中国市场：25Q4实现包裹量58.9亿件，日均6400万件，符合预期；10月以来中国快递行业包裹量增速有 所放缓，10月增速下降至双位数以下，行业向高质量发展方向转变。 智通财经APP获悉，浙商证券发布研报称，维持极兔速递-W(01519)"买入"评级，考虑公司在东南亚市 场继续保持竞争优势，随着件量增长，新市场规模优势显现以及中国市场持续拓展与各电商平台的合 作。 浙商证券主要观点如下： 25Q4公司总体实现包裹量84.6亿件，同比增长14.5%，日均包裹量9200万件 东南亚市场：25Q4极兔实现包裹量24.4亿件，同比增73.6%，日均件量2650万件，同比+73.6%，公司在 东南亚业务量表现持续强劲，主要由于电商传统旺季及东南亚整体线上渗透率持续提升，极兔凭借稳健 的业务策略不断提升竞争有优势，当地行业份额持续向龙头集中。 新市场(包括沙特阿拉伯、阿联酋、墨西哥、巴西及埃及)：25Q4极兔继续维持了自上个季度以来的强劲 增速，2025年第四季度实现包裹量破亿，达1.3亿件，同比升79.7%，日均包裹量145万件，同比 +79.7%。主要由于公司积极把握电商增长红利拓展与TikTok、Mercado ...

Core Viewpoint - The company maintains a "Buy" rating for Jitu Express-W (01519), citing its competitive advantage in the Southeast Asian market, growth in package volume, emerging market scale advantages, and ongoing collaborations with various e-commerce platforms in China [1] Group 1: Package Volume Performance - In Q4 2025, the company achieved a total package volume of 8.46 billion pieces, a year-on-year increase of 14.5%, with an average daily volume of 92 million pieces [2] - In Southeast Asia, Jitu achieved a package volume of 2.44 billion pieces in Q4 2025, representing a year-on-year growth of 73.6%, with a daily average of 26.5 million pieces [2] - The new markets (including Saudi Arabia, UAE, Mexico, Brazil, and Egypt) saw a package volume of 130 million pieces in Q4 2025, a year-on-year increase of 79.7%, with a daily average of 1.45 million pieces [2] - In China, the package volume reached 5.89 billion pieces in Q4 2025, with a daily average of 64 million pieces, aligning with expectations [2] Group 2: Annual Performance Overview - For the full year of 2025, the total package volume surpassed 30 billion pieces, reaching 30.13 billion pieces, a year-on-year increase of 22.2%, with an average daily volume of 82.5 million pieces [2] - In Southeast Asia, the annual package volume was 7.66 billion pieces, a year-on-year increase of 67.8%, with a daily average of 21 million pieces [2] - The new markets achieved an annual package volume of 400 million pieces, a year-on-year increase of 43.6%, with a daily average of 1.1 million pieces [3] - In China, the annual package volume was 22.07 billion pieces, a year-on-year increase of 11.4%, with a daily average of 60.5 million pieces [3] Group 3: Strategic Acquisitions - The company announced plans to acquire approximately 36.99% of Jet Global for $950 million, aiming for full ownership, and to acquire approximately 46.55% of JNTExpress KSA for $106 million, achieving full control of the Saudi entity [4] - Jet Global, covering markets like Brazil, Egypt, and Mexico, is expected to significantly reduce its pre-tax losses in 2024 compared to 2023, with total assets of $640 million and net liabilities of $590 million [4] - JNTExpress KSA is also projected to improve its pre-tax losses in 2024 compared to 2023, with total assets of $8.6 million and net assets of $3.7 million [4] - These acquisitions are part of the company's strategy to enhance control over key emerging markets and improve operational efficiency [4]

