Group 1: Market Overview - The Hong Kong stock market performed poorly in October 2025, with the Hang Seng Index declining by 3.5% and the Hang Seng Technology Index falling by 8.6% [5] - The average daily trading volume in October was HKD 211.3 billion, a decrease of 16.6% compared to September 2025 [5] - Value sectors outperformed growth sectors, with coal, oil and petrochemicals, electricity, and utilities leading the gains [5] Group 2: Fund Flow Analysis - Southbound capital saw a total net inflow of HKD 925 billion in October 2025, with a cumulative net inflow of HKD 1.26 trillion for the year, marking a 156% increase compared to 2024 [6] - The market value proportions of southbound funds, foreign capital, domestic capital, and Hong Kong capital as of October 28, 2025, were 21.49%, 58.86%, 12.66%, and 6.99% respectively [6] Group 3: Industry Insights Consumer Goods - The oral care market in China reached a retail scale of CNY 30.2 billion in 2023, with a growth rate of 0.2% year-on-year [16] - The sanitary napkin market is projected to grow to CNY 105 billion in 2024, with a year-on-year growth of 2.9% [17] - The global wet wipes market is expected to reach USD 18.4 billion in 2024, growing at 2.7% year-on-year [17] Military Industry - The demand for titanium materials in aerospace and naval applications is expected to reach 49,000 tons by 2027 [22] - The titanium material usage in the shipbuilding sector is projected to grow significantly, driven by national strategies for marine development [24] - Beneficiary stocks in the titanium sector include BaoTi Co., West Superconducting, and West Materials [26] Automotive Industry - SAIC Group reported a revenue of CNY 468.99 billion for the first three quarters of 2025, a year-on-year increase of 9.0% [31] - The company’s Q3 sales volume reached 1.1407 million vehicles, reflecting a 38.7% increase year-on-year [32] - The company is focusing on enhancing decision-making efficiency and optimizing resource allocation through the establishment of a new passenger vehicle division [33] Nonferrous Metals - Yun Aluminum Co. achieved a revenue of CNY 44.072 billion in the first three quarters of 2025, with a year-on-year increase of 12.47% [35] - The company’s net profit for Q3 was CNY 1.63 billion, a year-on-year increase of 25.31% [35] - The company plans to increase its dividend payout ratio, enhancing investor confidence [38] Semiconductor Testing - The company reported a revenue of CNY 737 million for the first three quarters of 2025, a year-on-year increase of 44.01% [40] - The company has successfully developed the first domestic open X-ray source, marking a significant advancement in high-end detection equipment [41] - The acquisition of SSTI is expected to enhance the company's performance in the high-end semiconductor testing equipment sector [42]

- The report introduces the "Hong Kong Multi-Factor Model," which includes four categories of factors: technical, capital, fundamental, and analyst expectations. These factors are applied to Hong Kong Stock Connect constituent stocks and have demonstrated excellent performance in group analysis[36][41] - The "Hong Kong Stock Connect Preferred 20 Portfolio" is constructed monthly by selecting the top 20 stocks with the highest scores based on the multi-factor model. The portfolio is equally weighted, and the benchmark index is the Hong Kong Composite Index (HKD) (930930.CSI)[38] - The construction process of the "Hong Kong Stock Connect Preferred 20 Portfolio" involves evaluating stocks using the multi-factor model, ranking them based on their scores, and selecting the top 20 stocks for equal-weighted allocation[38] - The report evaluates the "Hong Kong Stock Connect Preferred 20 Portfolio" positively, noting its strong historical performance with an annualized excess return of 12.9% and an excess return volatility ratio of 1.0 over the period from January 2015 to October 2025[38][40] - The October 2025 performance of the "Hong Kong Stock Connect Preferred 20 Portfolio" showed a return of -3.8%, compared to the benchmark index return of -3.6%, resulting in an excess return of -0.1%[38] - The historical performance metrics of the "Hong Kong Stock Connect Preferred 20 Portfolio" include an annualized excess return of 12.9%, annualized excess volatility of 13.5%, excess return volatility ratio of 1.0, and maximum drawdown of 18.2% over the period from January 2015 to October 2025[39][40]

