Core Viewpoint - The article analyzes the investment strategy of the social security fund, highlighting its preference for stable investments in the banking sector and strategic positions in resource stocks, reflecting a balanced approach to risk and return [1][14]. Group 1: Social Security Fund Holdings - As of March 29, the social security fund appeared in the shareholder lists of 139 companies, demonstrating both patience and decisiveness in its investment approach [3]. - The fund maintains significant holdings in major banks, with Industrial and Commercial Bank of China and Bank of Communications holding 4.57% and 11.91% respectively, totaling over 180 billion yuan in market value [5]. - The fund's top holdings include China Life Insurance with a market value of 51 billion yuan, indicating a strong preference for stable, large-cap stocks [5]. Group 2: Investment in Specific Sectors - The social security fund slightly increased its stake in BYD by 2.05 million shares, bringing its total holdings to 39.02 million shares, valued at approximately 3.8 billion yuan [7]. - The fund's strategy includes a focus on financial stocks, with five of its top twenty holdings in the financial sector, including major banks and insurance companies [10]. - Resource stocks, particularly in aluminum and gold, are also favored, with companies like China Aluminum and Nanshan Aluminum being notable mentions [10][20]. Group 3: Long-term Holdings and Performance - The fund has consistently held shares in China Jushi for 36 quarters, reflecting confidence in the company's resilience and profitability, especially as its net profit nearly doubled in 2025 [15][17]. - The article notes that 19 out of 20 long-term holdings reported profits, with significant growth in companies like Jushi and Chifeng Gold, reinforcing the fund's strategy of investing in stable and profitable firms [23]. - The fund's long-term holdings strategy is complemented by a tactical approach in the fourth quarter, where it initiated positions in 35 new stocks and increased stakes in 43 others, indicating responsiveness to market changes [24]. Group 4: Recent Additions and Increases - In the fourth quarter, the fund significantly increased its holdings in companies like Hengmingda and Xinxing Technology, with some holdings doubling, reflecting confidence in their growth potential [26]. - New additions such as Shouhua Gas and Gao Neng Environment have shown impressive performance, with Shouhua Gas achieving a revenue increase of 82.06% in 2025 [28][31]. - Gao Neng Environment's net profit grew by 140% year-on-year, showcasing the fund's focus on companies with strong growth trajectories [34].

Group 1 - Baidu's Apollo Go has officially launched fully autonomous commercial operations in Dubai, deploying a fleet of thousands of vehicles in a dual-line strategy with partnerships with DTC and Uber [2] - The National Information Platform for New Energy Vehicle Battery Traceability has been officially launched, marking a new phase in digital and full-chain management of battery recycling in China [2] - Toyota plans to join the fuel cell joint venture Cellcentric, formed by Daimler Trucks and Volvo Group, as an equal shareholder [2] Group 2 - Tesla's Cybercab project faces significant setbacks as key executives continue to leave, with three high-level departures in just over a month [2] - Volvo Cars has agreed to convert approximately $274 million of unpaid shareholder loans into equity in Polestar, raising its stake to about 19.9% [2]

Investment Rating - The report maintains a "Strong Buy" recommendation for BYD, indicating an expected stock price increase exceeding 20% compared to the benchmark index [5]. Core Insights - BYD's revenue for 2025 reached 803.97 billion yuan, a year-on-year increase of 3.46%, while net profit attributable to shareholders was 32.62 billion yuan, a decrease of 18.97% year-on-year [1]. - The fourth quarter of 2025 saw a revenue of 237.70 billion yuan, a year-on-year decline of 13.52% but a quarter-on-quarter increase of 21.91% [2]. - The overseas market has become a significant growth engine, with exports surpassing 1 million vehicles for the first time, generating 310.74 billion yuan in overseas revenue, accounting for 38.65% of total revenue [3]. - The company has established a dual-driven model of "complete vehicle export + localized production," which is expected to mitigate some geopolitical trade barriers [4]. - R&D investment reached 63.4 billion yuan in 2025, a 17% increase year-on-year, significantly contributing to technological advancements [4]. Financial Performance - The gross profit margin for the fourth quarter was 17.44%, showing a slight year-on-year increase of 0.43 percentage points [2]. - The net profit margin for the fourth quarter was 4.01%, down 1.57 percentage points year-on-year [2]. - The company’s cash reserves stood at 167.8 billion yuan by the end of 2025, indicating a strong financial position [9]. - The projected net profit for 2026 is 47.43 billion yuan, reflecting a 45% year-on-year growth [8]. Market Expansion - BYD's electric vehicles are now present in 119 countries and regions, with significant growth in Latin America, Europe, and Southeast Asia [4]. - The company has successfully penetrated high-end markets with its premium brands, achieving a combined sales volume of 397,000 units, doubling year-on-year [4]. Future Outlook - The report anticipates continued strong demand in overseas markets, particularly in the context of geopolitical influences [9]. - The introduction of the second-generation blade battery is expected to enhance charging efficiency and low-temperature performance, driving domestic market momentum [9].

