Group 1 - The core viewpoint of the articles highlights the increasing interest of insurance capital in specific sectors and companies, particularly in regional banks and new productivity sectors, as indicated by their extensive research activities [1][2][3] - Since the beginning of 2026, over 300 A-share listed companies have been researched by insurance companies and asset management firms, with significant participation from 96 insurance companies and 32 asset management companies [2] - Key areas of focus for insurance capital include regional banks such as Shanghai Bank and Nanjing Bank, as well as sectors like electronic components, semiconductor materials, and devices [2][3] Group 2 - Insurance capital is increasingly favoring high-dividend stocks as a stable source of cash flow, particularly in a low-interest-rate environment, which drives the demand for equity assets [4] - The strategy of investing in high-dividend stocks is seen as a way to enhance returns and stabilize portfolios, with a focus on long-term holdings and dividend yields [4][5] - The shift towards high-dividend stocks is also a response to new accounting standards that increase profit statement volatility, making these investments more attractive [4] Group 3 - Insurance capital is aligning with the new productivity sector, which relies on technological innovation and strategic emerging industries, requiring long-term and stable capital support [5][6] - Investments are being directed towards technology leaders with clear business models and performance track records, while emerging tech sectors may be approached through industry-themed ETFs or funds to mitigate risks [6] - The focus on AI-driven technology and high-end manufacturing is expected to be central to future technological revolutions, with a commitment to direct investments in companies with strong competitive advantages [6]

【DW电子】精智达空间测算：CC和H的进展超预期，存储大周期的最大弹性设备股，空间上修到609亿 由于目前nand的可预见供需缺口之大，以及两存上市融资，拟对未来两存扩产量级进行上修，假设未来两存每年 各扩产6万片，存储测试机市场从60亿增加到80亿（6万片NAND，6万片DRAM，0.5万片HBM8层），公司预期两 存存储测试机收入40亿，净利率25%，利润10亿。 H存储测试机市场18亿 探针卡，一供美国企业9月份出现全球断供，精智达将从二供变成一供，两存每年15亿市场，70%份额，10亿收 入，10%净利率，1亿利润增量。 主业面板检测，每年稳定6-7亿收入，1.5亿利润。 GPU+SOC测试机，每年国内80亿市场，给公司30%份额，24亿收入，25%净利率，6亿利润。 合计总收入89.5亿，总利润20.3亿，30倍PE，609亿市值。 其中存储业务59亿收入，12.8亿利润，384亿市值；GPU+SOC测试机24亿收入，6亿利润，180亿市值；主业1.5亿 利润，45亿市值。 【DW电子】精智达空间测算：CC和H的进展超预期，存储大周期的最大弹性设备股，空间上修到609亿 由于目前nand的可预见供需 ...

Investment Rating - The industry investment rating is maintained as "Positive" [4] Core Insights - The demand for AI computing power is driving a persistent shortage in storage [2][8] - Major storage companies are experiencing strong performance, with AI demand expected to continue creating incremental opportunities [6] - The supply of niche storage is under pressure from mainstream storage, leading to a sustained tight supply situation [7] Summary by Sections Investment Recommendations and Targets - Key investment targets include domestic storage chip design companies such as Zhaoyi Innovation, Puran, Jucheng, Dongxin, Beijing Junzheng, and Hengsuo [2][8] - Domestic storage module manufacturers like Jiangbolong, Demingli, and Baiwei Storage are also highlighted [2] - Companies benefiting from storage technology iterations include Lanke Technology, Lianyun Technology, and Aojie Technology [2] - Semiconductor equipment firms such as Zhongwei Company, Jingzhida, and Beifang Huachuang are recommended [2] - Domestic packaging and testing companies like Shentek, Huicheng, and Tongfu Microelectronics are included in the investment targets [2] Market Dynamics - TrendForce has revised upward the price growth rates for DRAM and NAND Flash products for the first quarter, with DRAM contract prices expected to rise by 90-95% and NAND Flash by 55-60% [7] - AI computing demand is becoming the dominant factor in storage demand, with significant price increases anticipated for Server DRAM and Enterprise SSDs [7] - The AI inference process is expected to significantly alter data center storage structures, leading to increased demand for active data storage [7] Niche Storage Supply - Niche storage products like NOR Flash and MLC/SLC NAND Flash are expected to remain in tight supply due to reduced production from major suppliers focusing on mainstream products [7] - The global capacity for MLC NAND Flash is projected to decrease by 41.7% in 2026 due to supply constraints [7]

