Quantitative Models and Construction Methods - **Model Name**: Neutral Constraint Maximum Factor Exposure Portfolio **Construction Idea**: Maximize the exposure of the target factor in the portfolio while maintaining neutrality in industry and style exposures relative to the benchmark index[60][61][63] **Construction Process**: 1. **Objective Function**: Maximize portfolio exposure to the target factor $ \text{Max}\quad w^{\prime}X_{\text{target}} $ 2. **Constraints**: - Industry neutrality: $ (w - w_b)^{\prime}X_{\text{inad}} = 0 $ - Style neutrality: $ (w - w_b)^{\prime}X_{\text{Beta}} = 0 $ - Weight deviation limit: $ |w - w_b| \leq 1\% $ - No short selling: $ w \geq 0 $ - Full allocation: $ w^{\prime}1 = 1 $ - Constituents from benchmark index: $ w^{\prime}B = 1 $ **Evaluation**: The model ensures that the portfolio remains neutral to industry and style biases while maximizing factor exposure[60][61][63] Factor Construction and Definitions - **Factor Name**: Beta Factor **Construction Idea**: Capture the sensitivity of individual stock returns to market returns[14][15] **Construction Process**: - Calculate the regression coefficient of individual stock daily returns against the market index (CSI All Share Index) over the past 252 trading days using a half-life weighting of 63 days **Formula**: $ \text{Beta} = \text{Regression Coefficient} $ **Evaluation**: Reflects market risk sensitivity, useful for identifying high-risk or low-risk stocks[14][15] - **Factor Name**: Book-to-Price (BP) **Construction Idea**: Measure valuation by comparing book equity to market capitalization[14][15] **Construction Process**: - $ \text{BP} = \frac{\text{Shareholders' Equity}}{\text{Market Capitalization}} $ **Evaluation**: Indicates undervaluation or overvaluation of stocks, commonly used in value investing[14][15] - **Factor Name**: Sales Growth (SGRO) **Construction Idea**: Assess growth potential by analyzing historical revenue trends[14][15] **Construction Process**: - Perform regression on annual revenue data from the past five fiscal years - Divide the regression slope by the average revenue to calculate growth rate **Formula**: $ \text{SGRO} = \frac{\text{Regression Slope}}{\text{Average Revenue}} $ **Evaluation**: Useful for identifying companies with strong growth trajectories[14][15] Factor Backtesting Results - **Beta Factor**: Weekly long-short return of 7.50%, monthly return of 8.74%[16] - **Book-to-Price (BP)**: Weekly return of -0.27%, monthly return of 0.39%[21][26][30] - **Sales Growth (SGRO)**: Not explicitly tested in the report[14][15] Portfolio Backtesting Results - **Neutral Constraint Maximum Factor Exposure Portfolio**: - **CSI 300 Enhanced Portfolio**: Weekly excess return of 0.03%, monthly return of 1.91%, annual return of 1.34%[57][58] - **CSI 500 Enhanced Portfolio**: Weekly excess return of -1.29%, monthly return of -1.24%, annual return of -2.54%[57][58] - **CSI 800 Enhanced Portfolio**: Weekly excess return of -0.32%, monthly return of 1.68%, annual return of 1.19%[57][58] - **CSI 1000 Enhanced Portfolio**: Weekly excess return of -0.95%, monthly return of 1.33%, annual return of 13.01%[57][58] - **CSI 300 ESG Enhanced Portfolio**: Weekly excess return of 0.51%, monthly return of 2.44%, annual return of 7.72%[57][58] Factor Performance in Different Stock Pools - **CSI 300 Stock Pool**: - Weekly top-performing factors: Log Market Cap (0.83%), Single Quarter Operating Profit Growth (0.72%), 20-Day Specificity (0.71%)[21][23] - Monthly top-performing factors: Single Quarter EP (3.19%), EP_TTM (2.93%), Single Quarter ROE (2.63%)[24] - **CSI 500 Stock Pool**: - Weekly top-performing factors: 20-Day Specificity (1.39%), 60-Day Volume Ratio (1.13%), 60-Day Reversal (1.00%)[26][28] - Monthly top-performing factors: Single Quarter Revenue Growth (3.31%), Single Quarter Operating Profit Growth (2.73%), Single Quarter ROE Growth (2.72%)[28] - **CSI 800 Stock Pool**: - Weekly top-performing factors: Log Market Cap (1.59%), Single Quarter ROE Growth (1.20%), Single Quarter Operating Profit Growth (1.06%)[30][32] - Monthly top-performing factors: Single Quarter EP (4.36%), Single Quarter ROE Growth (3.90%), Single Quarter ROE (3.90%)[33] - **CSI 1000 Stock Pool**: - Weekly top-performing factors: 60-Day Reversal (1.40%), Single Quarter SP (1.30%), SP_TTM (1.29%)[35][37] - Monthly top-performing factors: Log Market Cap (3.66%), 60-Day Reversal (3.43%), Single Quarter Net Profit Growth (3.24%)[38] - **CSI 300 ESG Stock Pool**: - Weekly top-performing factors: Log Market Cap (1.05%), 20-Day Volume Ratio (0.63%), 20-Day Specificity (0.60%)[40][41] - Monthly top-performing factors: Log Market Cap (4.20%), Single Quarter ROE (2.55%), EP_TTM (2.49%)[42] - **All-Market Stock Pool**: - Weekly top-performing factors: Log Market Cap (24.81% Rank IC), 20-Day Specificity (21.07% Rank IC), 60-Day Reversal (19.50% Rank IC)[44][45] - Monthly top-performing factors: 20-Day Specificity (11.25% Rank IC), 20-Day Three-Factor Model Residual Volatility (10.96% Rank IC), 60-Day Specificity (10.73% Rank IC)[45]

