Investment Rating - The report initiates coverage with a "Buy" rating for the company [2][8]. Core Insights - The company is a leader in low-power Bluetooth SoC, focusing on wearable devices and AIoT applications, with significant market share in TWS earphones and smartwatches [7][8]. - Revenue projections for 2025-2027 are estimated at 42.53 billion, 54.41 billion, and 67.11 billion yuan, with corresponding growth rates of 30%, 28%, and 23% [8]. - The company has a strong competitive position due to its advanced technology and established relationships with major brands like Samsung, OPPO, and Xiaomi [7][8]. Financial Data and Profit Forecast - Total revenue for 2024 is projected at 3,263 million yuan, with a year-on-year growth rate of 49.9% [6]. - The net profit attributable to the parent company is expected to reach 798 million yuan in 2025, reflecting a growth rate of 73.2% [6]. - The company maintains a low asset-liability ratio of 7.59% and a high return on equity (ROE) of 10.9% in 2025 [6]. Market Position and Growth Drivers - The company holds approximately 10% of the global TWS main control chip market, ranking fourth in terms of shipment volume [7]. - The smart wearable chip segment is expected to see significant growth, with revenue projected to reach 10.45 billion yuan in 2024, a 116% increase year-on-year [7]. - The introduction of AI glasses and the development of proprietary ISP technology position the company for future growth in high-performance wearable SoCs [7]. Product Development and Technology - The company has developed a unified software and algorithm framework that enhances customer stickiness and supports multiple product lines [7]. - The BES2800 chip, built on a 6nm process, integrates advanced features such as dual-core Cortex-M55 and self-developed NPU, catering to the needs of AI and low-power applications [7][8]. - The company’s strategy of "one chip for multiple uses" allows for a versatile application of its chips across various devices, enhancing platform reuse [31]. Competitive Landscape - The company is positioned against both domestic and international competitors, with a focus on high-end markets and a strategy to maintain technological leadership [10][38]. - The competitive advantage is bolstered by a strong customer base, with the top five clients accounting for 74% of sales in 2024 [38]. Valuation Metrics - As of November 17, 2025, the company's price-to-earnings (PE) ratio is projected at 45 times for 2025 and 34 times for 2026, indicating a potential upside of 29% compared to comparable companies [8].

Revenue and Expenditure Overview - In the first ten months of 2025, national general public budget revenue reached 186,490 billion yuan, a year-on-year increase of 0.8%[6] - National general public budget expenditure was 225,825 billion yuan, with a year-on-year growth of 2%[6] Fiscal Spending Decline - In October 2025, the year-on-year growth rate of broad fiscal expenditure plummeted to -19.1%, a decrease of 21.4 percentage points compared to September[1] - The budget completion rate for broad fiscal expenditure in October was 5.6%, lower than 7.2% in 2024 and the five-year average of 6.2%[7] Factors Contributing to Decline - The decline in fiscal expenditure is attributed to three main factors: high base effect from 2024, revenue decline, and a decrease in government debt financing[1] - Broad fiscal revenue in October fell by -0.6%, a drop of 3.8 percentage points from September, with government fund revenue down by -18.4%[4] Government Debt Financing - Government net financing in October 2025 decreased by 5,602 billion yuan year-on-year, contributing to the slowdown in fiscal expenditure growth[3] - The rapid use of fiscal funds in 2025, including special bonds and support for commercial banks, has been largely completed by mid-August[3] Future Outlook - With the implementation of 500 billion yuan in new policy financial tools and another 500 billion yuan in local debt limits, there may be a recovery in fiscal expenditure growth towards the end of the year[4] - The support from "quasi-fiscal" funds is expected to accelerate as these funds are deployed in key sectors like digital economy and artificial intelligence[4]

Revenue and Expenditure Overview - In the first ten months of 2025, the national general public budget revenue was 186,490 billion yuan, a year-on-year increase of 0.8%[6] - National general public budget expenditure reached 225,825 billion yuan, a year-on-year increase of 2%[6] Fiscal Spending Decline - In October 2025, the year-on-year growth rate of broad fiscal expenditure dropped to -19.1%, a decrease of 21.4 percentage points from September[1] - The completion rate of the broad fiscal expenditure budget in October was 5.6%, lower than 7.2% in 2024 and the five-year average of 6.2%[7] Factors Contributing to Decline - The decline in fiscal expenditure was attributed to a high base effect from 2024, a drop in revenue, and a decrease in government debt financing[1] - Broad fiscal revenue in October fell by -0.6%, a decline of 3.8 percentage points compared to September[4] Government Debt Financing - Government net financing in October 2025 decreased by 5,602 billion yuan year-on-year, contributing to the slowdown in fiscal expenditure growth[12] - The rapid use of fiscal funds in 2025, including special bonds and other projects, limited the available financing for October[12] Future Outlook - With the introduction of 5,000 billion yuan in new policy financial tools and local debt limits, there may be a recovery in fiscal expenditure growth towards the end of the year[18] - The support from "quasi-fiscal" funds is expected to accelerate as these funds are deployed in key sectors like digital economy and artificial intelligence[14]

