投资逻辑 公司基本盘复苏，国产替代打开主业增长空间。谐波减速器是技术 密集型行业，材料、加工工艺、加工设备等方面均存在较高技术壁 垒，以公司为首的国产谐波减速器厂商经过多年发展，打破了国际 品牌在国内机器人谐波减速器领域的垄断、并持续深化国产替代。 公司技术+成本优势领先，中商情报局披露，2024 年公司市占率 达到全球 12%，位居全球第二，国产第一。受公共安全事件结束和新 能源汽车、3C 电子等下游需求拉动影响，2024-2025 年行业持续回 暖，国家统计局披露，2024/2025 年中国工业机器人产量分别同比提 升 14.2%/28.0%，2025 年产量达到 77 万台，创历史新高。 人形机器人风口将至，公司是人形领域谐波减速器的龙头。人形机 器人市场随着 AI 技术的进步和以特斯拉为首的科技巨头加码，有望 迎来快速爆发，人形机器人自由度有持续增长趋势，将带动谐波减 速器行业数倍增长的需求。以特斯拉 Optimus 为例，单台人形机器 人谐波减速器需求量为 14 台，后续有望提升到 20 个以上。国产厂商 具备较强的创新及降本能力，相对优势显著，有望充分受益人形机 器人市场爆发带来的产业机遇。公司在 ...

Investment Rating - The report assigns a target price of 21.04 RMB for the company, based on a 13x PE for 2027 [5]. Core Insights - The company has effectively integrated its forestry, pulp, and paper operations, demonstrating strong profitability across industry cycles. Its core advantages stem from cost advantages through integrated operations, differentiated products, and precise market control, maintaining a leading profitability level in the industry [3][15]. - The pulp supply-demand dynamics are expected to improve, providing a moderate recovery in paper prices. Domestic pulp production is nearing its peak, and limited new overseas capacity is anticipated, which will support pulp prices and consequently paper prices [3][30]. - The company is set to achieve significant capacity growth from 2025 to 2027, with 1.7 million tons of packaging paper and 470,000 tons of cultural paper expected to come online, ensuring a high degree of certainty in future earnings growth [4][5]. Summary by Sections 1. Industry Leadership and Profitability - The company has maintained a compound annual growth rate (CAGR) of 12.20% in revenue and 12.71% in net profit from 2015 to 2024, showcasing stable growth [15]. - The company operates three major production bases, ensuring a balanced supply to both northern and southern markets, with a total pulp capacity of nearly 5 million tons and paper capacity exceeding 7 million tons [15]. 2. Pulp Supply-Demand Dynamics - The domestic pulp production capacity is projected to reach 36.05 million tons by 2025, reflecting a 67.67% increase from 2021, while the growth rate of pulp production capacity significantly outpaces that of paper production [30]. - The report anticipates that the pulp price will experience a moderate recovery due to reduced supply from international producers and increased demand from domestic paper manufacturers [30][32]. 3. Integrated Operations and Cost Advantages - The company plans to launch 1.1 million tons of self-produced pulp, enhancing its integrated operations and ensuring stable profitability in the short term [4][19]. - The company benefits from a 300 RMB/ton energy cost advantage through its self-supplied power and steam, further solidifying its competitive edge [4][19]. 4. Earnings Forecast and Valuation - Projected revenues for 2025-2027 are 471.22 billion, 473.10 billion, and 516.25 billion RMB, with corresponding net profits of 33.60 billion, 38.67 billion, and 45.24 billion RMB, indicating growth rates of 8.34%, 15.11%, and 16.97% respectively [5][9].

