- The report tracks the performance of various broad-based indices in the A-share market, noting that on February 2, 2026, all indices fell by more than -2%, with the CSI 500 and CSI 1000 experiencing the largest declines of -3.98% and -3.39%, respectively[3][11] - The report compares the indices with their moving averages, highlighting that all tracked indices have simultaneously fallen below the 5, 10, and 20-day moving averages, with the CSI 500 and CSI 1000 experiencing significant single-day declines and a retreat of over 5.5% from their recent 250-day highs[3][13] - The report provides data on the trading volume and turnover rates of the indices, with the CSI 2000 having the highest turnover rate at 4.26, followed by the ChiNext Index at 3.85, and the CSI 1000 at 3.1[3][17] - The distribution of daily returns is analyzed, showing that the ChiNext Index has the largest negative skewness and kurtosis, while the CSI 500 has the smallest negative skewness and kurtosis[3][24][25] - The risk premium of the indices relative to the 10-year government bond yield is examined, with the ChiNext Index and CSI 2000 having relatively high 5-year percentile values of 5.56% and 5.24%, respectively, while the CSI 500 has a relatively low value of 0.4%[3][27][31] - The PE-TTM ratios of the indices are analyzed, with the CSI 500 and CSI 1000 having high 5-year percentile values of 98.68%, while the ChiNext Index has a lower value of 61.07%[3][42][43] - The dividend yield of the indices is tracked, with the ChiNext Index and CSI 300 having relatively high 5-year historical percentile values of 56.36% and 38.68%, respectively, while the CSI 500 and CSI 2000 have lower values of 8.1% and 5.62%[3][53][55] - The report also notes the percentage of stocks trading below their net asset value, with the CSI 500 having a rate of 11.0%, the CSI 1000 at 7.0%, and the CSI 2000 at 2.7%[3][57]

Report Industry Investment Rating No investment rating for the industry is provided in the report. Core Viewpoints of the Report - In the market review from January 26 to January 30, 2026, most major equity market indices declined, with the Small and Medium - sized Board Index experiencing the largest drop of 3.78%. Among the 31 Shenwan primary industries, 10 industries rose, with the top five gainers being petroleum and petrochemicals, communications, coal, non - ferrous metals, and agriculture, forestry, animal husbandry, and fishery; the top five decliners were national defense and military industry, electrical equipment, automobiles, computers, and comprehensive industries [1][12]. - In the public fund market, the CSRC solicited public opinions on the "Content and Format of Regular Reports of Publicly Offered Securities Investment Funds" and the Asset Management Association of China officially established the performance comparison benchmark element library for public funds. In terms of fund performance, quantitative funds in equity funds had the largest decline, with an average drop of 1.10% and a positive return ratio of 24.74%; fixed - income + funds averaged a 0.20% decline with a positive return ratio of 35.23%; pure - bond funds averaged a 0.03% increase with a positive return ratio of 84.81%; pension target FOFs averaged an 0.81% increase with a positive return ratio of 94.97%. QDII funds averaged a 0.77% increase with a positive return ratio of 63.95%. Actively managed equity funds increased their positions in non - ferrous metals, petroleum and petrochemicals, and food and beverages last week, while reducing positions in pharmaceutical biology, electronics, and household appliances. As of January 30, 2026, the position of actively managed equity funds was 73.88%, a decrease of 1.07 pct from the previous period [1][2]. - In the ETF market, last week, the overall ETF market had a net capital outflow of 298.095 billion yuan, with the outflow scale narrowing slightly compared to the previous period. Stock - type ETFs had the largest net outflow of 317.982 billion yuan. The average daily trading volume of the overall ETF market reached 635.407 billion yuan, the average daily trading volume was 225.627 billion shares, and the average daily turnover rate was 9.11%. Chemical, gold, non - ferrous metals, and convertible bond sectors were the main capital inflow varieties, while broad - based indices such as the CSI 300, CSI 1000, SSE 50, and CSI Small - cap 500 continued to see large - scale capital outflows, with the capital outflow of the CSI 300 index exceeding 240 billion yuan [3][50]. - Regarding fund issuance, last week, 45 new funds were issued, 5 more than the previous period; 47 new funds were established, 5 more than the previous