Group 1 - The average stock price of A-shares is 14.06 yuan, with 168 stocks priced over 100 yuan, an increase of 3 stocks compared to the previous trading day [1] - The Shanghai Composite Index closed at 4016.33 points, up 0.70%, while stocks priced over 100 yuan had an average increase of 1.59%, outperforming the index by 0.89 percentage points [1] - The highest closing price among stocks over 100 yuan is 1461.00 yuan for Cambrian, which decreased by 1.19% [1] Group 2 - In the past month, stocks priced over 100 yuan have averaged a 6.44% increase, outperforming the Shanghai Composite Index's 4.92% increase [2] - Notable stocks with significant gains include Yunhan Chip City, Jiangbo Long, and Ding Tai High-Tech, with increases of 102.23%, 93.49%, and 81.86% respectively [2] - C He Yuan's stock price reached 113.22 yuan, marking a 24.28% increase, with a turnover rate of 0.51% and a trading volume of 2.171 billion yuan [2] Group 3 - Among stocks priced over 100 yuan, the electronics sector is the most concentrated, with 63 stocks, accounting for 37.50% of the total [2] - The main board has 35 stocks, the ChiNext board has 53, and the Sci-Tech Innovation Board has 76 stocks, making up 45.24% of the total [2] - 22 stocks priced over 100 yuan received buy ratings from institutions, including Zhongrong Electric and Zhongjian Technology [2] Group 4 - Among the stocks with buy ratings, four stocks have an upside potential exceeding 20%, with Jibite having the highest potential at 34.33% [3] - The stock prices of high-priced stocks show varied performance, with some experiencing significant fluctuations [3][4]

Investment Rating - The report maintains an "Outperform" rating for the company [1] Core Insights - The company reported Q3 2025 revenue of 190 million yuan, a year-on-year increase of 75.68%, exceeding market expectations of around 30%. The net profit attributable to the parent company was -80 million yuan, compared to -150 million yuan in the same period last year [6] - The revenue growth was primarily driven by the rapid expansion of computing power construction business, with accelerated project delivery contributing significantly to revenue [6] - The reduction in net loss is attributed to improved cash flow and effective cost control, with Q3 operating cash flow turning positive at 60 million yuan [6] - The gross margin is expected to be impacted by the increasing proportion of lower-margin AI-related business [6] - The company is focusing on large model projects across various industries, including collaborations with Shanghai Jiao Tong University and Huawei [6] - The revenue forecasts for 2025-2027 are set at 5.44 billion, 7.42 billion, and 11.0 billion yuan, with net profits projected at -455 million, -360 million, and -217 million yuan respectively [6] Financial Data and Profit Forecast - Total revenue for 2025 is estimated at 544 million yuan, with a year-on-year growth rate of 36.8% [5] - The gross margin for 2025 is projected to be 42.7%, with a significant increase expected in subsequent years [5] - The company’s return on equity (ROE) is forecasted to improve from -35.1% in 2025 to -16.0% in 2027 [5]

Core Insights - The market experienced a rebound today, with the growth style sector leading the gains, as evidenced by the 1.7% increase in the Guozheng Growth 100 Index, marking its fourth consecutive day of gains [1] - Key stocks in the index included Honghe Technology, which hit the daily limit, Fujida rising over 14%, Dingtai High-Tech increasing over 12%, and Dazhu CNC up over 10% [1] - According to Industrial Securities, with the easing of U.S.-China trade tensions and strengthened expectations for Federal Reserve rate cuts, the most disruptive period may be gradually passing, and the "14th Five-Year Plan" is expected to boost confidence and consensus, supporting a positive long-term narrative for the market [1] Industry Analysis - The Guozheng Growth 100 Index focuses on A-share stocks with prominent growth characteristics, closely aligned with the economic transformation, particularly in high-growth sectors such as electronics, communications, and computers [1] - Wind data indicates that the latest expected net profit growth rate for the index's constituent stocks is over 100% for 2025, highlighting significant performance potential [1] - Historically, the index has shown an annualized return of over 20% since its base date at the end of 2012, with returns exceeding 115% since the beginning of 2024 and over 55% year-to-date, outperforming similar style indices [1] - The Growth ETF (159259) is currently the only ETF product tracking the Guozheng Growth 100 Index, providing investors with an opportunity to capitalize on growth style investments [1]