Market Overview - The Shanghai Composite Index rose by 1.04% and the ChiNext Index increased by 3.11% on June 25, 2025, with sectors like comprehensive finance, non-bank finance, and defense industry leading the gains at 5.7%, 4.4%, and 3.49% respectively, while oil and petrochemicals, coal, and transportation sectors lagged behind with changes of -0.15%, -0.04%, and 0.25% [1] Reasons for Market Fluctuation - The market experienced a significant increase in volume, with brokerage, computer, and military sectors showing the highest gains, contributing to the Shanghai Composite Index reaching a new high for the year. Recent improvements in the international market environment, including dovish signals from the Federal Reserve and a potential ceasefire agreement between Israel and Iran, have positively influenced global risk assets. Additionally, the domestic economic fundamentals are improving, supported by steady capital market reforms [2] Future Market Outlook - The outlook for the second half of the year remains moderately optimistic, driven by ongoing growth stabilization policies, accelerated infrastructure investment, and effective consumption stimulus measures. Industrial profits are expected to recover in the latter half of the year. Capital market reforms, such as relaxing insurance capital market entry ratios and optimizing dividend repurchase systems, are set to enhance the A-share market ecosystem. The strong policy intent to stabilize the capital market suggests limited chances for significant market corrections. Two asset categories are highlighted: high-elasticity new productivity sectors, including new technologies and materials, and stable industries focusing on core operations and shareholder returns, which are less affected by economic downturns in developed economies [3] Factors to Monitor - Key factors to watch include geopolitical situations, upcoming US-China trade negotiations in early August, EU-US trade talks in early July, and marginal changes in domestic real estate sales data [4]