period. New funds raised a total of 48.272 billion yuan, an increase of 3.818 billion yuan from the previous period [4]. Summary by Relevant Catalogs 1. Market Review 1.1 Domestic Market Conditions - From January 26 to January 30, 2026, most major equity market indices declined, with the Small and Medium - sized Board Index dropping 3.78%, the largest decline. Among the 31 Shenwan primary industries, 10 industries rose, and the top five gainers and decliners were as mentioned above. In the bond market, the ChinaBond Composite Full - Price Index remained unchanged, while the ChinaBond Treasury Bond, Financial Bond, and Credit Bond Total Full - Price Indices fluctuated from a 0.03% decline to a 0.05% increase, and the CSI Convertible Bond Index dropped 2.61%. In the commodity market, the Nanhua Commodity Index rose 2.60% [12]. 1.2 European, American and Asian - Pacific Market Conditions - Last week, most major indices in European, American, and Asian - Pacific markets declined. In the US stock market, the S&P 500 index rose 0.21%, the Dow Jones Industrial Average fell 0.39%, and the Nasdaq Composite fell 0.17%. In the European market, the French CAC40 fell 0.20% and the German DAX fell 1.45%. In the Asian - Pacific market, the Hang Seng Index rose 2.38% and the Nikkei 225 fell 0.97% [20]. 1.3 Market Valuation Conditions - Last week, the valuation quantiles of most major market indices declined. In terms of the historical quantiles of price - to - earnings ratios, the SSE 50 had the highest increase of 5.7 pct. In terms of the historical quantiles of price - to - book ratios, the SSE 50 also had the highest increase of 2.5 pct. Among industries, the top five industries with the highest historical quantiles of price - to - earnings ratios in the Shenwan primary index were real estate, electronics, chemicals, commercial trade, and comprehensive industries. The lowest five were non - bank finance, agriculture, forestry, animal husbandry, and fishery, food and beverages, beauty care, and pharmaceutical biology [23]. 2. Active Public Fund Conditions Market Hotspots - The CSRC solicited public opinions on the "Content and Format of Regular Reports of Publicly Offered Securities Investment Funds", integrating and revising relevant regulations to strengthen industry transparency and protect the legitimate rights and interests of fund share - holders. The Asset Management Association of China also solicited industry opinions on the "XBRL Template for Information Disclosure of Securities Investment Funds", which requires adding long - term performance data and other information [31][32]. - The Asset Management Association of China officially established the performance comparison benchmark element library for public funds, including 155 indices in total, with adjustments in the number of indices and operation rules [33]. Fund Performance - As mentioned above, different types of funds had different performance, and the top - performing funds in each category last week and this year were also listed [39][40][43]. Industry Positions of Actively Managed Equity Funds - Last week, actively managed equity funds increased their positions in non - ferrous metals, petroleum and petrochemicals, and food and beverages, and reduced positions in pharmaceutical biology, electronics, and household appliances. As of January 30, 2026, the position of actively managed equity funds was 73.88%, a decrease of 1.07 pct from the previous period [45][46]. 3. ETF Fund Conditions - Last week, the overall ETF market had a net capital outflow of 298.095 billion yuan, with stock - type ETFs having the largest net outflow of 317.982 billion yuan. The average daily trading volume of the overall ETF market was 635.407 billion yuan, the average daily trading volume was 225.627 billion shares, and the average daily turnover rate was 9.11%. Chemical, gold, non - ferrous metals, and convertible bond sectors were the main capital inflow varieties, while broad - based indices such as the CSI 300, CSI 1000, SSE 50, and CSI Small - cap 500 continued to see large - scale capital outflows [3][50]. 4. Fund Issuance Statistics - Last week, 45 new funds were issued, 5 more than the previous period, including 24 actively managed equity funds and 12 passive index funds. The 12 passive index funds were all stock - type, mainly tracking indices such as the SZSE GEM New Energy Vehicle Battery Index, CSI Industrial Non - ferrous Metals Theme Index, and CSI Photovoltaic Industry Index. 47 new funds were established, 5 more than the previous period, and new funds raised a total of 48.272 billion yuan, an increase of 3.818 billion yuan from the previous period [4][58][63].

