Quantitative Models and Construction Methods Barra Style Factors - **Model Name**: Barra Style Factors - **Construction Idea**: The Barra style factors are designed to capture the performance of different market styles, such as size, value, growth, and profitability, through specific factor definitions[4][14] - **Construction Process**: - **Size Factor**: Measures the market capitalization of stocks - **Value Factor**: Captures the book-to-market ratio of stocks - **Growth Factor**: Reflects the growth potential of stocks - **Profitability Factor**: Based on earnings expectations[4][14] - **Evaluation**: These factors are widely used in the industry to analyze market trends and style rotations[4][14] --- Open-source Trading Behavior Factors - **Factor Name**: Ideal Reversal Factor - **Construction Idea**: Identifies the strongest reversal days by analyzing the average transaction size of large trades[5][15] - **Construction Process**: 1. Retrieve the past 20 trading days' data for a stock 2. Calculate the average transaction size per day (transaction amount/number of transactions) 3. Identify the 10 days with the highest transaction sizes and sum their returns (M_high) 4. Identify the 10 days with the lowest transaction sizes and sum their returns (M_low) 5. Compute the factor as $M = M_{high} - M_{low}$[43] - **Evaluation**: Captures the microstructure of reversal forces in the A-share market[5][15] - **Factor Name**: Smart Money Factor - **Construction Idea**: Tracks institutional trading activity by analyzing minute-level price and volume data[5][15] - **Construction Process**: 1. Retrieve the past 10 days' minute-level data for a stock 2. Construct the indicator $S_t = |R_t| / V_t^{0.25}$, where $R_t$ is the return at minute $t$, and $V_t$ is the trading volume at minute $t$ 3. Sort minute-level data by $S_t$ in descending order and select the top 20% of minutes by cumulative trading volume 4. Calculate the volume-weighted average price (VWAP) for smart money trades ($VWAP_{smart}$) and all trades ($VWAP_{all}$) 5. Compute the factor as $Q = VWAP_{smart} / VWAP_{all}$[42][44] - **Evaluation**: Effectively identifies institutional trading patterns[5][15] - **Factor Name**: APM Factor - **Construction Idea**: Measures the difference in trading behavior between morning (or overnight) and afternoon sessions[5][15] - **Construction Process**: 1. Retrieve the past 20 days' data for a stock 2. Calculate daily overnight and afternoon returns for both the stock and the index 3. Perform a regression of stock returns on index returns to obtain residuals 4. Compute the difference between overnight and afternoon residuals for each day 5. Calculate the statistic $\mathrm{stat} = \frac{\mu(\delta_t)}{\sigma(\delta_t) / \sqrt{N}}$, where $\mu$ is the mean, $\sigma$ is the standard deviation, and $N$ is the sample size 6. Regress the statistic on momentum factors and use the residual as the APM factor[43][45][46] - **Evaluation**: Captures intraday trading behavior differences[5][15] - **Factor Name**: Ideal Amplitude Factor - **Construction Idea**: Measures the structural differences in amplitude information between high and low price states[5][15] - **Construction Process**: 1. Retrieve the past 20 trading days' data for a stock 2. Calculate the daily amplitude as $(\text{High Price}/\text{Low Price}) - 1$ 3. Compute the average amplitude for the top 25% of days with the highest closing prices ($V_{high}$) 4. Compute the average amplitude for the bottom 25% of days with the lowest closing prices ($V_{low}$) 5. Compute the factor as $V = V_{high} - V_{low}$[48] - **Evaluation**: Highlights amplitude differences across price states[5][15] - **Factor Name**: Composite Trading Behavior Factor - **Construction Idea**: Combines the above trading behavior factors using ICIR-based weights to enhance predictive power[31] - **Construction Process**: 1. Standardize and winsorize the individual factors within industries 2. Use the past 12 periods' ICIR values as weights to compute the composite factor[31] - **Evaluation**: Demonstrates superior performance in small-cap stock pools[32] --- Backtesting Results of Models and Factors Barra Style Factors - **Size Factor**: Return of 0.64% in July 2025[4][14] - **Value Factor**: Return of 0.59% in July 2025[4][14] - **Growth Factor**: Return of 0.16% in July 2025[4][14] - **Profitability Factor**: Return of -0.32% in July 2025[4][14] Open-source Trading Behavior Factors - **Ideal Reversal Factor**: - IC: -0.050 - RankIC: -0.061 - IR: 2.52 - Long-short monthly win rate: 78.3% (historical), 66.7% (last 12 months) - July 2025 long-short return: 0.47%[6][16] - **Smart Money Factor**: - IC: -0.037 - RankIC: -0.061 - IR: 2.76 - Long-short monthly win rate: 82.2% (historical), 91.7% (last 12 months) - July 2025 long-short return: 1.78%[6][19] - **APM Factor**: - IC: 0.029 - RankIC: 0.034 - IR: 2.30 - Long-short monthly win rate: 77.4% (historical), 58.3% (last 12 months) - July 2025 long-short return: 1.42%[6][23] - **Ideal Amplitude Factor**: - IC: -0.054 - RankIC: -0.073 - IR: 3.03 - Long-short monthly win rate: 83.6% (historical), 75.0% (last 12 months) - July 2025 long-short return: 3.86%[6][28] - **Composite Trading Behavior Factor**: - IC: 0.067 - RankIC: 0.092 - IR: 3.30 - Long-short monthly win rate: 82.6% (historical), 83.3% (last 12 months) - July 2025 long-short return: 2.13%[6][31]