Core Viewpoint - The China Securities Index for non-bank financial themes has shown significant growth, with a 9.38% increase over the past month and a 22.93% increase year-to-date, reflecting strong performance in the Hong Kong stock market [1][2]. Group 1: Index Performance - The China Securities Index for non-bank financial themes rose by 3.98% to 3715.3 points, with a trading volume of 26.594 billion [1]. - The index has increased by 12.23% over the past three months and 22.93% year-to-date [1]. Group 2: Index Composition - The index comprises up to 50 listed companies that meet the non-bank financial theme criteria, selected from the Hong Kong Stock Connect securities [1]. - The top ten weighted companies in the index include China Ping An (14.97%), AIA Group (14.53%), and Hong Kong Exchanges and Clearing (14.11%) [1]. Group 3: Sector Allocation - The index's holdings are primarily in the insurance sector, which accounts for 64.29%, followed by other capital markets at 21.65% and securities companies at 12.73% [2]. - Other financial services and consumer credit represent smaller portions of the index, at 1.02% and 0.31% respectively [2]. Group 4: Index Adjustment Mechanism - The index samples are adjusted biannually, with changes implemented on the next trading day following the second Friday of June and December [2]. - Special adjustments may occur in cases of delisting or significant corporate actions such as mergers or acquisitions [2].

Market Performance - On June 24, 2025, the market saw a significant increase, with the ChiNext Index leading the gains, rising by 2.30%[2] - The Shanghai Composite Index rose by 1.15%, while the Shenzhen Component Index increased by 1.68%[2] - Total market turnover reached 14,142.73 billion yuan, an increase of 2,918.16 billion yuan from the previous trading day[2] Sector and Style Analysis - All 30 sectors in the CITIC first-level industry index experienced gains, with the top performers being: Comprehensive (3.32%), Non-Bank Financials (2.70%), and Automotive (2.59%)[19] - The style performance ranked as follows: Growth > Financial > Cyclical > Consumer > Stable[19] - Fund-heavy stocks outperformed the CSI All Share Index[19] Capital Flow - On June 24, 2025, the net inflow of main funds was 177.00 billion yuan, with large orders contributing 155.11 billion yuan and small orders seeing a continuous outflow of 25.73 billion yuan[23] - Major ETFs such as the Huatai-PB CSI 300 ETF and the China Southern CSI 500 ETF saw significant increases in trading volume, with changes of +19.07 billion yuan and +11.32 billion yuan respectively[28] Global Market Trends - Major Asia-Pacific indices closed higher, with the Hang Seng Index up 2.06% and the Nikkei 225 Index up 1.14%[31] - In contrast, European indices saw declines, with the DAX down 0.35% and the FTSE 100 down 0.19%[32] - U.S. markets showed positive performance, with the Dow Jones Industrial Average rising by 0.89%[32]