Investment Rating - The report maintains an "Accumulate" investment rating for the company [2] Core Insights - The company has significantly improved its operational quality, with its seating business entering a realization phase. In 2025, it achieved a revenue of 22.78 billion yuan, a year-on-year increase of 2.4%, and a net profit attributable to shareholders of 450 million yuan, a substantial increase of 180.0% [1][5] - The company has implemented cost reduction and efficiency enhancement measures, resulting in a historical high gross margin of 16.1% in 2025, up 2.1 percentage points from 2024 [5] - The passenger car seating business has shown rapid growth, with revenue reaching 5.62 billion yuan in 2025, a year-on-year increase of 80.7% [5] Financial Performance - In 2025, the company reported a net profit of 450 million yuan, a significant turnaround from a loss in the previous year, with a non-recurring net profit of 410 million yuan, up 175.0% year-on-year [1][5] - The fourth quarter of 2025 saw revenue of 6.65 billion yuan, with a quarter-on-quarter increase of 24.3% and a year-on-year increase of 18.6% [1] - The company’s gross margin reached 17.0% in Q4 2025, marking a five-year high [5] Business Segments - The company’s subsidiary, Jifeng, generated revenue of 8.28 billion yuan in 2025, a year-on-year increase of 28.7%, primarily driven by the growth in passenger car seating [5] - The Grammer segment reported revenue of 14.9 billion yuan in 2025, a decrease of 7.5% year-on-year, mainly due to the sale of the US TMD company, but it achieved a net profit of 180 million yuan, a significant recovery from a loss of 630 million yuan in the previous year [5] Future Outlook - The company aims for a 40-80% increase in revenue from the passenger car seating business in 2026, building on the strong performance in 2025 [5] - The report forecasts net profits of 860 million yuan, 1.14 billion yuan, and 1.42 billion yuan for 2026, 2027, and 2028, respectively, indicating a positive growth trajectory [6][9]

Group 1 - The core viewpoint of the article indicates mixed performance among Chinese concept stocks in the US market, with some stocks experiencing gains while others face declines [1] Group 2 - Baidu saw an increase of 0.7% in pre-market trading [1] - Pinduoduo experienced a slight rise of 0.1% [1] - BeiGene and Alibaba both declined by 0.1% [1] - JD.com fell by 0.5% [1] - NetEase dropped by 0.8% [1] - Li Auto experienced a decrease of 2% [1]

Quantitative Models and Construction GAN_GRU Model - **Model Name**: GAN_GRU - **Construction Idea**: The GAN_GRU model combines Generative Adversarial Networks (GAN) for feature generation and Gated Recurrent Units (GRU) for time-series feature encoding to create a stock selection factor[4][13][22] - **Construction Process**: 1. **GAN Component**: - **Generator**: Generates realistic data samples from random noise using the loss function: $$L_{G}\,=\,-\mathbb{E}_{z\sim P_{z}(z)}[\log(D(G(z)))]$$ where \(z\) represents random noise, \(G(z)\) is the generated data, and \(D(G(z))\) is the discriminator's output probability that the generated data is real[24][25][26] - **Discriminator**: Distinguishes real data from generated data using the loss function: $$L_{D}=-\mathbb{E}_{x\sim P_{data}(x)}[\log\!D(x)]-\mathbb{E}_{z\sim P_{z}(z)}[\log(1-D(G(z)))]$$ where \(x\) is real data, \(D(x)\) is the discriminator's output probability for real data, and \(D(G(z))\) is the output probability for generated data[27][29][30] - **Training Process**: Alternating