投资逻辑： 国产海风机组龙头，短中长三重逻辑支撑业绩进入向上通道。短 期维度，国内陆风重回通胀，我们不完全统计 2025 年各功率段陆 风机组不含塔筒中标均价同比提升超 10%，随着 2026-2027 年高价 订单交付占比提升，预计公司制造端业绩弹性有望持续释放。中期 维度，国内海风建设在经历三年调整后，需求景气度有望逐步回 暖，我们预计"十五五"阶段国内海风年平均装机有望从"十四五" 的 8GW 提升至 15-20GW，看好公司作为国内海风龙头充分受益。长 期维度，欧洲海风进入高速建设阶段，预计 2030 年后年均装机有 望提升至 15GW 以上，而当前欧洲本土海上大风机产能仅 4GW，叠 加欧洲开发商对项目降本的强烈诉求，预计公司凭借英国本土基 地实现欧洲海风市场突破，从而打开长期成长空间。 收购卫星能源系统研制商，太空光伏技术路线全面布局。2026 年 1 月 22 日，公司公告拟通过发行股份及支付现金的方式收购中山 德华芯片 100%的股权，并募集配套资金。德华芯片业务主要聚焦 于柔性空间太阳电池芯片、柔性太阳电池电路等产品，具备砷化镓 组件级供应能力，总经理为蓝箭航天前高级副总裁杨文奕。2025 ...

经济增长：补贴退潮，车市走弱 (1) 猪价涨势渐颓。1 月 27 日，猪肉平均批发价为 18.7 元/公斤，较 1 月 20 日上涨 1.0%。 (2) 农产品价格指数偏强运行。1 月 27 日，农产品批发价格指数较 1 月 20 日上涨 0.1%。分品种看，鸡蛋（上涨 4.7%）> 猪肉（上涨 1.0%）>羊肉（上涨 0.8%）>牛肉（上涨 0.2%）>水果 (上涨 0.1%）>蔬菜（下跌 0.7%）>鸡肉（下跌 1.3%）。 PPI：油价温和上涨 (1) 油价温和上涨。1 月 27 日，布伦特和 WTI 原油现货价报 69.5 和 62.4 美元/桶，较 1 月 20 日分别上涨 2.0%和上 涨 3.4%。 (2) 铜铝回升。1 月 27 日，LME3 月铜价和铝价较 1 月 20 日分别上涨 0.8%和上涨 1.3%。 (3) 国内商品指数环比转涨。1 月 27 日，南华工业品指数较 1 月 20 日上涨 2.1%；1 月 27 日，CRB 指数较 1 月 20 日 上涨 2.1%。 生产：电厂日耗超出去年同期 通货膨胀：猪价涨势渐颓 CPI：猪价涨势渐颓 风险提示 统计口径误差。数据统计大多为抽样， ...

Investment Rating - The report maintains a "Buy" rating for the company, indicating an expected price increase of over 15% in the next 6-12 months [5][13]. Core Views - The company is projected to achieve a net profit attributable to shareholders of RMB 1.526-1.659 billion for 2025, representing a year-on-year growth of 15%-25% [2]. - The company has faced short-term profit impacts due to impairment in tower crane assets but is expected to see accelerated profit release in 2026 as asset quality improves and domestic demand stabilizes [3]. - The overseas demand is showing signs of recovery, with significant growth in export revenues for loaders and excavators, which is anticipated to continue driving profit growth [3]. - The company is experiencing pressure on margins due to price competition in the domestic electric loader market, but the launch of new products is expected to enhance profitability [4]. - The company's "14th Five-Year Plan" aims for revenue of RMB 60 billion by 2030, with over 60% from overseas markets and a net profit margin of no less than 8% [4]. Summary by Sections Performance Review - The company forecasts a net profit of RMB 1.526-1.659 billion for 2025, with a quarterly net profit of RMB 0.68-2.01 billion for Q4 2025, showing significant year-on-year growth [2]. Operational Analysis - The company has increased provisions for credit impairment losses to RMB 2.7 billion in Q3 2025 due to a sharp decline in the domestic tower crane industry, which has affected profit growth [3]. - Export revenues for loaders grew over 20% in H1 2025, and excavator sales increased by 22.1% year-on-year, indicating strong overseas demand [3]. - The company’s gross margin was impacted by price competition in the domestic market, but the introduction of the T-series loaders is expected to improve profitability [4]. Profit Forecast and Valuation - The company’s revenue projections for 2025-2027 are RMB 33.564 billion, RMB 37.973 billion, and RMB 43.695 billion, respectively, with net profits of RMB 1.601 billion, RMB 2.092 billion, and RMB 2.640 billion [5].

