证券研究报告 跟踪经济、掘金市场 | 主要观点： | 报告日期：2025-10-09 | | --- | --- | | √ 中证全指的风险溢价百分位为 45.07%，表明市场整体处于正 | 执业信息 | | 常回报区域。 | 林烽 策略分析师 执业编号：S1750522120001 | | √ 沪深 300 的风险溢价当前值为 5.17%，回报水平较高，值得重 | 电话：18605980882 | | 点关注。 | 邮件：linfeng@jypscnet.com | | √ 中证全指的市净率百分位为 41.77%，表明市场整体处于正常 | 免责声明 | | 估值状态。 | 报告观点基于逻辑分析、 | | √ 上证指数的市净率百分位为 22.68%，估值水平相对较低，值 | 数据规律推演，并不能预知不 同市场主体在复杂约束下的 | | 得重点关注。 | 多样选择结果。 | | √ 中证全指乖离率为 18.59%，表明市场整体价格水平处于正常 | 相关报告 | | 偏强区域。 | 20250201《策略月报：指 | | √ 科创 50 和创业板 50 处于超买状态，适度警惕短线风险。 | 数化投资策略月报（20 ...

Core Viewpoint - The article discusses the unique characteristics and advantages of the China Securities A500 Index, highlighting its role in the A-share market and its potential for investment opportunities [3][8][33]. Group 1: Index Characteristics - The China Securities A500 Index includes leading companies from all industries, making it distinct in its comprehensive coverage [8][9]. - The selection process for the A500 involves multiple rounds of elimination based on trading activity, market capitalization, and ESG ratings, ensuring only the most viable stocks are included [12][14][18][19]. Group 2: Selection Process - The first round eliminates stocks with low trading activity, specifically those in the bottom 10% of average daily trading volume over the past year [12]. - The second round removes stocks with small market capitalization, specifically those in the bottom 70% [14]. - The third round excludes stocks that do not support trading through the Shanghai-Hong Kong or Shenzhen-Hong Kong Stock Connect, enhancing liquidity [16]. - The final round eliminates stocks with poor ESG ratings, ensuring the selected companies are sustainable and responsible [18]. Group 3: Industry Coverage - The A500 Index is designed to have a balanced industry representation, which helps mitigate risks associated with overexposure to any single sector [23]. - Compared to the CSI 300 Index, the A500 has a higher representation of emerging industries like industrials and information technology, while having less exposure to traditional sectors like finance and consumer goods [25]. Group 4: Advantages and Disadvantages - The balanced industry allocation of the A500 enhances its risk resilience, but it may lead to relatively average returns during market rallies driven by specific sectors [28]. - The A500 has a shorter historical data period compared to other indices like the CSI 300, which limits the ability to assess its performance across various market conditions [31]. Group 5: Performance Insights - The A500 has shown significant performance, with some quantitative private equity funds achieving nearly 35% returns year-to-date, compared to 14% for the CSI 300 Index [33].

Core Viewpoint - The article emphasizes that investment is based on future expectations, while valuation is a retrospective indicator, making investment decisions based solely on valuation highly limited [3]. Group 1: Valuation and Index Performance - Comparing valuation growth with index growth provides significant insights into the health of index increases and whether they are driven by earnings or valuation [4][5]. - If valuation growth closely matches index growth, the increase is primarily driven by valuation rather than earnings [6]. - A situation where valuation growth exceeds index growth indicates that the index's rise is entirely driven by valuation, often accompanied by negative earnings growth [6][7]. - Conversely, if valuation growth is smaller than index growth, the increase is primarily driven by earnings, which is considered a healthier and more sustainable rise [7]. Group 2: Recent Index Performance Analysis - Since September 24 of the previous year, major A-share indices have seen increases primarily driven by valuation growth, with significant contributions from indices like the Dividend Low Volatility and the CSI 500, where valuation growth greatly exceeded index growth [9][10]. - In contrast, the Hang Seng Technology and China Internet 50 indices have experienced increases primarily driven by earnings growth, with minimal valuation changes [10][11]. Group 3: Phase-by-Phase Index Performance - An analysis of index performance from September 24 to April 30 shows that A-share indices like the CSI 500 and Dividend Low Volatility were entirely driven by valuation growth, with earnings showing negative growth [12][14]. - From April 30 to August 29, A-share indices continued to see increases primarily driven by valuation growth, while the Hang Seng Technology indices experienced increases largely driven by earnings [17][19]. Group 4: Investment Viability - A review of the health of index increases and historical valuation percentiles indicates that most A-share indices are at high valuation levels, suggesting that further investment may not be supported by retrospective indicators [21][22]. - In contrast, the Hang Seng Technology and China Internet 50 indices are at significantly undervalued positions, indicating better investment potential due to their earnings-driven growth [23][24]. - The S&P 500 and Nasdaq 100 indices are at high valuation levels, with recent performance primarily driven by valuation rather than earnings, raising concerns about the sustainability of their growth [25][26].

