Group 1 - The core index of the China Securities Index for Hong Kong Stock Connect leisure consumption theme has shown a significant increase, with a 13.33% rise in the past month, 5.47% in the past three months, and 6.86% year-to-date [1] - The index consists of 40 listed companies involved in the leisure consumption industry, reflecting the overall performance of these companies within the Hong Kong Stock Connect [1] - The index is based on a starting point of 1000.0 points as of December 30, 2016 [1] Group 2 - The top ten weighted companies in the index include Pop Mart (18.77%), Anta Sports (11.04%), Yum China (8.59%), Meituan-W (8.14%), Shenzhou International (7.59%), Li Ning (5.87%), Haidilao (5.74%), Tongcheng Travel (4.32%), Samsonite (2.98%), and Chow Tai Fook (2.95%) [1] - The index is exclusively composed of stocks listed on the Hong Kong Stock Exchange, with a 100% allocation [1] - The industry composition of the index includes textiles and apparel with 38.68%, consumer services at 33.32%, durable goods at 21.82%, media at 3.83%, and retail at 2.34% [1] Group 3 - The index samples are adjusted biannually, with changes implemented on the next trading day following the second Friday of June and December [2] - Weight factors are generally fixed until the next scheduled adjustment, with special circumstances allowing for temporary adjustments [2] - Companies that are delisted or undergo mergers, acquisitions, or splits will be handled according to specific calculation and maintenance guidelines [2]

Summary of Key Points from the Conference Call Industry Overview - The conference call discusses the performance of the Hong Kong stock market (港股) in 2024, highlighting a recovery trend in overall earnings growth with a 1.2% increase in revenue and a 9.8% year-on-year growth in net profit attributable to shareholders [1][3][6]. Core Insights and Arguments - **Earnings Growth**: The second half of 2024 saw a significant acceleration in earnings, with a year-on-year increase of 13.3% [1][6]. - **Key Sectors Driving Growth**: - The information technology sector benefited from breakthroughs in AI technology, with net profit growth of 77.4% in the software and services sub-sector and 76.4% in the technology hardware and equipment sub-sector [1][10]. - The financial sector, particularly the insurance industry, experienced a 70.8% increase in net profit, while diversified financial services saw a 20.5% growth [1][10]. - The healthcare sector, including pharmaceuticals, biotechnology, and life sciences, improved profitability by nearly 20 percentage points [1][10]. - **Struggling Sectors**: The consumer sector showed weak growth, with significant declines in return on equity (ROE) for household and personal products, and food retail. The optional consumer retail sub-sector's profit growth decreased by 36 percentage points, while media and consumer services saw declines of approximately 18% and 19% respectively [1][11]. Financial Metrics - **Return on Equity (ROE)**: The ROE for Hong Kong stocks rose to 7% in 2024, up from 6.7% in the first half of the year, but still below the average of around 10% since 2016. The DuPont analysis indicated that the increase in asset turnover was the primary driver of the ROE improvement [1][7][8]. - **Revenue Trends**: The revenue growth rate for Hong Kong stocks showed signs of bottoming out, with a 1.2% increase for the year, slightly down from 1.9% in the first half of 2024 [1][5]. Comparative Analysis - **Performance vs. A-shares**: The earnings recovery speed of Hong Kong stocks is superior to that of A-shares, which reported negative growth rates of -0.2% for the year and -0.5% for the first half of 2025 in terms of revenue and -2.7% for both periods in net profit [4][6]. Future Outlook - **Support Factors for 2025**: The global technology cycle is expected to rebound, with the AI-driven industrial revolution continuing to support the performance of the information technology sector. Additionally, macroeconomic policies aimed at stabilizing growth are anticipated to benefit mainland companies, which constitute over 60% of the market [4][12].

