Investment Rating - The investment rating for the information services industry is "Outperform the Market" and is maintained [2]. Core Insights - The release of Manus, the world's first general AI Agent, signifies that China's AI research capabilities have reached a world-class level, indicating that AI Agents are at a critical point of commercial explosion [8]. - The government work report emphasizes the importance of technology sectors, including artificial intelligence, smart driving, and quantum technology, which are expected to benefit from favorable policies [8]. - The report suggests that 2025 is likely to be the year of significant commercial breakthroughs for AI Agents, with major tech companies like Google and Microsoft actively developing AI Agent applications [8]. Summary by Sections Industry Overview - The report highlights the launch of Manus, which outperforms OpenAI's Deep Research in benchmark tests, showcasing its capabilities as a powerful general assistant capable of executing complex tasks independently [6][8]. - Manus is positioned as a versatile assistant that can perform various tasks, including HR functions, educational content creation, and financial report analysis, demonstrating its advanced learning and adaptability [6]. Government Policy and Economic Outlook - The government aims for a GDP growth of around 5% in 2025, with a focus on implementing proactive fiscal policies and increasing government debt to stimulate economic activity [6]. - The report outlines the government's commitment to advancing the digital economy and supporting the widespread application of large models in various sectors [6]. Investment Opportunities - The report recommends focusing on companies such as Kingsoft Office, Hongsoft Technology, and Runze Technology, which are expected to benefit from the growth in the AI sector [8].

Quantitative Models and Construction Methods 1. Model Name: Macro Timing Model - **Model Construction Idea**: The model predicts future macroeconomic environments using proxy variables and selects optimal assets for absolute return portfolios based on these predictions[25] - **Model Construction Process**: - The model uses proxy variables to forecast macroeconomic conditions such as inflation, economic growth, interest rates, exchange rates, and risk sentiment[25] - Based on these forecasts, the model selects assets that are expected to perform best in the predicted environment[25] - Example formula: $ \text{Expected Return} = \alpha + \beta \times \text{Macro Variable} $ where $\alpha$ is the intercept and $\beta$ is the coefficient representing the sensitivity to the macro variable[25] - **Model Evaluation**: The model is effective in predicting macroeconomic conditions and selecting optimal assets for different environments[25] - **Model Test Results**: - Q1 2025 predictions: Inflation environment - Asset returns: CSI 300: 0.10%, CSI 2000: 6.05%, Nanhua Commodity Index: 3.26%, China Bond Total Wealth Index: 0.51%[25] 2. Model Name: Macro Momentum Model - **Model Construction Idea**: The model uses multiple dimensions such as economic growth, inflation, interest rates, exchange rates, and risk sentiment to time major asset classes like stocks and bonds[25] - **Model Construction Process**: - The model constructs macro momentum indicators based on economic growth, inflation, interest rates, exchange rates, and risk sentiment[25] - These indicators are used to time investments in major asset classes[25] - Example formula: $ \text{Momentum Score} = \sum_{i=1}^{n} w_i \times \text{Indicator}_i $ where $w_i$ is the weight of the $i$-th indicator and $\text{Indicator}_i$ is the value of the $i$-th indicator[25] - **Model Evaluation**: The model is effective in timing investments based on macroeconomic conditions[25] - **Model Test Results**: - February 2025 returns: CSI 300: 3.19%, China Bond Total Wealth Index: 0.08%, Shanghai Gold Exchange AU9999 contract: 6.43%[25] Model Backtest Results 1. Macro Timing Model - **Weekly Return**: -0.12%[32] - **Monthly Return**: 0.36%[32] - **Year-to-Date Return**: -0.31%[32] - **Annualized Volatility**: 2.71%[32] - **Maximum Drawdown**: 0.51%[32] - **Sharpe Ratio**: -0.95[32] 2. Macro Momentum Model - **Weekly Return**: -0.20%[32] - **Monthly Return**: 0.18%[32] - **Year-to-Date Return**: 0.15%[32] - **Annualized Volatility**: 1.50%[32] - **Maximum Drawdown**: 0.47%[32] - **Sharpe Ratio**: 0.87[32] Quantitative Factors and Construction Methods 1. Factor Name: PB Profitability - **Factor Construction Idea**: The factor selects stocks based on their price-to-book (PB) ratio and profitability metrics[38] - **Factor Construction Process**: - Stocks are ranked based on their PB ratio and profitability metrics[38] - The top-ranked stocks are selected for the portfolio[38] - Example formula: $ \text{PB Profitability Score} = \frac{\text{Net Income}}{\text{Book Value}} $ where $\text{Net Income}$ is the company's net income and $\text{Book Value}$ is the company's book value[38] - **Factor Evaluation**: The factor is effective in selecting stocks with high profitability relative to their book value[38] 2. Factor Name: High Dividend Yield - **Factor Construction Idea**: The factor selects stocks based on their dividend yield[38] - **Factor Construction Process**: - Stocks are ranked based on their dividend yield[38] - The top-ranked stocks are selected for the portfolio[38] - Example formula: $ \text{Dividend Yield} = \frac{\text{Annual Dividends}}{\text{Stock Price}} $ where $\text{Annual Dividends}$ is the total dividends paid annually and $\text{Stock Price}$ is the current stock price[38] - **Factor Evaluation**: The factor is effective in selecting stocks with high dividend yields[38] Factor Backtest Results 1. PB Profitability Factor - **Weekly Return**: 0.09%[39] - **Monthly Return**: 0.36%[39] - **Year-to-Date Return**: 0.38%[39] - **Annualized Volatility**: 2.63%[39] - **Maximum Drawdown**: 1.82%[39] - **Sharpe Ratio**: -0.44[39] 2. High Dividend Yield Factor - **Weekly Return**: 0.03%[39] - **Monthly Return**: 0.15%[39] - **Year-to-Date Return**: 0.01%[39] - **Annualized Volatility**: 2.34%[39] - **Maximum Drawdown**: 1.39%[39] - **Sharpe Ratio**: -0.64[39]

