Sales Performance - In the third week of May (5/12-5/18), the top three new force terminal sales were Li Auto (9,200 units, up 12.2% MoM), Leap Motor (7,500 units, down 3.8% MoM), and AITO (7,500 units, unchanged) [9] - The top three brand terminal sales during the same period were BYD (55,700 units, down 19.4% MoM), Volkswagen (29,400 units, down 35.9% MoM), and Toyota (25,400 units, down 19.4% MoM) [9] New Vehicle Releases - New vehicles released from May 17 to May 23 include BYD e7 (priced between 103,800 to 115,800 CNY) and Deep Blue S09 (priced between 239,900 to 309,900 CNY) [10] Lithium Battery Market Insights - As of May 23, the average price of battery-grade lithium carbonate was reported at 63,000 CNY per ton, continuing a downward trend due to an oversupply situation [11] - Recent price fluctuations in battery cells, modules, and PACKs indicate a stable yet pressured market environment for lithium carbonate [11] Investment and Financing Events - From May 17 to May 23, three significant financing events in the smart vehicle sector occurred, including: - Feiman Technology completed an angel round financing of several million CNY to accelerate the development of non-inflatable tire technology [18] - Heimholtz completed a C round financing to enhance R&D in thermal management systems for new energy vehicles [19] - Shiyu Technology completed an A round financing, with investors including Dongfang Chanyin and Anhui Haiyuan Capital [20] Risk Factors - Potential risks include lower-than-expected sales of new energy vehicles, changes in production plans, and delays in product development [23]

Investment Rating - The report assigns an "Overweight" rating for the non-ferrous metals industry [1] Core Viewpoints - The macroeconomic disturbances, including uncertainties surrounding Trump's tax reform and tariff threats, are expected to lead to fluctuations in metal prices. Domestic macroeconomic benefits may offset some overseas impacts, but attention should be paid to downstream demand feedback during the traditional off-season [3][6] - Gold prices are anticipated to continue fluctuating due to market sentiment and geopolitical tensions, while industrial metals are expected to experience price volatility influenced by macroeconomic factors and seasonal demand [4][6] Summary by Sections 1. Cycle Assessment - Trump's tax reform has passed in the U.S. House Budget Committee, raising concerns about the U.S. fiscal deficit and increasing market risk aversion, leading to a rise in gold prices. However, uncertainties remain regarding the final implementation of the tax reform and tariff threats, resulting in expected price fluctuations for gold and industrial metals [4][6] 2. Industry and Stock Performance - As of May 23, the SW non-ferrous metals index increased by 1.25%, ranking 4th among all industries [11] 3. Metal Prices and Inventory 3.1 Industrial Metals - As of May 23, copper prices on SHFE decreased by 0.45% to 77,790 CNY/ton, while LME copper increased by 1.72% to 9,610 USD/ton. The overall inventory of copper decreased by 8.76% week-on-week [21][22][9] 3.2 Precious Metals - As of May 23, SHFE gold prices rose by 3.76% to 780.10 CNY/gram, while COMEX gold increased by 6.25% to 3,386.50 USD/ounce. The total gold inventory on COMEX decreased by 3.76 tons [24][25] 4. Macro Data Tracking - The report highlights various macroeconomic indicators, including U.S. CPI and PPI, which are essential for understanding the broader economic context affecting metal prices [30][34] 5. Recommended Stocks - The report recommends several stocks including Zijin Mining, Luoyang Molybdenum, Western Mining, China Aluminum, Tianshan Aluminum, Shenhuo Co., Yun Aluminum, Shandong Gold, Shanjin International, Xiamen Tungsten, and Zhongtung High-tech, all rated as "Overweight" [4][91]

