证券研究报告 | 2025年07月13日 债市阿尔法追踪 6 月：债市普遍上涨，超长债涨势突出 主要结论：不考虑票息收益，行业维度来看，交运行业债券净价涨幅靠前， 单月上涨 0.12%，存在一定的α。期限维度来看，6 月 10 年期以上国债和地 方政府债存在正α。次级维度来看，6 月商业银行次级债存在明显阿尔法。 6 月各品种收益率全景：6 月债市普遍上涨。利率债方面，6 月全部利率债收 益率下行，国债、国开债和地方政府债收益率平均下行 7BP、5BP 和 5BP。信 用债方面，几乎全部信用债品种收益率下行，其中 20 年期、隐含评级 AA+ 城投债收益率平均下行 17BP，为信用债下行幅度最大的品种。 行业阿尔法追踪：行业维度来看，6 月全部行业信用债上涨，平均净价涨跌 幅为 0.07%，其中交运行业债券净价涨幅靠前，单月上涨 0.12%，存在一定 的α。城投债和地产债平均净价上涨 0.03%，为涨幅相对较小的行业。 期限阿尔法追踪：6 月 10 年期以上国债和地方政府债存在正α。数据显示， 6 月 10 年以上国债上涨 1.1%、地方政府债上涨 0.93%，涨幅显著超过其他利 率债品种。其原因主要是超长利 ...

港股市场速览 优于大市 资金显著流入金融，制造业持续交易反内卷 股价表现：市场窄幅震荡，制造业表现领先 本周，恒生指数涨 0.9%，恒生科技涨 0.6%。风格方面，小盘（恒生小型股 +2.6%）＞中盘（恒生中型股+1.5%）＞大盘（恒生大型股+0.9%）。 概念指数多数上涨，表现领先的有：恒生金融（+2.2%）、恒生汽车（+2.1%）； 表现较弱的有：恒生公用事业（-1.3%）、恒生创新药（-0.7%）。 港股通行业中，25 个行业上涨，5 个行业下跌。涨幅居前的有：轻工制造 （+8.3%）、国防军工（+8.2%）、钢铁（+6.3%）、电力设备及新能源（+5.9%）、 农林牧渔（+5.2%）；下跌的有：有色金属（-4.0%）、纺织服装（-2.7%）、 食品饮料（-1.1%）、基础化工（-0.3%）、商贸零售（-0.2%）。 证券研究报告 | 2025年07月13日 资金强度：资金显著流入金融、互联网与房地产 本周，资金显著流入港股通成分股，总体日均资金强度（日均涨跌 x 日均 成交量）为+20.5 亿港元/日，上周为+4.8 亿港元/日，近 4 周平均为+7.2 亿 港元/日；近 13 周为+4.3 亿港元/ ...

Investment Rating - The report maintains a "Weaker than Market" investment rating for the U.S. stock market [1] Core Insights - The U.S. stock market experienced narrow fluctuations with most sectors declining, as the S&P 500 fell by 0.3% and the Nasdaq by 0.1% [3] - There were 8 sectors that increased while 16 sectors decreased, with notable gains in Energy (+2.6%), Semiconductor Products and Equipment (+2.4%), and Transportation (+1.2%) [3] - Conversely, sectors that saw significant declines included Telecommunications (-4.8%), Insurance (-2.6%), and Banks (-2.5%) [3] Summary by Sections Market Overview - The S&P 500's estimated fund flow was -$5.7 billion this week, a decrease from the previous week's +$23.4 billion, with a total of +$216.4 billion over the last 13 weeks [4] - Fund inflows were observed in 11 sectors, with Semiconductor Products and Equipment leading at +$17.2 billion, followed by Transportation (+$6.0 billion) and Energy (+$4.1 billion) [4] - Sectors experiencing fund outflows included Software and Services (-$15.9 billion) and Automotive and Parts (-$8.2 billion) [4] Earnings Forecast - The dynamic F12M EPS forecast for S&P 500 constituents was adjusted upward by 0.3%, following a 0.2% increase the previous week [5] - Earnings expectations were raised for 21 sectors, with the highest adjustments in Integrated Finance (+0.8%), Automotive and Parts (+0.8%), and Semiconductor Products and Equipment (+0.8%) [5] - Three sectors saw downward revisions, notably Healthcare Equipment and Services (-1.0%) and Telecommunications (-0.2%) [5] Price Performance - The Energy sector recorded a price return of +2.6% this week, while the Telecommunications sector saw a decline of -4.8% [15] - Over the past 52 weeks, the Energy sector has increased by 5.1%, while the Telecommunications sector has decreased by 4.0% [15] - The Semiconductor Products and Equipment sector has shown a remarkable increase of +48.0% over the past 13 weeks [15] Fund Flow Analysis - The Industrial sector led with a net fund inflow of $781 million this week, followed by Energy with $409 million [19] - The Semiconductor Products and Equipment sector also saw significant inflows of $1.716 billion, indicating strong investor interest [19] - In contrast, the Software and Services sector experienced the largest outflow of -$1.594 billion [19]

