Quantitative Models and Construction Methods 1. Model Name: Diffusion Index Model - **Model Construction Idea**: The model is based on the principle of price momentum, aiming to capture upward trends in industries and sectors[22][23] - **Model Construction Process**: The diffusion index is calculated for each industry based on its price momentum. The model ranks industries by their diffusion index values and selects the top-performing industries for portfolio allocation. The model has been tracking out-of-sample performance since 2021, with adjustments made monthly or weekly based on updated diffusion index rankings[22][23] - **Model Evaluation**: The model has shown strong performance in capturing industry trends during momentum-driven markets but struggles during market reversals[22][36] 2. Model Name: GRU Factor Model - **Model Construction Idea**: This model leverages minute-level price and volume data processed through a GRU (Gated Recurrent Unit) deep learning network to generate industry factors for rotation strategies[37] - **Model Construction Process**: The GRU model uses historical price and volume data as input to train a deep learning network. The network identifies patterns and generates factors that are used to rank industries. The top-ranked industries are selected for portfolio allocation. The model is updated weekly to reflect changes in the rankings[30][31][37] - **Model Evaluation**: The GRU model performs well in short-term trading environments but has shown limited effectiveness in long-term scenarios. It is also sensitive to extreme market conditions[37] --- Backtesting Results of Models 1. Diffusion Index Model - **Weekly Average Return**: -5.50% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: -0.42% - **November-to-Date Excess Return**: -1.13% - **Year-to-Date Excess Return**: 1.22%[26][22][23] 2. GRU Factor Model - **Weekly Average Return**: -4.71% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: 0.35% - **November-to-Date Excess Return**: 2.92% - **Year-to-Date Excess Return**: -2.74%[35][30][31] --- Quantitative Factors and Construction Methods 1. Factor Name: Diffusion Index - **Factor Construction Idea**: The diffusion index measures the momentum of industries by analyzing price trends and ranks industries based on their momentum[22][23] - **Factor Construction Process**: The diffusion index is calculated for each industry using price momentum data. Industries are ranked based on their diffusion index values, and the top-ranked industries are selected for portfolio allocation. The index is updated weekly or monthly to reflect changes in industry momentum[22][23] - **Factor Evaluation**: The factor effectively captures upward trends in industries but may underperform during market reversals[22][36] 2. Factor Name: GRU Industry Factor - **Factor Construction Idea**: The GRU industry factor is derived from minute-level price and volume data processed through a GRU deep learning network to identify patterns and rank industries[37] - **Factor Construction Process**: The GRU model processes historical price and volume data through a deep learning network. The network generates factors that are used to rank industries. The top-ranked industries are selected for portfolio allocation, with updates made weekly[30][31][37] - **Factor Evaluation**: The factor is effective in short-term trading environments but less so in long-term scenarios. It is also sensitive to extreme market conditions[37] --- Backtesting Results of Factors 1. Diffusion Index Factor - **Weekly Average Return**: -5.50% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: -0.42% - **November-to-Date Excess Return**: -1.13% - **Year-to-Date Excess Return**: 1.22%[26][22][23] 2. GRU Industry Factor - **Weekly Average Return**: -4.71% - **Excess Return over Equal-Weighted CSI First-Level Industry Index**: 0.35% - **November-to-Date Excess Return**: 2.92% - **Year-to-Date Excess Return**: -2.74%[35][30][31]

