Core Viewpoint - Jiangbolong (301308) emphasizes its adherence to information disclosure and insider information management regulations, ensuring confidentiality of sensitive information such as performance data, which has not yet been disclosed [1] Group 1 - The company responds to investor inquiries on its interactive platform, reinforcing its commitment to confidentiality regarding undisclosed information [1] - The company clarifies that market behaviors are based on individual judgments and should not be improperly linked to undisclosed information [1]

证券代码：301308 证券简称：江波龙 公告编号：2026-006 深圳市江波龙电子股份有限公司 股东询价转让结果报告书 股东宁波龙熹一号自有资金投资合伙企业（有限合伙）、宁波龙乙自有资金 投资合伙企业（有限合伙）、宁波龙熹三号自有资金投资合伙企业（有限合伙）、 宁波龙舰自有资金投资合伙企业（有限合伙）、宁波龙熹五号自有资金投资合伙 企业（有限合伙）保证向本公司提供的信息内容不存在任何虚假记载、误导性陈 述或者重大遗漏，并对其真实性、准确性和完整性依法承担法律责任。 本公司及董事会全体成员保证公告内容与信息披露义务人提供的信息一 致。 重要内容提示： 1、本次参与深圳市江波龙电子股份有限公司（以下简称"江波龙"或"公司"） 首次公开发行前（以下简称"首发前"）股东询价转让的股东为宁波龙熹一号自有 资金投资合伙企业（有限合伙）（以下简称"龙熹一号"）、宁波龙乙自有资金投 资合伙企业（有限合伙）（以下简称"龙熹二号"）、宁波龙熹三号自有资金投资 合伙企业（有限合伙）（以下简称"龙熹三号"）、宁波龙舰自有资金投资合伙企 业（有限合伙）（以下简称"龙舰管理"）、宁波龙熹五号自有资金投资合伙企业 （有限合伙）（以下简 ...

中信证券股份有限公司 关于深圳市江波龙电子股份有限公司 股东向特定机构投资者询价转让股份的核查报告 深圳证券交易所： 中信证券股份有限公司（以下简称"中信证券"或"组织券商"）受委托担任宁波龙熹 一号自有资金投资合伙企业（有限合伙）（以下简称"龙熹一号"）、宁波龙乙自有资金 投资合伙企业（有限合伙）（以下简称"龙熹二号"）、宁波龙熹三号自有资金投资合伙 企业（有限合伙）（以下简称"龙熹三号"）、宁波龙舰自有资金投资合伙企业（有限合 伙）（以下简称"龙舰管理"）、宁波龙熹五号自有资金投资合伙企业（有限合伙）（以下 简称"龙熹五号"）（以下合称"转让方"）以向特定机构投资者询价转让（以下简称"询 价转让"）所持有的深圳市江波龙电子股份有限公司（以下简称"公司"或"江波龙"）首 次公开发行前已发行股份的组织券商。 经核查，中信证券就本次询价转让的股东、转让方是否符合《深圳证券交易所上市 公司自律监管指引第 16 号——创业板上市公司股东询价和配售方式转让股份（2025 年 修订）》（以下简称"《询价转让和配售指引》"）要求，本次询价转让的询价、转让过程 与结果是否公平、公正，是否符合《询价转让和配售指引》的规定作出 ...