证券研究报告 （优于大市，维持） 《海外新能源车销量月报：25年1月美国同 比+12%，欧洲同比+24%》 马天一（电力设备及新能源联席首席分析师） SAC号码：S0850523030004 联系人：李依雯 欧洲：25年1月新能源车销量17.1万辆，同比+23.8% 销量：2025年1月欧洲新能源车销量170909辆，同比+23.8%，环比-25.7%。 渗透率：2025年1月欧洲新能源车渗透率23.2%，同比+4.7pct，环比-4.1pct。 2025年2月19日 摘要 请务必阅读正文之后的信息披露和法律声明 2 欧洲：2025年1月欧洲新能源车销量17.1万辆，同比+23.8%，环比-25.7%；渗透率23.2%，同比+4.7pct， 环比-4.1pct，德国、意大利销量显著恢复。其中，25年1月销量前三的国家为：1）德国：25年1月新能 源车销量5.2万辆，同比+41.8%，环比-0.8%；渗透率25.1%，同比+7.9pct，环比+1.7pct；2）英国： 25年1月新能源车销量4.2万辆，同比+28.4%，环比-25.1%；渗透率30.3%，同比+7.3pct，环比-9.7%； 3）法国：25年1 ...

[Table_MainInfo] 每日报告精选 证券研究报告 最新研究与资讯 2025 年 02 月 18 日 | [Table_Marketinfo] | | | | | --- | --- | --- | --- | | | 重要市场数据 | | | | 名称 | 日涨跌% | 周涨跌% | 年涨跌% | | 海通风格指数 | | | | | 大盘 100 | -0.17 | 1.13 | -3.10 | | 小盘 200 | 1.30 | 1.34 | 6.06 | | 表现最好前五行业 | | | | | 通讯服务 | 6.62 | 14.20 | 25.33 | | 信息设备 | 1.58 | 1.84 | 6.79 | | 农业指数 | 1.12 | 2.63 | 0.52 | | 造纸指数 | 1.03 | 1.02 | -0.57 | | --- | --- | --- | --- | | 公用事业 | 0.98 | 1.08 | -4.39 | | 表现最差前五行业 | | | | | 传媒指数 | -2.19 | 6.67 | 15.57 | | 有色金属 | -2.16 | -2.83 ...