Group 1 - The report indicates that since 2022, the decline in deposit and loan rates has outpaced the decline in government bond rates and policy rates, suggesting that the bond market has not fully priced in the expectations of interest rate cuts [4][9][10] - The analysis emphasizes that using loan rates as a benchmark provides a more accurate reflection of the bond market's pricing, indicating that there is still room for bond rates to decline further [10][16][21] - The report suggests that the current yield spread between long-term bonds and loans is at a historically low level, indicating that purchasing long-term bonds is a more cost-effective choice compared to mortgage loans [21][24] Group 2 - The report highlights that the recent interest rate cuts have led to a compression of yield spreads, and the market needs to identify the next strategic rotation direction [24][26] - It notes that the capital gains opportunity in the bond market may re-emerge in the third quarter, contingent on further interest rate cuts [26][27] - The report concludes that the bond market's current pricing is reasonable and even conservative when using loan rates as a benchmark, suggesting potential for further declines in bond rates [27][28]

Quantitative Models and Construction Methods Quantitative Factors and Their Construction 1. **Factor Name**: Intraday Skewness Factor **Construction Idea**: Captures the skewness of intraday stock returns to identify potential return asymmetry[3][6] **Construction Process**: Referenced in the report "Stock Selection Factor Series Research (19) - High-Frequency Factors on Stock Return Distribution Characteristics"[11] **Evaluation**: Demonstrates mixed performance with positive returns in some periods but underperformance in others[3][6] 2. **Factor Name**: Downside Volatility Proportion Factor **Construction Idea**: Measures the proportion of downside volatility in intraday price movements to assess risk[3][6] **Construction Process**: Referenced in the report "Stock Selection Factor Series Research (25) - High-Frequency Factors on Realized Volatility Decomposition"[16] **Evaluation**: Shows consistent positive returns in certain periods but limited robustness in others[3][6] 3. **Factor Name**: Post-Open Buy Intention Proportion Factor **Construction Idea**: Quantifies the proportion of buy orders after market open to gauge investor sentiment[3][6] **Construction Process**: Referenced in the report "Stock Selection Factor Series Research (64) - Low-Frequency Applications of High-Frequency Data Using Intuitive Logic and Machine Learning"[20] **Evaluation**: Exhibits moderate performance with occasional strong returns[3][6] 4. **Factor Name**: Post-Open Buy Intention Intensity Factor **Construction Idea**: Measures the intensity of buy orders after market open to reflect market momentum[3][6] **Construction Process**: Referenced in the report "Stock Selection Factor Series Research (64) - Low-Frequency Applications of High-Frequency Data Using Intuitive Logic and Machine Learning"[24] **Evaluation**: Performance is inconsistent, with periods of underperformance[3][6] 5. **Factor Name**: Post-Open Large Order Net Buy Proportion Factor **Construction Idea**: Tracks the proportion of large net buy orders after market open to identify institutional activity[3][6] **Construction Process**: Derived from high-frequency trading data[30] **Evaluation**: Generally positive performance with strong returns in specific periods[3][6] 6. **Factor Name**: Post-Open Large Order Net Buy Intensity Factor **Construction Idea**: Measures the intensity of large net buy orders after market open to capture market trends[3][6] **Construction Process**: Derived from high-frequency trading data[35] **Evaluation**: Mixed results with moderate returns in some periods[3][6] 7. **Factor Name**: Improved Reversal Factor **Construction Idea**: Enhances traditional reversal factors by incorporating high-frequency data[3][6] **Construction Process**: Derived from intraday price reversals[40] **Evaluation**: Limited performance improvement over traditional reversal factors[3][6] 8. **Factor Name**: Tail-End Trading Proportion Factor **Construction Idea**: Measures the proportion of trading activity near market close to capture end-of-day effects[3][6] **Construction Process**: Derived from high-frequency trading data[45] **Evaluation**: Underperformance in most periods[3][6] 9. **Factor Name**: Average Single Transaction Outflow Proportion Factor **Construction Idea**: Tracks the proportion of outflows in single