Investment Rating - The investment rating for the airline industry is "Overweight" indicating a positive outlook for the sector [2][5]. Core Insights - The October National Day holiday has driven an increase in travel demand, with passenger transport volume reaching approximately 68.41 million, a year-on-year growth of 6.7% compared to 2024 [2]. - Domestic capacity increased by 2.1% year-on-year, while domestic passenger flow grew by 4.5% [2]. - The average aircraft utilization rate in October was 7.99 hours per day, reflecting a 1.4% increase year-on-year [2]. - Airlines are increasing capacity, with passenger turnover growth outpacing capacity growth. For instance, China Eastern Airlines and China Southern Airlines both saw a 7% increase in ASK (Available Seat Kilometers) compared to 2024 [2][3]. - The international market has shown recovery, with international flights reaching approximately 60,000, recovering to 90% of the levels seen in 2019 [2]. - The report highlights a significant increase in international capacity for airlines like China Eastern Airlines and Spring Airlines, with year-on-year ASK growth of 14% and 153% respectively compared to 2019 [2][3]. - The report suggests that the airline industry is at a turning point, with potential for significant improvement in airline profitability due to rising demand and constrained supply [2]. Summary by Sections Domestic Market - Overall demand growth is outpacing capacity growth, with Spring Airlines showing significant increases in both capacity and volume [2]. - ASK and RPK for major airlines like China Southern and China Eastern have shown positive growth compared to 2024 and 2019 [3]. International Market - Major airlines have exceeded 2019 levels in international operations, with significant year-on-year growth in ASK and RPK for airlines like China Eastern and Spring Airlines [2][3]. Regional Market - Capacity and volume recovery is uneven across regions, with China Southern and China Eastern showing strong recovery compared to 2019 [2][3]. Investment Analysis - The report emphasizes the unprecedented challenges in the aircraft manufacturing chain and the aging fleet, predicting a continued supply constraint over the next 5-10 years [2]. - The report recommends focusing on the airline sector, highlighting strong supply logic and elastic demand, with specific recommendations for airlines such as China Eastern, China Southern, and Spring Airlines [2][5].

Group 1 - The steel industry is expected to see improved profitability due to three main factors: declining raw material prices, supply-side adjustments, and resilient demand from manufacturing [3][5][9] - The West Simandou iron ore project is set to commence production in November 2025, significantly increasing iron ore supply and contributing to a downward trend in iron ore prices [3][71] - Government policies aimed at reducing overcapacity and promoting energy efficiency are expected to accelerate the exit of outdated production capacity, leading to a more optimized supply structure in the steel industry [3][16][10] Group 2 - Demand for steel is projected to stabilize in the construction sector, while manufacturing demand remains resilient, particularly for flat steel and special steel products [3][19][25] - The overall steel demand in China is forecasted to decline slightly, with total demand expected to be 9.05 billion tons in 2025, a decrease of 0.11% from 2024 [19][20] - The construction sector's share of steel demand is decreasing, while the manufacturing sector's share is increasing, indicating a shift in consumption patterns [3][19] Group 3 - The report highlights that the profitability of steel companies is recovering, with a stronger performance expected in flat steel compared to long steel products [3][85][82] - The average profit margin for steel companies is projected to improve as cost pressures ease, with a focus on companies with stable demand and low valuations [3][87][90] - Investment recommendations include focusing on companies like Baosteel, Nanjing Steel, and Hualing Steel, which are expected to benefit from the shift towards manufacturing [3][95][94]