Quantitative Models and Construction Methods - **Model Name**: Monte Carlo Backtesting **Model Construction Idea**: Shift from historical path fitting to future robustness testing by generating multiple random paths to evaluate strategy performance across diverse scenarios [1][10] **Model Construction Process**: 1. Generate thousands of random price paths that follow historical statistical characteristics (e.g., return distribution, volatility, correlation) but differ from the original historical path [10] 2. Perform stress tests on strategies across these simulated paths to observe performance under various market conditions [10] 3. Calculate risk metrics such as Sharpe ratio, maximum drawdown, and value-at-risk (VaR) based on the distribution of strategy returns [10] **Model Evaluation**: Effectively reduces overfitting to specific historical paths and provides a more comprehensive robustness assessment [10][46] - **Model Name**: Non-Parametric Monte Carlo Simulation **Model Construction Idea**: Use historical data directly without assuming any parametric distribution, preserving cross-sectional correlation [2][13] **Model Construction Process**: 1. **Method 1**: Multi-Asset Time-Series Return Joint Rearrangement - Extract daily returns of all assets as a "data block" - Randomly sample and sequentially concatenate these blocks to form simulated paths [18] 2. **Method 2**: Multi-Asset Time-Series Return Block Bootstrap - Divide historical returns into fixed-length overlapping/non-overlapping blocks - Randomly sample blocks and concatenate them to form simulated paths [19] **Model Evaluation**: Preserves cross-sectional correlation but disrupts time-series structures like volatility clustering and autocorrelation [14][20] - **Model Name**: Residual Bootstrap (Factor Model-Based) **Model Construction Idea**: Separate systematic risk and idiosyncratic risk using factor models, then randomize residuals for simulation [2][23] **Model Construction Process**: 1. Construct risk factors (e.g., market, size, value, momentum) and calculate historical daily returns [23] 2. Perform cross-sectional regression to estimate factor exposures (β) and extract residual returns [23] 3. Randomly shuffle residuals while preserving cross-sectional correlation [23] 4. Reconstruct paths using historical factor returns and randomized residuals [23] **Model Evaluation**: Useful for analyzing alpha and risk exposure but limited by the explanatory power of the factor model [24][25] - **Model Name**: Geometric Brownian Motion (GBM) Simulation **Model Construction Idea**: Assume asset returns follow a normal distribution and simulate paths using drift and volatility parameters [2][28] **Model Construction Process**: $$d S_{i}(t)=\mu_{i}S_{i}(t)d t+\sigma_{i}S_{i}(t)d W_{i}(t),i=1,\ldots,n$$ - \( \mu_{i} \): Drift rate (expected return) - \( \sigma_{i} \): Volatility - \( W_{i}(t) \): Standard Brownian motion Discretized path: $$S_{i}^{(j)}(t_{k})=X_{i}(0)\,e x p[(\,k\Delta t+\sum_{l=1}^{k}\sum_{p=1}^{n}L_{i p}Z_{l,p}^{(j)}\,]$$ - \( L \): Cholesky decomposition of covariance matrix - \( Z_{l,p}^{(j)} \): Independent standard normal random variables [28] **Model Evaluation**: Accurately replicates volatility and correlation but fails to capture tail risks and price jumps [28][47] Model Backtesting Results - **Monte Carlo Backtesting**: - Historical price path Sharpe ratio: 0.96 (25-day window) - Simulated path Sharpe ratio: 0.19 (25-day window, GBM method) [45][46] - **Non-Parametric Monte Carlo Simulation**: - Historical price path Sharpe ratio: 0.96 (25-day window) - Simulated path Sharpe ratio: 0.22 (15-day window, joint rearrangement method) [45][46] - **Residual Bootstrap**: - Historical price path Sharpe ratio: 0.96 (25-day window) - Simulated path Sharpe ratio: 0.19 (25-day window) [45][46] - **Geometric Brownian Motion (GBM)**: - Historical price path Sharpe ratio: 0.96 (25-day window) - Simulated path Sharpe ratio: 0.19 (25-day window) [45][46] Quantitative Factors and Construction Methods - **Factor Name**: Momentum and Volatility Dual Factor **Factor Construction Idea**: Combine momentum and volatility factors using Z-score normalization and equal weighting [35] **Factor Construction Process**: $$S c o r e_{i}=0.5*Z S c o r e_{i,m o m}+0.5*Z S c o r e_{i,v o l}$$ - Momentum and volatility calculated over different window lengths (N ∈ [15, 20, 40]) [35] **Factor Evaluation**: Provides a balanced scoring mechanism for style rotation strategies [35][37] Factor Backtesting Results - **Momentum and Volatility Dual Factor**: - Historical price path cumulative return: 535% (25-day window) - Simulated path cumulative return: 62.25% (15-day window, GBM method) [38][42]

Core Viewpoint - TaoTao Automotive's performance is expected to increase by 91% year-on-year, exceeding expectations, solidifying its position as a leader in the North American leisure vehicle market [1] Group 1: Company Developments - The company has acquired 100% of Champion Motorsports Group Holdings, LLC for $15 million, which is expected to enhance its brand matrix and channel advantages [1] - The target company has stable clients including Walmart and over 2,000 retail stores, along with online channels, which will synergize with the company's existing resources [1] - The company plans to conduct its initial public offering (IPO) of H-shares on the Hong Kong Stock Exchange to promote its global strategy, enhance international brand influence, and improve overseas financing capabilities [1] Group 2: Market and Operational Insights - The North American electric low-speed vehicle industry is expected to see a continuous decline in inventory, allowing the company to further increase its market share [1] - The production efficiency in North America is now on par with the company's domestic levels, and preparations for a second production line are actively underway [1] - The company has established a 140,000 square meter local warehousing and manufacturing base in North America, supported by a local talent team of nearly 400 people covering the entire chain from R&D to after-sales [1]