- The report introduces a multi-factor model for Hong Kong stocks, which includes four categories of factors: technical, capital, fundamental, and analyst expectations[12][36][37] - The construction of the "Hong Kong Stock Preferred 20 Portfolio" is based on selecting the top 20 stocks with the highest scores from the Hong Kong Stock Connect sample stocks at the end of each month, using an equal-weighted approach. The benchmark index is the Hong Kong Composite Index (930930.CSI)[5][39][40] - The "Hong Kong Stock Preferred 20 Portfolio" demonstrates an annualized excess return of 12.9% over the entire backtesting period (2015.1~2025.9), with an excess return volatility ratio of 1.0[5][40] - In September 2025, the portfolio's return was 0.25%, while the benchmark index return was 7.65%, resulting in an excess return of -7.41%[5][39] - The October 2025 portfolio allocation increased its exposure to the non-ferrous metals sector, reflecting adjustments based on market trends[6][43][44]

- Model Name: Hong Kong Stock Selection 20 Portfolio; Model Construction Idea: The model selects the top 20 stocks with the highest scores at the end of each month and constructs an equally weighted portfolio; Model Construction Process: The model uses four types of factors (technical, capital, fundamental, and analyst expectations) to evaluate Hong Kong Stock Connect constituent stocks. The portfolio is benchmarked against the Hong Kong Composite Index (HKD) (930930.CSI). The formula for the excess annualized return is: $$ \text{Excess Annualized Return} = \frac{\text{Portfolio Return} - \text{Benchmark Return}}{\text{Benchmark Return}} $$ Model Evaluation: The model has shown superior performance in the Hong Kong Stock Connect constituent stocks[4][32][34] - Factor Name: Technical Factor; Factor Construction Idea: The factor is based on technical indicators; Factor Construction Process: The factor is constructed using various technical indicators such as moving averages, relative strength index (RSI), and others. The formula for the technical factor score is: $$ \text{Technical Factor Score} = \sum_{i=1}^{n} w_i \cdot \text{Indicator}_i $$ where \( w_i \) represents the weight of each indicator and \( \text{Indicator}_i \) represents the value of each technical indicator; Factor Evaluation: The technical factor has shown good performance in the Hong Kong Stock Connect constituent stocks[32][33] - Factor Name: Capital Factor; Factor Construction Idea: The factor is based on capital flow data; Factor Construction Process: The factor is constructed using data on capital inflows and outflows. The formula for the capital factor score is: $$ \text{Capital Factor Score} = \frac{\text{Capital Inflow} - \text{Capital Outflow}}{\text{Total Capital}} $$ Factor Evaluation: The capital factor has shown good performance in the Hong Kong Stock Connect constituent stocks[32][33] - Factor Name: Fundamental Factor; Factor Construction Idea: The factor is based on fundamental financial data; Factor Construction Process: The factor is constructed using various financial metrics such as price-to-earnings ratio (P/E), return on equity (ROE), and others. The formula for the fundamental factor score is: $$ \text{Fundamental Factor Score} = \sum_{i=1}^{n} w_i \cdot \text{Metric}_i $$ where \( w_i \) represents the weight of each metric and \( \text{Metric}_i \) represents the value of each financial metric; Factor Evaluation: The fundamental factor has shown good performance in the Hong Kong Stock Connect constituent stocks[32][33] - Factor Name: Analyst Expectations Factor; Factor Construction Idea: The factor is based on analyst ratings and expectations; Factor Construction Process: The factor is constructed using data on analyst ratings, target prices, and earnings forecasts. The formula for the analyst expectations factor score is: $$ \text{Analyst Expectations Factor Score} = \sum_{i=1}^{n} w_i \cdot \text{Analyst Rating}_i $$ where \( w_i \) represents the weight of each analyst rating and \( \text{Analyst Rating}_i \) represents the value of each analyst rating; Factor Evaluation: The analyst expectations factor has shown good performance in the Hong Kong Stock Connect constituent stocks[32][33] Model Backtest Results - Hong Kong Stock Selection 20 Portfolio, Excess Annualized Return: 13.8%, Excess Annualized Volatility: 13.3%, Excess Return Volatility Ratio: 1.0, Maximum Drawdown: 18.2%[35][36][37]