transactions to assess liquidity[3][6] **Construction Process**: Derived from high-frequency trading data[50] **Evaluation**: Limited effectiveness in predicting returns[3][6] 10. **Factor Name**: Large Order Push-Up Factor **Construction Idea**: Measures the impact of large orders on price increases to identify market movers[3][6] **Construction Process**: Derived from high-frequency trading data[55] **Evaluation**: Moderate performance with occasional strong returns[3][6] 11. **Factor Name**: Deep Learning High-Frequency Factor (Improved GRU(50,2)+NN(10)) **Construction Idea**: Combines GRU and neural networks to capture complex patterns in high-frequency data[3][6] **Construction Process**: Utilizes GRU(50,2) and NN(10) architectures for feature extraction and prediction[59] **Evaluation**: Strong performance in certain periods but underperformance in others[3][6] 12. **Factor Name**: Deep Learning High-Frequency Factor (Residual Attention LSTM(48,2)+NN(10)) **Construction Idea**: Incorporates residual attention mechanisms with LSTM and neural networks for enhanced prediction[3][6] **Construction Process**: Utilizes LSTM(48,2) and NN(10) architectures with residual attention layers[61] **Evaluation**: Consistently strong performance across multiple periods[3][6] 13. **Factor Name**: Deep Learning Factor (Multi-Granularity Model - 5-Day Label) **Construction Idea**: Uses multi-granularity modeling with 5-day labels for short-term predictions[3][6] **Construction Process**: Trained using bidirectional AGRU[64] **Evaluation**: Strong performance with high returns in most periods[3][6] 14. **Factor Name**: Deep Learning Factor (Multi-Granularity Model - 10-Day Label) **Construction Idea**: Uses multi-granularity modeling with 10-day labels for medium-term predictions[3][6] **Construction Process**: Trained using bidirectional AGRU[65] **Evaluation**: Consistently strong performance across multiple periods[3][6] AI-Enhanced Portfolio Construction 1. **Portfolio Name**: CSI 500 AI Enhanced Wide Constraint Portfolio **Construction Idea**: Maximizes expected returns under wide constraints using deep learning factors[69][70] **Construction Process**: - Weekly rebalancing - Constraints on individual stocks, industries, market cap, and other factors - Objective function: $$ max\sum\mu_{i}w_{i} $$ where \( w_i \) is the weight of stock \( i \) and \( \mu_i \) is its expected excess return[71] **Evaluation**: Strong cumulative excess returns since 2017[72] 2. **Portfolio Name**: CSI 500 AI Enhanced Strict Constraint Portfolio **Construction Idea**: Similar to the wide constraint portfolio but with stricter constraints[69][70] **Construction Process**: Same as above with stricter constraints on market cap, ROE, SUE, and volatility[71] **Evaluation**: Moderate cumulative excess returns since 2017[73] 3. **Portfolio Name**: CSI 1000 AI Enhanced Wide Constraint Portfolio **Construction Idea**: Maximizes expected returns under wide constraints using deep learning factors for smaller-cap stocks[69][70] **Construction Process**: Same as CSI 500 portfolios but applied to CSI 1000 index[71] **Evaluation**: Strong cumulative excess returns since 2017[76] 4. **Portfolio Name**: CSI 1000 AI Enhanced Strict Constraint Portfolio **Construction Idea**: Similar to the wide constraint portfolio but with stricter constraints for smaller-cap stocks[69][70] **Construction Process**: Same as above with stricter constraints on market cap, ROE, SUE, and volatility[71] **Evaluation**: Strong cumulative excess returns since 2017[79] Backtest Results for Factors 1. **Intraday Skewness Factor**: IC (2025): 0.057, Multi-Period Returns: 14.35% (2025)[3][6] 2. **Downside Volatility Proportion Factor**: IC (2025): 0.055, Multi-Period Returns: 11.77% (2025)[3][6] 3. **Post-Open Buy Intention Proportion Factor**: IC (2025): 0.033, Multi-Period Returns: 10.32% (2025)[3][6] 4. **Post-Open Buy Intention Intensity Factor**: IC (2025): 0.026, Multi-Period Returns: 11.19% (2025)[3][6] 5. **Post-Open Large Order Net Buy Proportion Factor**: IC (2025): 0.039, Multi-Period Returns: 12.32% (2025)[3][6] 6. **Post-Open Large Order Net Buy Intensity Factor**: IC (2025): 0.028, Multi-Period Returns: 6.78% (2025)[3][6] 7. **Improved Reversal Factor**: IC (2025): 0.003, Multi-Period Returns: 9.34% (2025)[3][6] 8. **Tail-End Trading Proportion Factor**: IC (2025): 0.022, Multi-Period Returns: 5.43% (2025)[3][6] 9. **Average Single Transaction Outflow Proportion Factor**: IC (2025): 0.012, Multi-Period Returns: 0.82% (2025)[3][6] 10. **Large Order Push-Up Factor