Group 1 - The core viewpoint of the article highlights the progress of Bertelli's L3 and the imminent mass production of EMB, indicating a strong growth trajectory in the humanoid robot business [1] - The company has secured multiple clients for its EMB solutions, including a major domestic automotive enterprise, which will provide a complete EMB solution for its entire range of pure electric mid-to-large luxury sedans by October 31, 2025 [1] - The EMB production line has been completed and is expected to deliver small batches by the end of 2025, with full-scale production commencing in the first half of 2026 [1] Group 2 - The company plans to initiate the development of robot screws and motors in 2026, with mass production anticipated by mid-2026 [1] - The research report maintains a "buy" rating for the company's stock, reflecting confidence in its growth prospects [1]

Group 1 - The core viewpoint of the news is the performance and market position of Dazhu CNC Technology Co., Ltd., which saw a stock price increase of 5.87% to 131.15 CNY per share, with a total market capitalization of 55.806 billion CNY [1] - Dazhu CNC specializes in the research, production, and sales of PCB (Printed Circuit Board) equipment, with its main revenue sources being drilling equipment (71.02%), testing equipment (8.78%), and other categories [1] - The company is located in Shenzhen, Guangdong Province, and was established on April 22, 2002, with its stock listed on February 28, 2022 [1] Group 2 - From the perspective of fund holdings, Zhejiang Merchants Securities Asset Management has a fund that heavily invests in Dazhu CNC, specifically the Zhejiang Merchants Huijin Transformation Growth Fund (000935), which holds 18,200 shares, accounting for 3.43% of the fund's net value [2] - The fund has a total scale of 51.7885 million CNY and has achieved a year-to-date return of 3.37%, ranking 3481 out of 8823 in its category, while its one-year return is 60.21%, ranking 1282 out of 8083 [2]

Core Viewpoint - The price dynamics of silver and oil have diverged significantly, with silver prices surging while oil prices remain subdued, indicating a potential shift in market sentiment and supply-demand dynamics in 2026 [1][4]. Group 1: Price Movements - As of January 6, 2026, COMEX silver futures are trading around $77 per ounce, while WTI crude oil futures are at $58 per barrel, resulting in a silver-to-oil ratio of approximately 1.3 [1]. - Over the past six months, oil prices have dropped over 32% from a high of $74 per barrel to a low of $50, while silver prices have doubled from around $40 per ounce to a peak of $80 [2]. - The last time silver was more expensive than oil was about 45 years ago, with historical instances showing significant fluctuations in the silver-to-oil ratio [2]. Group 2: Market Dynamics - The current silver-to-oil ratio fluctuates between 1.2 and 1.3, with silver showing strong rebound momentum despite a recent drop from its historical high [3]. - Financial institutions are increasing their net long positions in COMEX silver futures, indicating strong bullish sentiment, while oil prices are experiencing a decline due to oversupply concerns [3][5]. - The geopolitical situation in Venezuela has limited impact on oil prices, as the country’s production capacity is currently low, and global supply remains excessive [3][5]. Group 3: Supply and Demand Factors - The contrasting performance of silver and oil reflects a re-evaluation of their values amid changing supply-demand dynamics and macroeconomic conditions [4]. - Silver is increasingly recognized for its industrial applications, particularly in electronics and solar energy, which are expected to drive demand, although growth in solar installations is projected to slow down [4][5]. - Oil supply remains weak globally, with the U.S. Energy Information Administration projecting record-high oil production, reinforcing expectations of oversupply in the market [5]. Group 4: Future Outlook - Analysts suggest that while the silver-to-oil ratio may remain above 1.0, significant further increases are unlikely, with key factors such as OPEC+ production cuts and global energy policies influencing future price relationships [5].

