2000: Weekly return 1.24%, monthly return 1.21%, annualized return 90.84%[39] - GEM: Weekly return 1.03%, monthly return 2.76%, annualized return 21.85%[43] Quantitative Model Construction - **Model Name**: Maximized Factor Exposure (MFE) Portfolio - **Construction Idea**: Constructs portfolios that maximize exposure to a single factor while controlling for industry, style, and stock-specific constraints[62][63][66] - **Construction Process**: $ \begin{array}{ll} max & f^{T}w \\ 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} $ - Maximizes factor exposure $ f^{T}w $ - Constraints include style, industry, stock-specific deviations, and turnover limits[62][63][66] - **Evaluation**: Effective in isolating factor performance under realistic portfolio constraints, widely used in index enhancement strategies[62][63][66] Model Backtesting Results - **MFE Portfolio** - CSI 300: Weekly excess return max 1.67%, min -0.65%, median 0.21%[54] - CSI 500: Weekly excess return max 1.13%, min -0.76%, median 0.24%[57] - CSI 1000: Weekly excess return max 1.11%, min -0.52%, median 0.24%[61]

- The report discusses the dividend prediction model for the August contracts of the SSE 50, CSI 300, CSI 500, and CSI 1000 indices, with respective dividend points of 1.42, 2.59, 4.93, and 3.19[5][9] - The annualized hedging costs for the August contracts, excluding dividends and calculated on a 365-day basis, are -1.22% for SSE 50, 6.13% for CSI 300, 17.91% for CSI 500, and 19.73% for CSI 1000[5][9] - The report suggests that investors should pay attention to the short-term positive arbitrage opportunities in the SSE 50 index futures, given its current slight premium state and relatively low hedging cost[6][9] - For the CSI 300 index futures, the report advises investors to closely monitor the potential for discount recovery and the changes in hedging costs due to increased volatility, as it has shifted from a neutral to a moderate discount state[6][9] - The CSI 500 and CSI 1000 index futures are currently in a deep discount state, with significantly expanded discount margins compared to the previous period. The report recommends that investors with arbitrage execution capabilities and risk management experience consider participating in the phase discount arbitrage opportunities for these small and mid-cap index futures[6][9] - The dividend prediction process involves estimating the net profit of constituent stocks, calculating the pre-tax total dividend for each stock, determining the impact of dividends on the index, and predicting the impact of dividends on each contract[7][19][22] - The formula used to estimate the weight of each stock in the index is: $$ \mathrm{w_{it}={\frac{w_{i0}\times\mathrm{\scriptsize{\boldmath~(~1+R~)}~}}{\sum_{1}^{n}w_{i0}\times\mathrm{\scriptsize{\boldmath~(~1+R~)}~}}}} $$ where \( w_{i0} \) is the accurate weight of stock \( i \) on day \( t0 \), and \( R \) is the rate of change in the stock price from \( t0 \) to \( t \)[22] - The theoretical pricing model for stock index futures under discrete dividend distribution is: $$ F (S D)(1 r) t t = − + $$ where \( F_t \) is the futures price at time \( t \), \( S_t \) is the spot price, \( D \) is the present value of the dividend stream during the period \( T-t \), and \( r \) is the risk-free rate during the period \( T-t \)[28] - The theoretical pricing model for stock index futures under continuous dividend distribution is: $$ (r d)(T-t) t t F S e − = $$ where \( F_t \) is the futures price at time \( t \), \( S_t \) is the spot price, \( d \) is the annualized dividend rate, and \( r \) is the annualized risk-free rate during the period \( T-t \)[29] Model Backtest Results - SSE 50 index futures (IH) August contract: actual spread -0.13, dividend-inclusive spread 1.29, annualized hedging cost -1.22%[1][10] - CSI 300 index futures (IF) August contract: actual spread -12.13, dividend-inclusive spread -9.53, annualized hedging cost 6.13%[1][11] - CSI 500 index futures (IC) August contract: actual spread -47.60, dividend-inclusive spread -42.67, annualized hedging cost 17.91%[1][12] - CSI 1000 index futures (IM) August contract: actual spread -53.67, dividend-inclusive spread -50.48, annualized hedging cost 19.73%[1][13]

Group 1 - The company, Ningbo Jintian Copper Industry (Group) Co., Ltd., issued 14.5 million convertible bonds with a total amount of 1.45 billion yuan, which will be traded on the Shanghai Stock Exchange starting from August 28, 2023 [1][2] - The initial conversion price of the bonds was set at 6.75 yuan per share, which was later adjusted to 6.63 yuan per share due to the company's annual equity distribution [2][3] - The conversion price was further adjusted to 5.90 yuan per share following a board resolution and will remain at this level until the next adjustment [3][4] Group 2 - The company has a conditional redemption clause for the convertible bonds, which allows redemption if the stock price exceeds 130% of the conversion price for a specified period [5] - The redemption condition was met as the stock price was above 7.53 yuan per share for fifteen trading days [5][6] - The company decided to exercise its right to redeem the convertible bonds early, with the redemption price being the face value plus accrued interest [6][7] Group 3 - The company’s major shareholders and executives did not trade the convertible bonds within six months prior to the redemption condition being met [6] - The sponsor institution, Dongfang Securities, confirmed that the redemption process complied with relevant regulations and internal procedures [7]

