证券研究报告·金融工程·金工定期报告 金工定期报告 20250701 证券分析师 高子剑 执业证书：S0600518010001 021-60199793 gaozj@dwzq.com.cn 证券分析师 庞格致 执业证书：S0600524090003 panggz@dwzq.com.cn 证券分析师 凌志杰 执业证书：S0600525040007 lingzhj@dwzq.com.cn 相关研究 新价量相关性因子绩效月报 20250630 2025 年 07 月 01 日 [Table_Tag] [Table_Summary] 报告要点 《 新 价 量 相 关 性 因 子 绩 效 月 报 20250530》 2025-06-06 《"技术分析拥抱选股因子"系列研究 （十四）：RPV 聪明版——聪明换手率 是更好的配料》 2023-09-27 东吴证券研究所 1 / 7 请务必阅读正文之后的免责声明部分 ◼ 新价量相关性 RPV 因子多空对冲绩效（全市场）：2014 年 1 月至 2025 年 6 月，新价量相关性 RPV 因子在全体 A 股（剔除北交所股票）中， 10 分组多空对冲的年化收益为 14.57%， ...

Quantitative Models and Construction Methods 1. Model Name: "Day and Night Convergence" New Momentum Factor - **Model Construction Idea**: This model improves traditional momentum factors by incorporating the price-volume relationship during intraday and overnight trading periods. It aims to capture distinct characteristics and logic in these two periods to enhance the stability and effectiveness of momentum signals [6][7]. - **Model Construction Process**: 1. The trading session is divided into intraday and overnight periods. 2. The price-volume relationship is separately analyzed for each period. 3. Based on these analyses, the intraday and overnight factors are improved and synthesized into a new momentum factor [7]. - **Model Evaluation**: The model demonstrates significant stock selection ability, outperforming traditional momentum factors in terms of stability and performance [6][7]. --- Model Backtesting Results 1. "Day and Night Convergence" New Momentum Factor - **Annualized Return**: 18.15% [7][14] - **Annualized Volatility**: 8.79% [7][14] - **Information Ratio (IR)**: 2.07 [7][14] - **Monthly Win Rate**: 77.37% [7][14] - **Maximum Drawdown**: 9.07% [7][14] --- Quantitative Factors and Construction Methods 1. Factor Name: "Day and Night Convergence" New Momentum Factor - **Factor Construction Idea**: The factor is based on the price-volume relationship during intraday and overnight trading periods. It leverages the distinct characteristics of these periods to refine momentum signals [7]. - **Factor Construction Process**: 1. Divide the trading session into intraday and overnight periods. 2. Analyze the price-volume relationship for each period. 3. Construct separate momentum factors for intraday and overnight periods. 4. Synthesize the two factors into a new momentum factor [7]. - **Factor Evaluation**: The factor shows superior performance compared to traditional momentum factors, with higher stability and stock selection capability [6][7]. --- Factor Backtesting Results 1. "Day and Night Convergence" New Momentum Factor - **Annualized Return**: 22.64% [6] - **Information Ratio (IR)**: 2.85 [6] - **Monthly Win Rate**: 83.33% [6] - **Maximum Drawdown**: 5.79% [6]

Quantitative Factors and Construction Methods 1. Factor Name: CP (Overconfidence Factor) - **Construction Idea**: Based on the behavioral finance concept of overconfidence, the factor uses the time difference between rapid price increases and decreases as a proxy variable to measure investor overconfidence [6] - **Construction Process**: - The factor is derived from the DHS model, which posits that investor overconfidence impacts stock prices - The time difference between rapid price increases (positive news) and rapid price decreases (negative news) is calculated to quantify overconfidence [6] - **Evaluation**: The CP factor innovatively captures overconfidence behavior but does not account for subsequent overcorrections in stock prices [6] 2. Factor Name: RCP (Reclaimed Confidence Factor) - **Construction Idea**: Extends the CP factor by considering potential overcorrections (excessive pessimism) during price pullbacks, followed by subsequent rebounds due to positive news [6] - **Construction Process**: - The CP factor is orthogonalized with intraday returns to remove noise - The residual term from this process is used to construct the RCP factor, which represents reclaimed confidence after overcorrection [6] - In the 2.0 version, standardized factor values replace ranking values to retain more factor information, improving the purity and effectiveness of the RCP factor [7] - **Evaluation**: The RCP factor demonstrates superior performance compared to traditional factor-based portfolio construction methods, particularly after the 2.0 enhancements [6][7] --- Factor Backtesting Results 1. CP Factor - No specific backtesting results provided for the CP factor in the report 2. RCP Factor (2.0 Version) - **Annualized Return**: 18.45% [7][10] - **Annualized Volatility**: 7.69% [7][10] - **Information Ratio (IR)**: 2.40 [7][10] - **Monthly Win Rate**: 78.10% [7][10] - **Maximum Drawdown**: 5.89% [7][10] 3. June 2025 Performance (RCP Factor) - **Long Portfolio Return**: 4.75% [11] - **Short Portfolio Return**: 5.64% [11] - **Long-Short Portfolio Return**: -0.89% [11]