Quantitative Models and Construction Methods 1. Model Name: Mean-Variance Model - **Model Construction Idea**: The model determines the optimal portfolio by balancing expected returns and risks, based on the mean and variance of asset returns[8] - **Model Construction Process**: 1. Define the portfolio return as a random variable 2. Use the expected return ($E[R]$) and variance ($Var[R]$) to measure the portfolio's performance 3. Solve the optimization problem to maximize expected return for a given level of risk or minimize risk for a given level of return - Formula: $ \text{Minimize: } \sigma_p^2 = \sum_{i=1}^n \sum_{j=1}^n w_i w_j \sigma_{ij} $ $ \text{Subject to: } \sum_{i=1}^n w_i = 1 $ Where $w_i$ is the weight of asset $i$, $\sigma_{ij}$ is the covariance between assets $i$ and $j$[8] - **Model Evaluation**: Flexible in adjusting portfolios based on expected returns and risks, but struggles to incorporate new market dynamics and subjective views[8] 2. Model Name: Black-Litterman Model - **Model Construction Idea**: Combines the Bayesian framework with the mean-variance model to incorporate subjective views into the portfolio optimization process[8] - **Model Construction Process**: 1. Start with a prior distribution of expected returns based on market equilibrium 2. Incorporate subjective views as additional constraints 3. Use the Bayesian approach to update the prior distribution with subjective views to form a posterior distribution - Formula: $ \Pi = \tau \Sigma w_{mkt} $ $ E[R] = \left( \tau \Sigma^{-1} + P^T \Omega^{-1} P \right)^{-1} \left( \tau \Sigma^{-1} \Pi + P^T \Omega^{-1} Q \right) $ Where $\Pi$ is the implied equilibrium return, $\tau$ is a scaling factor, $\Sigma$ is the covariance matrix, $w_{mkt}$ is the market portfolio weights, $P$ is the view matrix, $\Omega$ is the uncertainty matrix, and $Q$ is the view vector[8] - **Model Evaluation**: Flexible and allows integration of subjective views, but requires strong assumptions about return distributions and is computationally complex[8] 3. Model Name: Risk Parity Model - **Model Construction Idea**: Focuses on balancing the risk contribution of each asset in the portfolio rather than their weights[7] - **Model Construction Process**: 1. Calculate the risk contribution of each asset: $RC_i = w_i \cdot \sigma_i \cdot \rho_{i,p}$ 2. Adjust weights to equalize the risk contributions across all assets - Formula: $ RC_i = w_i \cdot \sigma_i \cdot \rho_{i,p} $ Where $RC_i$ is the risk contribution of asset $i$, $w_i$ is the weight of asset $i$, $\sigma_i$ is the standard deviation of asset $i$, and $\rho_{i,p}$ is the correlation between asset $i$ and the portfolio[7] - **Model Evaluation**: Enhances risk control and can incorporate multiple risk dimensions, but lacks a mechanism to optimize returns and may struggle with unrecognized risks[7] 4. Model Name: All-Weather Model (Bridgewater) - **Model Construction Idea**: Aims to achieve stable performance across all economic environments by focusing on risk parity under growth and inflation sensitivity[11] - **Model Construction Process**: 1. Classify assets based on their sensitivity to growth and inflation 2. Allocate weights to achieve risk parity across these dimensions - Formula: Not explicitly provided, but the model emphasizes balancing risk rather than returns[11] - **Model Evaluation**: Stable allocation structure with a focus on low-risk assets, but may underperform in specific market conditions due to its heavy reliance on bonds and cash[15] --- Model Backtesting Results 1. Mean-Variance Model - **Maximum Drawdown**: Exceeded 4% in some periods (e.g., 2018-2019), but quickly recovered[57] - **Sharpe Ratio**: Higher than benchmarks in optimistic scenarios, demonstrating strong risk-adjusted returns[57] 2. Black-Litterman Model - **Maximum Drawdown**: Similar to the mean-variance model, with better adaptability to subjective views[57] - **Sharpe Ratio**: Improved compared to the mean-variance model due to the integration of subjective views[57] 3. Risk Parity Model - **Maximum Drawdown**: Generally lower than the mean-variance model, reflecting its focus on risk control[57] - **Sharpe Ratio**: Moderate, as the model does not explicitly optimize returns[57] 4. All-Weather Model - **Maximum Drawdown**: Comparable to fixed-ratio models, with a focus on stability[15] - **Sharpe Ratio**: Similar to benchmarks, reflecting its conservative allocation[15] --- Quantitative Factors and Construction Methods 1. Factor Name: Monthly Frequency Slicing - **Factor Construction Idea**: Use historical slices of monthly data to reflect maximum drawdown and market sentiment[41] - **Factor Construction Process**: 1. Extract rolling 20-day returns for each year 2. Use the bottom 20% quantile to estimate pessimistic scenarios and maximum drawdown - Formula: $ \text{Max Drawdown} = \text{Min} \left( \frac{P_t - P_{peak}}{P_{peak}} \right) $ Where $P_t$ is the price at time $t$, and $P_{peak}$ is the peak price[41] - **Factor Evaluation**: Effective in capturing extreme market conditions, but limited in predicting long-term trends[41] 2. Factor Name: BootStrap State Space - **Factor Construction Idea**: Use BootStrap sampling to create a state space of asset returns under different scenarios[45] - **Factor Construction Process**: 1. Sample historical data with replacement to create new sequences 2. Calculate return distributions for pessimistic, neutral, and optimistic scenarios - Formula: $ F = B - \alpha \cdot C $ Where $F$ is the objective function, $B$ is the expected return under risk constraints, $C$ is the penalty for exceeding risk constraints, and $\alpha$ is the penalty parameter[50] - **Factor Evaluation**: Provides a robust framework for scenario analysis, but computationally intensive[45] --- Factor Backtesting Results 1. Monthly Frequency Slicing - **Maximum Drawdown**: Successfully captured extreme drawdowns in historical data, with 90% coverage for A-shares and Hong Kong stocks[40] - **Sharpe Ratio**: Not explicitly provided, but the factor is more focused on risk control[40] 2. BootStrap State Space - **Maximum Drawdown**: Achieved a 4% maximum drawdown target in most scenarios, with only minor deviations in extreme conditions[57] - **Sharpe Ratio**: Optimized under different scenarios, with higher ratios in optimistic environments[57]