Group 1: Dividend Strategy Outlook for 2026 - The dividend strategy in 2025 significantly underperformed the market, primarily due to the emergence of new growth sectors like AI, which shifted market focus from dividend yield (d) to growth rate (g) from 2022 to mid-2024[2] - For 2026, the core judgment on whether dividend strategies can achieve excess returns hinges on whether the market continues to prioritize marginal changes in fundamentals[2] - With a low macro risk environment for AI investments and a recovery in corporate earnings expected, the focus may remain on growth rates rather than dividend yields, making excess returns from dividend strategies unlikely[2] Group 2: A-Shares vs. Hong Kong Stocks - Since April 2024, Hong Kong's low-volatility dividend index has outperformed A-shares by 49%, driven mainly by the industrial, financial, and energy sectors[3] - Despite the higher dividend yield of Hong Kong stocks, the PE valuation levels are now comparable to A-shares, indicating limited room for further convergence[3] - The relative performance of Hong Kong stocks is attributed more to stock selection rather than industry allocation, with financials, energy, and industrials contributing the most to excess returns[3] Group 3: Constructing the 2026 Dividend Portfolio - The 2026 dividend strategy should focus on sectors benefiting from AI investment, manufacturing recovery, and domestic consumption recovery, with traditional manufacturing and resource sectors expected to have the broadest benefits[3] - A scoring system combining payout ratios and stability with profitability metrics (ROE) is proposed to optimize sector allocation for dividends[3] - Recommended sectors for increased allocation include insurance, textile manufacturing, and logistics, while sectors with high potential but lower success rates, like banks and construction, should be considered for long-term investment[3]

Industry Trends - The EU's revised Cybersecurity Law is expected to maintain a shortage of storage chips until 2027, with improvements anticipated in 2028[12] - Storage chip prices are projected to rise by approximately 20% in Q2 2026, following significant increases in Q1 2026 (DRAM up 55-60%, NAND Flash up 33-38%) due to strong AI demand[13] - The global storage chip market is forecasted to reach $551.6 billion in 2026, a 134% year-on-year increase, and $842.7 billion in 2027, a 53% increase[13] Financial Performance - Intel's Q4 2025 revenue was $13.7 billion with a non-GAAP gross margin of 37.9%, but Q1 2026 revenue is expected to decline to between $11.7 billion and $12.7 billion due to supply constraints[24] - OpenAI's annual revenue for 2025 has surpassed $20 billion, a significant increase from $6 billion in 2024, driven by expanded computing capabilities[15] - Anthropic's annual revenue has increased from approximately $4 billion in mid-2025 to over $9 billion by the end of 2025[16] Market Developments - Major companies like OpenAI, Apple, and ByteDance are actively developing AI applications, with OpenAI planning to test ads in ChatGPT and launch its first AI device in late 2026[18][19] - Alibaba is considering spinning off its chip design subsidiary, T-Head, into an independent company to enhance its competitiveness in the AI sector[29] - The Gemini API usage by Google has more than doubled to 85 billion calls, with enterprise subscriptions reaching 8 million, indicating strong growth in AI model applications[30]