金工定期报告 20250701 估值异常因子绩效月报 20250630 2025 年 07 月 01 日 [Table_Tag] [Table_Summary] 报告要点 证券研究报告·金融工程·金工定期报告 证券分析师 高子剑 执业证书：S0600518010001 021-60199793 gaozj@dwzq.com.cn 证券分析师 庞格致 执业证书：S0600524090003 panggz@dwzq.com.cn 相关研究 《估值异常因子绩效月报 20250530》 2025-06-06 《从布林带到估值异常因子》 2022-06-17 东吴证券研究所 1 / 7 请务必阅读正文之后的免责声明部分 ◼ 估值偏离 EPD 因子多空对冲绩效（全市场）：2010 年 2 月至 2025 年 6 月，估值偏离 EPD 因子在全体 A 股（剔除北交所股票）中，5 分组多 空对冲的年化收益为 17.61%，年化波动为 9.98%，信息比率为 1.76，月 度胜率为 70.81%，月度最大回撤为 8.93%。 ◼ 缓慢偏离 EPDS 因子多空对冲绩效（全市场）：2010 年 2 月至 2025 年 6 月，缓慢 ...

Investment Rating - The investment rating for the company is "Buy" (maintained) [1] Core Views - The company is expected to achieve a net profit attributable to shareholders of 16.3 to 17.0 billion yuan in the first half of 2025, representing a year-on-year increase of 12.6% to 17.4% [5] - The company anticipates a significant increase in net profit in the second quarter of 2025, with estimates ranging from 8.3 to 9.0 billion yuan, reflecting a year-on-year growth of 12.5% to 22.0% [5] - The strong performance in the Yiwu import and export market, with a total import and export value of 327.13 billion yuan from January to May 2025, shows a year-on-year growth of 23.7% [5] - The company's payment platform, Yi Payment, has seen a substantial increase in cross-border collection amounts, exceeding 2.5 billion USD, which is a year-on-year growth of over 47% [5] - The global digital trade center's market segment has exceeded the company's expectations in terms of招商 (招商 means "investment attraction"), with the first batch of 389 fashion jewelry industry shops fully completed [5] - The company maintains a strong strategic position as a non-US export hub, with profit forecasts for 2025-2027 set at 42.3 billion, 57.1 billion, and 68.3 billion yuan respectively, indicating year-on-year growth rates of 38%, 35%, and 19% [5] Financial Summary - Total revenue for 2023 is projected at 11.3 billion yuan, with a year-on-year growth of 48.3% [1] - The diluted earnings per share (EPS) for 2025 is estimated to be 0.77 yuan, with a price-to-earnings (P/E) ratio of 26.80 based on the latest diluted figures [1] - The company's total assets are expected to reach 43.34 billion yuan by 2025, with a debt-to-asset ratio of 48.56% [6]

Quantitative Models and Construction Methods 1. Model Name: Expected High Dividend Portfolio - **Model Construction Idea**: The model uses a two-stage process to construct the expected dividend yield indicator. The first stage calculates the dividend yield based on annual report profit distribution data, while the second stage predicts and calculates the dividend yield using historical dividend data and fundamental indicators. Additionally, two short-term factors—reversal factor and profitability factor—are used to assist in stock selection. The portfolio is optimized within the CSI 300 constituents[4][9] - **Model Construction Process**: 1. Exclude suspended and limit-up stocks from the CSI 300 constituents to form the initial stock pool[14] 2. Remove the top 20% of stocks with the highest short-term momentum (21-day cumulative returns)[14] 3. Exclude stocks with declining profitability (quarterly net profit growth rate < 0)[14] 4. Rank the remaining stocks by expected dividend yield and select the top 30 stocks to construct an equal-weighted portfolio[10] - **Model Evaluation**: The model demonstrates a systematic approach to identifying high-dividend stocks, leveraging both historical data and fundamental analysis for robust stock selection[4][9] --- Model Backtesting Results 1. Expected High Dividend Portfolio - **Cumulative Return**: 