Investment Rating - The report indicates a positive outlook for the tin industry, driven by strong demand and limited supply, suggesting a favorable investment environment [2][3]. Core Insights - The global tin market is experiencing structural tightness, with supply heavily reliant on a few resource-rich countries. In 2024, global tin production is projected to be 300,000 tons, a decrease of 1.63% year-on-year, while demand is expected to reach 385,200 tons, an increase of 3.33% year-on-year [5][15]. - Tin prices are expected to rise due to weak supply and strong demand. The prolonged suspension of mining operations in Myanmar and conflicts affecting supply from the Democratic Republic of Congo have exacerbated material shortages, driving prices upward [5][22]. - Key companies in the tin sector include: - **Yunnan Tin Company**: Leading in tin production and sales globally, with a comprehensive integrated supply chain [33]. - **Xingye Silver Tin**: Notable for its silver and tin production, with ongoing acquisitions of overseas tin resources [36]. - **Hua Tin Nonferrous Metals**: A state-owned platform benefiting from regional resource consolidation and industrial clustering [39]. Summary by Sections 1. Tin Industry Overview - Tin is a crucial metal in electronic soldering, characterized by its stability and resistance to oxidation, making it suitable for various applications [8]. - The global tin supply is concentrated, with the top four countries (Indonesia, China, Myanmar, and Australia) accounting for over 60% of reserves [14]. 2. Tin Price Trends - Tin prices are influenced by supply constraints and high demand, particularly from the electronics and renewable energy sectors. The report anticipates that if new production capacity remains limited, tin prices will likely stay elevated [22][24]. 3. Related Companies - **Yunnan Tin Company**: Achieved a market share of 25.03% globally in 2024, focusing on high-value products and sustainable practices [33]. - **Xingye Silver Tin**: Reported significant revenue growth, with a strong focus on resource acquisition and production expansion [36]. - **Hua Tin Nonferrous Metals**: Leveraging its integrated operations to enhance resource recovery and sustainability [39].

Investment Rating - Industry rating: Overweight [1] Core Insights - On January 6, 2026, NVIDIA CEO Jensen Huang officially launched the latest NVIDIA Rubin platform at CES 2026, stating that it has entered full-scale production. The Rubin platform consists of six new chips: Vera CPU, Rubin GPU, NVLink 6 switch, ConnectX-9 SuperNIC, BlueField-4 DPU, and Spectrum-6 Ethernet switch, designed to form an AI supercomputer that significantly reduces AI training time and lowers inference token generation costs. The training performance of the Rubin platform is 3.5 times that of the previous Blackwell generation, with software performance improved by 5 times, and the cost per token for inference reduced by 10 times compared to the Blackwell platform. Additionally, the number of GPUs required for training MoE models is reduced to one-fourth of the previous requirement [3][13][15]. - The Rubin platform integrates five key technologies to achieve breakthroughs in performance enhancement and cost reduction: 1) New NVLink interconnect technology ensures low latency and high bandwidth during multi-chip collaboration; 2) The third-generation Transformer engine optimizes for AI tasks, greatly improving model training and inference efficiency; 3) Confidential computing technology provides end-to-end security for sensitive AI data, meeting compliance needs in finance and healthcare; 4) RAS engine ensures stable performance under 24/7 high-load operation; 5) Vera CPU is specifically designed for agent inference [4][13]. - Major cloud providers, including Amazon AWS, Google Cloud, Microsoft Azure, and Oracle Cloud, have confirmed plans to deploy instances based on Vera Rubin in 2026, allowing global users to access top-tier AI computing power through cloud services. This will enable AI startups and SMEs, previously limited by high computing costs, to easily utilize the Rubin platform's powerful capabilities without significant hardware investment. Efficient computing power will accelerate breakthroughs in basic scientific