Quantitative Models and Construction Diffusion Index Model - **Model Name**: Diffusion Index Model [5][17] - **Construction Idea**: The model monitors the market's diffusion index to identify critical turning points for trading signals [5][17] - **Construction Process**: - The diffusion index is calculated based on the relative price movements of constituent stocks within the micro-cap index over a specific time window [37] - The model uses three methods: - **First Threshold Method (Left-Side Trading)**: Triggered when the diffusion index reaches a predefined risk threshold. For example, on November 14, 2025, the index value of 0.925 triggered a sell signal [41] - **Delayed Threshold Method (Right-Side Trading)**: Provides a sell signal when the index value drops below a delayed threshold, such as 0.8975 on November 17, 2025 [46] - **Dual Moving Average Method (Adaptive Trading)**: Generates buy signals based on the crossover of two moving averages, such as the buy signal on October 13, 2025 [47] - **Evaluation**: The model effectively identifies market turning points and provides actionable trading signals [5][17] Small-Cap Low-Volatility 50 Strategy - **Model Name**: Small-Cap Low-Volatility 50 Strategy [7][16][33] - **Construction Idea**: Selects 50 stocks with small market capitalization and low volatility from the micro-cap index [7][33] - **Construction Process**: - Stocks are screened based on market capitalization and volatility metrics [7][33] - Portfolio is rebalanced bi-weekly [7][33] - Transaction costs are set at 0.3% for both buying and selling [7] - **Evaluation**: The strategy demonstrates strong performance in specific market conditions but underperforms during broader market downturns [7][33] --- Model Backtesting Results Diffusion Index Model - **First Threshold Method**: Triggered sell signal at 0.925 on November 14, 2025 [41] - **Delayed Threshold Method**: Triggered sell signal at 0.8975 on November 17, 2025 [46] - **Dual Moving Average Method**: Generated buy signal on October 13, 2025 [47] Small-Cap Low-Volatility 50 Strategy - **2024 Performance**: Annual return of 7.07%, excess return of -2.93% [7][33] - **2025 YTD Performance**: Annual return of 63.78%, weekly excess return of -2.23% [7][33] --- Quantitative Factors and Construction Weekly Factor Performance - **Top 5 Factors**: - **Leverage Factor**: Weekly rank IC of 0.182, historical average of -0.005 [4] - **Free Float Ratio Factor**: Weekly rank IC of 0.138, historical average of -0.012 [4] - **Turnover Factor**: Weekly rank IC of 0.116, historical average of -0.081 [4] - **Liquidity Factor**: Weekly rank IC of 0.075, historical average of -0.041 [4] - **Dividend Yield Factor**: Weekly rank IC of 0.064, historical average of 0.022 [4] - **Bottom 5 Factors**: - **Unadjusted Stock Price Factor**: Weekly rank IC of -0.311, historical average of -0.017 [4] - **Beta Factor**: Weekly rank IC of -0.3, historical average of 0.003 [4] - **Non-Liquidity Factor**: Weekly rank IC of -0.161, historical average of 0.039 [4] - **Inverse PE_TTM Factor**: Weekly rank IC of -0.138, historical average of 0.016 [4] - **Single-Quarter ROE Factor**: Weekly rank IC of -0.089, historical average of 0.021 [4] Additional Weekly Factor Performance - **Top 5 Factors**: - **Logarithmic Market Cap Factor**: Weekly rank IC of 0.225, historical average of -0.034 [16] - **Nonlinear Market Cap Factor**: Weekly rank IC of 0.225, historical average of -0.034 [16] - **Beta Factor**: Weekly rank IC of 0.083, historical average of 0.003 [16] - **Unadjusted Stock Price Factor**: Weekly rank IC of 0.065, historical average of -0.017 [16] - **Past Year Volatility Factor**: Weekly rank IC of 0.06, historical average of -0.033 [16] - **Bottom 5 Factors**: - **Past 10-Day Return Factor**: Weekly rank IC of -0.226, historical average of -0.061 [16] - **Momentum Factor**: Weekly rank IC of -0.196, historical average of -0.006 [16] - **Leverage Factor**: Weekly rank IC of -0.114, historical average of -0.005 [16] - **Single-Quarter Net Profit Growth Factor**: Weekly rank IC of -0.11, historical average of 0.019 [16] - **Standardized Expected Earnings Factor**: Weekly rank IC of -0.104, historical average of 0.013 [16] --- Factor Backtesting Results Weekly Factor Performance - **Leverage Factor**: Weekly rank IC of 0.182 [4] - **Free Float Ratio Factor**: Weekly rank IC of 0.138 [4] - **Turnover Factor**: Weekly rank IC of 0.116 [4] - **Liquidity Factor**: Weekly rank IC of 0.075 [4] - **Dividend Yield Factor**: Weekly rank IC of 0.064 [4] - **Unadjusted Stock Price Factor**: Weekly rank IC of -0.311 [4] - **Beta Factor**: Weekly rank IC of -0.3 [4] - **Non-Liquidity Factor**: Weekly rank IC of -0.161 [4] - **Inverse PE_TTM Factor**: Weekly rank IC of -0.138 [4] - **Single-Quarter ROE Factor**: Weekly rank IC of -0.089 [4] Additional Weekly Factor Performance - **Logarithmic Market Cap Factor**: Weekly rank IC of 0.225 [16] - **Nonlinear Market Cap Factor**: Weekly rank IC of 0.225 [16] - **Beta Factor**: Weekly rank IC of 0.083 [16] - **Unadjusted Stock Price Factor**: Weekly rank IC of 0.065 [16] - **Past Year Volatility Factor**: Weekly rank IC of 0.06 [16] - **Past 10-Day Return Factor**: Weekly rank IC of -0.226 [16] - **Momentum Factor**: Weekly rank IC of -0.196 [16] - **Leverage Factor**: Weekly rank IC of -0.114 [16] - **Single-Quarter Net Profit Growth Factor**: Weekly rank IC of -0.11 [16] - **Standardized Expected Earnings Factor**: Weekly rank IC of -0.104 [16]