Quantitative Models and Construction Methods Model Name: Hong Kong Stock Selection 20 Portfolio - **Model Construction Idea**: The model aims to track the monthly performance of a long portfolio by selecting the top 20 stocks with the highest scores based on multiple factors. The benchmark is the Hong Kong Composite Index (HKD) (930930.CSI) [40][42] - **Model Construction Process**: - The model uses four types of factors: technical, capital, fundamental, and analyst expectations [40][41] - At the end of each month, the top 20 stocks with the highest scores are selected and equally weighted to construct the Hong Kong Stock Selection 20 Portfolio [42] - **Model Evaluation**: The model has shown excellent performance in the Hong Kong Stock Connect sample stocks [40] Model Backtesting Results - **Hong Kong Stock Selection 20 Portfolio**: - **July 2025**: Portfolio return 11.6%, benchmark index return 4.8%, excess return 6.8% [42] - **Overall Period (2015.1~2025.7)**: Excess annualized return 13.9%, excess return volatility ratio 1.0 [42][44] Quantitative Factors and Construction Methods Factor Name: Technical, Capital, Fundamental, Analyst Expectations - **Factor Construction Idea**: These factors are used to evaluate the performance of Hong Kong Stock Connect sample stocks [40] - **Factor Construction Process**: - **Technical**: Based on stock price movements and technical indicators - **Capital**: Based on capital flow and trading volume - **Fundamental**: Based on financial metrics such as PE ratio, ROE, etc. - **Analyst Expectations**: Based on analyst ratings and forecasts [40][41] - **Factor Evaluation**: These factors have shown excellent performance in the Hong Kong Stock Connect sample stocks [40] Factor Backtesting Results - **Technical, Capital, Fundamental, Analyst Expectations**: - **July 2025**: Excess annualized return 13.9%, excess return volatility ratio 1.0 [42][44]

- Model Name: Hong Kong Stock Selection 20 Portfolio; Model Construction Idea: The model selects the top 20 stocks with the highest scores based on four types of factors (technical, capital, fundamental, and analyst expectations) from the Hong Kong Stock Connect sample stocks and constructs an equal-weighted portfolio at the end of each month; Model Construction Process: The model uses the Hong Kong Composite Index (HKD) (930930.CSI) as the benchmark. The specific construction process involves selecting the top 20 stocks with the highest scores based on the four types of factors and constructing an equal-weighted portfolio at the end of each month[3][37][39]; Model Evaluation: The model has shown excellent performance in the Hong Kong Stock Connect sample stocks[37] - Factor Name: Technical Factors; Factor Construction Idea: Technical factors are constructed based on the price and volume data of stocks; Factor Construction Process: The specific construction process involves calculating various technical indicators such as moving averages, relative strength index (RSI), and moving average convergence divergence (MACD) to evaluate the stock's price trend and momentum[37][38]; Factor Evaluation: Technical factors have shown good performance in the Hong Kong Stock Connect sample stocks[37] - Factor Name: Capital Factors; Factor Construction Idea: Capital factors are constructed based on the capital flow data of stocks; Factor Construction Process: The specific construction process involves calculating the net capital inflow and outflow of stocks to evaluate the stock's capital flow trend[37][38]; Factor Evaluation: Capital