[Table_MainInfo] 行业研究/交通运输 证券研究报告 行业周报 2025 年 02 月 18 日 [Table_InvestInfo] 投资评级 优于大市 维持 周报：西延高铁全线隧道贯通 资料来源：海通证券研究所 市场表现 相关研究 [Table_QuoteInfo] -5.37% -0.50% 4.37% 9.23% 14.10% 18.97% 2024/2 2024/5 2024/8 2024/11 交通运输 海通综指 [Table_ReportInfo] 《周报：全国城市轨道交通线路达 325 条》2025.01.22 《周报：优化交通运输市场要素资源配 臵，为加快建设统一开放的交通运输市场 提供有力保障》2025.01.15 《周报：民航春运旅客量预计突破九千万 人次》2025.01.07 分析师:虞楠 Tel:(021)23219382 Email:yun@haitong.com 证书:S0850512070003 分析师:罗月江 Tel:(010)58067993 Email:lyj12399@haitong.com 证书:S0850518100001 分析师:杜清丽 Tel:(0 ...

[Table_MainInfo] 行业研究/金融/银行 证券研究报告 行业周报 2025 年 02 月 17 日 [Table_InvestInfo] 投资评级 优于大市 维持 市场表现 [Table_QuoteInfo] -3.14% 5.18% 13.49% 21.80% 30.11% 38.43% 2024/1 2024/4 2024/7 2024/10 银行 海通综指 资料来源：海通证券研究所 相关研究 | [Table_ReportInfo] 《周报：1 月 LPR 维持不变，长期资金 | | --- | | 入市利好高股息板块》2025.01.27 | | 《周报：12 月社融数据公布，4 家银行全 | 年净利润均正增长》2025.01.20 《周报：央行暂停公开市场国债买入，2 万亿元置换债券发行工作已启动》 2025.01.13 分析师:董栋梁 Tel:(021)23185697 Email:ddl13206@haitong.com 证书:S0850523100001 周报：政府债券有力支撑社融，央行将择 机调整优化政策力度和节奏 [Table_Summary 投资要点：本周央行发布 2024 ...

[Table_MainInfo] 金融工程研究 证券研究报告 金融工程周报 2025 年 02 月 17 日 [Table_Title] 相关研究 [Table_ReportInfo] 《下周 A 股的上行趋势不会改变——量 化择时和拥挤度预警周报（20250216）》 2025.02.16 《本周高频因子表现继续分化，AI 增强组 合依然回撤——高频选股因子周报 风格 50 组合均跑赢均衡组合——风格 Smart beta 组 合跟踪周报（2025.02.10-2025.02.14） [Table_Summary] 投资要点： 风险提示：市场环境变动风险，有效因子变动风险。 分析师:郑雅斌 Tel:(021)23219395 Email:zhengyb@haitong.com 证书:S0850511040004 联系人:卓洢萱 Tel:(021)23183938 Email:zyx15314@haitong.com 请务必阅读正文之后的信息披露和法律声明 （20250210-20250214）》2025.02.15 《小盘成长组合累计收益 17%，三大指增 组合均获正超额——量化选股周报 （2025.02. ...

上周资金净流入105亿元 ——立体投资策略周报 2025年2月17日 证券研究报告 吴信坤 （策略首席分析师） 证书：S0850521070001 Tel：(021) 23154147 E-mail：wxk12750@haitong.com 余培仪（策略资深分析师） 证书：S0850523040002 Tel：021-23185663 E-mail：ypy13768@haitong.com 陆嘉瑞（联系人） Tel：021-23185659 E-mail： ljr16250@haitong.com 每周资金入市合计 上周资金净流入105亿元，而前一周净流出16亿元。 资料来源：Wind，海通证券研究所测算 请务必阅读正文之后的信息披露和法律声明 资料来源：Wind，海通证券研究所 请务必阅读正文之后的信息披露和法律声明 2500 2700 2900 3100 3300 3500 3700 3900 -1000 -500 0 500 1000 1500 2000 2500 3000 19/06 19/08 19/10 19/12 20/02 20/04 20/06 20/08 20/10 20/12 21/02 ...