training of the generator and discriminator until convergence[30][34] 2. **GRU Component**: - Two GRU layers (GRU(128,128)) followed by an MLP (256,64,64) to encode time-series features and predict future returns[22] - Input features include 18 price-volume metrics (e.g., closing price, turnover rate) sampled over 40 days to predict cumulative returns for the next 20 trading days[14][18][19] - Data preprocessing involves outlier removal, normalization, and cross-sectional standardization[18] - Training uses semi-annual rolling windows with hyperparameters such as batch size equal to the number of stocks, Adam optimizer, learning rate of \(1e-4\), and IC-based loss function[18][22] 3. **Feature Generation**: - GAN's generator processes raw price-volume time-series features (Input_Shape=(40,18)) and outputs transformed features with preserved time-series properties[37] - **Evaluation**: The model effectively combines GAN's feature generation capabilities with GRU's time-series encoding, providing robust predictive power for stock selection[4][22][37] --- Model Backtesting Results GAN_GRU Model Performance Metrics - **IC Mean**: 0.1095*** - **ICIR (Non-Annualized)**: 0.88 - **Turnover Rate**: 0.82X - **Recent IC**: 0.1008*** - **One-Year IC Mean**: 0.0514*** - **Annualized Return**: 36.03% - **Annualized Volatility**: 21.87% - **IR**: 1.55 - **Max Drawdown**: 27.29% - **Annualized Excess Return**: 21.87%[41][42][45] Industry-Level Performance - **Top 5 Industries by Recent IC**: - Media: 0.4279*** - Coal: 0.2355*** - Retail: 0.2003*** - Food & Beverage: 0.1701*** - Chemicals: 0.1395***[41][42][45] - **Top 5 Industries by One-Year IC Mean**: - Media: 0.1304*** - Steel: 0.1212*** - Retail: 0.1191*** - IT: 0.1064*** - Food & Beverage: 0.0988***[41][42][45] - **Top 5 Industries by Recent Excess Return**: - Media: 4.57% - Agriculture: 3.26% - Construction Materials: 3.19% - Light Manufacturing: 2.53% - Coal: 2.22%[45][46][48] - **Top 5 Industries by One-Year Average Excess Return**: - Real Estate: 1.83% - Retail: 1.41% - Consumer Services: 1.39% - Automotive: 1.18% - Utilities: 1.07%[45][46][48] --- Quantitative Factors and Construction GAN_GRU Factor - **Factor Name**: GAN_GRU - **Construction Idea**: Derived from the GAN_GRU model, this factor leverages GAN for feature generation and GRU for time-series encoding to predict stock returns[4][13][22] - **Construction Process**: - Input features include 18 price-volume metrics sampled over 40 days[14][18][19] - GAN generates transformed features while preserving time-series properties[37] - GRU encodes these features and outputs predicted returns as the factor[22][37] - Factor values undergo industry and market-cap neutralization and standardization[22] - **Evaluation**: The factor demonstrates strong predictive power across multiple industries and time periods, with significant IC values and excess returns[4][22][37] --- Factor Backtesting Results GAN_GRU Factor Performance Metrics - **IC Mean**: 0.1095*** - **ICIR (Non-Annualized)**: 0.88 - **Turnover Rate**: 0.82X - **Recent IC**: 0.1008*** - **One-Year IC Mean**: 0.0514*** - **Annualized Return**: 36.03% - **Annualized Volatility**: 21.87% - **IR**: 1.55 - **Max Drawdown**: 27.29% - **Annualized Excess Return**: 21.87%[41][42][45] Industry-Level Performance - **Top 5 Industries by Recent IC**: - Media: 0.4279*** - Coal: 0.2355*** - Retail: 0.2003*** - Food & Beverage: 0.1701*** - Chemicals: 0.1395***[41][42][45] - **Top 5 Industries by One-Year IC Mean**: - Media: 0.1304*** - Steel: 0.1212*** - Retail: 0.1191*** - IT: 0.1064*** - Food & Beverage: 0.0988***[41][42][45] - **Top 5 Industries by Recent Excess Return**: - Media: 4.57% - Agriculture: 3.26% - Construction Materials: 3.19% - Light Manufacturing: 2.53% - Coal: 2.22%[45][46][48] - **Top 5 Industries by One-Year Average Excess Return**: - Real Estate: 1.83% - Retail: 1.41% - Consumer Services: 1.39% - Automotive: 1.18% - Utilities: 1.07%[45][46][48]