证券代码：688627 证券简称：精智达 公告编号：2026-004 深圳精智达技术股份有限公司 关于以集中竞价交易方式回购公司股份的进展公告 本公司董事会及全体董事保证本公告内容不存在任何虚假记载、误导性陈述 或者重大遗漏，并对其内容的真实性、准确性和完整性依法承担法律责任。 重要内容提示： | 回购方案首次披露日 | 2025/3/12 | | --- | --- | | 回购方案实施期限 | 待董事会审议通过后 12 个月 | | 预计回购金额 | 3,000万元~5,000万元 | | 回购用途 | □减少注册资本 √用于员工持股计划或股权激励 □用于转换公司可转债 | | | □为维护公司价值及股东权益 | | 累计已回购股数 | 56.9149万股 | | 累计已回购股数占总股本比例 | 0.61% | | 累计已回购金额 | 4,016.70万元 | | 实际回购价格区间 | 60.53元/股~75.19元/股 | 深圳精智达技术股份有限公司（以下简称"公司"）于 2025 年 3 月 10 日召 开第三届董事会第二十六次会议，审议通过了《关于以集中竞价交易方式回购公 司股份方案的议案》，同意公 ...

格隆汇2月2日丨精智达(688627.SH)公布，自2025年3月10日第三届董事会第二十六次会议审议通过《关 于以集中竞价交易方式回购公司股份方案的议案》之日起至2026年1月31日，公司通过上海证券交易所 交易系统以集中竞价交易方式已累计回购股份56.91万股，占公司总股本比例为0.61%，回购成交的最高 价为75.19元/股，最低价为60.53元/股，支付的资金总额为人民币4016.70万元(不含印花税、交易佣金等 交易费用)。 ...

Group 1 - The core point of the article highlights that Jingzhida (精智达) received the highest number of institutional research visits among listed companies, with 170 institutions conducting research during the last working week of January [1][2] - Jingzhida signed a significant sales contract worth 1.311 billion yuan (including tax) for semiconductor testing equipment, which has garnered considerable market attention [1][3] - The order is seen as a strong validation of the company's long-term investments and its solid market position, especially amid tight delivery schedules from international suppliers [3] Group 2 - In January, over 600 listed companies disclosed records of institutional investor research, with Dajin Heavy Industry (大金重工) receiving the most visits at 209 institutions [3][4] - The electronic and mechanical equipment sectors have shown high levels of interest from institutional investors, with these industries leading in the number of research visits [5] - The overall trend indicates a sustained enthusiasm for institutional research in the machinery and computer sectors, with a notable focus on electronic and mechanical equipment industries [5]

Group 1 - Institutional research enthusiasm remains high, particularly in the machinery and computer sectors, with electronics and machinery equipment industries leading in the number of institutions surveyed over the past five days [2][7] - From January 26 to January 30, Jingzhida received the most institutional surveys, totaling 170, following a significant contract signing worth 1.311 billion yuan for semiconductor testing equipment [3][5][6] - Over 600 companies have been surveyed by institutions this year, with Dajin Heavy Industry receiving the highest number of surveys at 209 [3] Group 2 - The top ten A-share companies by the number of institutional surveys this week include Jingzhida, which received 170 surveys, and Ninebot Company, which received 160 [5][9] - The machinery and electronics sectors have seen increased attention, with a notable focus on the semiconductor testing equipment market, highlighting Jingzhida's competitive position in the domestic supply chain [6][7] - Ninebot Company is focusing on electric motorcycles as a core growth driver, with sales of electric motorcycles surpassing electric bicycles since 2025, indicating a strong growth trend in the two-wheeler market [12]