Global Market Overview - The global equity markets showed mixed performance with moderate valuation changes during the week of July 7-11, 2025. The Asia-Pacific region experienced significant divergence, with South Korea leading gains and India lagging behind. Japan saw a slight decline, while Singapore and Hong Kong indices rose [2][8] - In terms of valuation, the German DAX's PE ratio expanded by 1.65x, approaching historical highs, while the French CAC40 increased by 1.73% but saw a PE decrease of 0.64x, indicating earnings upgrades. Other indices in Hong Kong, except for the Hang Seng Technology Index, maintained high valuation levels [2][8] A-share Market Analysis - The A-share core indices mostly rose with moderate valuation expansion. The CSI 1000 and National CSI 2000 led the gains with increases of 2.36% and 2.29%, respectively. Small-cap stocks outperformed, with various small-cap indices rising over 2%. The large-cap value index slightly declined due to bank sector pressures [21][22] - As of July 11, 2025, the PE, PB, PS ratios of major A-share indices were positioned between the 96%-100% percentile for the past year, while the PCF ratio was between 90%-93%. Overall, large-cap growth indices showed superior percentile levels compared to large-cap value indices [22][23] Industry Performance - Most primary industries experienced gains with moderate valuation expansions. The real estate sector led with a 6.12% increase, followed by non-bank financials at 3.96%. The banking sector saw a slight decline of 1%. Other sectors like steel and building materials continued their upward trend [42][44] - Valuation changes were generally consistent with stock price movements, with the PE of computing and real estate sectors expanding by over 2x, while steel, media, and comprehensive sectors saw PE expansions exceeding 1x [42][44] Valuation Comparisons - The essential consumer sector demonstrated superior valuation attractiveness. The banking sector's valuations are at historical highs, with PE, PB, and PS ratios nearing 100% in both 1-year and 3-year dimensions. In contrast, essential consumer sectors like food and beverage, and agriculture show significant valuation recovery potential, with 3-year/5-year average valuation percentiles at 11.13% / 6.68% and 27.20% / 19.14%, respectively [44]

请务必阅读正文之后的免责声明及其项下所有内容 证券研究报告 | 2025年7月12日 锂电产业链双周评（7月第1期） 欧洲新能源车需求持续复苏，固态电池产业发展快速推进 行业研究 · 行业周报 电力设备新能源 · 锂电池 投资评级：优于大市（维持） 证券分析师：王蔚祺 010-88005313 wangweiqi2@guosen.com.cn S0980520080003 证券分析师：徐文辉 021-60375426 xuwenhui@guosen.com.cn S0980524030001 证券分析师：李全 021-60375434 liquan2@guosen.com.cn S0980524070002 投资建议 【行业动态】 【新能源车产业链数据】 【投资建议】 • 建议关注：1）低空经济与机器人产业布局领先企业（卧龙电驱、宁德时代、亿纬锂能、蔚蓝锂芯、科达利）；2）固态电池材料布局领先企业（厦钨新能、容百科技、当升科技、天奈科 技）；3）需求持续回暖的消费电池企业（珠海冠宇、豪鹏科技）；4）充电桩行业领先企业（特锐德、盛弘股份）；5）电动自行车铅酸电池领军企业（天能股份）；6）高压直流继电器 领先企业 ...

