Core Viewpoint - Southbound capital inflow into Hong Kong stocks has accelerated, with a cumulative net inflow of HKD 395.2 billion in Q3, an increase compared to Q2 [1][2] Flow Perspective - In Q3, southbound funds continued to flow into Hong Kong stocks, with a cumulative net inflow of HKD 395.2 billion, which is an increase from Q2 [2] - The outflow of foreign capital has slowed down, with a cumulative net outflow of HKD 66.4 billion in Q3, marking a decrease in outflow for three consecutive quarters [2] - The proportion of southbound holdings in Hong Kong stocks has reached a new high, with the Hong Kong Stock Connect holding amount rising from 20.7% at the end of Q2 to 21.8% at the end of Q3 [2] Industry Perspective - In Q3, the main inflows from southbound funds were into consumer discretionary, non-bank financials, and pharmaceuticals, while software and hardware saw net outflows in Q2 [3] - Foreign capital dominates most sub-sectors in Hong Kong stocks, particularly in the internet, finance, and most consumer sectors [3] - Southbound funds have gained significant pricing power in sectors such as semiconductors, general consumption, and general dividends over the past two years [3]

Core Insights - The article discusses the experiences of young investors in the A-share market, highlighting their struggles and learning curves as they navigate the volatile stock environment [3][4][11]. Group 1: Market Performance - On October 9, 2025, the A-share market reached a nearly ten-year high, with the Shanghai Composite Index closing at 3933.97 points, marking a 37.4% increase since the start of the "9·24" rally [4]. - The total market capitalization of A-shares increased by 51.57% since the "9·24" rally began, with the Shenzhen Component Index rising by 62.71% and several indices exceeding 100% growth [4]. - From September 24, 2024, to October 9, 2025, the Shanghai Composite Index surged from 2800 points to 3600 points before experiencing a quick drop to around 3300 points [6]. Group 2: Investor Experiences - Young investors, such as Mr. Bai and Xiao Chen, faced challenges like "cutting losses" and "missing opportunities," leading to a deeper understanding of market dynamics [3][7]. - Xiao Chen initially invested in a white wine stock but faced a loss of nearly 4000 yuan, prompting him to diversify his investments into real estate and steel stocks [5][12]. - Mr. Bai reported a total return of 111% from his investments, equating to earnings comparable to six months of his salary, after successfully navigating the market [9]. Group 3: Investment Strategies - Investors are learning to adapt their strategies, with Mr. Bai emphasizing the importance of diversification and timing in stock purchases [8][14]. - The article notes that many young investors are now focusing on technology stocks, which have shown significant growth, with some stocks experiencing over 80% increases [14]. - Analysts suggest that the technology sector is expected to remain a focal point for investment, driven by favorable market conditions and policy support [15][16].

Core Insights - The article provides a comprehensive analysis of market factors and their recent performance, highlighting the positive returns from liquidity and leverage factors, while noting negative returns from beta and growth factors [4][5]. Factor Performance - In the last two weeks, the liquidity factor and leverage factor yielded positive returns of 0.36% and 0.34% respectively, while the profitability factor achieved a positive return of 0.27%. Other factors like valuation and market capitalization also showed positive returns, albeit lower [4]. - For the CSI 300 stock pool, the best-performing factors included quarterly operating profit growth rate (2.54%) and quarterly net profit growth rate (2.36%), while total asset growth rate showed a negative return of -1.94% [5]. - In the CSI 500 stock pool, the top factors were the inverse of price-to-sales ratio (1.90%) and net profit gap (1.55%), with the worst performers being quarterly total asset gross margin (-2.12%) [5]. - The liquidity 1500 stock pool saw strong performance from the price-to-earnings ratio (2.19%) and inverse price-to-earnings ratio (2.09%), while total asset gross margin factors performed poorly [5]. Industry Factor Performance - Recent weeks showed a divergence in fundamental factors across industries, with net asset growth rate and net profit growth rate performing well in textiles, non-bank financials, and leisure services [6][7]. - Valuation factors, particularly the BP factor, achieved positive returns across multiple industries, while liquidity factors showed significant positive returns in the beauty and personal care sector [7]. Combination Tracking - The PB-ROE-50 combination achieved positive excess returns in the CSI 800 and overall market stock pools, with a notable excess return of 1.45% in the CSI 800 pool [8]. - Public and private fund research strategies yielded positive excess returns, with public research strategies outperforming the CSI 800 by 1.03% and private strategies by 1.89% [9]. Block Trade and Directed Issuance Tracking - The block trade combination underperformed relative to the CSI All Index, with an excess return of -0.57% [10]. - Similarly, the directed issuance combination also showed negative excess returns of -1.13% compared to the CSI All Index [11].