research and technology, promoting deep applications of AI in healthcare, education, and environmental protection [5][14]. - The Rubin platform's dual breakthroughs in performance and cost reduction will significantly lower hardware procurement and operational costs for AI companies, facilitating the widespread adoption of AI applications such as intelligent customer service, autonomous driving, drug development, industrial quality inspection, and scientific research. It is recommended to pay attention to domestic and international AI computing infrastructure and related companies, including Cambrian, Zhongke Shuguang, Yonyou Network, Dingjie Zhizhi, Kingsoft Office, Tonghuashun, Jiao Dian Technology, Saiyi Information, and Fubo Group [6][15]. Market Overview - As of the week, the Shanghai Composite Index rose by 3.82%, the ChiNext Index increased by 3.89%, and the CSI 300 Index went up by 2.79%. The computer industry index surged by 8.49%, outperforming the Shanghai Composite Index by 4.67 percentage points, the ChiNext Index by 4.60 percentage points, and the CSI 300 Index by 5.70 percentage points. Year-to-date, the computer industry index has also increased by 8.49% [17][20]. - The computer industry index ranked 5th among 31 industry indices this week and 2nd among the four major TMT industries (electronics, communications, computers, media) [17]. Company Dynamics - The report highlights significant movements in the software and information technology sectors, with companies like Huijin Technology, Ersan Siwu, and Zhuoyi Information showing notable performance. Future investment opportunities are suggested in the financial IT, industrial software, and trusted innovation sectors, which are expected to see upward trends [22].

Market Insights - The market is experiencing a strong upward trend driven by positive factors such as stable prices and improved investment expectations, with overall liquidity remaining ample and trading activity active [3][4] - The CPI for December showed a year-on-year increase of 0.8%, better than the previous value of 0.7%, while the PPI decreased by 1.9%, a smaller decline compared to the previous 2.2% [15][19] - The recovery in PPI indicates price stabilization, which is expected to positively impact corporate profitability and enhance market risk appetite [4][15] Industry Configuration - The military industry sector has reached a historical high in trading congestion, with the defense military trading congestion at 9.4%, the highest since 2000, and the aerospace equipment sector also hitting a record high of 2.3% [21][22] - The growth phase of the market is not yet at its end, as key indicators such as the simultaneous new highs of major growth sectors have not been met, particularly in the electric equipment, computer, and communication sectors [25][26] - The current growth style is showing signs of acceleration, but it does not fully meet the characteristics of a strong market, indicating that the growth phase may still be in its early stages [29][31] Investment Opportunities - The AI industry chain is identified as the strongest mainline investment opportunity, with a focus on computing power, supporting components, and applications [34][35] - Other sectors to watch include storage and energy chains, military industry, and machinery equipment, which are expected to benefit from rising prices and demand driven by AI and geopolitical events [35][36]

Quantitative Models and Construction Methods 1. Model Name: Predatory Trading Game with Disinformation - **Model Construction Idea**: This model incorporates disinformation into a predatory trading game framework, where participants act based on distorted information, leading to deviations in equilibrium and market volatility[3][16][23] - **Model Construction Process**: 1. The model builds on the microstructure frameworks of Carlin et al. (2007) and Carmona & Yang (2011), introducing a victim (forced to adjust risky asset positions) and predators (seeking profit from the victim's constraints)[23] 2. The trading rate of participant \( n \) is defined as: $$ X^{n}(t) = X^{n}(0) + \int_{0}^{t}\alpha^{n}(s)\mathrm{d}s \tag{1} $$ where \( \alpha^{n} \) represents the trading rate, constrained by: $$ \alpha_{t}^{n} \in \mathbb{A}^{n} = \left\{\alpha_{t}^{n} \mid \mathcal{H}_{[0,T]}^{2}, X_{T}^{n} = 0 \right\} $$ 3. Temporary price impact is modeled as: $$ P_{t} - X_{t}^{0} = \lambda \sum_{i=1}^{N}\alpha_{t}^{i} \tag{4} $$ where \( \lambda \) is the elasticity factor[24] 4. Permanent price impact is expressed as: $$ \mathrm{d}X_{t}^{0} = \gamma \sum_{i=1}^{N}a_{t}^{i}\mathrm{d}t + \sigma\mathrm{d}W_{t} \tag{5} $$ where \( \gamma \) represents market plasticity, and \( \sigma \) is the volatility parameter[24] 5. Participants aim to maximize profits: $$ J^{n}(\mathbf{\alpha}) = \mathbb{E}\left(\int_{0}^{T}\alpha^{n}\left(X_{t}^{0} + \lambda\sum_{i=1}^{N}\alpha_{t}^{i}\right)\mathrm{d}t\right) \tag{8} $$ 6. Disinformation is introduced as a random distortion \( \tilde{x}_{0,1} = x_{0,1} + \epsilon \), where \( \epsilon \) represents the distortion[27] 7. The price process under disinformation is given by: $$ X_{t}^{0} = X^{0}(0) - \frac{1-e^{-\frac{N-1}{N+1}\frac{T_{T}}{\lambda}}}{1-e^{-\frac{N-1}{N+1}\frac{T_{T}}{\lambda}}}\gamma\left(\sum_{i=1}^{N}x_{0}^{i}+\bar{\nu}\right) + \frac{e^{\frac{T t}{\lambda}}-1}{e^{\frac{T t}{\lambda}}-1}\gamma\bar{\nu} + \sigma\left(W_{t}-W_{0}\right) $$ where \( \bar{\nu} \) is the error factor[30][31] - **Model Evaluation**: The model effectively captures the impact of disinformation on market dynamics, highlighting its role in amplifying volatility and disrupting equilibrium[16][30] --- Model Backtesting Results 1. Predatory Trading Game with Disinformation - **Maximum Price Fluctuation (MPF)**: $$ MPF_{\nu}(t_{*},t^{*}) := \operatorname*{max}_{t_{1},t_{2}\in[t_{*},t^{*}]}\left|\mathbb{E}\left(X_{t_{1}}^{0}-X_{t_{2}}^{0}\right)\right| $$ The model demonstrates that disinformation increases MPF, with a lower bound determined by: $$ MPF_{\tilde{\nu}^{*}}(0,T) \geq \operatorname*{min}_{\tilde{\nu}\in\mathbb{R}} MPF_{\tilde{\nu}}(0,T) = \gamma\sum_{i=1}^{N}x_{0}^{i} $$[34][37] - **Error Factor Impact**: The error factor \( \nu \) significantly influences price trajectories, with higher \( \nu \) leading to greater volatility[30][33] - **Tolerance Thresholds**: The system tolerates disinformation within specific boundaries \( b_{1} \) and \( b_{2} \), beyond which volatility escalates[38][40] --- Quantitative Factors and Construction Methods 1. Factor Name: Error Factor (\( \nu \)) - **Factor Construction Idea**: The error factor quantifies the degree and spread of disinformation in the market, serving as a key determinant of price volatility[30][33] - **Factor Construction Process**: 1. Defined as: $$ \tilde{\nu} := \frac{N_{w}}{N}\left(\tilde{x}_{0}^{1} - x_{0}^{1}\right) $$ where \( N_{w} \) is the number of misinformed participants, and \( \tilde{x}_{0}^{1} - x_{0}^{1} \) represents the distortion magnitude[30] 2. Generalized for multiple distortions: $$ \nu := \frac{1}{N}\,\sum_{l=1}^{\kappa}N_{w_{l}}\left(\bar{x}_{0,w_{l}}^{1} - x_{0}^{1}\right) $$ where \( \kappa \) is the number of distinct distortions[56] - **Factor Evaluation**: The error factor effectively captures the interplay between disinformation magnitude and its spread, providing insights into its impact on market dynamics[30][56] --- Factor Backtesting Results 1. Error Factor (\( \nu \)) - **Maximum Price Fluctuation (MPF)**: Higher \( \nu \) values correspond to increased MPF, with a minimum threshold determined by: $$ MPF_{\nu}(0,T) \geq \gamma\sum_{i=1}^{N}x_{0}^{i} $$[34][37] - **Tolerance Thresholds**: The system tolerates \( \nu \) within boundaries \( b_{1} \) and \( b_{2} \), with specific dependencies on market parameters and game duration[38][40] - **Dynamic Evolution**: The tolerance for \( \nu \) increases over time, reducing the potential for disinformation to amplify volatility in the long term[90][91] --- Additional Insights - **Information Updates**: New information can mitigate the impact of disinformation by adjusting the error factor \( \nu \), with the timing of updates being critical to minimizing volatility[84][92][95] - **Randomness and Misjudgment**: Random price movements can lead even informed participants to misjudge their information, complicating the detection and correction of disinformation[100][101][103] - **Profit Implications**: Disinformation affects profit expectations, with informed participants benefiting under certain conditions, while widespread disinformation can erode these advantages[49][51][56]