Core Insights - The "New National Nine Policies" emphasize market value management and dividend regulation, promoting valuation recovery for undervalued state-owned enterprises, while highlighting the importance of "new productive forces" for the growth of technology companies [1] - The "Everyday Brand 100 Index" has seen significant growth, achieving a maximum annual increase of 17.37% and reaching new highs [1][3] Market Performance - The Everyday Brand 100 Index reached a new high of 1181 points, marking a strong performance in its third year despite a complex international environment [2] - The index experienced a significant rebound, rising from 820 points to 1146 points in just ten trading days, reflecting a nearly 40% increase following the introduction of the "924" policy [2][3] Economic Indicators - Key economic indicators such as industrial production, fixed asset investment, and retail sales growth have been below expectations, leading to increased market concerns about corporate profitability [2] - The index's performance has outpaced major A-share indices, demonstrating strong investment elasticity and resilience against risks [5] Valuation Metrics - As of May 7, the Everyday Brand 100 Index had a price-to-earnings (P/E) ratio of 9.5 and a price-to-book (P/B) ratio of 1.17, which are significantly lower than the benchmark indices [7] - The index's valuation advantage is evident, as it remains below the P/E ratios of the Shanghai 50 and CSI 100 indices, as well as the Hang Seng Technology Index [7] Component Stocks - The Everyday Brand 100 Index includes leading companies across various sectors, with significant weightings in Tencent, Alibaba, and Kweichow Moutai, among others [9][10] - The index spans A-shares, Hong Kong stocks, and U.S. stocks, with A-shares accounting for 49.07% and Hong Kong stocks 47.23% of the index [9] Future Outlook - The index is expected to continue its stable operation above the 1000-point mark, with potential for further brand value and valuation increases as component companies enhance their competitive strengths [6] - The rise of domestic AI models and digital transformation is anticipated to reshape brand value and growth logic for listed companies, contributing to the index's growth potential [13]

