Report Industry Investment Rating No relevant content provided. Core Viewpoints of the Report - From July 14 - 18, 2025, the A - share market continued to rise, with the Shanghai Composite Index up 0.69%, the CSI 300 up 1.09%, the ChiNext Index up 3.17%, and growth style outperforming value style. Sectors such as optical modules, innovative drugs, and rare earths led the gains [1][12]. - Policy game may intensify. The July Politburo meeting is approaching, and "anti - involution" measures have become the focus, which may drive market enthusiasm in the short term [2][12]. - The technology chain has many catalysts. The AI industry is still in a high - prosperity stage, with the domestic model iteration accelerating and narrowing the gap with overseas advanced models. The restart of large companies' computing power expenditure may drive the computing power infrastructure and the entire AI industry chain [3][13]. - The valuation of innovative drugs is ahead. The valuation of innovative drugs is significantly advanced, making it difficult to make investment decisions based on company performance tracking. If future liquidity remains abundant, attention should be paid to the diversion effect of other thematic sectors [3][14]. - The China Securities A500 Free Cash Flow Index was officially launched on July 16, 2025, which provides a differentiated index selection [15]. Summary by Relevant Catalogs 1. Weekly Market Observation 1.1. Equity Market Review and Observation - **Market Performance**: From July 14 - 18, 2025, the A - share market continued to rise. The Shanghai Composite Index rose 0.69%, the CSI 300 rose 1.09%, the CSI 500 rose 1.20%, and the ChiNext Index rose 3.17%. The average daily trading volume of A - shares was 1546.2 billion, showing a month - on - month increase [12]. - **Policy and Economic Situation**: In the second - quarter economic data, although domestic demand indicators such as consumption and investment declined in June, the strong production side drove the GDP to grow by 5.2% year - on - year in the second quarter. The Central Urban Work Conference focused on old - city renovation and urban village renewal. The July Politburo meeting is approaching, and "anti - involution" measures may drive short - term market enthusiasm [12]. - **Technology Chain Catalysts**: In the technology chain, especially in the AI field, there were many positive events last week. The approval of the H20 chip for sale in China, the release of the Kimi K2 model, and the launch of ChatGPT Agent all indicate that the AI industry is in a high - prosperity stage. The restart of large companies' computing power expenditure may drive the industry chain [13]. - **Innovative Drugs**: The 11th batch of centralized procurement of drugs was announced, and the new rules left room for innovation. The valuation of innovative drugs is significantly advanced, and attention should be paid to the diversion effect of other sectors [14]. 1.2. Public Fund Market Dynamics - The China Securities A500 Free Cash Flow Index was officially launched on July 16, 2025. It selects 50 listed company securities with high free cash flow rates from the CSI A500 Index samples to reflect the performance of companies with strong cash - generating capabilities. It provides a differentiated index selection [15][16]. 2. Active Equity Fund Index Performance Tracking | Index Classification | Last Week | Last Month | Year - to - Date | Since Inception | | --- | --- | --- | --- | --- | | Strategy and Thematic | Active Equity Fund Selection | 3.42% | 6.55% | 14.46% | 15.39% | | Investment Style | Value Equity Fund Selection | 0.81% | 2.94% | 6.45% | 6.53% | | | Balanced Equity Fund Selection | 3.61% | 7.42% | 11.87% | 9.42% | | | Growth Equity Fund Selection | 4.96% | 9.19% | 22.90% | 11.85% | | Industry Thematic | Pharmaceutical Equity Fund Selection | 9.79% | 16.18% | 46.28% | 26.72% | | | Consumption Equity Fund Selection | - 1.42% | 1.34% | 8.82% | 1.81% | | | Technology Equity Fund Selection | 4.92% | 9.57% | 17.07% | 18.91% | | | High - end Manufacturing Equity Fund Selection | 4.14% | 8.82% | 7.49% | 2.30% | | | Cyclical Equity Fund Selection | 0.66% | 3.37% | 12.54% | 4.59% | Each sub - index has its own positioning and performance benchmark: - **Active Equity Fund Selection**: Select 15 funds each period, with equal - weight allocation. The core positions select funds based on performance competitiveness and style stability, and the style allocation is balanced according to the CSI Active Stock Fund Index. The performance benchmark is the Active Equity Fund Index (930980.CSI) [18]. - **Value Equity Fund Selection**: Select 10 funds with deep - value, quality - value, and balanced - value styles. The performance benchmark is the CSI 800 Value Index (H30356.CSI) [20]. - **Balanced Equity Fund Selection**: Select 10 relatively balanced and value - growth style funds. The performance benchmark is the CSI 800 (000906.SH) [20][22]. - **Growth Equity Fund Selection**: Select 10 growth - style funds. The performance benchmark is the 800 Growth Index (H30355.CSI) [23]. - **Pharmaceutical Equity Fund Selection**: Select 15 funds with a high proportion of pharmaceutical industry holdings. The performance benchmark is the Pharmaceutical Thematic Fund Index (fitted by Huabao Fund Research and Investment Platform) [24][27][28]. - **Consumption Equity Fund Selection**: Select 10 funds with a high proportion of consumption - related industry holdings. The performance benchmark is the Consumption Thematic Fund Index (fitted by Huabao Fund Research and Investment Platform) [28]. - **Technology Equity Fund Selection**: Select 10 funds with a high proportion of technology - related industry holdings. The performance benchmark is the Technology Thematic Fund Index (fitted by Huabao Fund Research and Investment Platform) [31]. - **High - end Manufacturing Equity Fund Selection**: Select 10 funds with a high proportion of high - end manufacturing industry holdings. The performance benchmark is the High - end Manufacturing Thematic Fund Index (fitted by Huabao Fund Research and Investment Platform) [31]. - **Cyclical Equity Fund Selection**: Select 5 funds with a high proportion of cyclical industry holdings. The performance benchmark is the Cyclical Thematic Fund Index (fitted by Huabao Fund Research and Investment Platform) [36].