Group 1: Federal Reserve and Interest Rate Expectations - The next Federal Reserve chair is expected to lower interest rate cut expectations, impacting market sentiment positively[2] - The market anticipates a pause in rate cuts during the January FOMC meeting, with a focus on maintaining the current target rate[11] - The 1-year Treasury yield decreased from 1.402% to 1.337%, a drop of 6 basis points, indicating a shift in short-term interest rate expectations[2] Group 2: Domestic Market Trends - The Shanghai Composite Index rose from 3888.6 to 3968.84, a 2.06% increase, driven by improved macro policies and a significant rise in the construction PMI[2] - The growth style index increased from 8331.69 to 8741.04, reflecting a 4.91% rise, supported by favorable liquidity conditions[2] - The construction PMI improved significantly, indicating a potential stabilization in investment and economic recovery[17] Group 3: Commodity and Currency Insights - Brent crude oil prices fell from $58.55 to $57.42 per barrel, a decrease of 1.93%, suggesting a bearish outlook on oil due to supply dynamics[2] - The US dollar index decreased from 99.44 to 98.27, a drop of 1.18%, reflecting a slight weakening of the dollar amid lower rate cut expectations[2] - The COMEX copper price increased from $5.19 to $5.649 per pound, an 8.84% rise, indicating strong demand amid supply constraints[2]

- Theoretical new stock yield for Class A accounts with a scale of 2 billion is 3.80%[2][10] - Theoretical new stock yield for Class B accounts with a scale of 2 billion is 2.88%[2][10] - Theoretical new stock yield for Class A accounts with a scale of 10 billion is 1.74%[2][10] - Theoretical new stock yield for Class B accounts with a scale of 10 billion is 1.03%[2][10] - The average first-day increase for STAR Market stocks is 258.09%[2][20] - The average first-day increase for ChiNext stocks is 231.27%[2][20] - The number of valid quotation accounts for the latest STAR Market new stock is 4687 for Class A and 2065 for Class B[2][26] - The number of valid quotation accounts for the latest ChiNext new stock is approximately 3879 for Class A and 2610 for Class B[2][26] - The number of valid quotation accounts for the latest Shanghai Main Board new stock is 5200 for Class A and 2944 for Class B[2][26] - The number of valid quotation accounts for the latest Shenzhen Main Board new stock is 4683 for Class A and 2918 for Class B[2][26] - The highest first-day increase among newly listed stocks in the past month is 600.07% for Muxi Shares-U[37] - The highest fundraising amount among newly listed stocks in the past month is 80 billion for Moore Threads-U[37] - The highest full subscription yield among newly listed stocks in the past month is 671.65 thousand yuan for Moore Threads-U[41][43] - The full subscription yield for Muxi Shares-U is 343.75 thousand yuan[41][43] - The full subscription yield for Angrui Micro-UW is 42.24 thousand yuan[41][43] - The full subscription yield for China Uranium Industry is 36.49 thousand yuan[41][43] - The full subscription yield for Baiao Saitu is 14.67 thousand yuan[41][43] - The full subscription yield for Youxun Shares is 24.68 thousand yuan[41][43] - The full subscription yield for Tiansu Measurement is 5.54 thousand yuan[41][43] - The full subscription yield for Nabai Chuan is 7.86 thousand yuan[41][43] - The full subscription yield for Xihua Technology is 4.51 thousand yuan[41][43] - The full subscription yield for Jianxin Superconducting is 12.53 thousand yuan[41][43] - The full subscription yield for C Shuangxin is 12.56 thousand yuan[41][43] - The full subscription yield for C Yufan is 2.35 thousand yuan[41][43] - The full subscription yield for C Qiangyi is 40.15 thousand yuan[41][43] - The full subscription yield for C Xinguangyi is 9.93 thousand yuan[41][43] - The monthly offline new stock yield for Class A accounts with a scale of 2 billion in December 2025 is 195.55 thousand yuan[48][49] - The monthly offline new stock yield for Class B accounts with a scale of 2 billion in December 2025 is 94.99 thousand yuan[53][54] - The cumulative offline new stock yield for Class A accounts with a scale of 2 billion in 2025 is 3.80%[48][49] - The cumulative offline new stock yield for Class B accounts with a scale of 2 billion in 2025 is 2.88%[53][54]