Group 1: Macro Economic Insights - The Federal Reserve maintained the interest rate at 4.25%-4.5% during the July FOMC meeting, indicating high economic uncertainty and internal divisions within the Fed regarding potential rate cuts [4][5][6] - The U.S. GDP for Q2 recorded a growth of 3.0% quarter-on-quarter, showing resilience despite signs of economic softening, which reduces the urgency for rate cuts [5][6] - The political bureau meeting in China emphasized the need to enhance awareness of potential risks while focusing on expanding domestic demand and maintaining strategic determination during the 14th Five-Year Plan [9][10][11] Group 2: Industry Insights - Communication - Meta's Q2 revenue reached $47.52 billion, exceeding expectations, and the company raised its full-year capital expenditure guidance to between $66 billion and $72 billion, reflecting significant investments in AI and smart glasses [27] - Microsoft reported a strong performance in its cloud business, with Q4 revenue of $76.44 billion, a year-on-year increase of 18%, driven by a 26% growth in its intelligent cloud segment [28] - The AI computing industry is expected to enter a valuation uplift phase, with significant investment opportunities identified in various segments such as optical modules and liquid cooling technologies [29] Group 3: Industry Insights - Banking - Insurance capital is increasingly allocated to bank stocks, driven by high dividend yields and favorable tax conditions in the Hong Kong market, indicating a shift towards long-term equity investments [36][37] - The current environment of declining asset yields and regulatory changes is prompting insurance companies to seek higher dividend investments, particularly in the banking sector [37] - The evolving PB-ROE curve suggests a shift in valuation logic from fundamental factors to dividend-based assessments, highlighting the importance of maintaining reasonable PB differentials among banks [39][40] Group 4: Industry Insights - Pharmaceuticals - Guobang Pharmaceutical reported a 4.63% year-on-year increase in revenue for H1 2025, with a significant 70.37% growth in its animal health segment, indicating strong market demand [42][43] - WuXi AppTec's H1 revenue grew by 20.64% year-on-year, driven by robust performance in its TIDES business, with a significant increase in orders and revenue projections for the upcoming years [46][48] - Enhua Pharmaceutical's revenue for H1 2025 reached 3.01 billion yuan, with a notable 107.33% growth in its neurology segment, reflecting successful product differentiation and innovation [52][54]