Core Viewpoint - Skoda's exit from the Chinese market highlights the challenges faced by traditional automotive brands in adapting to rapidly changing consumer preferences and market dynamics, contrasting sharply with its success in India where it has effectively localized its strategy and offerings [4][30]. Group 1: Skoda's Performance in China - Skoda's sales in China plummeted from 340,000 units to just 15,000 units, representing a decline of over 95% in seven years [9]. - The brand's retail sales in January and February 2026 were only 300 and 357 units, respectively, with its main model, the Superb, selling as few as 25 units in a month [9]. - The decline was attributed to increased competition from Volkswagen's own models, which began to offer similar pricing, leading consumers to prefer the more recognized Volkswagen brand [10][12]. Group 2: Skoda's Strategy in India - In contrast, Skoda's sales in India reached 72,700 units in 2025, marking a 107% increase year-on-year, driven by a localized production strategy [17]. - The "India 2.0" project involved a €1 billion investment to develop a platform specifically for the Indian market, resulting in models like Kushaq and Slavia that cater to local needs [17][18]. - Over 90% of the components for the Kylaq model are locally sourced, demonstrating a commitment to local manufacturing and market adaptation [17]. Group 3: Market Dynamics and Consumer Preferences - The Chinese automotive market has shifted towards a focus on smart technology and advanced features, with local brands achieving a 35% penetration of L2-level intelligent driving, while Skoda's offerings lagged behind [12][13]. - In India, the market prioritizes reliability and cost-effectiveness, aligning well with Skoda's strengths in industrial efficiency and practical vehicle offerings [30][31]. - The decline of Skoda in China reflects broader trends affecting second-tier joint venture brands, as local manufacturers increasingly meet consumer demands for technology and features [14][30]. Group 4: Financial Performance and Brand Positioning - Skoda's profit margin reached 8.3%, significantly higher than the overall Volkswagen group margin of 4.7%, indicating its efficiency in cost management [5][24]. - The brand's strategy focuses on maximizing platform reuse and minimizing unnecessary features, which is perceived as practical in many global markets but not in China [22][23]. - The contrasting fortunes of Skoda in China and India illustrate the importance of aligning brand strategies with local market expectations and consumer behavior [30][31].

2025 年业绩符合我们预期 公司公布2025 业绩：全年实现收入391.7 亿元，同比+2.1%；归母净利润为11.9 亿元，同比-22.7%。其 中4Q25 营收118.8 亿元，同比+11.6%、环比+29.2%；归母净利润4.4 亿元，同比+18.1%、环比大幅增 长。2025 业绩符合我们预期。 维持2026 年盈利预测基本不变,首次引入2027 年净利润18.8 亿元。当前股价对应2026/2027 年8.9 倍/8.1 倍P/E。维持跑赢行业评级，由于板块估值下移，我们下调目标价10.7%至25.00 元,对应12.6 倍/11.5 倍 2026/2027 年P/E，有41.2%上行空间。 风险 新能源产品销量不及预期，行业竞争加剧，出口不及预期。 福特科技业务调整致业绩下滑，长期有望修复盈利水平。4Q25毛利率同环比-2.3ppt/-1.4ppt 至12.5%， 主要受新能源产品结构调整及终端价格承压所致。受控股子公司江铃福特科技调整影响，3Q25 转回递 延所得税资产5.8 亿元，拖累盈利。4Q25 开始已无该项影响，归母净利润环比大幅增长至4.4 亿元。 2025 年销管研费用率总计同比- ...