Quantitative Models and Construction Methods 1. Model Name: Stock Timing Model - **Construction Idea**: The model is based on the comprehensive judgment of economic growth and liquidity easing[18] - **Construction Process**: - Construct timing factors from two core dimensions: economic growth and liquidity easing[18] - Factors include PMI YoY smoothed value, manufacturing fixed asset investment completion amount cumulative YoY, CPI YoY smoothed value, and new medium and long-term loans cumulative value YoY[19] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using CSI 800 total return as the benchmark[19] - **Evaluation**: The model effectively captures stock market cycles, avoiding downturns[21] 2. Model Name: Bond Timing Model - **Construction Idea**: The model analyzes from the perspective of monetary liquidity supply and demand[23] - **Construction Process**: - Factors include DR007, SHIBOR, and social financing scale stock YoY smoothed value[24] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if short-term average < long-term average} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using ChinaBond Treasury Total Net Price Index as the benchmark[24] - **Evaluation**: The model captures bond market trends, minimizing drawdowns[25] 3. Model Name: All-Weather Strategy - **Construction Idea**: The model adjusts risk budgets for different assets based on timing signals[17] - **Construction Process**: - Use a risk parity model to allocate risk contributions of assets[30] - Adjust risk budgets based on stock and bond timing signals[32] - Optimize the model: $$ \begin{array}{c} \min \sum_{i=1}^{N} \left( RC_i - b_i \sigma_p \right)^2 \\ \text{s.t.} \sum_{i=1}^{N} \omega_i = 1 \\ 0 \leq \omega_i \leq 1 \end{array} $$ - Backtest using a combination of CSI 800, ChinaBond Treasury Total Wealth Index, CSI Convertible Bond Index, S&P 500 ETF, and AAA Credit Bonds[31] - **Evaluation**: The strategy provides higher absolute returns while controlling risk[38] Model Backtest Results Stock Timing Model - Annualized Return: 14.1%[21] - Benchmark Annualized Return: 5.4%[21] - Excess Annualized Return: 8.7%[21] - Monthly Win Rate: 56.7%[21] Bond Timing Model - Annualized Return: 2.3%[25] - Benchmark Annualized Return: 1.1%[25] - Excess Annualized Return: 1.1%[25] - Monthly Win Rate: 68.3%[25] All-Weather Strategy - Annualized Return: 6.1%[38] - Benchmark Annualized Return: 5.1%[38] - Excess Annualized Return: 1.0%[38] - Maximum Drawdown: 2.6%[38] - Sharpe Ratio: 2.04[38] Quantitative Factors and Construction Methods 1. Factor Name: Value-Growth Rotation Factor - **Construction Idea**: The factor is based on economic recovery, liquidity, and market sentiment[47] - **Construction Process**: - Factors include manufacturing fixed asset investment completion amount, PPI YoY smoothed value, M2 YoY smoothed value, social financing YoY smoothed value, medium and long-term loan growth YoY smoothed value, market turnover rate, and margin balance percentile[48] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using the National Growth Index and National Value Index[48] - **Evaluation**: The factor captures the cyclical characteristics of value and growth styles[47] 2. Factor Name: Size Rotation Factor - **Construction Idea**: The factor is based on economic prosperity, liquidity, and market sentiment[55] - **Construction Process**: - Factors include manufacturing fixed asset investment completion amount, PPI YoY smoothed value, gold daily return rate, government bond yield, credit spread, M1 YoY smoothed value, market turnover rate, and margin balance percentile[56] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using the CSI 300 Index and CSI 1000 Index[57] - **Evaluation**: The factor captures the cyclical characteristics of large-cap and small-cap styles[55] Factor Backtest Results Value-Growth Rotation Factor - Annualized Return: 9.2%[51] - Benchmark Annualized Return: 1.7%[51] - Excess Annualized Return: 7.5%[51] - Monthly Win Rate: 60.2%[51] Size Rotation Factor - Annualized Return: 9.2%[59] - Benchmark Annualized Return: 0.1%[59] - Excess Annualized Return: 9.0%[59] - Monthly Win Rate: 58.3%[59] Industry Rotation Solution 1. Factor Name: Macro Factor - **Construction Idea**: The factor is based on the second-order changes in economic growth and liquidity[67] - **Construction Process**: - Factors include PMI, social financing scale, manufacturing fixed asset investment completion amount, CPI, M2 growth rate, 10-year government bond yield, and credit spread[70] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using industry indices[73] - **Evaluation**: The factor captures the marginal inflection points of macro trends[67] 2. Factor Name: Fundamental Factor - **Construction Idea**: The factor is based on historical prosperity, prosperity changes, and prosperity expectations[79] - **Construction Process**: - Factors include industry component stock median, industry profitability, and industry consensus profit expectations[79] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using industry indices[82] - **Evaluation**: The factor captures the core of industry prosperity[79] 3. Factor Name: Technical Factor - **Construction Idea**: The factor is based on index momentum, leading stock momentum, and K-line patterns[87] - **Construction Process**: - Factors include industry index relative excess return IR, leading stock sharp ratio, and K-line pattern score[89] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using industry indices[96] - **Evaluation**: The factor captures the technical evaluation of industry trends[87] 4. Factor Name: Crowding Factor - **Construction Idea**: The factor is based on financing inflows, turnover rate, and transaction proportion[100] - **Construction Process**: - Factors include industry financing buy amount, industry turnover rate, and industry transaction amount proportion[101] - Use the formula: $$ \text{Factor} = \begin{cases} 1 & \text{if indicator improves} \\ 0 & \text{otherwise} \end{cases} $$ - Backtest using industry indices[104] - **Evaluation**: The factor captures the crowding level of industries[100] Industry Rotation Backtest Results Macro Factor - Annualized Return: 42.9%[73] - Benchmark Annualized Return: -22.8%[73] - Excess Annualized Return: 65.7%[73] Fundamental Factor - Annualized Return: 11.3%[85] - Benchmark Annualized Return: 2.8%[85] - Excess Annualized Return: 8.5%[85] - IC Mean: 8.2%[85] Technical Factor - Annualized Return: 9.7%[97] - Benchmark Annualized Return: 2.8%[97] - Excess Annualized Return: 6.9%[97] - IC Mean: 8.2%[97] Crowding Factor - Annualized Return: -2.9