Quantitative Models and Construction 1. Model Name: CDS Timing Strategy - **Model Construction Idea**: The model uses the 20-day difference signal of China's sovereign CDS as a timing indicator for Hong Kong stocks, leveraging the negative correlation between CDS and stock performance[12][13] - **Model Construction Process**: 1. Calculate the 20-day difference of China's sovereign CDS 2. Use the signal to time Hong Kong stock investments 3. Evaluate the annualized excess return relative to the benchmark - **Model Evaluation**: The model demonstrates a strong fit with Hong Kong stock returns and provides a reliable timing signal[12][13] 2. Model Name: Duration Timing Strategy - **Model Construction Idea**: The model estimates the expected return of government bonds for any duration and holding period using a multi-step process[17] - **Model Construction Process**: 1. Decompose government bond yields 2. Predict interest rates using modeling techniques 3. Simulate scenarios via Monte Carlo methods 4. Calculate expected returns for different durations and holding periods - **Model Evaluation**: The strategy is effective for short-term bond timing and provides actionable insights for duration allocation[17][19] 3. Model Name: Equity Index Return Prediction Model - **Model Construction Idea**: Predict the future returns of broad-based indices using a combination of macroeconomic and valuation factors[22][27] - **Model Construction Process**: 1. Use macroeconomic indicators and valuation metrics 2. Apply the model to predict returns for indices like CSI 300, CSI 500, etc. 3. Compare predicted returns to historical benchmarks - **Model Evaluation**: The model shows strong predictive power for large-cap indices like CSI 300, while small-cap indices like CSI 500 exhibit lower reliability[22][27] 4. Model Name: Industry Rotation Strategy - **Model Construction Idea**: Evaluate industries based on momentum, turnover, volatility, and beta to identify rotation opportunities[60] - **Model Construction Process**: 1. Calculate 12-month information ratios for industry momentum 2. Assess turnover, volatility, and beta for crowding metrics 3. Combine these dimensions to rank industries - **Model Evaluation**: The strategy effectively identifies high-potential industries and provides actionable rotation insights[60][63] 5. Model Name: Odds + Win Rate Strategy - **Model Construction Idea**: Combine odds and win rate metrics to allocate assets dynamically[65][70] - **Model Construction Process**: 1. Construct odds and win rate indicators for each asset 2. Combine the two metrics into a unified score 3. Allocate assets based on the combined score - **Model Evaluation**: The strategy balances risk and return effectively, achieving stable performance over time[65][70] --- Model Backtest Results 1. CDS Timing Strategy - Annualized Return: 11.8% - Annualized Volatility: 13.9% - Maximum Drawdown: 19.1% - Sharpe Ratio: 0.851[15] 2. Duration Timing Strategy - Annualized Return: 6.8% - Annualized Volatility: 2.1% - Maximum Drawdown: 2.3% - Calmar Ratio: 2.94[19] 3. Equity Index Return Prediction Model - CSI 300: Predicted Return 19.7% - CSI 500: Predicted Return -27.8%[22][26] 4. Industry Rotation Strategy - Annualized Excess Return: 12.2% (since 2011) - Tracking Error: 10.9% - Maximum Drawdown: 25.4% - IR: 1.12[61] 5. Odds + Win Rate Strategy - Annualized Return: 6.9% (since 2011) - Annualized Volatility: 2.3% - Maximum Drawdown: 2.8% - Sharpe Ratio: 3.03[72] --- Quantitative Factors and Construction 1. Factor Name: Quality Factor - **Factor Construction Idea**: Combines odds, trend, and crowding metrics to evaluate quality stocks[46] - **Factor Construction Process**: 1. Calculate odds (valuation) at 1.3 standard deviations 2. Assess trend at -0.1 standard deviations 3. Measure crowding at -1.1 standard deviations 4. Combine metrics into a composite score - **Factor Evaluation**: High composite score indicates strong potential for long-term allocation[46] 2. Factor Name: Growth Factor - **Factor Construction Idea**: Evaluates growth stocks based on trend, odds, and crowding metrics[47] - **Factor Construction Process**: 1. Calculate trend at 0.5 standard deviations 2. Assess odds at -1.1 standard deviations 3. Measure crowding at 0.2 standard deviations 4. Combine metrics into a composite score - **Factor Evaluation**: Low composite score suggests limited allocation value[47] 3. Factor Name: Dividend Factor - **Factor Construction Idea**: Focuses on dividend-paying stocks with moderate odds and low crowding[50] - **Factor Construction Process**: 1. Calculate trend at -1.7 standard deviations 2. Assess odds at -0.2 standard deviations 3. Measure crowding at -1.6 standard deviations 4. Combine metrics into a composite score - **Factor Evaluation**: Low composite score indicates limited allocation potential[50] 4. Factor Name: Small-Cap Factor - **Factor Construction Idea**: Evaluates small-cap stocks based on trend, odds, and crowding metrics[53] - **Factor Construction Process**: 1. Calculate trend at -0.06 standard deviations 2. Assess odds at -0.05 standard deviations 3. Measure crowding at 0.3 standard deviations 4. Combine metrics into a composite score - **Factor Evaluation**: High uncertainty and low composite score suggest caution[53] --- Factor Backtest Results 1. Quality Factor - Odds: 1.3 SD - Trend: -0.1 SD - Crowding: -1.1 SD - Composite Score: 3[46] 2. Growth Factor - Odds: -1.1 SD - Trend: 0.5 SD - Crowding: 0.2 SD - Composite Score: 0[47] 3. Dividend Factor - Odds: -0.2 SD - Trend: -1.7 SD - Crowding: -1.6 SD - Composite Score: 0[50] 4. Small-Cap Factor - Odds: -0.05 SD - Trend: -0.06 SD - Crowding: 0.3 SD - Composite Score: 0[53]