Quantitative Models and Construction Methods Model: Duration Timing Model - **Construction Idea**: Predict the yield curve and map the expected returns of bonds with different durations[20] - **Construction Process**: - Use the improved Diebold2006 model to predict the instantaneous yield curve - Predict level, slope, and curvature factors - Level factor prediction based on macro variables and policy rate following - Slope and curvature factors prediction based on AR(1) model[20] - **Evaluation**: The model effectively predicts the yield curve and provides actionable insights for bond duration management[20] - **Test Results**: - July return: 6.6bp - Benchmark return: -25.8bp - Strategy excess return: 32.4bp[21] Model: Gold Timing Model - **Construction Idea**: Relate the forward real returns of gold and US TIPS to construct the expected return model for gold[32] - **Construction Process**: - Use the formula: $E[Real\_Return^{gold}]=k\times E[Real\_Return^{Tips}]$ - Estimate parameter k using OLS with an extended window - Use the Fed's long-term inflation target of 2% as a proxy[32] - **Evaluation**: The model provides a robust framework for predicting gold returns based on TIPS yields[32] - **Test Results**: - Expected return for the next year: 22.4% - Past year absolute return: 39.77%[33][35] Model: Active Risk Budget Model - **Construction Idea**: Combine the risk parity model with active signals to construct an active risk budget model for optimal stock and bond allocation[37] - **Construction Process**: - Use the Fed model to define equity risk premium (ERP): $ERP={\frac{1}{PE_{ttm}}}-YTM_{TB}^{10Y}$ - Adjust asset weights dynamically based on ERP, stock valuation percentiles, and market liquidity (M2-M1 spread) - Convert equity asset signal scores into risk budget weights using the softmax function: $softmax(x)={\frac{\exp(\lambda x)}{\exp(\lambda x)+\exp(-\lambda x)}}$[39][47] - **Evaluation**: The model dynamically adjusts asset weights based on multiple dimensions, providing a balanced risk-return profile[37] - **Test Results**: - July stock position: 18.72% - Bond position: 81.28% - July portfolio return: 0.84% - August stock position: 7.44% - Bond position: 92.56%[51] Model Backtest Results 1. **Duration Timing Model** - July return: 6.6bp - Benchmark return: -25.8bp - Strategy excess return: 32.4bp[21] 2. **Gold Timing Model** - Expected return for the next year: 22.4% - Past year absolute return: 39.77%[33][35] 3. **Active Risk Budget Model** - July stock position: 18.72% - Bond position: 81.28% - July portfolio return: 0.84% - August stock position: 7.44% - Bond position: 92.56%[51] Quantitative Factors and Construction Methods Factor: High-Frequency Macroeconomic Factors - **Construction Idea**: Use asset portfolio simulation to construct a high-frequency macro factor system to observe market macro expectations[12] - **Construction Process**: - Combine real macro indicators to form low-frequency macro factors - Select assets leading low-frequency macro factors - Use rolling multiple leading regression to determine asset weights and simulate macro factor trends[12] - **Evaluation**: High-frequency macro factors provide leading indicators for market expectations, offering valuable insights for asset allocation[12] Factor: Convertible Bond Valuation Factors - **Construction Idea**: Compare the relative valuation of convertible bonds and stocks, and between convertible bonds and credit bonds[25] - **Construction Process**: - Construct the "100-yuan conversion premium rate" to compare the valuation of convertible bonds and stocks - Use the "modified YTM - credit bond YTM" median to compare the valuation of debt-biased convertible bonds and credit bonds - Construct style rotation portfolios based on market sentiment indicators like 20-day momentum and volatility deviation[25][27] - **Evaluation**: The factors effectively capture the relative valuation and style characteristics of convertible bonds, aiding in portfolio construction[25][27] - **Test Results**: - "100-yuan conversion premium rate": 33.71% - "Modified YTM - credit bond YTM" median: -2.06% - Style rotation annualized return: 24.54% - Maximum drawdown: 15.89% - IR: 1.47 - Monthly win rate: 65.17% - 2025 return: 35.17%[26][29] Factor Backtest Results 1. **High-Frequency Macroeconomic Factors** - High-frequency economic growth: Upward trend - High-frequency consumer inflation: Downward trend - High-frequency producer inflation: Upward trend[17] 2. **Convertible Bond Valuation Factors** - "100-yuan conversion premium rate": 33.71% - "Modified YTM - credit bond YTM" median: -2.06% - Style rotation annualized return: 24.54% - Maximum drawdown: 15.89% - IR: 1.47 - Monthly win rate: 65.17% - 2025 return: 35.17%[26][29]

Investment Rating - The investment rating for Guobang Pharmaceutical is "Buy" (maintained) [1] Core Views - In Q2 2025, the company's performance exceeded expectations, with significant growth in the animal health sector. The company achieved a revenue of 30.26 billion yuan in the first half of 2025, representing a year-on-year increase of 4.63%. The net profit attributable to the parent company was 4.56 billion yuan, up by 12.6% [4][5] - The animal health segment saw a remarkable revenue increase of 70.37% in the first half of 2025, with the sales volume of Florfenicol surpassing 2000 tons, indicating a continuous rise in market share [5] - The company maintains its profit forecast, expecting net profits of 9.95 billion yuan, 12.35 billion yuan, and 13.91 billion yuan for 2025, 2026, and 2027 respectively, with a current price-to-earnings ratio of 13.3, 10.7, and 9.5 times for the respective years, indicating high valuation attractiveness [4][5] Financial Summary - In the first half of 2025, the company reported a gross margin of 26.85% and a net margin of 15.00%, with improvements in both metrics compared to the previous year [4] - The company’s revenue for the pharmaceutical segment was 17.35 billion yuan, down by 9.87%, while the animal health segment generated 12.59 billion yuan [5] - Research and development expenses increased to 0.97 billion yuan, representing a growth of 4.80%, with a research expense ratio of 3.22% [6] Financial Forecast - The company forecasts revenues of 67.86 billion yuan, 76.15 billion yuan, and 82.65 billion yuan for 2025, 2026, and 2027 respectively, with year-on-year growth rates of 15.2%, 12.2%, and 8.5% [7] - The net profit attributable to the parent company is projected to be 9.95 billion yuan, 12.35 billion yuan, and 13.91 billion yuan for the same years, with corresponding year-on-year growth rates of 27.4%, 24.1%, and 12.7% [7][10]