Investment Rating - The industry investment rating is Neutral, indicating performance is expected to be in line with the CSI 300 Index [26]. Core Insights - Since May, precious metal prices have risen significantly, while fixed asset investment growth has decreased to 4.00% as of April 2025 [2][11]. - Retail sales growth has improved, with a nominal year-on-year growth rate of 4.70% in April 2025, and the decline in property sales area growth has narrowed to -3.38% [3][12]. - Exports to the US and EU have decreased, while exports to Japan and ASEAN have increased, reflecting a mixed export performance [4][13]. - Oil prices have dropped, with WTI at $61.57 per barrel as of May 21, 2025, and pork prices have also seen a decline [5][14]. Summary by Sections Investment Chain - Precious metal prices, including gold, copper, and aluminum, have risen since May 2025. Fixed asset investment growth in manufacturing and infrastructure has decreased, with real estate development investment showing a smaller decline [2][11]. Consumption Chain - Retail sales have shown a recovery, with automotive sales increasing by 9.78% year-on-year in April 2025. The home appliance retail sector has seen a significant growth of 42.55% year-on-year [3][12]. Export Chain - The export growth rate for furniture, lamps, and other products has increased, while agricultural products and machinery exports have seen declines. Exports to Japan and ASEAN have improved, contrasting with declines to the US and EU [4][13]. Price Chain - Oil prices have decreased, while prices for certain agricultural products like pork have also fallen. The price of PVC has dropped to 4838 yuan per ton, while MDI prices have increased [5][14].

【AI 产业跟踪】Gemini 2.5 Pro 突破视频处理 产业研究中心 长度限制,Speech-02 强势登顶语音评测榜单 < | 摘要:产业最新趋势跟踪,点评产业最新风向 | | --- | O AI 行业动态 AI 整合应用平台 Poe 发布 AI 模型使用趋势报告 黄仁勋:AI工厂是下个千兆瓦级产业革命 AI 产品的四种付费模式 a16z提出 AI 时代的 9 种全新软件开发模式 红杉 AI峰会:AI 不再卖工具,而是卖收益 英伟达 Jim Fan 演讲揭秘具身 Scaling Law 美国正式废除《AI 扩散规则》并提出新规则 O AI 应用资讯 国内资讯 | AA | ર્ | 李嘉琪(分析师) | | --- | --- | --- | | | S | 021-38676666 | | | 登记编号 | S0880524040001 | | | S | 刘峰(研究助理) | | | 8 | 021-38676666 | | | 登记编号 | S0880124060013 | MiniMax 语音模型 Speech-02 登顶 Artificial Analysis 榜单 阿里 Wan2.1-V ...

Investment Rating - The investment rating for the company is "Accumulate" [11][19]. Core Views - The company has a substantial reserve of series projects and has signed multiple cultural tourism contracts, with several films expected to be released during the summer season, leading to a forecasted rapid growth in revenue [3][11]. - The company is expected to have a significant year in 2025 with nearly ten series anticipated for release, including several headlining series that have been recommended by major platforms like Mango TV [11]. - The film business has underperformed since 2021, with several films, including "Lion Boy 2," failing to meet box office expectations, which has negatively impacted the company's overall performance [11]. - The target price has been adjusted to 6.90 yuan, down from a previous estimate of 7.84 yuan, reflecting a decrease of 12% based on comparable company valuations [11][13]. Financial Summary - Projected revenue for 2023 is 432 million yuan, with a significant increase to 739 million yuan in 2024, and further growth to 985 million yuan in 2025, representing a year-on-year growth of 71.1% [5]. - The net profit attributable to the parent company is expected to turn positive in 2025, with estimates of 140 million yuan, following losses of 186 million yuan in 2023 and 393 million yuan in 2024 [5]. - The earnings per share (EPS) is projected to be -0.20 yuan in 2023, -0.42 yuan in 2024, and is expected to recover to 0.15 yuan in 2025 [5]. Market Data - The company's stock price has ranged between 3.80 yuan and 7.03 yuan over the past 52 weeks, with a total market capitalization of 4,417 million yuan [6]. - The company has a total share capital of 942 million shares, with 929 million shares in circulation [6]. Business Development - The company has confirmed revenue from several series in 2024, exceeding 400 million yuan, and anticipates further growth if the planned series are released in 2025 [11]. - The cultural tourism business is progressing steadily, with new projects signed in various locations, which are expected to provide stable revenue growth [11].