证券研究报告：房地产|行业周报 发布时间：2025-11-24 | 行业基本情况 | | --- | | 收盘点位 | | 2271.52 | | --- | --- | --- | | 52 | 周最高 | 2506.48 | | 52 | 周最低 | 1870.99 | 行业相对指数表现 -19% -15% -11% -7% -3% 1% 5% 9% 13% 17% 21% 2024-11 2025-02 2025-04 2025-06 2025-09 2025-11 房地产 沪深300 资料来源：聚源，中邮证券研究所 研究所 分析师:高丁卉 SAC 登记编号:S1340524080001 Email:gaodinghui@cnpsec.com 近期研究报告 行业投资评级 强于大市|维持 《地产数据加速下滑 政策放松预期升 温》 - 2025.11.17 房地产行业报告 （2025.11.17-2025.11.23） 量价承压 信心与预期仍待修复 ⚫ 投资要点 当前房地产行业仍处于调整周期，销售端整体同比延续下滑态 势，政策层面持续加码城市更新与存量盘活，成为推动行业转型的关 键抓手。我们认为目前市场信心 ...

Investment Rating - The report maintains a "Buy" rating for the company [1] Core Insights - The company has demonstrated a strong performance in the first three quarters of 2025, achieving a revenue of 5.071 billion yuan, representing a year-on-year growth of 9.29%, and a net profit attributable to shareholders of 698 million yuan, up 17.51% year-on-year [4][5] - The increase in revenue is attributed to the rising penetration of edge AI applications and the continuous expansion of new product sales [5] - The company has launched several new products compatible with its edge AI model, enhancing its market presence and driving growth in both consumer and business sectors [6][7] Financial Performance - The company reported a historical high in revenue for the first three quarters, with a quarterly revenue of 1.741 billion yuan in Q3, reflecting a year-on-year increase of 7.20% [5] - The net profit for Q3 was 201 million yuan, showing a year-on-year decrease of 13.14% and a quarter-on-quarter decrease of 34.76% due to market conditions affecting storage chip prices and delivery delays [5] - The company expects revenue for 2025, 2026, and 2027 to be 7.064 billion yuan, 8.971 billion yuan, and 10.658 billion yuan respectively, with net profits projected at 1.013 billion yuan, 1.406 billion yuan, and 1.808 billion yuan [8][12] Product and Market Development - The company has seen significant growth in product shipments, with over 14 million units of self-developed edge AI chips shipped, a year-on-year increase of over 150% [7] - Collaborations with major brands like Samsung and Walmart have expanded the company's product offerings and market reach [6][7] - The integration of the chip design team is expected to enhance the company's multi-dimensional communication technology stack, broadening application scenarios [7]