Core Conclusions - The overall valuation of A-shares has expanded this week, with the non-ferrous metals industry continuing to lead the market [1] - During the National Day holiday, favorable factors for the non-ferrous industry have emerged, contributing to its ongoing leadership [1] - The current overall PB (LF) of the non-ferrous metals industry is at the historical 87.8 percentile, with specific sectors like copper, aluminum, lithium, and gold at 92.1%, 96.3%, 40.7%, and 83.6% percentiles respectively, indicating greater valuation upside potential for lithium [1] A-share Valuation Overview - The overall PE (TTM) of A-shares increased from 22.36 times last week to 22.78 times this week, while PB (LF) rose from 2.17 times to 2.21 times [10] - The PE (TTM) of the ChiNext board increased from 81.61 times to 82.22 times, while its PB (LF) remained stable at 4.88 times [19] - The PE (TTM) of the Sci-Tech Innovation Board rose from 272.77 times to 276.66 times, with PB (LF) increasing from 6.72 times to 6.81 times [21] Industry Valuation Levels - From a static PE (TTM) perspective, major industries such as consumer discretionary, midstream manufacturing, and cyclical sectors have absolute and relative valuations above historical medians, with consumer discretionary and midstream manufacturing exceeding the 90th percentile [27] - In terms of PB (LF), TMT, midstream manufacturing, and consumer discretionary also show absolute and relative valuations above historical medians, while financial services and consumer staples are below historical medians [29] - The overall valuation of key companies in A-shares based on dynamic PE increased from 15.17 times to 15.19 times this week [14] Relative Valuation Expansion - The relative PE (TTM) for computing infrastructure, excluding operators and resource categories, decreased from 5.80 times to 5.66 times, while relative PB (LF) fell from 5.69 times to 5.54 times [23] - The current comparison of odds (PB historical percentiles) and win rates (ROE historical percentiles) indicates that industries like oil and petrochemicals, as well as agriculture, forestry, animal husbandry, and fishery, exhibit characteristics of low valuation and high profitability [2] ERP and Equity-Debt Yield Spread - The non-financial ERP of A-shares decreased from 0.80% to 0.76%, while the equity-debt yield spread fell from -0.19% to -0.24% [60] - The dynamic ERP of key non-financial companies in A-shares increased from 2.76% to 2.77% this week [64]