factors have shown good performance in the Hong Kong Stock Connect sample stocks[37] - Factor Name: Fundamental Factors; Factor Construction Idea: Fundamental factors are constructed based on the financial data of stocks; Factor Construction Process: The specific construction process involves calculating various financial ratios such as price-to-earnings (P/E) ratio, return on equity (ROE), and total market value to evaluate the stock's financial health and valuation[37][38]; Factor Evaluation: Fundamental factors have shown good performance in the Hong Kong Stock Connect sample stocks[37] - Factor Name: Analyst Expectation Factors; Factor Construction Idea: Analyst expectation factors are constructed based on the analyst ratings and target prices of stocks; Factor Construction Process: The specific construction process involves collecting and analyzing the analyst ratings and target prices of stocks to evaluate the stock's future performance expectations[37][38]; Factor Evaluation: Analyst expectation factors have shown good performance in the Hong Kong Stock Connect sample stocks[37] Model Backtest Results - Hong Kong Stock Selection 20 Portfolio, Annualized Excess Return: 13.3%, Excess Return Volatility Ratio: 1.0[4][40][41] Factor Backtest Results - Southbound Capital, Average Return: 25.7%[32][36] - Foreign Capital, Average Return: 13.5%[32][36] - Domestic Capital, Average Return: 14.0%[32][36] - Hong Kong Capital and Others, Average Return: 10.2%[32][36]

Quantitative Models and Construction Methods 1. Model Name: Hong Kong Stock Multi-Factor Model - **Model Construction Idea**: The model integrates four categories of factors: technical, capital flow, fundamental, and analyst expectations, to evaluate Hong Kong Stock Connect constituent stocks[38][39] - **Model Construction Process**: 1. Select Hong Kong Stock Connect constituent stocks as the sample universe 2. Construct four categories of factors: - **Technical factors**: Indicators derived from price and volume data - **Capital flow factors**: Metrics based on fund flow data, such as net inflow - **Fundamental factors**: Metrics like valuation ratios (e.g., PE, PB) and profitability indicators (e.g., ROE) - **Analyst expectation factors**: Metrics based on analyst ratings and earnings forecasts 3. Combine these factors into a composite score for each stock 4. Rank stocks based on their composite scores and select the top 20 stocks to form the portfolio[38][39][40] - **Model Evaluation**: The model demonstrates strong performance in historical backtesting, with significant excess returns over the benchmark[38][40] 2. Model Name: Hong Kong Stock Preferred 20 Portfolio - **Model Construction Idea**: This portfolio is constructed monthly by selecting the top 20 stocks with the highest composite scores from the multi-factor model, using equal weighting[40] - **Model Construction Process**: 1. At the end of each month, rank stocks based on their composite scores from the multi-factor model 2. Select the top 20 stocks 3. Allocate equal weights to each stock in the portfolio 4. Use the Hong Kong Composite Index (HKD, 930930.CSI) as the benchmark for performance comparison[40] - **Model Evaluation**: The portfolio has shown robust performance over the long term, with a high excess annualized return and a stable risk-return profile[40][44] --- Model Backtesting Results 1. Hong Kong Stock Multi-Factor Model - **Excess Annualized Return**: 13.3% (2015.1–2025.5)[40][44] - **Excess Annualized Volatility**: 13.4%[44] - **Excess Sharpe Ratio**: 1.0[44] - **Maximum Drawdown**: 18.2%[44] 2. Hong Kong Stock Preferred 20 Portfolio - **May 2025 Monthly Return**: 2.44%[40] - **May 2025 Excess Return**: -2.36% (Benchmark return: 4.80%)[40] - **Excess Annualized Return**: 13.3% (2015.1–2025.5)[40][44] - **Excess Annualized Volatility**: 13.4%[44] - **Excess Sharpe Ratio**: 1.0[44] - **Maximum Drawdown**: 18.2%[44] --- Quantitative Factors and Construction Methods 1. Factor Name: Technical Factors - **Factor Construction Idea**: Derived from price and volume data to capture market trends and momentum[38][39] - **Factor Construction Process**: 