358.90% relative to the CSI 300 Total Return Index from February 2, 2009, to August 31, 2017[12] - **Cumulative Excess Return**: 107.44% over the same period[12] - **Annualized Excess Return**: 8.87%[12] - **Maximum Drawdown of Rolling One-Year Excess Return**: 12.26%[12] - **Monthly Excess Win Rate**: 60.19%[12] --- Quantitative Factors and Construction Methods 1. Factor Name: Expected Dividend Yield Factor - **Factor Construction Idea**: This factor predicts dividend yield by combining historical dividend data with fundamental indicators. It is used to identify stocks with high expected dividend yields[4][15] - **Factor Construction Process**: 1. Calculate dividend yield based on annual report profit distribution data[4][9] 2. Predict and calculate dividend yield using historical dividend data and fundamental indicators[4][9] - **Factor Evaluation**: The factor effectively integrates historical and fundamental data to predict dividend yields, providing a solid foundation for high-dividend stock selection[4][15] 2. Factor Name: Reversal Factor - **Factor Construction Idea**: This factor identifies stocks with short-term price reversals, which may impact dividend yield predictions[4][15] - **Factor Construction Process**: Measure short-term momentum using 21-day cumulative returns and exclude the top 20% of stocks with the highest momentum[14] - **Factor Evaluation**: The factor helps mitigate the impact of short-term price surges, ensuring a focus on stable dividend yield predictions[4][15] 3. Factor Name: Profitability Factor - **Factor Construction Idea**: This factor screens out stocks with declining profitability, ensuring the selection of fundamentally strong companies[4][15] - **Factor Construction Process**: Exclude stocks with quarterly net profit growth rates less than 0[14] - **Factor Evaluation**: The factor ensures the portfolio is composed of financially sound companies, enhancing the reliability of dividend yield predictions[4][15] --- Factor Backtesting Results 1. Expected Dividend Yield Factor - **June 2025 Average Return**: 1.84%[15] - **Excess Return Relative to CSI 300**: -0.83%[15] - **Excess Return Relative to CSI Dividend Index**: 2.40%[15] 2. Reversal Factor - **Impact**: Excluded the top 20% of stocks with the highest short-term momentum, ensuring stability in the portfolio's dividend yield predictions[14] 3. Profitability Factor - **Impact**: Excluded stocks with declining profitability, maintaining a focus on fundamentally strong companies[14]

Group 1 - The report indicates that the influx of funds into Hong Kong since May has not significantly boosted the stock market, as these funds have primarily flowed into deposits, bond trading, and other areas rather than equities, leading to a negative sentiment shift [1][2] - Investors who previously sold stocks are now considering re-entering the market, believing that a significant downturn in Hong Kong stocks is unlikely, which could create new incremental capital [2][3] - The report suggests that returning investors are likely to favor undervalued stocks rather than high-flying thematic stocks, focusing on those with lower price-to-earnings ratios [2] Group 2 - The report lists a selection of recommended stocks, including Tencent Holdings (market cap: 470.47 billion, 2025 EPS: 22.9), Xiaomi Group (market cap: 152.97 billion, 2025 EPS: 1.5), and others across various sectors [3][8] - Tencent Holdings is highlighted for its strong competitive position in gaming and advertising, with expected EPS growth driven by AI integration and a robust ecosystem [11][12] - Xiaomi Group is noted for its innovative automotive segment and strong performance in the smartphone market, with a focus on high-margin products and AI applications [19][20] - Sunny Optical Technology is recognized for its growth in the automotive sector and advancements in optical technology for smartphones, projecting significant revenue increases [27][28] - Anta Sports is expected to benefit from strong brand performance and strategic acquisitions, enhancing its market position [33][34] - Greentown Service is identified as a quality property management company with strong growth potential and high dividend yields [39][40] - Yuehai