港股精选组合年内上涨 43.22%，相对恒生指数超额 22.88% 核心观点 金融工程周报 港股精选组合绩效回顾 本周，港股精选组合绝对收益 1.35%，相对恒生指数超额收益 0.42%。 本年，港股精选组合绝对收益 43.22%，相对恒生指数超额收益 22.88%。 港股市场创新高热点板块跟踪 我们根据分析师关注度、股价相对强弱、股价路径平稳性、创新高连续性等 角度在过去 20 个交易日创出过 250 日新高的股票池中筛选出平稳创新高股 票。 证券研究报告 | 2025年07月12日 港股投资周报 近期，国泰海通等股票平稳创出新高。 按照板块来看，创新高股票数量最多的是大金融板块，其次为医药、消费、 科技和周期板块，具体个股信息可参照正文。高股票数量最多的是消费，其 次为医药、科技、大金融、周期和制造板块，具体个股信息可参见正文。 港股市场一周回顾 宽基指数方面，本周恒生小型股指数收益最高，累计收益 2.59%；恒生科技 指数收益最低，累计收益 0.62%。 行业指数方面，本周工业行业收益最高，累计收益 3.30%；原材料业行业收 益最低，累计收益-4.18%。 概念板块方面，本周本地券商概念板块收益最高， ...

Core Insights - The report highlights the strong performance of growth styles, with all four active quantitative portfolios outperforming the stock fund index this week [1][14] - The report tracks the performance of various active quantitative strategies, including the Excellent Fund Performance Enhancement Portfolio, the Exceeding Expectations Selection Portfolio, the Broker's Golden Stock Performance Enhancement Portfolio, and the Growth Stability Portfolio [13][14] Excellent Fund Performance Enhancement Portfolio - This portfolio achieved an absolute return of 0.95% this week and a year-to-date return of 7.36%, ranking in the 45.95 percentile among active stock funds [1][23] - The strategy focuses on enhancing performance by benchmarking against active stock funds rather than broad indices, utilizing quantitative methods to select top-performing funds [3][18] Exceeding Expectations Selection Portfolio - The portfolio recorded an absolute return of 2.11% this week and 19.99% year-to-date, with a year-to-date excess return of 10.87% over the stock fund index, ranking in the 10.69 percentile among active stock funds [1][31] - The strategy involves selecting stocks based on exceeding expectations and analyst upgrades, focusing on both fundamental and technical criteria [4][55] Broker's Golden Stock Performance Enhancement Portfolio - This portfolio achieved an absolute return of 1.60% this week and 11.98% year-to-date, with a year-to-date excess return of 2.86% over the stock fund index, ranking in the 27.13 percentile among active stock funds [1][39] - The strategy is based on a selection of stocks from the broker's golden stock pool, optimizing the portfolio to minimize deviations from this pool [5][60] Growth Stability Portfolio - The portfolio achieved an absolute return of 2.21% this week and 26.87% year-to-date, with a year-to-date excess return of 17.76% over the stock fund index, ranking in the 5.42 percentile among active stock funds [1][44] - The strategy employs a two-dimensional evaluation system for growth stocks, prioritizing those with upcoming earnings announcements to capture potential excess returns [6][65]