产业深度 [table_Header]2025.05.23 破局与固基——中外耐心资本赋能产业投融资启示录 产业研究中心 摘要： | [Table_Authors] | 朱峰(分析师) | | --- | --- | | | 021-38676666 | | 登记编号 | S0880522030002 | | | 鲍雁辛(分析师) | | | 021-38676666 | | 登记编号 | S0880513070005 | | | 汪玥(研究助理) | | --- | --- | | | 021-38676666 | | 登记编号 | S0880123070143 | 请务必阅读正文之后的免责条款部分 1 of 44 [Table_Summary] 发展耐心资本成为解决一级市场投融资难题的破局之道。随着经济增长动 能切换，叠加 IPO、再融资政策收紧影响，我国一级市场产业投融资面临 的不确定性增加，一级市场整体投资与融资活跃度有所降低。当前我国产 业投融资主要面临三大难点：1）优质标的供给减少；2）股权投资进程放 缓；3）项目退出变难，融资渠道不畅通。面对挑战，近年来我国在政策端 持续发力助推耐心资本发展：2 ...

股票研究 /[Table_Date] 2025.05.23 5 月游戏版号发布，《异环》等产品获批 [Table_Industry] 传播文化业 [Table_Invest] 评级： 增持 | [table_Authors] 陈筱(分析师) | 杨昊(分析师) | | --- | --- | | 021-38676666 | 021-38676666 | | 登记编号 S0880515040003 | S0880524020001 | 本报告导读： 5 月版号发放再创新高，腾讯、网易、恺英、完美等均有产品获批，《异环》《命运： 群星》等重磅产品获批，利好后续上线推进。 投资要点： 行 业 跟 踪 报 告 行业跟踪报告 表1：推荐公司盈利预测与估值情况表 | 代码 | 简称 | 股价（元） | 市值 | | EPS（元） | | | PE | | - | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | | | | （亿元） | 2024A | 2025E | 2026E | 2024A | 2025E | 2026E | ...

Investment Rating - The report assigns an "Accumulate" rating to the company [5]. Core Views - The company is expected to face pressure in Q1 2025 due to macroeconomic uncertainties, with a projected mid-single-digit decline in revenue and stable profit margins in Q2. However, revenue growth in India has turned positive, and TUMI is experiencing strong growth in Europe and China [3][10]. Financial Summary - Revenue is projected to decline from $3,589 million in 2024 to $3,367 million in 2025, representing a -6% change. By 2026, revenue is expected to recover to $3,506 million, followed by $3,671 million in 2027 [9]. - Gross profit is forecasted to decrease from $2,152 million in 2024 to $2,003 million in 2025, with a slight recovery to $2,089 million in 2026 and $2,194 million in 2027 [9]. - Net profit is expected to drop significantly from $346 million in 2024 to $254 million in 2025, with a gradual increase to $289 million in 2026 and $345 million in 2027 [9]. - The report anticipates a PE ratio of 15x for 2025, translating to a target price of HKD 20.29 per share based on a USD to HKD exchange rate of 7.8 [10]. Regional Performance - In Q1 2025, revenue changes by region were as follows: Asia -7%, North America -8%, Europe +4.4%, and Latin America 0%. Notably, North America experienced a decline of -5.2% when excluding the impact of early shipments [10]. - TUMI's revenue in Europe and China showed resilience, with growth rates of 11.1% and 10.9% respectively, driven by new store openings [10]. Valuation and Comparison - The report includes a comparison of the company's valuation with peers, indicating a PE of 7.8 for the company in 2025, which is competitive compared to other luxury brands [11].