Core Viewpoint - The recent rise in popularity of the CSI All Share Index among fund companies is attributed to its comprehensive coverage of the A-share market, allowing investors to avoid missing out on market trends while seeking excess returns through quantitative strategies [1][3][12]. Group 1: Characteristics of the CSI All Share Index - The CSI All Share Index, while considered "niche," encompasses a wide range of stocks across large, mid, and small-cap categories, effectively representing the entire A-share market [2]. - The index's balanced allocation helps investors avoid structural pitfalls associated with focusing on specific sectors, providing a sense of security during volatile market conditions [3][4]. Group 2: Demand for Enhanced Index Funds - Fund companies are increasingly interested in creating "enhanced" versions of the CSI All Share Index to meet the investment needs of ordinary investors, who seek to avoid missing market opportunities while also aiming for excess returns [3][12]. - Enhanced index funds utilize quantitative strategies to select higher-quality stocks within the index, allowing for potential excess returns without the risks associated with actively managed funds [4][10]. Group 3: Performance of Enhanced Funds - The "Hongde Smart Selection" fund, which tracks the CSI All Share Index, has consistently outperformed the index since its inception, demonstrating the effectiveness of its quantitative strategies [6][8]. - The fund has shown lower excess drawdowns, indicating that it can retain excess returns even during market fluctuations, making it a reliable option for investors [8][10]. Group 4: Cost-Effectiveness of Public Funds - Public funds generally have lower fees compared to private funds, making them more accessible to ordinary investors. Public funds typically charge fixed management fees, while private funds often take a percentage of profits, which can reduce net returns for investors [11]. - The lower investment threshold for public funds allows more investors to participate, enhancing liquidity and flexibility in investment choices [11]. Group 5: Investment Strategy Recommendations - The current market environment suggests that investors should consider stable, broad-market coverage options like the CSI All Share Index enhanced funds as a foundational investment strategy, rather than chasing high-risk, high-reward opportunities [12][13].