Quantitative Models and Construction Methods Model Name: MFE (Maximized Factor Exposure) Portfolio - **Model Construction Idea**: The MFE portfolio aims to maximize the exposure to a single factor while controlling for various constraints such as industry exposure, style exposure, and individual stock weight deviations[40][41]. - **Model Construction Process**: - The optimization model is formulated as follows: $$ \begin{array}{ll} \text{max} & f^{T} w \\ \text{s.t.} & s_{l} \leq X(w - w_{b}) \leq s_{h} \\ & h_{l} \leq H(w - w_{b}) \leq h_{h} \\ & w_{l} \leq w - w_{b} \leq w_{h} \\ & b_{l} \leq B_{b} w \leq b_{h} \\ & \mathbf{0} \leq w \leq l \\ & \mathbf{1}^{T} w = 1 \end{array} $$ - **Explanation of Parameters**: - \( f \): Factor values - \( w \): Stock weight vector - \( X \): Factor exposure matrix for style factors - \( w_{b} \): Benchmark index component weights - \( s_{l}, s_{h} \): Lower and upper bounds for style factor exposure - \( H \): Industry exposure matrix - \( h_{l}, h_{h} \): Lower and upper bounds for industry exposure - \( w_{l}, w_{h} \): Lower and upper bounds for individual stock weight deviations - \( B_{b} \): 0-1 vector indicating whether a stock is a benchmark component - \( b_{l}, b_{h} \): Lower and upper bounds for component stock weight - \( l \): Upper limit for individual stock weight - The model aims to maximize the factor exposure while satisfying constraints on style, industry, and individual stock weights[40][41][42]. Factor Construction and Performance Factor Name: Standardized Unexpected Earnings (SUE) - **Factor Construction Idea**: Measures the deviation of actual earnings from expected earnings, standardized by the standard deviation of expected earnings[17]. - **Factor Construction Process**: - Formula: $$ \text{SUE} = \frac{\text{Actual Earnings} - \text{Expected Earnings}}{\text{Standard Deviation of Expected Earnings}} $$ - **Explanation**: This factor captures the surprise in earnings relative to market expectations, which can indicate potential stock price movements[17]. Factor Name: DELTAROE - **Factor Construction Idea**: Measures the change in Return on Equity (ROE) from the same quarter of the previous year[17]. - **Factor Construction Process**: - Formula: $$ \text{DELTAROE} = \text{Current Quarter ROE} - \text{ROE of the Same Quarter Last Year} $$ - **Explanation**: This factor indicates the improvement or deterioration in a company's profitability over time[17]. Factor Performance Monitoring Performance in Different Index Spaces - **CSI 300 Index**: - Recent week: Factors like Standardized Unexpected Earnings, Specificity, and Single Quarter EP performed well, while factors like 3-Month Earnings Revisions, 1-Month Turnover, and 1-Year Momentum performed poorly[1][18]. - Recent month: Factors like Single Quarter EP, Expected EPTTM, and EPTTM performed well, while factors like 1-Year Momentum, Illiquidity Shock, and 1-Month Turnover performed poorly[18]. - Year-to-date: Factors like Single Quarter Earnings Growth, Single Quarter Revenue Growth, and DELTAROE performed well, while factors like 1-Year Momentum, 1-Month Turnover, and 3-Month Turnover performed poorly[18]. - **CSI 500 Index**: - Recent week: Factors like Standardized Unexpected Earnings, Specificity, and SPTTM performed well, while factors like Single Quarter ROA, Single Quarter ROE, and 3-Month Institutional Coverage performed poorly[1][20]. - Recent month: Factors like DELTAROE, Single Quarter Earnings Growth, and Single Quarter Net Profit Growth performed well, while factors like 3-Month Institutional Coverage, 1-Month Turnover, and Illiquidity Shock performed poorly[20]. - Year-to-date: Factors like Single Quarter Revenue Growth, 1-Month Reversal, and Expected PEG performed well, while factors like EPTTM, 3-Month Volatility, and 1-Month Turnover performed poorly[20]. - **CSI 1000 Index**: - Recent week: Factors like DELTAROE, Single Quarter Earnings Growth, and DELTAROA performed well, while factors like Expected EPTTM, 3-Month Institutional Coverage, and 3-Month Turnover performed poorly[1][22]. - Recent month: Factors like Standardized Unexpected Earnings, BP, and Single Quarter Net Profit Growth performed well, while factors like Illiquidity Shock, 3-Month Institutional Coverage, and 3-Month Turnover performed poorly[22]. - Year-to-date: Factors like Standardized Unexpected Earnings, Standardized Unexpected Revenue, and Illiquidity Shock performed well, while factors like 3-Month Volatility, 1-Month Volatility, and Single Quarter ROE performed poorly[22]. - **CSI A500 Index**: - Recent week: Factors like Specificity, Expected EPTTM, and Single Quarter Earnings Growth performed well, while factors like 3-Month Earnings Revisions, 1-Month Turnover, and 3-Month Turnover performed poorly[1][24]. - Recent month: Factors like Expected EPTTM, Single Quarter Earnings Growth, and Single Quarter EP performed well, while factors like 1-Month Turnover, 3-Month Turnover, and Illiquidity Shock performed poorly[24]. - Year-to-date: Factors like Expected PEG, Single Quarter Earnings Growth, and DELTAROE performed well, while factors like 1-Year Momentum, 1-Month Turnover, and SPTTM performed poorly[24]. - **Public Fund Heavyweight Index**: - Recent week: Factors like Specificity, DELTAROE, and DELTAROA performed well, while factors like 3-Month Earnings Revisions, 3-Month Turnover, and 1-Month Turnover performed poorly[1][26]. - Recent month: Factors like Expected EPTTM, Single Quarter Earnings Growth, and Single Quarter EP performed well, while factors like Illiquidity Shock, 1-Year Momentum, and 3-Month Institutional Coverage performed poorly[26]. - Year-to-date: Factors like DELTAROA, DELTAROE, and Standardized Unexpected Earnings performed well, while factors like 1-Month Volatility, BP, and Expected BP performed poorly[26]. Model Backtesting Results CSI 300 Index Enhanced Portfolio - Weekly excess return: -0.30% - Year-to-date excess return: 7.76%[5][14] CSI 500 Index Enhanced Portfolio - Weekly excess return: 0.31% - Year-to-date excess return: 9.34%[5][14] CSI 1000 Index Enhanced Portfolio - Weekly excess return: 0.39% - Year-to-date excess return: 14.45%[5][14] CSI A500 Index Enhanced Portfolio - Weekly excess return: 0.71% - Year-to-date excess return: 9.03%[5][14] Public Fund Index Enhanced Product Performance CSI 300 Index Enhanced Products - Weekly excess return: Highest 0.87%, Lowest -0.57%, Median 0.24% - Monthly excess return: Highest 2.06%, Lowest -0.45%, Median 0.63%[2][31] CSI 500 Index Enhanced Products - Weekly excess return: Highest 0.90%, Lowest -0.68%, Median 0.24% - Monthly excess return: Highest 2.46%, Lowest -0.12%, Median 1.02%[2][34] CSI 1000 Index Enhanced Products - Weekly excess return: Highest 1.06%, Lowest -0.31%, Median 0.29% - Monthly excess return: Highest 2.98%, Lowest -0.74%, Median 1.21%[2][37] CSI A500 Index Enhanced Products - Weekly excess return: Highest 0.80%, Lowest -0.35%, Median 0.20% - Monthly excess return: Highest 1.81%, Lowest -0.34%, Median 1.13%[3][39]