Investment Rating - The report suggests a focus on leading domestic generative model companies such as iFlytek, AI hardware companies like Yingshi Network, Hongsoft Technology, and Hesai, as well as companies like Maifushi that can enhance paid rates and ARPU values through AI-related functionalities [2]. Core Insights - The current market is in a relatively chaotic phase, with mixed macroeconomic signals and varying investor expectations. There is an increasing willingness among users to adopt AI technologies, although their payment capabilities remain limited. The industry is expected to see a shift towards theme-based investments driven by risk preferences, with potential for long-term adoption and market recovery [12][10]. - The report identifies high-growth sectors for 2025, including AI computing power and lidar, while noting that AI applications are accelerating. Stable growth is expected in software outsourcing, financial IT, quantum computing, data elements, EDA, overseas expansion, and domestic innovation [12][10]. Summary by Sections Industry Perspective - The computer industry index increased by 2.12% from July 11 to July 18, 2025, outperforming the CSI 300 index by 1.03 percentage points [15]. - The report highlights the performance of various segments within the computer industry, indicating that AI computing power and lidar maintain high growth, while software outsourcing and financial IT are accelerating [10][12]. Key Events and Trends - Significant product launches include the Kimi K2 model with 1 trillion parameters and the AI imaging agent "RoboNeo" from Meitu, which aims to enhance image production efficiency for small businesses [12]. - The report anticipates that the second half of the year may yield better operational performance due to base effects, new technology/product launches, and policy implementations [12][10]. Sector Performance - The report categorizes various sectors based on their growth potential, with AI computing power and lidar maintaining high growth, while sectors like industrial software and medical IT are under pressure [13][10]. - The report emphasizes the importance of the upcoming AI Glasses Industry Innovation Application Summit and the World Artificial Intelligence Conference as key events to watch for investment opportunities [28][29].

Core Viewpoint - The Kimi K2 model has been released and open-sourced, marking a significant advancement in the competitive landscape of large models, especially in the context of recent releases from other companies like xAI and Google [2][40]. Model Release and Features - Kimi K2 includes two models: the base model Kimi-K2-Base and the fine-tuned model Kimi-K2-Instruct, both available for commercial use [4]. - The pricing for Kimi K2 is set at 16 RMB per million tokens output [2]. - The model achieved nearly 12,000 downloads within the first 20 minutes of its release [5]. Performance and Benchmarking - Kimi K2 has surpassed several open-source models, becoming the new state-of-the-art (SOTA) in open-source models, and has shown competitive performance against closed-source models like GPT-4.1 and Claude 4 Opus in various benchmarks [9]. - The model demonstrates strong capabilities in knowledge, mathematical reasoning, and coding tasks, with users noting its code generation abilities as a highlight [20][17]. Technical Innovations - Kimi K2 was trained on 15.5 trillion tokens and utilized the MuonClip optimizer, which enhances model stability and performance during training [24][28]. - The model incorporates a novel approach to data synthesis for tool interaction, generating high-quality training data through a comprehensive pipeline that simulates real-world tool usage scenarios [31][35]. Future Implications - The advancements in Kimi K2's architecture and training methods may set a new trend in the industry, focusing on algorithmic innovation rather than merely increasing parameters and computational power [43]. - The model's ability to self-evaluate and adapt in complex environments could be crucial for the future evolution of model intelligence [38][37].