Core Viewpoint - The article discusses the performance differences among various index funds, particularly focusing on the volatility and returns of large-cap and small-cap indices over the past decade, highlighting the challenges in choosing the best investment strategy among them [3][5][24]. Performance Analysis of Different Indices - Historical data shows significant performance disparities among indices of different sizes over the past ten years, with the 中证2000 exhibiting the highest volatility and returns during bullish phases, while the 沪深300 remains relatively stable [5][7]. - The 中证全指 demonstrates a balanced performance, generally staying within a moderate range with fewer extreme fluctuations compared to other indices [5][7]. Bull Market Performance - In 2014, all five indices saw substantial gains, with 沪深300 and 中证2000 both around 50%, while 中证全指, 中证500, and 中证1000 had returns between 30%-45% [10]. - The year 2015 marked extreme differentiation, with 中证2000 soaring over 100%, while 沪深300 showed minimal growth [11]. - In 2019, all indices rose moderately, with gains concentrated in the 20%-35% range, favoring 沪深300 and 中证全指 slightly [12]. - The year 2020 saw a general tightening of gains, with most indices recording increases between 10%-20%, and 沪深300 slightly outperforming small-cap indices [13]. Bear Market Performance - During bear markets, indices generally experienced significant declines, with the depth of the drop closely related to market capitalization structure [17]. - In 2016, the 中证全指 and 沪深300 fell by 5%-8%, while 中证500 and 中证1000 dropped by 10%-15%, and 中证2000 remained relatively stable [17]. - The year 2018 witnessed a severe downturn, with 中证1000 and 中证2000 suffering losses of nearly 40% and over 35%, respectively, while large-cap indices also faced declines exceeding 25% [18]. - In 2022, all indices recorded declines in the 15%-25% range, with small-cap indices and 中证全指 experiencing slightly larger drops, while 沪深300 fared better [19]. - In 2023, most indices recorded slight declines or remained flat, with only 中证2000 achieving approximately 2% positive returns, indicating that small-cap indices often bear greater adjustment pressure in bear markets [20]. Summary of Returns and Volatility - 中证2000 has the highest cumulative return at nearly 197% with an annualized return of 10.19% and a volatility of 28.26%, indicating high elasticity and risk [23]. - 中证全指 and 沪深300 show long-term returns of 84.46% and 79.11%, respectively, with annualized returns in the 5%-6% range and lower volatility, reflecting stability and balanced returns [23]. - 中证500 and 中证1000 fall in between, with cumulative returns of 67.92% and 55.63%, annualized returns slightly below 5%, and volatility ranging from 21%-27% [23]. Investment Strategy Recommendations - The article suggests that small-cap indices perform better during favorable market conditions but come with higher volatility and drawdown risks, while large-cap and broad-based indices offer more stable returns [24]. - A diversified investment approach, such as balancing large-cap and small-cap allocations and integrating growth and value styles, is recommended to enhance adaptability across different market conditions [24].

Core Viewpoint - The article discusses the importance of understanding different stock indices, particularly the Shanghai Composite Index and the Shenzhen Composite Index, for making informed investment decisions in the Chinese stock market [5][9]. Group 1: Index Characteristics - The Shanghai Composite Index includes only stocks listed on the Shanghai Stock Exchange, while the Shenzhen Composite Index includes stocks from the Shenzhen Stock Exchange and the ChiNext board [5][9]. - Historically, from 2019 to 2021, the Shenzhen stocks experienced greater price increases compared to Shanghai stocks, indicating a disparity in performance during bull markets [5][6]. - The Shanghai stocks tend to have more value-oriented characteristics, resulting in smaller price fluctuations during both bull and bear markets [6][7]. Group 2: Market Performance - The overall performance of the A-share market is better assessed by looking at both the Shanghai and Shenzhen indices, as they each represent about half of the A-share market [9]. - The CSI All Share Index, which includes all listed companies from both exchanges, saw an approximate 80% increase from 2019 to 2021, reaching over 6000 points at its peak [10].

Group 1: Core Insights - The report emphasizes the importance of growth factors in investment strategies, highlighting various indices that represent growth styles [10][12][24] - It identifies three main expressions of growth styles: absolute growth, relative growth, and cash flow growth, each with specific metrics and methodologies for evaluation [15][24][28] Group 2: Growth Factors - The report defines several growth factors, including net profit growth, operating profit growth, and revenue growth, with specific calculation methods outlined for each [15][18] - Correlation analysis among growth factors shows strong relationships, indicating that net profit growth has a 100% correlation with itself and significant correlations with other factors like operating profit growth (94.22%) and revenue growth (52.02%) [18][21] Group 3: Growth Style Performance - Backtesting results indicate that absolute growth composite strategies yield excess returns across various indices, with the highest information ratio observed in the CSI 300 index [21][28] - The report presents performance metrics for different growth styles, showing that the SUE (Surprise Earnings) factor and analyst forecast growth have significant positive impacts on returns [24][28]