Quantitative Models and Construction - **Model Name**: PB-ROE-50 **Model Construction Idea**: The model combines Price-to-Book ratio (PB) and Return on Equity (ROE) to construct a stock selection strategy[25] **Model Construction Process**: The PB-ROE-50 model selects stocks based on their PB and ROE metrics. Stocks with favorable PB and ROE values are included in the portfolio. The model uses a monthly rebalancing approach to optimize the portfolio[25][26] **Model Evaluation**: The model demonstrates positive excess returns in most stock pools, indicating its effectiveness in capturing value and profitability factors[25][26] - **Model Name**: Institutional Research Tracking Strategy **Model Construction Idea**: This strategy leverages institutional research activities (public and private) to identify stocks with potential excess returns[27] **Model Construction Process**: The strategy tracks stocks that are frequently researched by public and private institutions. Stocks with higher research frequency are included in the portfolio. The portfolio is rebalanced periodically to reflect updated research trends[27][28] **Model Evaluation**: The strategy shows consistent positive excess returns, suggesting that institutional research activities can be a reliable indicator for stock selection[27][28] - **Model Name**: Block Trade Strategy **Model Construction Idea**: The strategy identifies stocks with high block trade activity and low volatility to construct a portfolio[31] **Model Construction Process**: Stocks are selected based on two criteria: high block trade transaction ratios and low 6-day transaction volatility. The portfolio is rebalanced monthly to maintain these characteristics[31][32] **Model Evaluation**: The strategy has mixed results, with negative excess returns in the recent 2-week period, but positive performance over the year[31][32] - **Model Name**: Directed Issuance Strategy **Model Construction Idea**: The strategy focuses on stocks involved in directed issuance events to capture potential investment opportunities[36] **Model Construction Process**: Stocks are selected based on the announcement date of directed issuance events. The strategy considers market capitalization, rebalancing frequency, and position control to construct the portfolio[36][37] **Model Evaluation**: The strategy shows negative excess returns in the recent 2-week period, raising questions about its effectiveness under current market conditions[36][37] Model Backtesting Results - **PB-ROE-50 Model**: - Excess return in CSI 500: -0.82% - Excess return in CSI 800: 1.45% - Excess return in the entire market: 0.75%[25][26] - **Institutional Research Tracking Strategy**: - Public research excess return: 1.03% - Private research excess return: 1.89%[27][28] - **Block Trade Strategy**: - Excess return relative to CSI All Index: -0.57%[31][32] - **Directed Issuance Strategy**: - Excess return relative to CSI All Index: -1.13%[36][37] Quantitative Factors and Construction - **Factor Name**: Liquidity Factor **Factor Construction Idea**: Measures the liquidity of stocks to identify those with higher trading activity[20] **Factor Construction Process**: The liquidity factor is calculated using metrics such as turnover rate and trading volume. Stocks with higher liquidity scores are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns in the recent 2-week period, indicating its effectiveness in capturing market liquidity trends[20] - **Factor Name**: Leverage Factor **Factor Construction Idea**: Evaluates the financial leverage of companies to identify those with higher risk-adjusted returns[20] **Factor Construction Process**: The leverage factor is derived from financial ratios such as debt-to-equity and interest coverage. Companies with optimal leverage levels are favored[20] **Factor Evaluation**: The factor demonstrates positive returns, suggesting its utility in identifying financially stable companies[20] - **Factor Name**: Profitability Factor **Factor Construction Idea**: Captures the profitability of companies to identify those with strong earnings performance[20] **Factor Construction Process**: The profitability factor is calculated using metrics such as ROE, ROA, and net profit margin. Stocks with higher profitability metrics are given positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its effectiveness in identifying profitable companies[20] - **Factor Name**: Valuation Factor **Factor Construction Idea**: Measures the relative valuation of stocks to identify undervalued opportunities[20] **Factor Construction Process**: The valuation factor is derived from metrics such as Price-to-Earnings (P/E) and Price-to-Book (P/B) ratios. Stocks with lower valuation scores are assigned positive weights[20] **Factor Evaluation**: The factor demonstrates positive returns, supporting its use in identifying undervalued stocks[20] - **Factor Name**: Non-linear Market Capitalization Factor **Factor Construction Idea**: Captures the non-linear relationship between market capitalization and stock returns[20] **Factor Construction Process**: The factor is constructed using a non-linear transformation of market capitalization data. Stocks with optimal market capitalization are assigned positive weights[20] **Factor Evaluation**: The factor shows positive returns, indicating its ability to capture market capitalization trends effectively[20] - **Factor Name**: Beta Factor **Factor Construction Idea**: Measures the sensitivity of a stock's returns to market movements[20] **Factor Construction Process**: The beta factor is calculated using historical return data and market indices. Stocks with lower beta values are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] - **Factor Name**: Residual Volatility Factor **Factor Construction Idea**: Evaluates the idiosyncratic risk of stocks to identify those with stable performance[20] **Factor Construction Process**: The residual volatility factor is derived from the standard deviation of residuals in a regression model of stock returns against market returns[20] **Factor Evaluation**: The factor shows negative returns, indicating its limited utility in the recent market conditions[20] - **Factor Name**: Growth Factor **Factor Construction Idea**: Captures the growth potential of companies based on their financial performance[20] **Factor Construction Process**: The growth factor is calculated using metrics such as revenue growth and earnings growth. Stocks with higher growth rates are assigned positive weights[20] **Factor Evaluation**: The factor shows negative returns, suggesting its limited effectiveness in the current market environment[20] Factor Backtesting Results - **Liquidity Factor**: Return: 0.36%[20] - **Leverage Factor**: Return: 0.34%[20] - **Profitability Factor**: Return: 0.27%[20] - **Valuation Factor**: Return: 0.18%[20] - **Non-linear Market Capitalization Factor**: Return: 0.18%[20] - **Market Capitalization Factor**: Return: 0.11%[20] - **Beta Factor**: Return: -0.65%[20] - **Residual Volatility Factor**: Return: -0.55%[20] - **Growth Factor**: Return: -0.21%[20]