Quantitative Models and Construction Methods 1. Model Name: 250-Day New High Distance Model - **Model Construction Idea**: This model tracks the distance of stock prices or indices from their 250-day high to identify market trends and hotspots. It is based on the momentum and trend-following strategy, which has been validated by various studies[11][19]. - **Model Construction Process**: The 250-day new high distance is calculated as: $ 250 \text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ Where: - $ Close_t $ is the latest closing price - $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days If the latest closing price reaches a new high, the distance is 0. If the price falls from the high, the distance is a positive value representing the degree of decline[11]. - **Model Evaluation**: The model effectively identifies stocks or indices with strong momentum and highlights market leaders, aligning with the principles of momentum investing[11][19]. 2. Model Name: Stable New High Stock Selection Model - **Model Construction Idea**: This model refines the momentum strategy by focusing on stocks with smooth price paths and consistent new highs, leveraging the "smooth momentum" effect[27]. - **Model Construction Process**: Stocks are selected based on the following criteria: - Analyst Attention: At least 5 buy or overweight ratings in the past 3 months - Relative Strength: Top 20% in 250-day price performance - Price Stability: - Price path smoothness: Ratio of price displacement to total price movement - Consistency of new highs: Average 250-day new high distance over the past 120 days - Trend Continuation: Average 250-day new high distance over the past 5 days The top 50 stocks meeting these criteria are selected[27][29]. - **Model Evaluation**: The model emphasizes stocks with stable momentum and consistent performance, which are less likely to experience sharp reversals, making it a robust enhancement to traditional momentum strategies[27][29]. --- Model Backtesting Results 1. 250-Day New High Distance Model - **Indices' 250-Day New High Distance**: - Shanghai Composite Index: 0.70% - Shenzhen Component Index: 0.00% - CSI 300: 1.84% - CSI 500: 0.00% - CSI 1000: 0.00% - CSI 2000: 0.00% - ChiNext Index: 1.15% - STAR 50 Index: 0.00%[12][13][34] 2. Stable New High Stock Selection Model - **Selected Stocks**: 50 stocks were identified, including Jiangbolong, Shengda Resources, and Yuanjie Technology. - **Sector Distribution**: - Cyclical Sector: 23 stocks, with the highest concentration in basic chemicals - Technology Sector: 18 stocks, with the highest concentration in electronics[30][35] --- Quantitative Factors and Construction Methods 1. Factor Name: 250-Day New High Distance - **Factor Construction Idea**: Measures the relative position of a stock's price to its 250-day high, capturing momentum and trend-following characteristics[11]. - **Factor Construction Process**: $ 250 \text{-day new high distance} = 1 - \frac{Close_t}{ts\_max(Close, 250)} $ Where: - $ Close_t $ is the latest closing price - $ ts\_max(Close, 250) $ is the maximum closing price over the past 250 trading days[11]. - **Factor Evaluation**: The factor is widely recognized for its ability to identify stocks with strong momentum and potential for continued outperformance[11]. 2. Factor Name: Price Path Smoothness - **Factor Construction Idea**: Quantifies the stability of a stock's price movement, favoring stocks with smoother trajectories[27]. - **Factor Construction Process**: - Price path smoothness is calculated as the ratio of price displacement to the total price movement over a given period[27]. - **Factor Evaluation**: This factor enhances the momentum strategy by reducing exposure to volatile stocks, improving risk-adjusted returns[27]. 3. Factor Name: Consistency of New Highs - **Factor Construction Idea**: Measures the persistence of a stock's new high performance over time, emphasizing sustained momentum[27]. - **Factor Construction Process**: - Average 250-day new high distance over the past 120 days is used as a proxy for consistency[27]. - **Factor Evaluation**: This factor ensures that selected stocks exhibit reliable momentum, reducing the likelihood of short-term reversals[27]. --- Factor Backtesting Results 1. 250-Day New High Distance Factor - **Indices' 250-Day New High Distance**: - Shanghai Composite Index: 0.70% - Shenzhen Component Index: 0.00% - CSI 300: 1.84% - CSI 500: 0.00% - CSI 1000: 0.00% - CSI 2000: 0.00% - ChiNext Index: 1.15% - STAR 50 Index: 0.00%[12][13][34] 2. Price Path Smoothness Factor - **Selected Stocks**: 50 stocks were identified, including Jiangbolong, Shengda Resources, and Yuanjie Technology. - **Sector Distribution**: - Cyclical Sector: 23 stocks, with the highest concentration in basic chemicals - Technology Sector: 18 stocks, with the highest concentration in electronics[30][35] 3. Consistency of New Highs Factor - **Selected Stocks**: Same as the Price Path Smoothness Factor, as it is part of the composite selection criteria[30][35]