Group 1 - The risk premium percentile of the CSI All Share Index is 71.95%, indicating that the market has returned from a high return area to a normal return area [1][8] - The price-to-book ratio percentile of the CSI All Share Index is 21.54%, suggesting that the market has returned from an undervalued state to a normal but slightly undervalued state [12] - The Shanghai Composite Index and CSI 800 are still in an undervalued state, warranting close attention [13] Group 2 - The CSI All Share Index's deviation rate is -0.03%, indicating that the overall price level of the market is in a normal range [16] - The ChiNext 50 has returned to a basic normal range after two months of recovery from an oversold state [19] - Over the past six months, the performance of value and growth styles has varied, and the value vs. growth style has yet to be defined, with future trends still to be observed [23] Group 3 - The performance of low valuation styles has generally been superior over the past six months, but high valuation styles have shown strong performance in the past month, suggesting investors should closely monitor the potential transition between high and low valuation styles [27] - Small-cap styles have significantly outperformed over the past six months, indicating a need for future focus on small-cap style targets [29] Group 4 - There has been a certain degree of excess return for convertible bonds relative to the CSI All Share Index over the past six months, suggesting that investors should consider convertible bond varieties from an asset allocation perspective [2][44] - Different types of convertible bonds have shown varying performance over the past six months, with a recommendation to focus on equity-oriented targets [48] Group 5 - The report emphasizes the importance of market style rotation, highlighting the differences in performance between value vs. growth, low vs. high valuation, and large vs. small capitalization stocks [20][21] - The report identifies that the performance of small-cap stocks has been notably superior, suggesting a focus on small-cap style targets moving forward [29] Group 6 - The report discusses industry/theme index rotation, focusing on low valuation rotation and dual momentum rotation strategies [33][34] - A selection of reference targets based on valuation factors or momentum factors is provided for investors to consider [37]

Key Points - The report indicates that the risk premium percentile of the CSI All Share Index is 80.41%, suggesting that the market is in a high return zone [1][5] - The report highlights that the price-to-book ratio percentile of the CSI All Share Index is 8.98%, indicating that the market is in a state of severe undervaluation [1][10] - The report notes that the deviation rate of the CSI All Share Index is -4.03%, suggesting that the overall price level of the market is in a normal range [1][13] - The report suggests that the performance of the value style has been significantly superior over the past six months, recommending a focus on value style targets [1][21] - The report also indicates that the performance of the low valuation style has been notably superior over the past six months, advising attention to low valuation style targets [1][24] - The report states that the performance of the small-cap style has been significantly superior over the past six months, recommending a focus on small-cap style targets [1][26] - The report identifies that there has been a certain degree of excess return for convertible bonds relative to the CSI All Share Index over the past six months, suggesting investors pay attention to convertible bond varieties from an asset allocation perspective [1][40]