[Table_MainInfo] 金融工程研究 证券研究报告 金融工程周报 2025 年 02 月 17 日 [Table_Title] 相关研究 《大类资产及择时观点月报（2025.02）》 2025.02.10 本周高频因子表现继续分化，AI 增强组合 依然回撤 — — 高 频 选 股 因 子 周 报 （20250210-20250214） [Table_Summary] 投资要点： 请务必阅读正文之后的信息披露和法律声明 [Table_AuthorInfo] [Table_ReportInfo] 《上周 514 只固收+产品业绩创历史新高 ——绝对收益产品及策略周报 （20250205-20250207）》2025.02.12 《2024 年绩优指数增强超额收益来源解 析》2025.02.11 分析师:郑雅斌 Tel:(021)23219395 Email:zhengyb@haitong.com 证书:S0850511040004 分析师:余浩淼 Tel:(021)23185650 Email:yhm9591@haitong.com 证书:S0850516050004 深度学习因子（多颗粒度模型-5 日 ...

Summary of Conference Call Notes Industry or Company Involved - The discussion primarily revolves around the convertible bond market and the stock market, with a focus on investment sentiment and market dynamics. Core Points and Arguments 1. **Market Sentiment and Trading Volume** The overall investment sentiment in the market has declined significantly, particularly in the stock market, where trading volumes have dropped from over 700 billion in December to around 400 billion. This indicates a rapid decrease in market activity [1] 2. **Performance of Convertible Bonds vs. Stocks** Despite the decline in the stock market, convertible bonds have shown relative strength, with a decrease of only 1% to 2%. This has resulted in a widening spread between convertible bonds and stocks, suggesting that convertible bonds are currently outperforming stocks [2][3] 3. **Historical Context of Convertible Bonds** The current relative strength of convertible bonds is at an extreme historical position, similar to previous market conditions in February 2019 and early 2024, where significant rebounds followed after similar patterns [3][4] 4. **Investment Strategy Recommendations** There is a recommendation to actively monitor convertible bonds for potential opportunities, especially around the Chinese New Year. If possible, investing in stocks is preferred due to their larger financial impact. If stocks are not feasible, convertible bonds should be considered for monthly opportunities [5] 5. **Market Dynamics and Policy Impact** The central bank's recent stance on liquidity and interest rates has led to adjustments in market expectations. The central bank's actions, including issuing offshore central bank bills, have influenced market sentiment and expectations regarding future interest rate cuts [6][7] 6. **Institutional Behavior and Market Support** The behavior of institutional investors, particularly funds, is crucial in the current market. Despite recent adjustments, there is still support for the bond market, with expectations that funds will not maintain a net selling position for long [8] 7. **Credit Bond Market Outlook** The credit bond market is experiencing a short-term rebound, but overall yields are slightly rising. The demand from institutional investors remains strong, and there is potential for credit spreads to narrow in the future [9][10] 8. **Focus on Specific Credit Instruments** Attention is drawn to specific credit instruments, such as three-year bonds with yields around 2.15% to 2.3%, and the potential for further tightening in the supply of certain bonds due to policy-driven debt replacement initiatives [11][12] 9. **Monitoring Policy Effects and Industry Recovery** Continuous monitoring of policy effects and the stability of industry fundamentals is recommended. There is a focus on healthy debt levels in state-owned enterprises and the potential for investment in long-term bonds from stable institutions [13] Other Important but Possibly Overlooked Content - The discussion highlights the importance of understanding the macroeconomic environment and the impact of government policies on market dynamics, particularly in the context of liquidity and interest rates. - The potential risks associated with the current market conditions, including the possibility of further declines in stock prices, are acknowledged, emphasizing the need for cautious investment strategies.