Market Overview - US stock market continues to rise, with Dow Jones up 0.63%, Nasdaq up 0.91%, and S&P 500 up 0.55% [1] - Meta shares increased by 5.66%, marking the largest single-day gain since July 31 [1] - Tesla shares rose by 4.15%, while Microsoft and Amazon saw increases of at least 1.31% [1] Company Developments - Intel's Q1 guidance is disappointing, leading to a post-market drop of over 10% [2] - Nvidia completed a $5 billion investment in Intel in Q4 [2] - Tesla plans to sell humanoid robots to the public by the end of this year or next year [3] - OpenAI is quietly developing humanoid robots with a team of 100 in San Francisco [4] - Meta's Threads platform has surpassed 400 million monthly active users and is launching ads globally [5] Commodity Insights - Goldman Sachs raised its gold price target to $5,400, indicating that wealthy individuals are competing with central banks for limited physical reserves [6] - COMEX gold futures rose by 1.97%, while silver futures increased by 4.05%, both reaching historical highs [7] - US natural gas futures prices surged by 81% within three days, reaching the highest level since December 2022 [7] Regulatory and Policy Updates - The People's Bank of China (PBOC) Governor Pan Gongsheng stated there is still room for further interest rate cuts and reserve requirement ratio reductions this year [8] - The Ministry of Commerce and other departments encourage horizontal mergers and acquisitions in the pharmaceutical retail sector [12] - The State Council's Food Safety Office is drafting national standards for prepared dishes and will seek public opinions soon [12] Industry Trends - The semiconductor industry is seeing significant developments, with Alibaba's T-HEAD planning for an independent IPO [10] - The prepared food sector is undergoing a transformation, with a focus on quality and safety in the supply chain [11] - The retail pharmacy industry is expected to accelerate consolidation, with a projected decrease in the number of pharmacies by nearly 20,000 since Q4 2024 [13] Financial Projections - Zhaoyi Innovation expects a net profit of approximately 1.61 billion yuan for 2025, a 46% increase year-on-year [17] - Shengmei Shanghai anticipates revenues between 6.68 billion and 6.88 billion yuan for 2025, reflecting a growth of 18.91% to 22.47% [18] - Runtu Co. forecasts a net profit of 600 million to 700 million yuan for 2025, representing a growth of 181.05% to 227.89% [18]

Core Viewpoint - The storage chip industry is experiencing a significant growth cycle driven by AI demand, with major companies like Demingli (德明利) forecasting substantial revenue and profit increases for 2025, indicating a robust market outlook for storage products [1][2][3]. Company Performance - Demingli expects 2025 revenue between 10.3 billion to 11.3 billion yuan, a year-on-year increase of 115.82% to 136.77%, with net profit projected at 650 million to 800 million yuan, reflecting an increase of 85.42% to 128.21% [1][2]. - In Q4 2025, Demingli anticipates revenue of 3.641 billion to 4.641 billion yuan, representing a growth of 209.72% to 294.79% [1]. - Other companies in the storage sector, such as Baiwei Storage (佰维存储) and Lanqi Technology (澜起科技), have also reported optimistic forecasts, with Baiwei expecting revenue of 10 billion to 12 billion yuan and net profit of 850 million to 1 billion yuan, and Lanqi projecting net profit of 2.15 billion to 2.35 billion yuan [2][3]. Market Trends - The storage market is undergoing a transformation, with major players like SanDisk, Micron, and Samsung raising product prices due to increased demand for high-performance storage chips driven by AI applications [3][6]. - The demand for high-performance storage solutions is growing as AI applications proliferate, leading to a significant increase in the market size [6][7]. - The supply side is tightening as major manufacturers reduce production of traditional storage chips while focusing on advanced processes for AI server applications, contributing to rising prices [6][7]. Industry Dynamics - The AI-driven storage supercycle is creating a favorable environment for domestic storage manufacturers, who are increasing capital expenditures to expand production capacity [5][8]. - Companies like Jiangbolong (江波龙) and Demingli are actively pursuing fundraising initiatives to enhance their production capabilities and market presence [7][8]. - Baiwei Storage is also investing in expansion projects, with plans for advanced packaging manufacturing to enhance competitiveness in the storage market [9].