Group 1 - The macro policy continues to strengthen, with a significant improvement in the construction PMI indicating that investment is expected to stabilize, and the possibility of a reserve requirement ratio cut is increasing, alongside currency appreciation and public fund allocation supporting micro liquidity, suggesting a gradual spring market may unfold [3][4][5] - The probability of a "good start" in the market is increasing, driven by continuous positive factors such as policy support in consumption and real estate, a significant improvement in construction PMI, and the potential for a reserve requirement ratio cut in January [4][5] - The economic fundamentals show marginal changes, with a focus on whether the investment sector can stabilize at the beginning of the year, as the construction PMI has rebounded significantly, indicating potential policy effectiveness in stabilizing investment [5][25][26] Group 2 - The industry configuration emphasizes "stories" and "performance" as key elastic opportunities, with the AI industry chain identified as the strongest mainline, focusing on computing power, supporting components, and key applications [6][40][41] - The first mainline is the AI industry chain, which is expected to continue its strong trend, with attention on computing power (CPO/PCB), supporting components (optical fibers/liquid cooling/power supply), and applications (robots/games/software) [40][41][43] - The second mainline focuses on sectors with high prosperity or significant event catalysts, including storage and energy storage chains, military industry, and machinery equipment, with expectations of long-term prosperity driven by AI demand and geopolitical events [41][42]

Investment Rating - The report provides a positive investment rating for the regenerative medicine sector, highlighting specific companies as key investment opportunities [1]. Core Insights - The regenerative medicine platform company is positioned in the high-end manufacturing field of neurosurgery, with a projected revenue growth of 30% and a net profit increase of 43% in Q1-Q3 of 2025. The company is expected to enter a product harvest phase from 2025 to 2027, stabilizing net profit margins and increasing profits [1]. - The report emphasizes the benefits of centralized procurement, with the company achieving significant growth by trading price for volume, projecting a 21% revenue increase and a 93% net profit growth in 2024 [1]. - The report identifies new product approvals and expanded indications as key growth drivers, with expectations of a 100% growth rate for certain products from 2025 to 2026 [1]. Summary by Relevant Sections Regenerative Medicine - The regenerative medicine company is expected to see a revenue increase of 30% and a net profit increase of 43% in Q1-Q3 of 2025, entering a product harvest phase from 2025 to 2027 [1]. - The company benefits from centralized procurement, achieving a 21% revenue increase and a 93% net profit growth in 2024 [1]. - New product approvals are anticipated to drive a 100% growth rate from 2025 to 2026 [1]. Automotive - The automotive sector shows a positive outlook with the introduction of a second brand expected to enhance performance significantly compared to Q3 [1]. - The company is projected to achieve a revenue of 1,099 million in 2026, with a growth rate of 37% [1]. Paper Industry - The white cardboard paper industry is expected to see a recovery in downstream demand, with the company positioned to benefit from high market concentration and improved pricing power [1]. - The company anticipates a revenue increase of 407 million in 2026, with a growth rate of 123% [1]. Chemical Industry - The chemical sector is experiencing high demand, with the agricultural market showing signs of recovery [1]. - The company is projected to achieve a revenue of 2,078 million in 2026, maintaining a growth rate of 14% [1]. Mining - The mining sector is benefiting from rising gold and copper prices, with the company expected to see a 54% increase in net profit [1]. - The projected revenue for 2026 is 50,478 million, with a growth rate of 10% [1].