Quantitative Models and Construction - **Model Name**: Three-dimensional Timing Framework **Construction Idea**: The model integrates liquidity, divergence, and prosperity indicators to assess market timing and risk levels[7][14][16] **Construction Process**: 1. **Liquidity Index**: Tracks market liquidity trends[22] 2. **Divergence Index**: Measures market disagreement levels[20] 3. **Prosperity Index**: Evaluates industrial prosperity trends[26] 4. Combines these three dimensions to form a comprehensive timing framework[14] **Evaluation**: Demonstrates stable performance in identifying market timing opportunities[16] - **Model Name**: Financing-Active Large Order Flow Intersection Strategy **Construction Idea**: Combines financing and large order flows to identify industries with strong capital inflows[34][40] **Construction Process**: 1. **Financing Flow Factor**: Neutralizes market capitalization and calculates the net financing buy-sell difference over a 50-day average[40] 2. **Active Large Order Flow Factor**: Neutralizes transaction volume and ranks net inflows over the past year, using a 10-day average[40] 3. Filters extreme industries and integrates both factors to enhance stability[40] **Evaluation**: Achieves stable annualized excess returns with reduced drawdowns compared to other strategies[40] Quantitative Models Backtesting Results - **Three-dimensional Timing Framework**: Historical performance shows stable risk assessment and timing capabilities[16] - **Financing-Active Large Order Flow Intersection Strategy**: - Annualized excess return: 13.5% - IR: 1.7[40] - Weekly absolute return: -1.6% - Weekly excess return: -0.1%[40] Quantitative Factors and Construction - **Factor Name**: Valuation Factors **Construction Idea**: Focuses on valuation metrics such as earnings yield and book-to-market ratios[46][47] **Construction Process**: 1. **Earnings Yield (ep_fy3)**: $ ep\_fy3 = \frac{1}{PE\_FY3} $ 2. **Book-to-Market Ratio (bp)**: $ bp = \frac{Shareholder\_Equity}{Market\_Value} $ 3. Neutralizes industry and market capitalization effects[46][48] **Evaluation**: Demonstrates strong performance across multiple timeframes and indices[46][48] - **Factor Name**: Growth Factors **Construction Idea**: Captures growth metrics such as revenue and profit growth rates[46][49] **Construction Process**: 1. **Revenue Growth (yoy_or)**: $ yoy\_or = \frac{Current\_Revenue - Previous\_Revenue}{Previous\_Revenue} $ 2. **Profit Growth (yoy_np)**: $ yoy\_np = \frac{Current\_Net\_Profit - Previous\_Net\_Profit}{Previous\_Net\_Profit} $ 3. Neutralizes industry and market capitalization effects[46][50] **Evaluation**: Performs better in large-cap indices and shows consistent excess returns[49][50] Quantitative Factors Backtesting Results - **Valuation Factors**: - Weekly excess return: 1.5%-2.18% - Monthly excess return: 1.46%-3.85%[48] - **Growth Factors**: - Weekly excess return: 1.52%-3.89% - Monthly excess return: 0.79%-3.02%[50] Quantitative Portfolios and Construction - **Portfolio Name**: Index Enhancement Portfolios **Construction Idea**: Adjusts factor selection based on research coverage to enhance index performance[51] **Construction Process**: 1. Divides stocks into high and low research coverage domains[51] 2. Applies suitable factors for each domain to optimize portfolio construction[51] **Evaluation**: Outperforms original index selection methods in terms of excess returns[51] Quantitative Portfolios Backtesting Results - **Index Enhancement Portfolios**: - **HS300**: - Weekly absolute return: -0.89% - Weekly excess return: 0.03% - Annualized excess return: 7.77%[52] - **CSI500**: - Weekly absolute return: 0.16% - Weekly excess return: 0.40% - Annualized excess return: 9.82%[52] - **CSI1000**: - Weekly absolute return: -0.58% - Weekly excess return: -0.74% - Annualized excess return: 9.26%[52]

行业研究 证 券 研 究 报 告 金融资金面跟踪：量化周报（2025/06/16~2025/06/21） 推荐（维持） 超额整体为正，市场成交量有所回落 证监会审核华创证券投资咨询业务资格批文号：证监许可（2009）1210 号 非银行金融 2025 年 06 月 21 日 金融资金面跟踪：量化周报（2025/06/16~2025/06/21） | 华创证券研究所 | | | --- | --- | | 证券分析师：徐康 | 证券分析师：刘潇伟 | | 电话：021-20572556 | 邮箱：liuxiaowei@hcyjs.com | | 邮箱：xukang@hcyjs.com | 执业编号：S0360525020001 | | 执业编号：S0360518060005 | | 各量化超额整体为正。上周样本量化私募收益及超额如下：1）300 增强策略周/月/ 年初以来平均收益分别为+0.1%/+1.7%/+2.7%，周/月/年初以来平均超额分别为 +0.2%/+0.8%/+4.9%；2）500 增强策略周/月/年初以来平均收益分别为+0%/+2.8%/+7.8%， 周/月/年初以来平均超额分别为+0.2%/ ...