1. Report Industry Investment Rating No relevant information provided. 2. Core Views of the Report - Aluminum price high volatility may become the norm. The market anticipates and fully prices in expectations in advance, and it's easy to misstep the rhythm if chasing after the reality materializes. It's advisable to adopt a box strategy and conduct timely high - selling and low - buying [4]. - The impact of unexpected production cuts and shutdowns on supply far exceeds the new production stimulated by high profits, and the gap in the balance sheet may further widen this year [4]. - The expected scale of Russian aluminum inflow is downgraded, and the domestic net import situation is expected to ease [4]. - The rhythm of automobile production and sales at the beginning of the year is similar to that in 2024, and policies are expected to play a role during the year [4]. - For unilateral trading, the second quarter may be a consolidation period for aluminum prices, and it's advisable to allocate and increase aluminum assets in advance [4]. - For arbitrage, when there are expectations of energy disturbances, it's recommended to first focus on cross - market arbitrage opportunities and then on arbitrage opportunities among domestic non - ferrous metal varieties [4]. - For cross - variety arbitrage, the long - term copper - aluminum price ratio is expected to rise, and the zinc - aluminum price ratio is expected to fall. When short - term conflict expectations decline, attention can be paid to reverse opportunities in the price ratio [4]. 3. Summary by Relevant Catalogs 3.1 This Year's Trading Precautions - Commodity high volatility may become the norm. The market anticipates and fully prices in expectations in advance. In the aluminum market, there are cases such as the market speculating on the expectation of Middle - East production cuts in advance and the market not following through on supply - side positive news after an actual production cut [10]. - Pay attention to the periodic counter - trend of the macro - environment. The long - term upward - driving logic of aluminum remains unchanged, but when the market's consistent expectations are too high and hot money floods in, sharp retracements should be expected [13]. 3.2 Supply: Unexpected Production Cuts > Stimulated Restarts - Overseas aluminum plants have seen more unexpected production cuts and shutdowns than profit - stimulated early restarts this year. For example, plants in Qatar, Bahrain, and Mozambique have experienced production cuts or shutdowns, while some plants in Norway, Iceland, etc. have restarted production [15][19][20]. - Supply - side disturbances are long - term risks. Aluminum is highly sensitive to energy supply, and energy shocks can have a significant impact on aluminum production. The current energy situation is different from that in 2022, and the impact of the current geopolitical situation on aluminum prices is expected to be less than that of the Russia - Ukraine war in 2022 [24]. 3.3 Cross - Variety Arbitrage - In the long - term, the copper - aluminum price ratio is expected to rise and the zinc - aluminum price ratio is expected to fall. Aluminum is short in supply due to policy constraints, while copper and zinc are constrained by the shortage of ore. In the energy shock window, the price ratio trends may reverse temporarily. The zinc - aluminum price ratio is expected to decline in the long - term, and aluminum prices are expected to exceed zinc prices gradually [33][36]. 3.4 Cross - Market Arbitrage - The supply pattern of overseas shortage and domestic surplus makes cross - market arbitrage the optimal strategy when overseas electrolytic aluminum plants face supply disturbances. Historical data shows that when European aluminum plants cut production due to rising natural gas prices, the cross - market price ratio dropped and then gradually recovered [40]. 3.5 Balance Sheet: Widening Gap - Due to unexpected production cuts caused by the US - Iran conflict, the expected increase in overseas electrolytic aluminum production this year is revised downwards. The global and overseas electrolytic aluminum balance sheet gaps are expected to further widen. The peak of production capacity investment will occur in the first half of the year, and the production growth rate will slow down in the second half of the year, while demand is expected to pick up seasonally [42][44]. 3.6 Cost: Rising in the Second Quarter - The price of alumina is expected to decline due to the release of new production capacity but will remain higher than in the first quarter due to the stable and rising ore prices. As a result, the cost of electrolytic aluminum is expected to rise in the second quarter [48]. 3.7 Import: Downgraded Expectation of Russian Aluminum Inflow - Russia is the main source of China's aluminum ingot imports. Since February this year, the inflow of Russian aluminum has decreased year - on - year, and the scale of Russian aluminum imports for the whole year is expected to be downgraded. Although the import of aluminum ingots from Indonesia is expected to increase, it cannot fully make up for the reduction in Russian aluminum imports [54]. 3.8 Demand: Upgraded Forecast of Aluminum Product Exports - **Automobile**: The annual growth rate of automobile production is expected to be around 5%. The high - speed growth of automobile exports in the first two months of this year is expected to continue. The production rhythm this year is similar to that in 2024, and if the market faces excessive downward pressure, new policies are expected to be introduced [59][65]. - **Export**: The export of aluminum products at the beginning of the year was remarkable. The export structure shows that the growth rate of aluminum products has exceeded that of aluminum materials, and the export of terminal products such as wheels is stable. The net export growth rate of aluminum products for the whole year is expected to be upgraded to 15% [68].