横盘之后，是涨是跌？ ——流动性周报 20251123 证券研究报告：固定收益报告 发布时间：2025-11-24 研究所 分析师:梁伟超 SAC 登记编号:S1340523070001 Email:liangweichao@cnpsec.com 近期研究报告 《从资管信托新规，看银行理财变局— — 机 构 行 为 专 题 二 20251120 》 - 2025.11.21 固收周报 ⚫ 上涨面依然大于下跌面 观点回顾：四季度债市或在震荡中前行。对短端而言，高配置价 值和交易价值是实实在在的，存单年末还将存在一定的供给压力，但 出现负反馈的概率不高，在资金稳定宽松背景下，同业存单利率处于 高配置价值区间，年末有超预期下行的可能。对于长端而言，前期期 限利差的扩张，给予了长端一定的修复空间。依然坚持四季度债市利 多因素多发，但赎回压力持续存在，需要以区间震荡思路做交易的判 断。随着宽松预期的升温，不妨对后期后续的债市行情更乐观点。 债市进入盘整状态，甚至不对风险偏好做出反应。近几周，债市 波动收窄的程度依然超出预期，即收益率波动幅度明显收窄，仅仅因 房地产政策预期等因素而出现小幅波动，甚至在全球风险偏好明显收 ...

Investment Rating - The report assigns a "Buy" rating for the company, marking its first coverage [1]. Core Insights - The company has shown steady revenue growth, with a 15.87% year-on-year increase in revenue for the first three quarters of 2025, reaching 1.784 billion yuan. However, net profit decreased by 12.06% to 172 million yuan due to rising expenses and one-time factors [4][5]. - The company is a leader in the automotive passive safety sector, with a product line that includes safety fabrics and airbags. It is also expanding into the semiconductor and computing power manufacturing sectors, aiming to create a second growth engine [5]. - The acquisition of a 57.84% stake in Fuchuang Youyue is planned, which would enhance the company's control over its operations in the AI and computing power manufacturing industry [6]. Financial Performance - For the first three quarters of 2025, the company reported a revenue of 1.784 billion yuan, with a quarterly revenue of 676 million yuan in Q3, reflecting an 18.34% year-on-year increase. However, net profit for Q3 fell by 43.72% to 36 million yuan [4]. - The company expects revenues of 2.7 billion yuan, 3.2 billion yuan, and 3.8 billion yuan for 2025, 2026, and 2027 respectively, with net profits projected at 387 million yuan, 573 million yuan, and 775 million yuan for the same years [6][9]. - The company’s financial ratios indicate a projected increase in earnings per share (EPS) from 0.84 yuan in 2024 to 2.35 yuan in 2027, alongside a decrease in price-to-earnings (P/E) ratio from 54.62 to 19.56 over the same period [9][12].

Investment Rating - The investment rating for the company is "Buy" and is maintained [1] Core Insights - The company plans to issue up to 19,013,200 convertible bonds to raise a total of no more than 1.901 billion yuan, which will be used for global R&D center construction, edge AI and supporting chips, automotive chips, and motion control chip development and industrialization projects [4][5] - The company has shown initial success in industrial interconnection and automotive electronics, with a revenue of 2.176 billion yuan for the first three quarters, a year-over-year decrease of 8.02%, but a net profit of 276 million yuan, reflecting a year-over-year increase of 54.98% [6] - The company is expected to achieve revenues of 3.05 billion yuan, 3.47 billion yuan, and 4.03 billion yuan for the years 2025, 2026, and 2027 respectively, with net profits of 400 million yuan, 530 million yuan, and 710 million yuan for the same years [7] Company Overview - The latest closing price of the company's stock is 71.82 yuan, with a total market capitalization of 16.7 billion yuan and a circulating market value of 9.7 billion yuan [3] - The company has a debt-to-asset ratio of 22.9% and a price-to-earnings ratio of 65.29 [3]

