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]

金融界4月11日消息，上证指数低开高走，中证1000可选消费指数 (1000可选，H30442)报4233.97点。 资料显示，指数样本每半年调整一次，样本调整实施时间分别为每年6月和12月的第二个星期五的下一 交易日。特殊情况下将对指数进行临时调整。当样本退市时，将其从指数样本中剔除。样本公司发生收 购、合并、分拆等情形的处理，参照计算与维护细则处理。当中证1000指数调整样本时，中证1000行业 指数样本随之进行相应调整。在样本有特殊事件发生，导致其行业归属发生变更时，将对中证1000行业 指数样本进行相应调整。 据了解，中证1000指数行业指数系列从每个行业内选取流动性和市场代表性较好的证券作为指数样本， 形成10条中证1000行业指数，为投资者提供更多样化的投资标的。该指数以2004年12月31日为基日，以 1000.0点为基点。 从指数持仓来看，中证1000可选消费指数十大权重分别为：麦格米特（4.82%）、银轮股份 （4.27%）、千里科技（3.07%）、富临精工（2.68%）、隆鑫通用（2.45%）、威孚高科（2.36%）、孩 子王（2.33%）、伟星股份（1.98%）、爱施德（1.87%）、奋 ...

金融工程 | 金工定期报告 金融工程 证券研究报告 在当前市场中，分析师报告数量众多，以行业报告为例，每周通常有超过 500 篇的报告。而阅读这些报告通常要花费大量的时间和成本。针对这一 需求，我们利用 DeepSeek-V3 大模型的总结能力对分析师行业报告进行智 能总结和整合，提炼出核心观点和关键信息。 利用大模型衡量景气度 行业研究报告通常提供分析师对行业趋势的深入分析与总体评价，但其应 用性较弱，主要有两个原因。首先，行业评级是行业研报中的标准化输出， 但其并非连续指标，通常仅分为三类，缺乏足够的区分度。因此，分析师 细微的态度和用词变化可能不会导致行业评级的调整。其次，不同证券公 司采用的行业分类标准并不一致，这些差异使得行业比较变得困难。 大模型普及之前，并不容易解决这些问题，而大模型的应用可能为此提供 更有效的支持。为了深入挖掘行业研报的信息，我们对其进行了进一步的 整理与标准化。我们构造了一个能够提取行业研报所涉具体中信一级、二 级行业名称以及对应行业景气度的提示词，并使用 DeepSeek-V3 模型，将 研报摘要作为输入文本得到该研报所属行业、景气度等指标结果。 最新行业研报文本景气度 我 ...