Group 1 - The market sentiment is influenced by the performance of stocks, leading to a reactive approach from investors who often miss opportunities due to their short-term focus [1][4] - Long-term holding strategies are emphasized, with references to the patience required to realize significant profits, as illustrated by the experiences of investors who have held stocks for hundreds of days without immediate gains [3][6] - The current market outlook suggests a likely scenario of initial declines followed by recoveries, with key sectors such as non-bank financials, securities, and liquor stocks positioned at relatively low levels [8] Group 2 - The discussion highlights the importance of absolute returns over high profit margins in large projects, indicating a preference for long-term investments rather than speculative short-term trades [4][6] - There is a caution against engaging in investment strategies without sufficient capital, suggesting that individuals lacking substantial funds should focus on building their capital before pursuing complex investment plans [6] - The commentary on technology assets indicates a cautious approach, with a focus on established investments rather than speculative tech stocks, while also noting the potential for mid-term trading opportunities in case of market downturns [8]

Core Viewpoint - The A-share market experienced a significant increase in trading volume during the first week after the holiday, with an average daily turnover of 2.60 trillion yuan, marking the highest weekly average since early September [1]. Trading Volume Summary - The average daily trading volume in the A-share market reached 2.60 trillion yuan from October 9 to 10, 2023, which is the highest since the week of September 5 [1]. - This trading volume is the second highest of the year, only behind the week of August 25 to 29 [1]. Active Stocks and Sectors - A total of 21 stocks had an average daily trading volume exceeding 10 billion yuan, with ZTE Corporation and SMIC surpassing 20 billion yuan [3]. - The most active sectors included electronics, power equipment, telecommunications, and non-ferrous metals, with electronics accounting for nearly 40% of the active stocks [3]. Turnover Rate Analysis - Excluding newly listed stocks in the past month, 13 stocks had an average turnover rate exceeding 30%, with notable mentions being Dixin Long and Chuling Information at 42.44% and 41.68% respectively [6]. - The active stocks in terms of turnover rate were primarily from the power equipment, electronics, machinery, and non-ferrous metals sectors [6]. Sector Performance - The electronics sector continued to attract significant capital, maintaining an average daily trading volume of 542.7 billion yuan, consistent with pre-holiday levels [9]. - The power equipment and non-ferrous metals sectors saw a notable increase in trading volume post-holiday, with the power equipment sector exceeding 300 billion yuan in daily trading volume over the first two days after the holiday [9]. - In terms of sub-sectors, digital chip design and consumer electronics components and assembly were among the top performers, each exceeding 100 billion yuan in average daily trading volume [11].

Investment Rating - The report maintains an investment rating of "Outperform the Market" for the non-bank financial sector [9][12]. Core Insights - The economic backdrop of stable growth and continuous supportive policies is expected to improve market sentiment towards equities, benefiting the cyclical financial sector. The resolution of risks in key areas like real estate is also anticipated to alleviate concerns regarding asset quality in the non-bank sector, favoring valuation recovery [4][12]. - The report recommends focusing on investment opportunities within the sector, highlighting specific companies such as New China Life, China Life, Ping An, China Pacific Insurance, China Property Insurance, GF Securities, CICC, CITIC Securities, Huatai Securities, Dongfang Securities, Dongfang Fortune, Jiangsu Jinzhong, Bohai Leasing, and Bank of China Aviation Leasing [4][12]. Summary by Sections Brokerage Sector - The brokerage sector is expected to see a significant recovery, with a projected year-on-year increase of 56% in net profit for the first nine months of 2025. The average daily trading volume in the equity market for Q3 2025 is estimated at 2.1 trillion yuan, reflecting a year-on-year increase of 210% and a quarter-on-quarter increase of 68% [10]. - The anticipated year-on-year growth rates for major brokerage firms' net profits include CICC (+135%), Dongfang Securities (+68%), GF Securities (+56%), and others [10]. Insurance Sector - The insurance sector is projected to experience growth in new business value (NBV) for life insurance companies, with expected growth rates for the first nine months of 2025 as follows: New China Life (+60%), Ping An (+42%), China Pacific Insurance (+33%), and China Life (+25%) [11]. - For property and casualty insurance, the combined ratio (COR) is expected to improve year-on-year, with estimates for major companies such as Ping An Property & Casualty (96.1%, -1.7 percentage points), China Property Insurance (97.0%, -1.2 percentage points), and China Pacific Property Insurance (98.0%, -0.7 percentage points) [11]. Leasing Sector - The aircraft leasing sector is expected to maintain a favorable supply-demand balance, with increasing aircraft values and rental rates. However, the ship leasing sector may face short-term impacts due to the US 301 investigation [12]. - Profit growth rankings for leasing companies are projected as follows: Jiangsu Jinzhong > China Ship Leasing > Bank of China Aviation Leasing > Bohai Leasing, with Bohai Leasing potentially facing challenges due to impairments [12].