Investment Rating - The industry investment rating is "Overweight" (maintained) [1] Core Viewpoints - The report highlights a positive outlook for the telecommunications industry, driven by significant growth in AI-related investments and advancements in optical communication technologies [4][5] - Major companies such as Meta and Microsoft are increasing their capital expenditures, indicating a robust investment environment in AI and cloud services [4][5] - The report emphasizes the importance of the AI computing power supply chain and suggests various investment opportunities across different segments, including optical modules, liquid cooling, and optical chips [5] Summary by Sections Industry Trends - The telecommunications sector is expected to outperform the overall market, with a focus on AI and optical communication growth [1][4] - Recent financial results from companies like Celestica and Corning show significant year-over-year revenue growth, indicating a strong market demand [4] Company Performance - Meta reported Q2 2025 revenue of $47.52 billion, exceeding expectations, and raised its full-year capital expenditure guidance to between $66 billion and $72 billion [4] - Microsoft’s cloud business showed impressive growth, with a 26% year-over-year increase in Azure revenue [4] Investment Opportunities - The report identifies key investment targets within the AI computing power supply chain, recommending specific companies in various segments such as optical modules and liquid cooling [5] - Notable recommended stocks include Zhongji Xuchuang and New Yisheng in the optical module sector, and Yingwei in the liquid cooling segment [5]

Investment Rating - The industry investment rating is "Overweight" [1][11] Core Views - The report highlights the strong performance of companies in the liquid cooling sector, driven by increasing demand due to the rise of AI technologies [4][5][6] - The report emphasizes that liquid cooling is transitioning from an optional solution to a necessary one in the AI era, due to factors such as increasing power consumption of mainstream computing chips and the need for high-density data centers [6] Summary by Sections Company Performance - Vertiv reported Q2 2025 revenue of $2.638 billion, exceeding the previous guidance of $2.35 billion, with a year-on-year growth of 35% and a quarter-on-quarter growth of 30% [4] - Celestica achieved Q2 2025 revenue of $2.89 billion, a 21% year-on-year increase, and raised its full-year revenue guidance to $11.55 billion from $10.85 billion [5] Market Trends - The report notes that the demand for liquid cooling solutions is expected to rise significantly, driven by the AI boom and the increasing power density of AI clusters [6] - The report recommends several companies as key players in the liquid cooling market, including Yingwei, Shunling Environment, and Yinhong Shares, among others [6]

Investment Rating - The investment rating for WuXi AppTec is maintained as "Buy" [1] Core Views - The company reported strong performance in H1 2025, with revenue reaching 20.64% year-on-year growth and a significant increase in net profit by 101.92% [4][5] - The TIDES business segment showed robust growth, with revenue increasing by 141.6% year-on-year, indicating strong demand and expansion potential [5] - The company has raised its revenue guidance for 2025 from 41.5-43 billion to 42.5-43.5 billion, reflecting positive market conditions and order growth [4] Financial Performance Summary - In H1 2025, the company achieved revenue of 20.799 billion, a 20.64% increase year-on-year, and a net profit of 8.561 billion, up 101.92% [4] - For Q2 2025, revenue was 11.145 billion, showing a 20.37% year-on-year increase and a 15.43% quarter-on-quarter increase [4] - The adjusted Non-IFRS net profit for H1 2025 was 6.31 billion, reflecting a 44.4% year-on-year growth [4] Business Segment Performance - The chemical business segment generated revenue of 16.3 billion in H1 2025, marking a 33.5% increase year-on-year [5] - The TIDES business segment's revenue was approximately 5.03 billion in H1 2025, with a 48.8% increase in orders by the end of June 2025 [5] - The clinical business segment reported a slight decline in revenue, but the overall performance remains stable with a focus on expanding new molecular types [6] Financial Projections - The company expects net profit for 2025-2027 to be 13.407 billion, 15.127 billion, and 17.939 billion respectively, with EPS projected at 4.67, 5.27, and 6.25 [4][8] - The current price-to-earnings ratio (PE) is projected at 21.2, 18.8, and 15.8 for the years 2025, 2026, and 2027 respectively [4][8]