Core Viewpoint - The China Securities Index for non-bank financial themes has shown a decline in the short term but has experienced significant growth year-to-date, indicating a mixed performance in the financial sector [1][2]. Group 1: Index Performance - The CSI Non-Bank Financial Theme Index fell by 2.62% to 3445.53 points, with a trading volume of 18.869 billion yuan [1]. - Over the past month, the index has increased by 8.98%, and over the last three months, it has risen by 6.39%, with a year-to-date increase of 21.74% [1]. Group 2: Index Composition - The index comprises up to 50 listed companies that meet the non-bank financial theme criteria, reflecting the overall performance of this sector within the Hong Kong Stock Connect [1]. - The top ten weighted companies in the index include China Ping An (14.86%), AIA Group (14.77%), Hong Kong Exchanges and Clearing (14.3%), China Life (8.75%), China Pacific Insurance (6.66%), and others [1]. Group 3: Industry Representation - The index exclusively represents the financial sector, with a 100% allocation to financial companies [2]. - The index samples are adjusted biannually, with changes implemented on the next trading day following the second Friday of June and December [2].

Investment Rating - The report does not explicitly provide an investment rating for the industry. Core Insights - The development of Real World Assets (RWA) is accelerating, supported by the regulatory framework for stablecoins, which enhances the liquidity and efficiency of asset financing [3][29]. - The Hong Kong Monetary Authority (HKMA) launched the Ensemble Project Sandbox in August 2024 to promote tokenization experiments for traditional securities and RWAs, indicating a significant step towards modernizing financing methods [28][29]. - The market value of RWAs has reached $23.9 billion, reflecting a growth of over 51% from $15.8 billion at the beginning of the year, showcasing increasing interest in RWAs as a new investment tool [10]. Summary by Sections Definition and Scale of RWA - RWA refers to the tokenization of real-world assets such as real estate, gold, and financial assets, allowing these assets to be split, traded, and circulated across borders [10][26]. - The advantages of RWA include increased asset liquidity, lower investment thresholds, reduced financing costs, improved financing efficiency, and enhanced asset transparency [10][26]. Comparison with Stablecoins - Stablecoins are blockchain-based digital currencies pegged to fiat currencies or commodities, focusing on maintaining stable value, while RWAs focus on tokenizing real-world assets [12][14]. - Stablecoins serve as a stable and trustworthy tool for purchasing RWAs, facilitating international transactions and enhancing liquidity in the RWA market [15][27]. Regulatory Framework and Projects - The HKMA's Ensemble Project Sandbox supports institutions in tokenization experiments, covering themes such as fixed income, liquidity management, green finance, and trade finance [28][29]. - Major cross-border RWA financing projects include Longshine Group's charging station project, GCL Energy Technology's photovoltaic project, and Xunying Travel's battery swapping project, with financing amounts ranging from CNY 100 million to over CNY 200 million [29][30]. Advantages of RWA Financing - RWA financing addresses traditional asset financing challenges by enabling the digitization and tokenization of assets, thus improving liquidity and reducing costs [10][9]. - The flexibility of RWA financing allows enterprises to customize transaction structures according to market demands, enhancing the likelihood of successful fundraising [9][10].

惠誉评级：充足的国内流动性降低亚太新兴市场非银行金融机构的再融资风险。 ...

Group 1 - The Hong Kong non-bank ETF (513750) has seen continuous net inflows for 18 consecutive trading days, reaching a new high of 2.64 billion yuan as of June 15, 2023, with shares increasing to 1.858 billion [1] - This ETF is the first and only one tracking the CSI Hong Kong Stock Connect Non-Bank Financial Theme Index (931024), focusing on the "insurance + brokerage" sectors, with a weight of 65.1% in the insurance industry and 32.5% in quality brokerage firms [1][2] - The index has a low price-to-earnings ratio of 8.52, placing it in the 17.93% percentile over the past decade, indicating a valuation below 82% of the time, combined with a dividend yield of 3.22%, showcasing a rare "low valuation + high dividend" characteristic [2] Group 2 - The investment outlook suggests focusing on two main areas: the potential for value re-evaluation in the insurance sector due to reduced liability costs and the expected performance boost in brokerages driven by ADT growth, particularly in the Hong Kong Stock Exchange [2]