Market Overview - Hong Kong's stock market has become deeply "localized" and "new economy-oriented," characterized by "low valuation" and "high dividend" features[3] - As of July 2025, mainland enterprises account for 57% of the total number of listed companies and 81% of the total market capitalization in Hong Kong[11] Market Structure - The main board of the Hong Kong Stock Exchange dominates with 2,337 listed companies and a total market capitalization of 44.82 trillion HKD, while the growth enterprise market has 314 companies with a market cap of 0.07 trillion HKD[10] - The market is highly concentrated, with 69.43% of companies having a market cap between 0-20 billion HKD, contributing only 1.80% to total market capitalization[42] Valuation Characteristics - As of August 15, 2025, the Hang Seng Index has a price-to-earnings (P/E) ratio of 11.52 and a price-to-book (P/B) ratio of 1.20, both lower than major global indices[49] - The average valuation premium of A-shares over H-shares is approximately 55%, with most dual-listed companies showing significant price differences[52] Shareholder Returns - The dividend yield of the Hang Seng Index has remained stable between 3%-5% since 2020, outperforming major markets like the US and Japan[64] - Annual cash dividends in the Hong Kong market have steadily increased from under 700 billion HKD in 2015 to over 1.2 trillion HKD in 2024[68] Investor Structure - The investor base in Hong Kong is highly internationalized, with foreign investors contributing 41% of total trading volume, and institutional investors accounting for 57%[79] - The market has seen a significant shift, with the market share of mainland funds through the Stock Connect program rising to 12.29% by July 2025[81] Southbound Capital - Cumulative net inflows from southbound funds have reached 4.60 trillion HKD as of August 2025, significantly impacting market liquidity and asset pricing[94] - The proportion of southbound funds in the Hong Kong market has increased, with their trading volume accounting for nearly 50% of total market transactions in 2025[96]

Market Overview - The two markets experienced a significant net outflow of 91.316 billion yuan, with 1,845 stocks seeing net inflows and 2,931 stocks experiencing net outflows [1] - The Shanghai Composite Index closed down by 0.94% [1] Industry Analysis - Among the 10 industries with net inflows, the textile and apparel sector led with a net inflow of 513 million yuan, and its index rose by 1.30% [1] - The food and beverage sector followed with a net inflow of 483 million yuan and a slight increase of 0.14% [1] - The electronic industry faced the highest net outflow of 31.197 billion yuan, followed by the power equipment sector with a net outflow of 19.144 billion yuan [1] Individual Stock Performance - 23 stocks had net inflows exceeding 200 million yuan, with Changcheng Military Industry leading at 849 million yuan [2] - New Lai Materials ranked second with a net inflow of 608 million yuan [2] - The average increase for stocks with net inflows over 200 million yuan was 8.30%, outperforming the Shanghai Composite Index [2] Top Net Inflow Stocks - Changcheng Military Industry: 849 million yuan, 10.00% increase [2] - New Lai Materials: 608 million yuan, 20.00% increase [2] - Blue Dai Technology: 563 million yuan, 4.92% increase [2] Top Net Outflow Stocks - Dongfang Wealth: -3.054 billion yuan, -2.50% decrease [4] - Ningde Times: -2.629 billion yuan, -6.82% decrease [4] - Northern Rare Earth: -2.546 billion yuan, -1.22% decrease [4]