Investment is focusing on core water supply operations, with expectations for stable cash flow and high dividends following the divestment of non-core assets [44][45] - Jiufang Zhitu Holdings is positioned for growth in the online investment space, leveraging technology to enhance its service offerings [49][50] - Dashih Holdings is expanding its store network significantly, with a focus on delivery services and menu optimization [56][57] - Far East Pharmaceutical is projected to see rapid growth in its nuclear medicine segment, with several innovative products in the pipeline [62][63] - Haitian International is expected to benefit from domestic upgrades and international expansion, with a focus on high-end markets [68][69] Group 3 - Financial data for the recommended stocks shows projected revenues and net profits for 2025, with Tencent Holdings expected to generate 716.55 billion in revenue and 210.26 billion in net profit [75] - Xiaomi Group is projected to achieve 491.83 billion in revenue and 39.60 billion in net profit for 2025 [75] - Sunny Optical Technology is expected to generate 42.68 billion in revenue and 3.32 billion in net profit in 2025 [75] - Anta Sports is projected to achieve 78.17 billion in revenue and 13.23 billion in net profit for 2025 [75] - Greentown Service is expected to generate 19.98 billion in revenue and 898 million in net profit in 2025 [75] - Yuehai Investment is projected to achieve 18.54 billion in revenue and 4.27 billion in net profit for 2025 [75] - Jiufang Zhitu Holdings is expected to generate 3.58 billion in revenue and 1.29 billion in net profit in 2025 [75] - Dashih Holdings is projected to achieve 5.37 billion in revenue and 129 million in net profit for 2025 [75] - Far East Pharmaceutical is expected to generate 12.20 billion in revenue and 2.08 billion in net profit in 2025 [75] - Haitian International is projected to achieve 18.25 billion in revenue and 3.52 billion in net profit for 2025 [75]

Investment Rating - The industry investment rating is "Overweight" indicating that the industry index is expected to outperform the benchmark by more than 5% in the next six months [23]. Core Insights - The brain-computer interface (BCI) sector is experiencing accelerated development, with the global market projected to reach approximately $7 billion by 2030, growing at a CAGR of 16.4% from 2025 to 2030 [1][7]. - The domestic BCI market is gaining significance, with its market size reaching 1.73 billion yuan in 2023, an increase of over 5 percentage points compared to 2020 [1][10]. - China has a first-mover advantage in the non-invasive BCI route, while also making strides in invasive technologies, evidenced by recent clinical trial breakthroughs [2][3]. Summary by Sections Market Growth and Trends - The global BCI market is on a growth trajectory, with significant increases in investment and financing in the past two years [1][14]. - The domestic market's share has been increasing, with a notable rise in the number of investment events and financing amounts in the BCI sector [16][14]. Technological Developments - Non-invasive BCI technologies are more fragmented, focusing on commercializing applications in vertical fields, while invasive technologies face higher technical barriers [2][3]. - Recent advancements include the development of the world's first "dual-loop" BCI system by Tianjin University and Tsinghua University, and successful clinical trials for invasive BCIs in China [2][3]. Government Policies and Support - The Chinese government is actively promoting the standardization and ethical guidelines for BCI research and applications, with several policies introduced to support the industry [3][17]. - Local governments, particularly in Beijing and Shanghai, are accelerating the development of BCI industries through specific action plans and funding initiatives [3][17]. Industry Chain and Key Players - The BCI industry chain includes upstream hardware suppliers, midstream product providers, and downstream applications in healthcare, smart living, and military sectors [4][18]. - Key companies in the BCI sector include Qi Sheng Technology, DiNaiKe, and others, with varying market capitalizations [19].