Group 1 - The overall holding value of northbound funds reached 2.24 trillion RMB as of March 31, 2025, an increase of approximately 25.7 billion RMB compared to the end of Q4 2024, accounting for about 5.5% of the free float market value of A-shares [1][8][11] - Long-term allocation funds from foreign banks held 1.71 trillion RMB, increasing by about 10.8 billion RMB, representing 4.2% of the free float market value, while short-term trading funds from foreign brokerages held 0.38 trillion RMB, increasing by approximately 11.2 billion RMB, accounting for 0.93% [1][8][11] Group 2 - Northbound funds showed a significant increase in allocation to momentum, liquidity, and growth styles in Q1, reversing the previous quarter's reduction in these areas [2][17][22] - The overall style preferences of northbound funds included overweight positions in market capitalization, momentum, volatility, profitability, growth, and leverage, while underweight positions were noted in beta, BP, and liquidity [2][20][25] Group 3 - The highest holding value proportion of northbound funds was in the consumer sector at 6.9%, followed by financials at 6.0%, with a slight increase in the cyclical sector [3][28][32] - Northbound funds were overweight in consumer and financial sectors compared to the overall A-share market, while they were underweight in stability, technology, and cyclical sectors [3][38][42] Group 4 - The top five industries for northbound funds in terms of holding proportion changes were automotive, retail, consumer services, machinery, and electronics, while the bottom five included utilities, financials, telecommunications, real estate, and construction [3][42][45] - Northbound funds were overweight in industries such as power equipment and new energy, food and beverage, home appliances, banking, and automotive, while underweight in computer, basic chemicals, machinery, defense, and electronics [3][51][52] Group 5 - In terms of index allocation, northbound funds showed a decrease in holding proportions for the Shanghai 50 (-0.5%), CSI 300 (-0.3%), and CSI 500 (-0.2%), while there was a slight increase for the CSI 1000 (+0.1%) [4][58][62] - Northbound funds were overweight in the Shanghai 50 and CSI 300 compared to the overall A-share market, while underweight in the CSI 500 and CSI 1000 [4][67]

Market Performance - In April, A-shares experienced significant volatility, with the Shanghai Composite Index down 1.7% to 3279.03 points, the Shenzhen Component Index down 5.75% to 9899.82 points, and the ChiNext Index down 7.4% to 1948.03 points [1][2]. Future Outlook - Analysts are optimistic about the A-share market in May, suggesting it is a good time for positioning, as historical data shows that the Shanghai Composite Index has risen in 7 out of the last 15 years during the 10 trading days following the May Day holiday [2][3]. Sector Performance - Historical analysis indicates that consumer and large financial sectors tend to perform well in the 10 trading days before and after the May Day holiday, driven by policy support and upward industry trends [3][4]. Investment Strategies - Analysts recommend focusing on three asset categories: stable assets (high dividends, gold), self-sufficient industrial chains, and domestic consumption [4][5]. - There is a consensus that the Chinese stock market's upward momentum is not over, with suggestions to increase allocations to Chinese assets due to improved economic policies and a decrease in risk premiums [4][5]. Structural Opportunities - May is expected to see a structural recovery in A-shares, with a focus on consumption, technology, and dividend stocks as key investment themes [5].

Group 1 - The A-share market maintained a volatile consolidation before the May Day holiday, while the Hong Kong stock market continued to rebound, with the Every Day Brand 100 Index slightly down by 0.12% to close at 1052 points [1][2] - Chinese concept stocks led the gains, with notable weekly increases for Xiaomi Group (11.32%), JD Group (6.7%), and Pinduoduo (6.64%), while several other stocks also showed strong performance [2] - In April, the Every Day Brand 100 Index exhibited a "V" shaped trend despite external shocks, indicating a slow recovery in market confidence and the need for a solid economic rebound [2][3] Group 2 - With the disclosure of Q1 2025 quarterly reports, public funds showed significant adjustments in their holdings, with Tencent Holdings, Alibaba-W, and SMIC seeing the largest increases in positions [4] - The total scale of public funds reached 31.62 trillion yuan, a decrease of 1.93% from the previous quarter, indicating a shift in investment strategies [4] - Alibaba's stock price surged by 55.34% in Q1 2025, driven by strategic divestments and a focus on core business operations, including advancements in its AI model [4] Group 3 - The Hong Kong stock market has shown strong performance since 2025, with both the Hang Seng Index and the Hang Seng Technology Index outperforming mainland indices, suggesting potential investment opportunities in specific Hong Kong stocks [5] - The Hong Kong Stock Connect Technology ETF covers a wide range of Chinese concept stocks, with Alibaba, Tencent, and Xiaomi accounting for approximately 45% of the index weight [6] Group 4 - The CSI Hong Kong Stock Connect Technology Index, which tracks 50 leading technology companies, reflects the overall performance of technology stocks within the Hong Kong Stock Connect framework [9] - The index has demonstrated superior returns over mainstream broad-based indices, with an annualized return of 12.34% and a Sharpe ratio of 0.52, indicating a favorable risk-return profile [12]