The provided content does not contain any quantitative models or factors, nor does it include their construction, evaluation, or backtesting results. The documents primarily focus on market performance, sector analysis, ETF premiums/discounts, institutional activity, and other market-related data. There are no references to quantitative models or factors in the provided text.

Investment Rating - The investment rating for the company is "Outperform the Market" [2][4][18] Core Viewpoints - The company has successfully established a new materials business unit, which is expected to create new profit growth points. The new materials include high-end polyurethane vibration damping products, silicone PACK functional materials, and HP-RTM PACK structural materials [3][5] - The company anticipates steady growth in its new materials business, with products such as polyurethane, silicone, and HP-RTM already achieving bulk supply, potentially enhancing profit margins [4] - The wind turbine blade orders are robust, with promising overseas market prospects. The wind power blade business is expected to see both volume and profit growth by 2025, with a factory in Vietnam projected to start production in early 2026 [4] - The rail transportation and industrial engineering businesses are expected to maintain stable revenue, with further growth anticipated post-2026 when production capacity is restored [4] - The automotive business is gradually shifting production capacity to lower-cost regions in Asia, with ongoing efforts to expand the customer base [4] Financial Projections - The company forecasts a net profit of 6.5 billion yuan for 2025, with slight upward adjustments for 2026 and 2027 to 8.4 billion yuan and 9.8 billion yuan, respectively, reflecting year-on-year growth rates of +46.7%, +28.8%, and +16.2% [4][18] - The projected revenue for 2025 is 22.75 billion yuan, with a year-on-year growth of +13.4%, and for 2026, it is expected to reach 25.43 billion yuan, with a growth of +11.8% [17][21] - The company's current price-to-earnings (PE) ratios are projected to be 16.7, 13.0, and 11.2 for 2025, 2026, and 2027, respectively [4][18]