Core Insights - The report focuses on adjusting index positions based on technical indicators to achieve excess returns, utilizing a variety of indicators derived from volume and price data [3][8] - A total of 27 technical indicators were constructed and tested across three major indices: CSI 300, CSI 500, and CSI 1000, as well as 31 industry indices, with an average excess annualized return of 3.75% achieved through indicators based on the concept of volume-price divergence [3][8] - The report highlights the performance of single and multiple signal strategies, with the 5-signal strategy yielding an annualized return of 2.54% on the CSI 1000 index and an excess annualized return of 11.27% [3][8] - The rolling synthesis of signals showed that a T+10 adjustment frequency could achieve an average excess annualized return of 3.99%, suitable for low-risk investors, termed the rolling steady strategy, while the rolling chasing strategy, which has higher volatility, is more suitable for high-risk investors [3][8] Latest Index Positioning - As of early July, the CSI 300 has 20 indicators signaling bullish, 3 signaling reduction; the optimal single indicator maintains its signal, and both rolling chasing and rolling steady strategies indicate bullish [19][22] - The CSI 500 has 18 bullish signals and 5 reduction signals, with the optimal single indicator also signaling bullish, and both strategies maintaining their signals [19][22] - The CSI 1000 shows 17 bullish signals and 7 reduction signals, with the optimal single indicator signaling bullish, and both strategies also indicating bullish [19][22] Model Performance Statistics - The rolling chasing strategy recorded excess returns of -0.92% for CSI 300, -4.45% for CSI 500, and 0.00% for CSI 1000 in June [9][12] - The report provides a detailed summary of excess returns across various indices, indicating that the rolling steady strategy performed better in certain sectors, while the rolling chasing strategy showed stronger performance in others [10][12][13] Signal Analysis - The report includes a comprehensive analysis of the number of bullish and reduction signals across various sectors, indicating a mixed outlook with some sectors showing more bullish indicators than others [23][24] - The analysis of positions and signals for both non-rolling and rolling strategies reveals varying levels of exposure and signal strength across different indices and sectors [24][25]

Quantitative Models and Construction Methods 1. Model Name: Five-Dimensional Industry Rotation Model - **Model Construction Idea**: The model is based on the Dongwu Securities multi-factor stock selection system, categorizing micro factors into five dimensions: volatility, fundamentals, trading volume, sentiment, and momentum. It leverages style indicators to classify stocks within industries and constructs final industry factors by combining intra-industry dispersion and traction indicators [6][7] - **Model Construction Process**: 1. Micro factors are categorized into five dimensions using the Dongwu Securities multi-factor classification standard [6] 2. Style indicators are used to classify stocks within industries, creating intra-industry dispersion and traction indicators [6] 3. The final industry factors are synthesized into five categories: volatility, fundamentals, trading volume, sentiment, and momentum [6] - **Model Evaluation**: The model effectively captures intra-industry style differences and integrates multiple dimensions to enhance industry rotation strategies [6] 2. Model Name: Five-Dimensional Industry Rotation Model for CSI 300 Index Enhancement - **Model Construction Idea**: This model applies the five-dimensional industry rotation framework to enhance the CSI 300 Index by overweighting high-scoring industries and underweighting low-scoring ones [22] - **Model