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The company's neuro-related business is experiencing rapid growth, and its innovative pipeline is gradually being realized. The performance drivers are clear, and the company is expected to maintain its profit forecast [4][5] Financial Performance Summary - In H1 2025, the company achieved revenue of 3.01 billion yuan (up 8.93% year-on-year, up 2.59% quarter-on-quarter) and a net profit attributable to shareholders of 700 million yuan (up 11.38% year-on-year, up 36.11% quarter-on-quarter). The gross margin was 75.24% (up 2.74 percentage points), and the net margin was 23.26% (up 0.59 percentage points) [3][4] - For Q2 2025, the company reported revenue of 1.499 billion yuan (up 6.64% year-on-year, down 0.77% quarter-on-quarter) and a net profit of 400 million yuan (up 9.94% year-on-year, up 32.95% quarter-on-quarter) [3] Business Segment Performance - In H1 2025, the revenue breakdown by business segment was as follows: Anesthesia products at 1.634 billion yuan (up 7.32%), psychiatric products at 621 million yuan (up 4.29%), neuro products at 166 million yuan (up 107.33%), raw materials at 90 million yuan (down 6.17%), and commercial pharmaceuticals at 394 million yuan (up 9.80%) [4] Future Profit Forecast - The company is expected to achieve net profits attributable to shareholders of 1.294 billion yuan, 1.495 billion yuan, and 1.746 billion yuan for the years 2025, 2026, and 2027, respectively. The expected EPS for these years is 1.27 yuan, 1.47 yuan, and 1.72 yuan per share, with corresponding P/E ratios of 17.5, 15.2, and 13.0 times [4][8] R&D and Innovation Pipeline - The company is focusing on product differentiation and has 17 innovative drug projects in development. It has completed one Phase III clinical trial and two Phase II trials, with several other projects at various stages of clinical research [5]

宏观经济点评 2025 年 07 月 31 日 美联储内部分歧加大，降息或尚需时日 宏观研究团队 ——7 月 FOMC 会议点评 hening@kysec.cn 证书编号：S0790522110002 何宁（分析师） 潘纬桢（分析师） panweizhen@kysec.cn 证书编号：S0790122110044 事件：美联储于北京时间 7 月 31 日凌晨 2 点发布 7 月 FOMC 会议声明，宣布保 持利率水平不变。 声明及发布会要点 1. 美联储在此次会议上宣布维持利率水平在 4.25%-4.5%区间。缩表方面，将继 续按照 3 月 FOMC 会议上的原定计划执行。 2. 再次维持利率水平不变，认为经济不确定性仍高，出现 2 张反对票。在声明 中，美联储的措辞同 6 月份相比略有变化，认为虽然净出口的波动影响了经济数 据，但上半年美国经济活动增长有所放缓。就业与通胀方面，与 6 月表述基本相 同。但美联储认为美国经济前景的不确定性依旧高涨。此外，本次会议中出现两 票反对，鲍曼以及沃勒认为本次会议中应该降息 25bp，与其前期表态一致，但 凸显出美联储内部的分歧进一步显性化。 3. 发布会上，鲍威尔表态 ...

Economic Outlook - The Politburo meeting on July 30 emphasized the strong vitality and resilience of the economy in the first half of the year, while urging caution for the second half[2] - The focus for the "14th Five-Year Plan" is expected to be on actively expanding domestic demand and responding to external changes, particularly in manufacturing investment and service consumption[2][3] Policy Direction - The macro policy will continue to exert force and adapt as necessary, with a key emphasis on effectively releasing policy effects and potential for domestic demand[3][4] - Fiscal policy will prioritize the implementation of existing policies, focusing on quality rather than quantity, to enhance the fiscal multiplier effect[4] Fiscal and Monetary Measures - The issuance of special bonds and ultra-long-term treasury bonds is expected to maintain a certain intensity in Q3, with a focus on consumption and investment[4] - There is a higher probability of interest rate cuts and reserve requirement ratio reductions in Q4 compared to Q3, given the economic pressures[5] Domestic Demand and Investment - The meeting highlighted the importance of effectively releasing domestic demand potential, with a focus on service consumption growth and investment in urban renewal projects[5][6] - Urban development is shifting from expansion to quality improvement, emphasizing the renovation of existing structures and infrastructure upgrades[6] Market and Trade Stability - The meeting underscored the need to stabilize foreign trade and foreign investment, with policies aimed at maintaining a solid foundation in these areas[6] - There is a continued emphasis on stabilizing the stock market to attract long-term capital and maintain market momentum[6]