Group 1 - Jiangbolong's stock price increased by 4.38%, closing at 361.81 yuan on January 22 [1] - A block trade occurred with a total volume of 10,000 shares and a transaction amount of 3.5457 million yuan [1] - The first transaction price was 354.57 yuan for 10,000 shares, with a premium rate of -2.00% [1] Group 2 - In the last three months, there has been one block trade for Jiangbolong, totaling 3.5457 million yuan [1] - Over the past five trading days, the stock has risen by 16.15%, with a net inflow of 301 million yuan from main funds [1]

Core Insights - The article discusses the challenges of managing excess inventory in the chip industry, highlighting the financial burden of storage and capital costs associated with unsold materials [1] - It promotes a service called "Chip Superman," which has served 22,000 users and offers rapid transaction completion for inventory clearance [2][10] - The article lists various semiconductor components available for sale at discounted prices, indicating a significant inventory of over 50 million chips valued at over 100 million [9] Group 1: Inventory Management - Excess inventory of 100,000 units incurs monthly storage and capital costs of at least 5,000, leading to a potential loss of 30,000 over six months [1] - The article emphasizes the need for effective promotion strategies for unsold materials to mitigate financial losses [1] Group 2: Sales and Services - "Chip Superman" has a large inventory with over 1,000 models and 100 brands, facilitating quick sales, often within half a day [2][10] - The service aims to assist those struggling to sell their inventory by providing a platform for better pricing and visibility [11] Group 3: Product Listings - A detailed list of available semiconductor components is provided, including brands like Micron, Xilinx, ON Semiconductor, and Samsung, with quantities ranging from thousands to hundreds of thousands [5][6] - The article also includes a section for requested components, indicating active demand in the market [7][8]

存储行业跟踪报告 TMT 及中小盘/电子 全球存储价格从 25H1 复苏上涨以来，25Q3-Q4 现货/合约价格加速上涨，近期 逐步发现 26Q1 各品类存储价格环比涨幅超预期，我们预计 2026 年全年全球存 储供给整体维持偏紧状态，AI 需求增长持续高于产能扩张速度，其他消费类存 储和利基型存储受到产能挤压和下游恐慌备货等因素，价格涨幅也远超常规水 平，我们认为今年国内存储产业链多环节都将受益于缺货涨价浪潮，核心建议 关注存储原厂+存储模组/芯片公司+存储封测/代工等环节。 ❑ AI 存储引发更多需求增量，多级存储体系优化补充急剧增多的 KV 缓存空间。 推荐（维持） 证券研究报告 | 行业点评报告 2026 年 01 月 21 日 26Q1 价格涨幅超市场预期，关注即将到来的密集财报催化 英伟达在CES 2026主题演讲上发布最新Inference Context Memory Storage Platform （推理上下文存储平台），利用 BlueField-4 DPU 构建在 Pod 级别 运行的专用上下文记忆层，在计算节点层面，KV 分层涵盖 GPU HBM、主机 内存、本地 SSD、ICMS 和 ...

Core Viewpoint - The article discusses the share transfer of Shenzhen Jiangbolong Electronics Co., Ltd., highlighting the pricing and participation of institutional investors in the transfer process [1][4]. Group 1: Share Transfer Details - On January 19, the company disclosed the pricing results, with five shareholders transferring a total of 12,574,358 shares at a price of 212.09 yuan per share, amounting to approximately 2.667 billion yuan [1]. - The transfer price represents a 36.92% discount compared to the closing price of 341.99 yuan on January 20 [1]. - A total of 59 institutions participated in the bidding, with 54 successfully allocated shares, indicating strong interest from institutional investors [8][10]. Group 2: Shareholder Information - The selling shareholders include Longxi No.1, Longxi No.2, Longxi No.3, Longjian Management, and Longxi No.5, which are not major shareholders holding over 5% of the company [1][4]. - The shareholding percentages of these shareholders are 4.18% for Longxi No.1 and Longxi No.2, 3.92% for Longxi No.3, 1.57% for Longjian Management, and 1.38% for Longxi No.5 [1]. Group 3: Market Reaction and Implications - Following the announcement of the discounted share transfer, Jiangbolong's stock price showed resilience, closing up 1.71% at 341.99 yuan, with a total market capitalization of 143.343 billion yuan and a trading volume of 7.495 billion yuan [11]. - The non-public nature of the transfer and the six-month lock-up period for the acquired shares are expected to mitigate short-term selling pressure on the stock price [11].