Group 1 - The core viewpoint of the article highlights the performance of the China Securities Index for Hong Kong-listed tradable mainland consumption, which has seen a recent increase of 0.57% to 1230.76 points, despite a decline of 8.09% over the past month [1] - The index has shown a year-to-date increase of 8.81% and a three-month increase of 7.24%, indicating a positive trend over a longer period [1] - The index is part of a series that includes HKT Hong Kong real estate, HKT mainland consumption, and HKT mainland banking, reflecting the overall performance of related thematic securities in the Hong Kong market [1] Group 2 - The top ten holdings of the index include BYD Company (12.92%), Alibaba-W (12.58%), JD Group-SW (8.05%), Trip.com Group-S (7.63%), Meituan-W (7.32%), Pop Mart (4.52%), Xpeng Motors-W (3.96%), Li Auto-W (3.96%), Yum China (3.88%), and Anta Sports (3.65%) [1] - The index's holdings are entirely composed of securities listed on the Hong Kong Stock Exchange, with the passenger vehicles and parts sector accounting for 29.45%, consumer services for 23.30%, and retail for 21.88% [2] - The index samples are adjusted biannually, with changes implemented on the next trading day following the second Friday of June and December, ensuring that the weight factors are updated accordingly [2]

本周是五一长假前的最后一个交易周，上市公司年报和一季报也将披露完毕，泓德基金表示，市场未来 三个月将进入业绩的真空期，外部环境的变化可能的对国内资本市场产生一定程度的扰动，但我们相 信，按照政治局会议的部署，统筹国内经济工作和国际经贸斗争，坚定不移办好自己的事，坚定不移扩 大高水平对外开放，着力稳就业、稳企业、稳市场、稳预期，以高质量发展的确定性应对外部环境急剧 变化的不确定性，中国经济这艘巨轮可以行稳致远。 MACD金叉信号形成，这些股涨势不错！ 整体来看，泓德基金分析，当前政策仍处于以"筹备"和"积蓄弹性"为主的阶段，结构性调控和局部支持 依然是主旋律，这使得市场将更多将目光聚焦于中美谈判进展以及潜在的降关税交易预期上。 从债券市场看，泓德基金表示，上周利率债收益率普遍上行。信用债收益率也多数上行。MLF超额续 作短暂提振但未能扭转观望情绪，超长端波动收窄显示市场分歧仍在，市场仍在等待央行降准降息。 上周国内权益市场延续小幅反弹走势，日均成交量相较上上周变化不大，维持在1.1万亿元附近，万得 全A周涨幅为1.15%。具体来看，国内主要股指中，小型股股指涨幅较大，中证1000（+1.8%）和中证 2000（ ...

Group 1 - The core index, the CSI Hong Kong-Shanghai-Shenzhen Interconnection Small Comprehensive Consumer Index, reported a decline of 6.26% over the past month, 0.49% over the past three months, and 0.83% year-to-date, currently standing at 2521.90 points [1] - The index is categorized into 11 industries based on the classification standards of the CSI Hong Kong-Shanghai-Shenzhen index series, which includes the CSI 500 and other indices [1] - The top ten weighted stocks in the index include Sichuan Changhong (2.11%), Laopu Gold (2.07%), Gongxiao Daji (1.99%), Leap Motor (1.8%), Fuyao Glass (1.76%), Tongcheng Travel (1.55%), BAIC Blue Valley (1.46%), Bertley (1.45%), Great Wall Motors (1.45%), and Yonghui Superstores (1.43%) [1] Group 2 - The market share of the index's holdings is distributed as follows: Shenzhen Stock Exchange 43.43%, Shanghai Stock Exchange 34.15%, and Hong Kong Stock Exchange 22.42% [2] - The industry composition of the index's holdings includes: Passenger Cars and Parts 43.12%, Durable Consumer Goods 18.17%, Textiles, Apparel, and Jewelry 14.86%, Retail 12.63%, and Consumer Services 11.21% [2] - The index samples are adjusted biannually, with adjustments implemented on the next trading day following the second Friday of June and December each year [2]