Quantitative Models and Construction Methods 1. Model Name: High-frequency "Gold" Portfolio CSI 1000 Index Enhanced Strategy - **Model Construction Idea**: This strategy combines three categories of high-frequency factors (price range, price-volume divergence, regret avoidance) equally weighted to enhance the CSI 1000 Index. It aims to leverage high-frequency data to capture microstructure insights and improve stock selection performance[4][38][39] - **Model Construction Process**: 1. Combine the three high-frequency factors (price range, price-volume divergence, regret avoidance) with equal weights (25%, 25%, 50%) 2. Apply industry and market capitalization neutralization to the combined factor 3. Implement weekly rebalancing with a transaction cost rate of 0.2% per side 4. Introduce turnover buffering mechanisms to reduce transaction costs[14][38][39] - **Model Evaluation**: The strategy demonstrates strong out-of-sample performance with stable excess returns, though it has experienced some recent adjustments[42] 2. Model Name: High-frequency & Fundamental Resonance Portfolio CSI 1000 Index Enhanced Strategy - **Model Construction Idea**: This strategy integrates high-frequency factors with fundamental factors (consensus expectations, growth, and technical factors) to improve multi-factor portfolio performance. The low correlation between high-frequency and traditional fundamental factors enhances diversification[43][45] - **Model Construction Process**: 1. Combine the three high-frequency factors and three fundamental factors equally weighted 2. Apply industry and market capitalization neutralization to the combined factor 3. Implement weekly rebalancing with a transaction cost rate of 0.2% per side 4. Introduce turnover buffering mechanisms to reduce transaction costs[43][45] - **Model Evaluation**: The strategy shows improved performance metrics compared to the high-frequency-only strategy, with higher annualized returns and lower maximum drawdowns[45][47] --- Model Backtesting Results 1. High-frequency "Gold" Portfolio CSI 1000 Index Enhanced Strategy - Annualized Return: 10.56% - Annualized Volatility: 23.75% - Sharpe Ratio: 0.44 - Maximum Drawdown: 47.77% - Annualized Excess Return: 9.58% - Tracking Error: 4.36% - Information Ratio (IR): 2.20 - Maximum Excess Drawdown: 6.53%[39] 2. High-frequency & Fundamental Resonance Portfolio CSI 1000 Index Enhanced Strategy - Annualized Return: 14.80% - Annualized Volatility: 23.39% - Sharpe Ratio: 0.63 - Maximum Drawdown: 39.60% - Annualized Excess Return: 13.70% - Tracking Error: 4.23% - Information Ratio (IR): 3.24 - Maximum Excess Drawdown: 4.97%[45] --- Quantitative Factors and Construction Methods 1. Factor Name: Price Range Factor - **Factor Construction Idea**: Measures the activity of stock transactions in different intraday price ranges, reflecting investor expectations for future stock trends[3] - **Factor Construction Process**: 1. Use 3-second snapshot data to calculate transaction volume and count in high (80%) and low (10%) price ranges 2. Construct sub-factors: - High price range transaction volume factor (VH80TAW) - High price range transaction count factor (MIH80TAW) - Low price range average transaction volume factor (VPML10TAW) 3. Combine sub-factors with weights of 25%, 25%, and 50%, respectively 4. Apply industry and market capitalization neutralization[11][14][16] - **Factor Evaluation**: Demonstrates strong predictive power and stable performance out-of-sample[3][16] 2. Factor Name: Price-Volume Divergence Factor - **Factor Construction Idea**: Measures the correlation between stock price and trading volume. Lower correlation indicates higher potential for future price increases[3][19] - **Factor Construction Process**: 1. Use high-frequency snapshot data to calculate correlations: - Price and transaction count correlation (CorrPM) - Price and transaction volume correlation (CorrPV) 2. Combine sub-factors equally weighted 3. Apply industry and market capitalization neutralization[19][22][23] - **Factor Evaluation**: Performance has declined since 2020 due to widespread adoption but remains stable with positive excess returns in 2023[23] 3. Factor Name: Regret Avoidance Factor - **Factor Construction Idea**: Based on behavioral finance, this factor captures investor regret avoidance emotions, such as the impact of selling stocks that later rebound[3][24] - **Factor Construction Process**: 1. Use tick-by-tick transaction data to identify active buy/sell directions 2. Construct sub-factors: - Sell rebound proportion factor (LCVOLESW) - Sell rebound deviation factor (LCPESW) 3. Combine sub-factors equally weighted 4. Apply industry and market capitalization neutralization[24][28][30] - **Factor Evaluation**: Exhibits stable out-of-sample performance, indicating significant influence of regret avoidance on stock returns[31] 4. Factor Name: Slope Convexity Factor - **Factor Construction Idea**: Captures the impact of order book slope and convexity on expected returns, reflecting investor patience and supply-demand elasticity[3][32] - **Factor Construction Process**: 1. Calculate order book slope using cumulative order volume and price at different levels 2. Construct sub-factors: - Low-level slope factor (Slope_abl) - High-level convexity factor (Slope_alh) 3. Combine sub-factors equally weighted 4. Apply industry and market capitalization neutralization[32][35][37] - **Factor Evaluation**: Performance has been stable since 2016, though recent results are relatively flat[35] --- Factor Backtesting Results 1. Price Range Factor - Annualized Excess Return: 3.24% (VH80TAW), 4.45% (MIH80TAW), -0.77% (VPML10TAW)[12][14][16] 2. Price-Volume Divergence Factor - Annualized Excess Return: 2.56% (CorrPM), 2.61% (CorrPV)[19][22][23] 3. Regret Avoidance Factor - Annualized Excess Return: -2.67% (LCVOLESW), 0.33% (LCPESW)[24][26][31] 4. Slope Convexity Factor - Annualized Excess Return: -2.35% (Slope_abl), 0.02% (Slope_alh)[34][35][37]