Investment Rating - The industry investment rating is "Overweight" [2] Core Insights - Antibody-drug conjugates (ADCs) have become one of the most promising and fastest-growing treatment methods, combining the precise targeting characteristics of antibody drugs with the strong cytotoxicity of small molecule drugs. ADCs show better clinical trial results compared to traditional chemotherapy, which has high off-target toxicity and increased risk of infection. The ADC market is expected to enter an explosive growth phase, with projections indicating a global market size of $115.1 billion by 2032 [5][22][68]. Summary by Sections ADC Drug Development - ADCs are characterized by their core components: highly effective cytotoxic drugs, specific monoclonal antibodies, and linkers that connect the two. The development of ADCs has made significant progress, with the first ADC approved by the FDA in 2000. The market for ADCs has grown rapidly from $2 billion in 2018 to $10.4 billion in 2023, with a CAGR of 38.6% [15][22]. ADC Industry Outlook - The ADC industry is experiencing high demand for outsourcing services, with an outsourcing rate of approximately 70%, significantly higher than the 34% for traditional biopharmaceuticals. The global ADC CXO market is projected to reach $11 billion by 2030, with a CAGR of 28.4% from 2022 to 2030 [6][31][69]. Key Companies - **WuXi AppTec**: A leading global CRDMO company in bioconjugates, with rapid revenue growth from $0.096 billion in 2020 to $4.052 billion in 2024, and a projected capital expenditure exceeding 7 billion RMB by 2029 [7][39]. - **Hao Yuan Medicine**: Focused on ADC development for over a decade, with over 90 ADC projects and more than 1,200 clients. The company has established a comprehensive ADC CDMO platform and is expanding its production capacity [7][53]. - **Easton Pharmaceuticals**: Provides a full range of CDMO services for ADCs and has supported multiple projects, including the first dual-load ADC project approved for clinical trials [8][61]. - **Kelaiying**: A leading CDMO that has entered the biopharmaceutical sector, with significant growth in ADC-related business and ongoing expansion of production capacity [9][64].

Group 1: Paper Industry - The paper industry is currently in a passive destocking phase, characterized by economic recovery and demand resurgence, while production lags behind, leading to a decrease in finished product inventory and a slight increase in finished paper prices [5][10] - The white cardboard paper segment is identified as having the best market structure, with a high concentration of production capacity that enhances pricing power among leading companies [8][10] - From 2026 to 2030, the growth rate of white cardboard paper capacity is expected to slow down to between 2% and 5% annually, alleviating concerns about oversupply and allowing prices to recover [10][19] - As of December 11, 2025, the average price of white cardboard paper increased by 7.99% since August 2025, indicating a positive price trend [13][28] - The cost of white cardboard paper has shown a slight increase of 2.51% since August 2025, with margins improving as companies adjust to rising raw material costs [19][28] Group 2: Packaging Industry - The packaging industry is experiencing accelerated consolidation, with the acquisition of Zhongliang Packaging by Aorikin marking a significant shift in market dynamics [50][54] - Following the acquisition, Aorikin's market share in the two-piece can segment is projected to rise to 37%, enhancing its pricing power and profitability [54][56] - The global two-piece can market is expected to grow steadily, with a projected CAGR of 3% from 2025 to 2031, driven by the expanding beer market, which constitutes a significant portion of the demand [58]