Group 1: Power Sector - The overall electricity consumption in China increased by 4.6% year-on-year in the first three quarters of 2025, with a total of 77,675 billion kilowatt-hours [7][19] - The electricity consumption in July and August 2025 exceeded 1 trillion kilowatt-hours for two consecutive months, indicating a normalization of high electricity usage [8][10] - The contribution of the secondary industry to electricity consumption growth has decreased to below 50%, with significant increases from the tertiary industry and urban-rural residential electricity usage [19][30] Group 2: Thermal Power - The improvement in capacity electricity prices is expected to enhance the profitability and dividend capacity of thermal power companies [3] - The stable capacity revenue from thermal power effectively hedges against fluctuations in electricity prices, transitioning the profit structure from reliance on electricity sales to a diversified model including capacity and auxiliary service revenues [40][41] - Recommended companies include Guodian Power, Inner Mongolia Huadian, and Datang Power, which have a high proportion of large units [3][40] Group 3: Hydropower - The hydropower sector is expected to benefit from improved financial conditions due to reduced capital expenditures and interest expenses during the interest rate decline cycle [56][59] - The depreciation of the Three Gorges hydropower units is expected to peak in 2026, opening up profit space for hydropower companies [52][59] - Recommended companies include Yangtze Power, Guotou Power, and Chuanwei Energy, which are major players in the hydropower sector [56][59] Group 4: Nuclear Power - The nuclear power sector is expected to see growth as the approval of 10 new units in 2025 continues the high growth trend, enhancing the valuation of nuclear power companies [3][41] - Recommended companies include China National Nuclear Power and China General Nuclear Power, which are positioned to benefit from this growth [3][41] Group 5: Renewable Energy - Wind and solar installations are expected to maintain high growth, with a total installed capacity of 1.7 billion kilowatts by September 2025, aiming for 3.6 billion kilowatts by 2035 [41][39] - The introduction of local renewable energy market rules is expected to stabilize the returns of existing projects, enhancing the long-term value for green electricity operators [3][41] - Recommended companies include Xintian Green Energy, Funiu Co., Longyuan Power, and China Resources Power [3][41] Group 6: Natural Gas - The natural gas sector is entering a cost reduction cycle, with falling oil and gas prices since early 2025, which is expected to improve profitability for urban gas companies [3][41] - The anticipated cold winter due to the La Niña effect is expected to boost gas sales volume growth in the fourth quarter of 2025 [3][41] - Recommended companies include China Resources Gas, Hong Kong and China Gas, and Kunlun Energy, which are quality urban gas enterprises [3][41]