Core Insights - The article discusses the allocation and performance of public funds in the computer industry, highlighting the absolute and relative configuration ratios of various stocks held by funds [2][6][10]. Group 1: Absolute Allocation of Public Funds - The absolute allocation ratio of public funds in the computer industry shows significant percentages for top holdings, with the highest being 13.36% [3]. - The data indicates a diverse range of allocation percentages among the top stocks, with several stocks holding between 4% to 6% of the total allocation [3][4]. Group 2: Relative Allocation of Public Funds - The relative allocation ratio reveals the most held stocks by the number of funds, with Industrial Fulian and Kingsoft Office being the most prominent [6][10]. - The market value held by funds also highlights key stocks, with Industrial Fulian and Kingsoft Office leading in total market value held [10][11]. Group 3: Fund Holdings and Changes - The top twenty stocks by fund holdings include notable companies such as Industrial Fulian, Kingsoft Office, and Deepin Technology, indicating strong investor interest [9][10]. - The article also notes which stocks have seen the most significant increases in fund holdings, with Industrial Fulian and Fangzheng Technology among the top gainers [9][10].

Group 1: Strong Stocks - As of October 29, the Shanghai Composite Index rose by 0.7% to 4016.33 points, the Shenzhen Component Index increased by 1.95% to 13691.38 points, and the ChiNext Index climbed by 2.93% to 3324.27 points [1] - A total of 62 stocks in the A-share market hit the daily limit up, with the top three strong stocks being Antai Group (600408), Yashi Chuangneng (603378), and Zhongtung Gaoxin (000657) [1] - Detailed data for the top 10 strong stocks includes metrics such as trading volume, turnover rate, and net buying amount from the top traders [1] Group 2: Strong Concept Sectors - The top three concept sectors based on A-share performance are Hainan Free Trade Zone, BC Battery, and Metal Zinc, with respective increases of 4.35%, 3.89%, and 3.6% [2] - The table of the top 10 concept sectors shows the percentage of limit-up stocks, rising stocks, and falling stocks within each sector [2] - The Hainan Free Trade Zone had 10.71% of its component stocks hitting the limit up, while 82.14% of its component stocks experienced an increase [2]