Quantitative Models and Construction Methods 1. Model Name: Volume Timing Model - **Model Construction Idea**: The model uses volume-based timing signals to assess market sentiment and provide trading signals[23] - **Model Construction Process**: - The model evaluates the volume timing signals of major broad-based indices - Signals are categorized as "cautious" or "optimistic" based on volume trends - As of January 30, 2026, all major indices (e.g., SSE Composite Index, CSI 300, etc.) showed "cautious" volume timing signals[24] - **Model Evaluation**: The model provides a straightforward approach to gauge market sentiment but may lack granularity in capturing nuanced market dynamics[23][24] 2. Model Name: Momentum Sentiment Indicator - **Model Construction Idea**: This model identifies market sentiment by analyzing the proportion of stocks with positive returns in the CSI 300 Index over a specific period[24] - **Model Construction Process**: - The indicator is calculated as: $ \text{CSI 300 N-day Upward Stock Proportion} = \frac{\text{Number of CSI 300 stocks with positive returns over N days}}{\text{Total number of CSI 300 stocks}} $ - The indicator is smoothed using two moving averages with different window periods (N1 = 50, N2 = 35) to create a "fast line" and a "slow line" - A buy signal is generated when the fast line exceeds the slow line, and a neutral signal is generated when the fast line falls below the slow line[26][28] - **Model Evaluation**: The indicator is effective in capturing upward market opportunities but may fail to predict downturns accurately. It also tends to miss gains during prolonged market exuberance[25] 3. Model Name: Moving Average Sentiment Indicator - **Model Construction Idea**: This model uses an eight-moving-average system to assess the trend state of the CSI 300 Index and generate trading signals[32] - **Model Construction Process**: - Calculate the eight moving averages of the CSI 300 Index closing price with parameters: 8, 13, 21, 34, 55, 89, 144, and 233 - Assign values to the indicator based on the number of moving averages the current price exceeds: - If the price exceeds more than five moving averages, the sentiment is bullish - Generate a buy signal when the current price exceeds five moving averages[36] - **Model Evaluation**: The model provides a clear framework for trend analysis but may oversimplify complex market dynamics[36] --- Model Backtesting Results 1. Volume Timing Model - All major indices (e.g., SSE Composite Index, CSI 300, CSI 500, etc.) showed "cautious" volume timing signals as of January 30, 2026[24] 2. Momentum Sentiment Indicator - The CSI 300 N-day upward stock proportion indicator was above 60% as of January 30, 2026, indicating high market sentiment[25] - The fast line was above the slow line, suggesting a bullish outlook for the CSI 300 Index[26] 3. Moving Average Sentiment Indicator - The CSI 300 Index was in a "sentiment prosperity zone" as of January 30, 2026, indicating a bullish sentiment[36] --- Quantitative Factors and Construction Methods 1. Factor Name: Cross-sectional Volatility - **Factor Construction Idea**: Measures the dispersion of returns among index constituents to assess the Alpha environment[37] - **Factor Construction Process**: - Calculate the cross-sectional volatility of index constituents (e.g., CSI 300, CSI 500, CSI 1000) - Compare the recent quarter's average volatility to historical percentiles to evaluate the Alpha environment[38] - **Factor Evaluation**: The factor effectively captures short-term Alpha opportunities but may not fully reflect long-term trends[37] 2. Factor Name: Time-series Volatility - **Factor Construction Idea**: Measures the volatility of index constituents over time to assess the Alpha environment[38] - **Factor Construction Process**: - Calculate the time-series volatility of index constituents (e.g., CSI 300, CSI 500, CSI 1000) - Compare the recent quarter's average volatility to historical percentiles to evaluate the Alpha environment[41] - **Factor Evaluation**: The factor provides insights into market stability but may be less effective in highly volatile markets[38] --- Factor Backtesting Results 1. Cross-sectional Volatility - CSI 300: Recent quarter average volatility at 2.14%, in the 69.55th percentile of the past two years[38] - CSI 500: Recent quarter average volatility at 2.45%, in the 50.79th percentile of the past two years[38] - CSI 1000: Recent quarter average volatility at 2.61%, in the 66.93rd percentile of the past two years[38] 2. Time-series Volatility - CSI 300: Recent quarter average volatility at 0.96%, in the 57.20th percentile of the past two years[41] - CSI 500: Recent quarter average volatility at 1.22%, in the 50.79th percentile of the past two years[41] - CSI 1000: Recent quarter average volatility at 1.17%, in the 64.94th percentile of the past two years[41]

Core Insights - Institutional interest in listed companies remains high, particularly in the machinery and computer sectors, with electronic and machinery equipment industries leading in the number of institutional surveys conducted in the past five days [2][8] - Jingzhida received the highest number of institutional surveys this week, with 170 institutions participating, following a significant contract signing worth 1.311 billion yuan for semiconductor testing equipment [2][6] - Over 600 companies have been surveyed by institutions this year, with Dajin Heavy Industry being the most frequently surveyed company at 209 times [2][3] Company-Specific Insights - Jingzhida's recent contract for semiconductor testing equipment is seen as a major market validation of the company's long-term investments and technological positioning [6] - The company has established a strong competitive edge within the domestic supply chain, especially amid tight delivery schedules from international suppliers [6] - The survey results indicate a robust interest in Jingzhida, reflecting confidence in its market position and future growth potential [2][5] Industry Trends - The machinery and electronic sectors are experiencing heightened attention from institutional investors, with a notable increase in survey participation over the past month [8] - The overall trend shows that machinery, electronics, and biopharmaceuticals are among the most surveyed industries, indicating a shift in investor focus [8] - The electric motorcycle segment is gaining traction, with companies like Ninebot reporting strong sales growth and a strategic focus on this market segment [15]

算力芯片测试机：公司将加快高端算力芯片测试样机的推出。结合战略客户新品节奏，存算一体背景 下，公司预期今年将取得进一步进展。 以智能眼镜为代表的端侧AI布局：智能眼镜作为AI时代的重要入口，前景乐观。公司将调动全部产品 线打造端侧AI的一站式解决方案，包括存储测试、SoC测试、光学检测等。 格隆汇1月30日丨精智达(688627.SH)近日在电话会议中表示，ASIC芯片：公司已经在稳步推动下一代高 速测试产品的研发工作，确保公司在下一代存储技术测试领域的持续领先。 ...