一问红利：2026 年是否会有超额？ 2025 年红利策略大幅跑输市场，最核心的原因在于市场找到了新的能够突破宏观趋势的成长性：以 AI 产业投资为代 表，以及景气度也开始逐步扩散到与 AI 强相关的"泛 AI"领域。所以市场的定价驱动力从 2022 年至 2024 年上半年 的股息率 d 逐步开始重新转向增长率 g。展望 2026 年，红利策略是否会有相较于全 A 的超额收益，核心判断还是在于 市场是否依旧以基本面的边际变化作为核心驱动力？基于我们年度策略《世界的中国》对于 2026 年的基本面展望， 在 AI 投资宏观风险较低、降息周期下全球制造业景气度向上的背景下，2026 年中国的企业盈利修复可能是股票市场 的核心驱动力，会有更多的行业景气度出现改善。在这种宏观背景下，我们认为投资者可能还是会更加关注基本面的 边际变化（增长率）而非股息率。所以 2026 年红利策略似乎很难获取超额收益。但这并不意味着红利策略不重要， 因为它依旧是很多投资者构建投资组合的压舱石和降低组合波动的重要工具：一方面，A 股权益资产内部红利资产的 估值水平最低，波动率也相对较低；另一方面，与主要城市二手住宅租金回报、10 年期 ...

孟灿 李忠宇 SAC:S1130524100002 lizhongyu01@gjzq.com.cn 1 N 产业研究中心 2026 年 1 月 26 日 产业研究周报 | 科技 英特尔财报佐证 AI 供不应求，巨头 AI 应用进展喜人 SAC:S1130522050001 mengcan@gjzq.com.cn | 证券研究报告 | 核心要点 产业前沿 欧盟委员会公布《欧盟网络安全法》修订草案，预计存储芯片 2026-2027 年仍 将是供不应求状态，2028 年才会改善，工信部印发《关于全面开展算力态势感 知自动化监测工作的通知》；OpenAI、Anthropic25 年年化收入已突破 200、90 亿美元；OpenAI 计划未来几周在 ChatGPT 的"免费版"和"Go 版"中测试广告， 26 年下半年推出首款 AI 设备；字节跳动 AI Agent 平台"扣子"宣布 2.0 升级。 资本风向 英特尔 25Q1 财报表现优异，但 26Q1 预期不佳，阿里考虑将平头哥分拆上市； Meta 新成立的人工智能实验室已于本月向内部交付首批重要 AI 模型，过去一年 谷歌 GeminiAPI 调用量增长逾一倍，达 ...