Investment Rating - The report maintains a "Hold" rating for the computer industry [2] Core Insights - The "14th Five-Year Plan" has laid a solid foundation for industrial and technological accumulation, addressing some core "bottleneck" issues in the industrial chain, with technology expected to be the leading force in the next five years [6] - The report emphasizes that high-level technological self-reliance is crucial for leading the development of new productive forces, transforming technology from a supportive role to a core engine for economic transformation [6] - The "Artificial Intelligence+" initiative is integrated into the "15th Five-Year Plan," aiming for widespread integration of AI across various sectors by 2030 [6][7] Summary by Sections Technological Development - The innovation output index for 2024 is projected at 215.8, reflecting an 8.1% increase from the previous year [6] - The number of high-value invention patents per 10,000 R&D personnel increased by 12.5%, maintaining double-digit growth for three consecutive years [6] - The proportion of registered trademark enterprises rose by 8.4%, while the number of scientific papers and average contract amounts in the technology market both increased by 5.8% [6] Key Areas of Focus - The report identifies quantum technology, biological manufacturing, hydrogen and nuclear fusion energy, brain-computer interfaces, embodied intelligence, and sixth-generation mobile communication as new economic growth points [6] - Quantum computing is expected to achieve commercial viability within the next decade, with the global market projected to grow from $1.1 billion in 2022 to approximately $7.6 billion by 2027 [6][7] - The brain-computer interface market is anticipated to reach $3.3 billion by 2027, driven by advancements in technology [7] Investment Recommendations - The main investment focus remains on the AI+ action plan, with expectations for AI agents to be implemented in industrial, autonomous driving, and financial sectors from 2025 to 2027 [7] - Key investment areas include AI computing infrastructure, AI agents, intelligent terminals, and green low-carbon initiatives [7] - Specific companies to watch include Hongsoft Technology, Daotong Technology, Kingdee International, and others [7]

Core Viewpoint - The Shenzhen State-Owned Enterprises ESGR Index (470055) closed at 1633.26 points, up 1.39%, with a trading volume of 40.107 billion yuan and a turnover rate of 1.08% on October 29 [1] Group 1: Index Performance - The ESGR Index had 30 constituent stocks rising, with Zhongtung High-tech leading at a 10.0% increase, while 16 stocks declined, with Tianhong Co. leading the decline at 3.74% [1] - The top ten constituent stocks of the ESGR Index include Hikvision, BOE Technology Group, and Wuliangye, with respective weights of 9.64%, 9.31%, and 8.62% [1] Group 2: Market Capitalization and Sector Breakdown - Hikvision has a market capitalization of 305.648 billion yuan, while BOE Technology Group and Wuliangye have market capitalizations of 152.274 billion yuan and 461.251 billion yuan, respectively [1] - The sectors represented in the top ten stocks include Computer, Electronics, Food & Beverage, Automotive, Defense, Non-Bank Financials, Nonferrous Metals, Pharmaceutical & Biotechnology, and Real Estate [1] Group 3: Capital Flow - The net outflow of main funds from the ESGR Index constituents totaled 282 million yuan, while retail investors saw a net inflow of 365 million yuan [1] - Notable net inflows from retail investors were observed in stocks like Langchao Information and Shunwan Hongyuan, while significant outflows were noted in stocks like Zhongtung High-tech and Deep Technology [2]

Core Points - The Shanghai Composite Index has surpassed the 4000-point mark, marking a significant milestone for the A-share market in the past decade, driven by a combination of policy support, improving economic data, and recovering market sentiment [3] - The North Exchange 50 Index has shown remarkable performance, with a closing increase of 8.41%, and several stocks on the North Exchange hitting the daily limit of 30% [3] - A total of 90 stocks have reported better-than-expected performance in their Q3 results, particularly in sectors such as computer, automotive, power equipment, and basic chemicals [5][6] Market Performance - The Shanghai Composite Index closed at 4016.33 points, while the ChiNext Index rose by 2.93%, reaching a nearly three-year high [1] - The North Exchange stocks experienced significant gains, with four stocks hitting the 30% limit up, including Litong Technology, Jinhua New Materials, Sanxiang Technology, and Digital People [3] Company Performance - Among the 90 stocks with Q3 results exceeding expectations, the computer sector had the highest representation, with notable companies like Hikvision, Tonghuashun, and Kingsoft [6] - New Q3 profit leaders include: - Xinqianglian: Net profit of 664 million yuan, turning from loss to profit [7] - Gaode Infrared: Net profit of 582 million yuan, a 10.59-fold increase [8] - Wancheng Group: Net profit of 855 million yuan, a 9.17-fold increase [9] Stock Trends - 27 stocks with over 10% cumulative gains since October have been identified, with Oke Yi leading at a 40.3% increase [10] - Stocks with low PE (Price-to-Earnings) and PB (Price-to-Book) ratios include Nanjing Bank, with a PE of 6.4, indicating potential value opportunities [11] Financing Activity - 21 stocks have seen significant net buying from margin traders, with Dongfang Caifu leading at 1.946 billion yuan in net purchases [12] - Hikvision reported a net profit of 9.319 billion yuan for the first three quarters, a 14.94% year-on-year increase, and has seen a 94.91% increase in average daily trading volume since October [12]