Quantitative Models and Construction Methods 1. Model Name: Basic Risk Parity Model - **Model Construction Idea**: The model ensures that each asset in the portfolio contributes equally to the overall portfolio risk[20][23] - **Model Construction Process**: - Let the return vector of assets at time T be **r** and the weight vector be **w** - Covariance between assets is denoted as **Σ**, and the portfolio's return and volatility are: $$ \sigma(w) = \sqrt{w^T \Sigma w} $$ - Marginal Risk Contribution (MRC) and Risk Contribution (RC) for asset i are: $$ MRC_i = \frac{\partial \sigma(w)}{\partial w_i} = \frac{(\Sigma w)_i}{\sqrt{w^T \Sigma w}} $$ $$ RC_i = w_i \cdot MRC_i = w_i \cdot \frac{(\Sigma w)_i}{\sqrt{w^T \Sigma w}} $$ - Total Risk Contribution (TRC) is: $$ TRC = \sum RC_i = \sqrt{w^T \Sigma w} $$ - Risk parity requires: $$ RC_i = RC_j \; \text{for all} \; i, j $$[23][24][25] - **Model Evaluation**: The model is effective in balancing risk contributions but may lead to conservative portfolios when asset volatilities differ significantly[5][20] 2. Model Name: Risk Budgeting Risk Parity - **Model Construction Idea**: Adjusts the risk budget to allocate higher weights to riskier assets, making the model more flexible for different risk preferences[5][33] - **Model Construction Process**: - Adjust the relative marginal contribution of assets to the benchmark: $$ RC_i : RC = k_i \; \text{for all} \; i $$ - When assets are uncorrelated, the allocation becomes: $$ RC_i = \frac{k_i w_i^2 \sigma_i^2}{\sum k_i} $$ - Risk budget and actual weights are related quadratically: $$ \text{If actual weight is } n \times \text{basic weight, then risk budget is } n^2 $$ - Static and dynamic risk budgeting rules: - Static: Fixed risk budgets for equities, commodities, and gold - Dynamic: Adjust risk budgets based on Sharpe ratios over the past 6 months[37][39][41] - **Model Evaluation**: Provides higher returns but increases risk. Dynamic budgeting improves returns further but has mixed effects on risk metrics[41] 3. Model Name: Macro Risk Parity Model - **Model Construction Idea**: Allocates risk based on shared macroeconomic factors rather than individual asset risks, addressing overlapping risk contributions among assets[10][64] - **Model Construction Process**: - General asset pricing model: $$ r = 1^T \times I \times f_{base} + B \times I \times F + \varepsilon $$ - **I**: Dummy variable matrix indicating asset categories - **f_base**: Benchmark returns for major asset classes - **F**: Factor returns explaining intra-class differences - **B**: Factor exposures (sensitivity of assets to factors) - **ε**: Residual returns not explained by factors[64][66][68] - Systematic and idiosyncratic risk contributions: $$ RCF_i = w_{new,i} \cdot \frac{(\Sigma_f w_{new})_i}{\sqrt{w^T \Sigma w}} $$ $$ RCE_i = w_{new,i} \cdot \frac{(E w_{new})_i}{\sqrt{w^T \Sigma w}} = \frac{w_{new,i}^2}{\sqrt{w^T \Sigma w}} $$[74][75] - **Model Evaluation**: Effective in reducing leverage and addressing overlapping risks but requires precise macro risk modeling[12][115] --- Model Backtest Results 1. Basic Risk Parity Model - **Annualized Return**: 5.03% - **Maximum Drawdown**: -5.10% - **Volatility**: 2.58% - **Sharpe Ratio**: 1.90 - **Monthly Win Rate**: 71.11% - **Monthly Profit-Loss Ratio**: 3.44[28] 2. Risk Budgeting Risk Parity - **Static Risk Budgeting**: - **Annualized Return**: 5.80% - **Maximum Drawdown**: -9.30% - **Volatility**: 5.80% - **Sharpe Ratio**: 0.97 - **Monthly Win Rate**: 58.89% - **Monthly Profit-Loss Ratio**: 2.05 - **Dynamic Risk Budgeting**: - **Annualized Return**: 6.98% - **Maximum Drawdown**: -12.38% - **Volatility**: 6.29% - **Sharpe Ratio**: 1.07 - **Monthly Win Rate**: 63.33% - **Monthly Profit-Loss Ratio**: 2.30[46] 3. Macro Risk Parity Model - **Basic Asset Classes**: - **Annualized Return**: 5.03% - **Maximum Drawdown**: -5.10% - **Volatility**: 2.58% - **Sharpe Ratio**: 1.90 - **Monthly Win Rate**: 71.11% - **Monthly Profit-Loss Ratio**: 3.44 - **Expanded Sub-Asset Classes**: - **Annualized Return**: 7.35% - **Maximum Drawdown**: -11.49% - **Volatility**: 6.63% - **Sharpe Ratio**: 1.07 - **Monthly Win Rate**: 63.33% - **Monthly Profit-Loss Ratio**: 2.29[89] 4. Refined Asset Pool - **Asset Risk Parity**: - **Annualized Return**: 6.63% - **Maximum Drawdown**: -2.84% - **Volatility**: 2.83% - **Sharpe Ratio**: 2.27 - **Monthly Win Rate**: 75.51% - **Monthly Profit-Loss Ratio**: 5.99 - **Macro Risk Parity**: - **Annualized Return**: 8.03% - **Maximum Drawdown**: -3.59% - **Volatility**: 3.79% - **Sharpe Ratio**: 2.04 - **Monthly Win Rate**: 72.45% - **Monthly Profit-Loss Ratio**: 4.32[110]