Group 1 - The core viewpoint is that the 2026 national subsidy policy for automobiles emphasizes quality improvement and efficiency, with a shift from fixed subsidies to percentage-based subsidies based on new car prices, along with a cap on the subsidy amount [1][2] - The new energy vehicle (NEV) scrap and replacement subsidy is set at 12% of the new car price, with a maximum of 20,000 yuan, while the replacement subsidy is 8% with a cap of 15,000 yuan. Compared to the 2025 policy, the subsidy decreases for cars priced below 166,700 yuan for scrap updates and below 187,500 yuan for replacement updates [2][3] - For fuel vehicles (2.0L and below), the scrap update subsidy is 10% of the new car price, capped at 15,000 yuan, and the replacement subsidy is 6%, capped at 13,000 yuan. Similar to NEVs, the subsidy decreases for vehicles priced below 150,000 yuan for scrap updates and below 216,700 yuan for replacement updates [3] Group 2 - The 2026 national subsidy policy is expected to exceed expectations, potentially driving demand for mid-to-high-end models and mitigating the negative impact of the reduction in purchase tax incentives for new energy vehicles. The policy's cap remains unchanged, but lower-priced electric vehicle subsidies decrease, which may boost sales and prices of higher-end models [3] - The commercialization of L3-level autonomous driving is set to begin, with the first batch of L3 vehicles receiving product access permits. This development is expected to enhance the penetration rate of core incremental components, such as EMB, which aligns with the stringent requirements for response speed and control precision in L3 and above autonomous driving [4] - Recommended stocks include Xpeng Motors and Geely Automobile for complete vehicles, Bertley for electronic control chassis, and Shanghai Yanpu, Jifeng Co., and Tiancai Zikong for automotive seating [4]

Core Viewpoint - Zhejiang Securities maintains a "Buy" rating for Alibaba Group (09988) with a target price of HKD 189.09, highlighting the company's leading position in the AI-integrated cloud platform and the high certainty of profit margin improvement in its cloud business, which is expected to drive valuation enhancement [1] Group 1: AI Application and Market Position - Alibaba's Qianwen AI application achieved over 30 million MAU within 23 days of public testing, making it one of the fastest-growing AI applications globally, competing with Doubao for AI entry points [1] - Qianwen adopts a "free + value-added + B-end open source" model, focusing on professional scenarios and long-context processing, while Doubao leads with over 100 million DAU using a closed-source multimodal agent approach [1] Group 2: Ecosystem Transformation and Consumer Experience - Qianwen is expected to reshape Alibaba's ecosystem with its AIAgent capabilities, enhancing the entire e-commerce chain by improving efficiency for merchants and optimizing consumer experiences through AI-driven search, price comparison, and personalized recommendations [2] - The integration of Qianwen with Fliggy's "Ask" feature will provide 24/7 assistance for complex travel needs, generating complete itineraries from real-time data [2] Group 3: Financial Performance and Cash Flow - Alibaba's capital expenditure reached RMB 31.428 billion in Q3 2025, a year-on-year increase of 85.12%, indicating a period of rapid growth [2] - The company reported a negative free cash flow of RMB -21.84 billion in Q3 2025, primarily due to increased capital expenditures and competitive pressures in the food delivery sector, although it still holds RMB 292.3 billion in net cash and liquid investments [2] Group 4: Cloud Business Profitability - Alibaba Cloud's EBITA margin remains lower compared to Amazon AWS and Microsoft Azure, but historical data from Google Cloud suggests significant profit margin improvement potential as scale increases [3] - The growth of Alibaba Cloud's scale is expected to lead to higher long-term profit margins, with substantial room for improvement as the company transitions past its initial high-investment phase [3]

资本开支高增、自由现金流承压但现金保障充裕，云业务利润率长期提升的确定性高 阿里巴巴25Q3的资本开支达到314.28亿人民币，同比增幅达到85.12%，处于高速增长期。阿里巴巴 25Q2、25Q3连续两个季度自由现金流下降引发市场担忧。公司25Q3自由现金流为-218.4亿，主要系"外 卖大战"和大幅增加资本开支的影响。截至25Q3，阿里巴巴集团账面仍有2923亿人民币净现金和其他流 动性投资，为新业务投入提供保障。 智通财经APP获悉，浙商证券发布研报称，维持阿里巴巴-W(09988)"买入"评级，对应目标价为189.09港 币，阿里巴巴作为国内领先的卡位AI全栈的云平台公司，云业务高景气+中期利润率提升的高确定性， 将带来估值提升。 浙商证券主要观点如下： 阿里千问公测23天MAU破3000万，成全球增长最快AI应用之一，与豆包竞争AI入口 阿里千问通过"免费+增值+B端开源"，同时与阿里生态融合，重点聚焦专业级场景与长上下文处理。豆 包则以超1亿DAU居国内AI原生应用榜首，采用闭源多模态Agent路线与"免费+增值+B端MaaS"模式， 覆盖全场景与轻量高频需求。二者在模型架构、生态布局、核心能力与 ...