1. Report Industry Investment Rating There is no information about the industry investment rating in the report. 2. Core Viewpoints of the Report - Deng Xinyu, a fund manager at China - Europe Fund, uses fundamental quantitative methods for the "plus" part of the "fixed - income +" investment framework, with multiple strategies such as dividend, value, quality, growth, and micro - cap strategies, and a macro - based asset allocation framework [3][9]. - China - Europe Dingli is a medium - to - high - volatility secondary bond fund with a quantitative boom - growth strategy. It emphasizes the company's financial health, profit sustainability, and growth momentum, and shows high return - risk performance and increasing investor profitability over time [12][14][32]. - China - Europe Enhanced Return is a low - volatility absolute - return product aiming for an absolute return within a 2% drawdown target. It emphasizes the safety margin of equity assets through valuation and has excellent performance in multiple core indicators [44][45][46]. 3. Summary by Relevant Catalogs 3.1. China - Europe Fund Deng Xinyu: A Practitioner of Fundamental Quantitative Fixed - Income + - Personal resume: Deng Xinyu joined China - Europe Fund in October 2023. He currently serves as a member of the fixed - income investment decision - making committee, the head of the hybrid asset group, and a fund manager. He manages multiple funds including China - Europe Dingli and China - Europe Enhanced Return [7]. - Investment framework: The "plus" part of the "fixed - income +" uses fundamental quantitative methods, with multiple strategies based on fundamental analysis and a macro - based asset allocation framework [9][11]. - Managed products: He manages products worth 8.768 billion yuan, covering first - tier and second - tier bond funds and flexible - allocation funds, achieving over 7% and 2% returns for China - Europe Dingli and China - Europe Enhanced Return respectively [8]. 3.2. China - Europe Dingli: A Medium - to - High - Volatility Secondary Bond Fund with a Boom - Growth Strategy - Product positioning: It is a medium - to - high - volatility secondary bond fund using a quantitative boom - growth strategy with three nested layers [12]. - Boom judgment: It uses financial statements to assess a company's financial health, profit sustainability, and growth momentum [14]. - Comparison with other products: It is comparable to Smart Beta products. Growth - style products have high volatility and high long - term returns, and China - Europe Dingli's equity return in 2025 has exceeded the growth index [19][30]. - Product characteristics: It has high return - risk performance, with a 2025 - to - date return of 11.41% (in the 10.16% percentile) and an annualized volatility of 8.44% (in the 8.59% percentile). Investor profitability increases with holding time [32][33]. - Portfolio: It has a stock position of 16.29% and a convertible bond position of 13.14%, with a focus on growth - oriented industries such as electronics, machinery, and power equipment [37]. 3.3. China - Europe Enhanced Return: A Low - Volatility Absolute - Return Product - Product positioning: It aims to create an absolute return within a 2% drawdown target, emphasizing the safety margin of equity assets through valuation [44][45]. - Performance: In 2025, it achieved a cumulative return of 3.53% with an annualized volatility of 2.26%, ranking in the 14.21% and 16.50% percentiles among first - tier bond funds with equity. Multiple core indicators rank high in the industry [45][46]. - Investor profitability: Investor profitability increases with holding time, with average returns of 0.49%, 1.08%, and 1.54% for 1 - month, 2 - month, and 3 - month holding periods respectively, and a 100% winning rate for 2 - and 3 - month holding periods [47].