Investment Rating - The report maintains a "Buy" rating for the company [2][7][11] Core Insights - The company is seizing opportunities in the semiconductor localization trend, actively expanding its layout in semiconductor equipment and component markets. The company achieved revenue of 2.255 billion yuan in the first three quarters of 2025, a year-on-year increase of 4.31%. However, overseas business experienced a decline due to macroeconomic factors [5][11] - The company plans to invest 2 billion yuan in a semiconductor core component project in Kunshan, which is expected to generate an annual output value of over 1.5 billion yuan upon reaching full production [6][11] - Revenue projections for the company are 3.019 billion yuan, 3.434 billion yuan, and 3.953 billion yuan for 2025, 2026, and 2027 respectively, with net profits of 192 million yuan, 258 million yuan, and 357 million yuan for the same years [7][10] Company Overview - The latest closing price of the company is 52.72 yuan, with a total market capitalization of 21.5 billion yuan and a circulating market value of 15.2 billion yuan. The company has a total share capital of 408 million shares, with 288 million shares in circulation [4][11] - The company has a debt-to-asset ratio of 61.5% and a price-to-earnings ratio of 94.14 [4][11]

Investment Rating - The industry investment rating is "Outperform" [1] Core Views - The report highlights that the real estate market in China is under pressure, with expectations for policy changes to stimulate demand, including mortgage subsidies for new home buyers and tax rebates for borrowers [4] - The construction materials sector is anticipated to see a valuation recovery as the fundamentals of cyclical building materials companies have bottomed out [4] - Cement prices are expected to rise in the short term due to supply constraints from seasonal production policies, despite a recent decline in demand [5] - The glass industry is facing a downward trend in demand, with high inventory levels among intermediaries, and the need for policy changes to improve market conditions [6] - The fiberglass sector is experiencing growth driven by demand from the AI industry, with expectations for a significant increase in both volume and price [6] - The consumer building materials segment has reached a profitability bottom, with strong price increase demands from companies following years of competition [6] Summary by Sections Cement - National cement market prices have decreased recently, with a production volume of 148 million tons in October, down 15.8% year-on-year [10] - Demand is still under pressure, but there is a slight improvement expected in November due to project rush [10] Glass - The glass industry is experiencing a continuous decline in demand, with traditional peak season orders showing limited improvement [17] - Supply-demand imbalances persist, and the industry is closely monitoring policy changes for potential recovery [17] Fiberglass - The fiberglass sector is seeing price increases of 5%-10% due to collaborative pricing efforts among manufacturers, with strong demand from the AI sector [6] Consumer Building Materials - The industry has reached a profitability bottom, with no further downward price pressure expected, and companies are actively seeking price increases [6]

Market Performance Review - The A-share market experienced a significant decline this week, with major indices unable to avoid losses. The Shanghai Composite Index fell by 2.72%, while the ChiNext Index saw the largest drop of 6.15%. The small-cap indices, CSI 500 and CSI 1000, also performed poorly, declining by 5.78% and 5.80% respectively [4][12] - All major styles recorded negative returns, with the financial style down by 2.85%, the smallest decline among styles, while the cyclical style dropped by 6.05%, the largest [4][12] - In terms of market capitalization, large-cap stocks outperformed small and mid-cap stocks, maintaining the trend of larger stocks being more resilient during downturns. Core assets represented by the "Mao Index" and "Ning Combination" also saw significant declines, with the Ning Combination down 7.64% and the Mao Index down 3.63% [4][12] Industry Analysis - All primary industries experienced declines, with banking showing relative resilience. The banking sector fell by only 0.89%, while other sectors like power equipment (-10.54%), comprehensive (-9.18%), and basic chemicals (-7.47%) faced larger losses [4][15] - The A-share market's recent downturn aligns with historical patterns of retreat following previous uptrends, particularly affecting sectors like AI, resource products, and new energy, which had previously seen gains [4][15] Future Outlook and Investment Strategy - The report anticipates continued market volatility, with the A-share market expected to remain under pressure due to a dual vacuum period in policy and performance from November to December. The lack of significant movement in household deposits suggests weaker future capital support for the market [5][33] - The investment strategy emphasizes maintaining a growth style, focusing on sectors with strong performance trends and favorable policy expectations. The transition from a fast bull market driven by corporate capital to a slower bull market led by public funds is expected to be challenging [5][33] - Two specific strategies are recommended: investing in photovoltaic equipment that meets the "turnaround + high growth" criteria post-Q3 reports, and targeting commercial sectors and low-altitude economy industries that have lagged since September [5][33]