1. Calculate indicators such as moving averages, RSI, and MACD 2. Normalize and rank the indicators across the stock universe 3. Combine the normalized scores into a composite technical factor score[38][39] 2. Factor Name: Capital Flow Factors - **Factor Construction Idea**: Based on fund flow data to identify stocks with strong capital inflows[38][39] - **Factor Construction Process**: 1. Measure net fund inflows for each stock 2. Normalize and rank the net inflow data 3. Combine the normalized scores into a composite capital flow factor score[38][39] 3. Factor Name: Fundamental Factors - **Factor Construction Idea**: Focused on valuation and profitability metrics to identify undervalued stocks with strong fundamentals[38][39] - **Factor Construction Process**: 1. Calculate valuation ratios (e.g., PE, PB) and profitability indicators (e.g., ROE) 2. Normalize and rank these metrics across the stock universe 3. Combine the normalized scores into a composite fundamental factor score[38][39] 4. Factor Name: Analyst Expectation Factors - **Factor Construction Idea**: Based on analyst ratings and earnings forecasts to capture market sentiment and expectations[38][39] - **Factor Construction Process**: 1. Collect analyst ratings and earnings forecast data 2. Normalize and rank the data 3. Combine the normalized scores into a composite analyst expectation factor score[38][39] --- Factor Backtesting Results 1. Technical Factors - **Performance**: Demonstrated strong predictive power in identifying stocks with upward momentum[38][39] 2. Capital Flow Factors - **Performance**: Effective in capturing stocks with significant fund inflows, indicating strong market interest[38][39] 3. Fundamental Factors - **Performance**: Successfully identified undervalued stocks with robust financial performance[38][39] 4. Analyst Expectation Factors - **Performance**: Provided valuable insights into market sentiment and future earnings potential[38][39]

- Model Name: Hong Kong Stock Selection 20 Portfolio; Model Construction Idea: The portfolio is constructed by selecting the top 20 stocks with the highest scores at the end of each month and equally weighting them; Detailed Construction Process: The model uses four types of factors (technical, capital, fundamental, and analyst expectations) to score Hong Kong Stock Connect constituent stocks. The top 20 stocks are selected based on these scores and equally weighted to form the portfolio. The benchmark is the Hong Kong Composite Index (HKD) (930930.CSI) [4][39]; Model Evaluation: The model has shown superior performance in the Hong Kong Stock Connect constituent stocks [4][37] - Factor Name: Technical Factor; Factor Construction Idea: The factor is constructed based on technical indicators; Detailed Construction Process: The specific technical indicators used and their calculation methods are not detailed in the report [4][37] - Factor Name: Capital Factor; Factor Construction Idea: The factor is constructed based on capital flow data; Detailed Construction Process: The specific capital flow data used and their calculation methods are not detailed in the report [4][37] - Factor Name: Fundamental Factor; Factor Construction Idea: The factor is constructed based on fundamental financial data; Detailed Construction Process: The specific fundamental financial data used and their calculation methods are not detailed in the report [4][37] - Factor Name: Analyst Expectations Factor; Factor Construction Idea: The factor is constructed based on analyst expectations; Detailed Construction Process: The specific analyst expectations data used and their calculation methods are not detailed in the report [4][37] Model Backtest Results - Hong Kong Stock Selection 20 Portfolio, Annualized Excess Return: 13.7%, Excess Return Volatility Ratio: 1.0 [4][40][41] Factor Backtest Results - Technical Factor, specific backtest results not detailed in the report - Capital Factor, specific backtest results not detailed in the report - Fundamental Factor, specific backtest results not detailed in the report - Analyst Expectations Factor, specific backtest results not detailed in the report