Group 1 - The report highlights a strong recovery in the cement and fiberglass sectors, with unique performance from various consumer building materials stocks driven by anti-involution, specialty fabrics, and overseas expansion [3][11]. - In 2026, the outlook for the building materials industry includes accelerated overseas expansion, benefiting companies that have adjusted their channel, product, and sales structures over the past four years [3][11]. - The report identifies key companies to watch, including Huaxin Cement, Keda Manufacturing, and Western Cement, which are positioned well for overseas growth [3][17]. Group 2 - The building materials sector outperformed the CSI 300 index with a cumulative increase of 22.35% from the beginning of 2025 to November 14, 2025, driven by high demand for specialty fiberglass and other catalysts [8][11]. - The report notes that the cement and fiberglass sectors have achieved profit recovery, with the fiberglass sector showing significant revenue growth [11][17]. - The report emphasizes the importance of overseas markets, particularly in Africa, where population growth and urbanization present substantial opportunities for building materials companies [27][35]. Group 3 - The report discusses the transformation of distribution channels in the consumer building materials sector, highlighting companies like Sanhe Tree and Dongpeng Holdings that have successfully adapted to market changes [3][17]. - The consumer building materials segment is expected to benefit from a recovery in domestic demand, with companies like China Liansu and Beixin Building Materials showing potential for growth [3][11]. - The report indicates that the fiberglass sector is experiencing stable profit improvements, with companies like China Jushi and China National Building Material expected to perform well [3][17]. Group 4 - The report outlines the significant growth potential in the fiberglass market, with expectations for continued high demand for specialty fabrics [3][17]. - The report highlights the competitive advantage of Chinese companies in the global market, particularly in cement production, where China accounts for 47% of global output [34][35]. - The report emphasizes the importance of overseas expansion for companies like Huaxin Cement and Keda Manufacturing, which are actively increasing their production capacities in emerging markets [42][54].

Investment Rating - The industry investment rating is "Overweight" indicating a positive outlook for the sector compared to the overall market performance [8]. Core Insights - The report emphasizes that intelligence will be a key theme in the market for 2026, with investment opportunities extending beyond smart driving to areas like Robotaxi. A data closed loop is identified as the core starting point for achieving full-stack self-research, which differs fundamentally from mere data collection [1][3]. - The establishment of a data closed loop is crucial for filtering effective information from massive data, enabling machines to understand data, feedback to correct models, and perform OTA updates for secondary verification. This requires not only data ownership but also the ability to identify data gaps and utilize data to enhance models [1][3]. - The report suggests that the scale of the data closed loop team (e.g., whether it reaches a hundred members) and related investments should be key indicators for assessing a company's commitment and capability for self-research [1][3]. Summary by Sections Data Closed Loop - The report highlights that when algorithm models are truly driven by PB-level data, it will create a competitive barrier that is difficult to replicate. Even if competitors acquire model architectures or poach key personnel, lacking a substantial underlying data accumulation will hinder their ability to replicate similar algorithm capabilities in the short term [2][4]. - Building a solid data closed loop is expected to provide companies with a certainty of competitive advantage for six months to a year. Companies like Xiaopeng, Li Auto, and Huawei are noted to have established a leading advantage in the smart driving sector, with a high degree of technical moat [2][4]. Investment Recommendations - The report recommends focusing on domestic strong alpha manufacturers such as BYD, Geely, and Xiaopeng, as well as companies that represent the trend of intelligence like Huawei's HarmonyOS. Attention is also drawn to companies like JAC Motors and Seres, with specific recommendations for Li Auto, Kobot, Desay SV, and Jingwei Hengrun [2]. - For state-owned enterprise integration, the report suggests monitoring SAIC Motor, Dongfeng Motor Group, and Changan Automobile. Additionally, it highlights component companies with strong performance growth and capabilities for overseas expansion, recommending Fuyao Glass, New Spring, Fuda, Shuanghuan Transmission, and Yinlun [2].

Group 1 - The beauty and personal care sector has shown a recovery in 2025, with the SW Beauty Index rebounding after a decline from 2022 to 2024, achieving a maximum increase of over 15% and becoming a key area in new consumption [3][9][10] - The cosmetics segment is characterized by intense competition among brands, with domestic brands making significant strides in R&D and distribution, while international brands are adopting localized strategies to regain market share [3][20][25] - The medical beauty market is transitioning from a blue ocean to a red ocean, with domestic companies expected to become major competitors by focusing on affordable and specialized products [3][19][24] Group 2 - The e-commerce operation sector is undergoing a transformation, with companies like RuYuchen and Shuiyang Co. leveraging brand incubation and AI to create new growth avenues [3][19] - Key investment recommendations include domestic brands with strong channel and brand matrices such as MaoGePing, ShangMei Co., and PoLaiYa, as well as companies in the medical beauty sector like AiMeiKe and LongZi Co. [3][19][24] - The report emphasizes the importance of brand matrix construction and product innovation in the cosmetics industry, with companies like ShangMei Co. and PoLaiYa leading the way [3][31][40] Group 3 - The skincare and makeup market is expected to enter a phase of consolidation, with strong brands likely to thrive while weaker ones may struggle [23][24] - The market share of domestic brands is increasing, with a notable decline in the market share of international brands, indicating a significant opportunity for domestic players [25][30] - The report highlights the importance of adapting to changing consumer preferences and channel dynamics, with a focus on online platforms and promotional strategies to enhance brand visibility [48][52][53]