Construction Process**: 1. At the end of each month, the top five industries (highest scores) are selected as enhancement industries, and the bottom five industries (lowest scores) are excluded [22] 2. Stocks in excluded industries are removed from the portfolio, and their weights are proportionally redistributed to stocks in enhancement industries [22] 3. The portfolio is rebalanced monthly [22] --- Model Backtesting Results 1. Five-Dimensional Industry Rotation Model - **Annualized Return**: 21.59% - **Annualized Volatility**: 10.77% - **IR**: 2.00 - **Monthly Win Rate**: 73.33% - **Maximum Drawdown**: 13.30% [10][14] 2. Five-Dimensional Industry Rotation Model (Long-Only, Market-Neutral) - **Annualized Return**: 10.52% - **Annualized Volatility**: 6.59% - **IR**: 1.60 - **Monthly Win Rate**: 70.83% - **Maximum Drawdown**: 9.36% [14][15] 3. Five-Dimensional Industry Rotation Model for CSI 300 Index Enhancement - **Annualized Excess Return**: 8.90% - **Annualized Excess Volatility**: 7.50% - **IR**: 1.19 - **Monthly Win Rate**: 69.42% - **Maximum Drawdown**: 12.74% [23] --- Quantitative Factors and Construction Methods 1. Factor Name: Volatility Factor - **Factor Construction Idea**: Measures the dispersion of stock returns within an industry to capture risk-adjusted opportunities [6] - **Factor Construction Process**: 1. Calculate the standard deviation of stock returns within each industry 2. Normalize the values to ensure comparability across industries [6] 2. Factor Name: Fundamentals Factor - **Factor Construction Idea**: Evaluates the financial health and valuation metrics of stocks within an industry [6] - **Factor Construction Process**: 1. Aggregate financial ratios such as ROE, P/E, and P/B for stocks within each industry 2. Normalize and rank the aggregated values [6] 3. Factor Name: Trading Volume Factor - **Factor Construction Idea**: Tracks liquidity and trading activity within industries to identify momentum-driven opportunities [6] - **Factor Construction Process**: 1. Calculate the average trading volume for stocks within each industry 2. Normalize and rank the values [6] 4. Factor Name: Sentiment Factor - **Factor Construction Idea**: Captures market sentiment through price trends and investor behavior within industries [6] - **Factor Construction Process**: 1. Analyze price momentum and news sentiment data for stocks within each industry 2. Aggregate and normalize the sentiment scores [6] 5. Factor Name: Momentum Factor - **Factor Construction Idea**: Identifies industries with strong upward price trends [6] - **Factor Construction Process**: 1. Calculate the relative strength index (RSI) and moving average convergence divergence (MACD) for stocks within each industry 2. Aggregate and normalize the momentum scores [6] --- Factor Backtesting Results 1. Volatility Factor - **Annualized Return**: 11.62% - **Annualized Volatility**: 10.16% - **IR**: 1.14 - **Monthly Win Rate**: 60.00% - **Maximum Drawdown**: 14.27% [14] 2. Fundamentals Factor - **Annualized Return**: 5.66% - **Annualized Volatility**: 9.93% - **IR**: 0.57 - **Monthly Win Rate**: 56.00% - **Maximum Drawdown**: 21.50% [14] 3. Trading Volume Factor - **Annualized Return**: 7.65% - **Annualized Volatility**: 12.11% - **IR**: 0.63 - **Monthly Win Rate**: 58.40% - **Maximum Drawdown**: 18.51% [14] 4. Sentiment Factor - **Annualized Return**: 7.87% - **Annualized Volatility**: 12.91% - **IR**: 0.61 - **Monthly Win Rate**: 64.00% - **Maximum Drawdown**: 14.79% [14] 5. Momentum Factor - **Annualized Return**: 11.69% - **Annualized Volatility**: 10.71% - **IR**: 1.09 - **Monthly Win Rate**: 61.29% - **Maximum Drawdown**: 13.52% [14] 6. Composite Factor - **Annualized Return**: 21.59% - **Annualized Volatility**: 10.77% - **IR**: 2.00 - **Monthly Win Rate**: 73.33% - **Maximum Drawdown**: 13.30% [14]