Group 1 - The core viewpoint of the article highlights the ongoing restructuring of brokerage branch layouts as firms aim to reduce costs and enhance efficiency, with over 20 brokerages having announced the closure of more than 60 branches by July 30 this year [2][3] - In July alone, three brokerages, including Founder Securities, announced the closure of their branches, with Founder Securities closing four branches, including its Henan branch [2][3] - The closures are primarily driven by high operational costs associated with physical branches, as well as a significant shift towards online trading platforms, which have become the mainstream mode of operation [3][5] Group 2 - Some brokerages are also actively expanding by opening new branches in regions with high business potential, such as the recent openings by Cheng Tong Securities and Wanlian Securities [5] - The restructuring of branch layouts is closely linked to the transformation towards wealth management, which is becoming increasingly important in the brokerage business model, contributing over 30% to brokerage income by 2024 [5][6] - Future adjustments in branch layouts are expected to focus on efficiency rather than scale, with a shift towards high-value, integrated service models, leveraging financial technology to enhance operations [6]

格隆汇8月1日｜东方证券研报指出，洽洽食品预计上半年归母净利润为8,000–9,750万元，同比下降约 71–76%，主因是原料采购价格大幅上涨带动毛利率下行。公司25Q1收入同比下降13.7%，反映出主力 品类动销放缓、渠道去库存延续。该行判断，公司当前主动压缩利润释放节奏，在保证终端投放与品牌 维护的前提下进行结构优化，为后续增长修复创造空间。考虑到原料端成本上行叠加主力品类出货节奏 偏慢，公司上半年利润显著下滑，我们修正了瓜子与坚果等核心品类的销售增速、新品导入的放量节奏 及毛利率改善幅度等关键假设。据此调整公司盈利预测，预计公司2025–2027年EPS分别为 1.25/1.42/1.67元（前次预测2025/2026年EPS为2.42/2.75元）。考虑公司在渠道端持续推进精耕、海外市 场具备中长期潜力，参考当前可比公司估值水平，给予公司2025年21倍PE，对应目标价26.25元，维 持"买入"评级。 ...

Core Viewpoint - The report from Dongfang Securities indicates a sustained high growth in overseas data center-related CAPEX since the first half of 2024, with upward revisions to future expectations driven by AI demand [1] Group 1: CAPEX Trends - Overseas CSPs have revised their CAPEX expectations upward, indicating an improving investment climate for data centers [1] - Microsoft, Google, and Meta have all increased their CAPEX forecasts for Q2 2025, with Meta raising its full-year CAPEX expectation to $66-72 billion (previously $64-72 billion) and Google adjusting its FY2025 CAPEX to $85 billion (previously $75 billion) [1] - Microsoft’s Q2 2025 CAPEX is projected at $24.2 billion, with expectations to exceed $30 billion in Q3 2025, reflecting a year-on-year growth of over 50% [1] Group 2: Importance of Power Supply - The transition from traditional computing to intelligent computing has led to significant increases in power consumption, necessitating advancements in AIDC power supply technology [2] - The importance of high efficiency, high density, and high stability power supplies is expected to continue rising as AI demand evolves [2] - The entire power supply chain, from grid power (10kV+) to final chip (<1V), is undergoing technological upgrades, enhancing the value of power systems in AIDC [2] Group 3: Export Opportunities - The overseas AIDC CSP cycle is leading, with AI power supply exports likely to be the first beneficiaries of the AI technology infrastructure wave [3] - High barriers to entry in the overseas AIDC power market favor companies like Delta and Vertiv, which possess strong technical and ecological advantages [3] - As domestic Chinese companies continue to close the technology gap with Taiwanese and foreign firms, they are expected to benefit from the overseas AICAPEX boom [3] Group 4: Investment Recommendations - Companies in the AIDC power sector that are likely to benefit from the improving overseas investment climate include Magpower (002851.SZ), Hewei Electric (603063.SH), Xinle Energy (300593.SZ), Tonghe Technology (300491.SZ), Oulu Tong (300870.SZ), and Zhongheng Electric (002364.SZ) [4] - In the AIDC power supply segment, key companies to watch include Jinpan Technology (688676.SH), Mingyang Electric (301291.SZ), Weiteng Electric (688226.SH), and Liangxin Co., Ltd. (002706.SZ) [4]