1. Report Industry Investment Rating No information provided in the given content. 2. Core Viewpoints of the Report - High - frequency economic data focuses on four aspects: production - end heat is differentiated with rising coke oven, blast furnace, and PX operating rates, and asphalt at a low level and declining, while tire operating rates remain stable; commercial housing transaction area rebounds, and the industrial land area decreases; price trends diverge, with prices of crude oil, coking coal, and non - ferrous metals rising, and agricultural product prices continuing the seasonal downward trend; residents' travel heat rebounds overall, with increases in subway passenger volume and domestic and international flight operations. Short - term concerns are on the impact of imported inflation on the price end and the real - estate recovery situation [2][31]. 3. Summary by Relevant Catalogs Production - Steel: In the week of March 27, the coke oven capacity utilization rate increased by 0.87pct, the blast furnace operating rate increased by 1.25pct, and the rebar production decreased by 5.46 tons [9]. - Petroleum asphalt: The operating rate decreased by 2.5pct compared with the previous week. On March 25, the operating rate of domestic petroleum asphalt plants was 19.3% [9]. - Chemical industry: The PX operating rate increased by 1.01pct compared with the previous week, and the PTA operating rate remained flat [9]. - Automobile tires: The all - steel tire operating rate increased by 0.03pct, and the semi - steel tire operating rate decreased by 0.01pct compared with the previous week [10]. Demand - Real estate: In the week of March 29, the commercial housing transaction in 30 large and medium - sized cities increased, the inventory - to - sales ratio of commercial housing in 10 large cities decreased, the land supply area in 100 large and medium - sized cities decreased, and the transaction premium rate of residential land in 100 large and medium - sized cities decreased [13]. - Movie box office: In the week of March 22, the total national movie box office revenue was 327 million yuan, a decrease of 45 million yuan compared with the previous week [13]. - Automobile sales: In the week of March 22, the daily average retail sales of national passenger car manufacturers increased by 6,293 vehicles, and the daily average wholesale sales increased by 4,809 vehicles compared with the previous week [17]. - Shipping freight rates: In the week of March 27, the Shanghai Containerized Freight Index (SCFI) increased by 119.82 points, the China Containerized Freight Index (CCFI) increased by 18.43 points, and the Baltic Dry Index (BDI) decreased by 25 points [20]. Prices - Energy: On March 27, the settlement price of Brent crude oil futures was 112.57 US dollars per barrel, with a weekly change of 0.34%; the settlement price of coking coal futures was 1,218 yuan per ton, with a weekly change of 4.82% [22]. - Metals: On March 27, the closing price of LME copper futures was 12,141 US dollars per ton, with a weekly change of 2.59%; the closing price of LME aluminum futures was 3,284.5 US dollars per ton, with a weekly change of 2.9%; the closing price of LME zinc futures was 3,106.5 US dollars per ton, with a weekly change of 1.65%; the settlement price of domestic rebar futures was 3,121 yuan per ton, with a weekly change of - 0.16% [23]. - Agricultural products: On March 27, the 200 - index of agricultural product wholesale prices decreased by 1.29% week - on - week. The weekly changes in the prices of pork, eggs, vegetables, and fruits were - 1.56%, 1.71%, - 1.85%, and 0.26% respectively [25]. Logistics - Subway passenger volume: On March 29, the seven - day moving average of Beijing's subway passenger volume increased by 61,700 person - times, with a weekly change of 0.61%; the seven - day moving average of Shanghai's subway passenger volume increased by 192,900 person - times, with a weekly change of 1.81% [27]. - Flight operations: On March 29, the seven - day moving average of domestic (excluding Hong Kong, Macao, and Taiwan) flight operations increased by 80.43 flights, with a weekly change of 0.61%; the seven - day moving average of domestic (Hong Kong, Macao, and Taiwan) flight operations increased by 11.29 flights, with a weekly change of 3.08%; the seven - day moving average of international flight operations increased by 0.71 flights, with a weekly change of 0.04% [29]. - Urban congestion: On March 29, the seven - day moving average of the peak congestion index in first - tier cities was 1.7, a decrease of 0.04 compared with the previous week, with a weekly change of - 2.21% [29].