Quantitative Models and Construction Methods - **Model Name**: Sparse Auto Encoder (SAE) **Model Construction Idea**: The model aims to compress high-dimensional features into low-dimensional sparse coding while ensuring the reconstructed features retain most of the original information. It also incorporates autoregressive loss and sparsity penalties to enhance robustness and reduce overfitting [7][8][9] **Model Construction Process**: 1. **Encoding**: Compress input features into sparse coding $ \text{code}_{i}=\text{Encoder}(x_{i}) $ Here, $ x_{i} $ represents input features, and $ \text{code}_{i} $ is the compressed sparse coding [8] 2. **Decoding**: Reconstruct features from sparse coding $ \hat{x}_{i}=\text{Decoder}(code_{i}) $ $ \hat{x}_{i} $ represents reconstructed features, which should closely resemble $ x_{i} $ [8] 3. **Prediction**: Predict future index returns using hidden layer features $ \hat{y}_{i}=\text{Predictor}(res_{i}) $ $ \hat{y}_{i} $ represents the predicted future returns [8] 4. **Loss Function**: Combines prediction error, reconstruction error, and sparsity penalty $$ Loss=\frac{1}{N}\sum\nolimits_{i=1}^{N}\left(\mathcal{J}(y_{i},{\hat{y}}_{i})+\lambda_{1}\mathcal{L}\left(x_{i},{\hat{x}}_{i}\right)+\lambda_{2}SparseLoss(code_{i})\right) $$ $ \mathcal{J} $ measures prediction error, $ \mathcal{L} $ measures reconstruction error, and $ SparseLoss $ applies sparsity penalties using KL divergence or vector norms [9][12] **Evaluation**: The model effectively selects features, enhances robustness, and learns the "true" patterns of index movements [11] - **Wavelet Transform for Noise Reduction** **Construction Idea**: Decompose time-series data into multiple components to isolate noise and retain meaningful information [19][20] **Construction Process**: 1. Select parent wavelet $ \varphi $ and mother wavelet $ \psi $ $ \varphi_{jk}=2^{-j/2}\varphi(2^{-j}-k) $ $ \psi_{jk}=2^{-j/2}\psi(2^{-j}-k) $ Parent wavelet captures low-frequency trends, while mother wavelet captures high-frequency fluctuations [19][20] 2. Reconstruct time-series data using wavelet coefficients $$ x(t)=\sum\nolimits_{k}s_{j,k}\varphi_{j,k}+\sum\nolimits_{k}d_{j,k}\psi_{j,k}+\ldots+\sum\nolimits_{k}d_{1,k}\psi_{1,k} $$ Coefficients $ S_{J,k} $ and $ d_{j,k} $ are calculated as: $ S_{J,k}=\int\varphi_{J,k}x(s)ds $ $ d_{j,k}=\int\psi_{J,k}x(s)ds $ [20] **Evaluation**: Reduces overfitting risks by filtering out noise and retaining meaningful components [21] Model Backtesting Results - **SAE Model** **Performance on CSI 500 Index**: - Multi-strategy annualized return: 43.86% - Long-only annualized return: 23.30% - Short-only annualized return: 16.68% - Sharpe ratio: 2.07 (multi-strategy), 1.39 (long-only), 1.28 (short-only) - Maximum drawdown: -14.00% (multi-strategy), -16.04% (long-only), -14.30% (short-only) [29][33][34] **Performance on CSI 1000 Index**: - Multi-strategy annualized return: 51.21% - Long-only annualized return: 26.00% - Short-only annualized return: 20.01% - Sharpe ratio: 1.41 (long-only), 1.27 (short-only) - Maximum drawdown: -22.08% (long-only), -19.85% (short-only) [43][46][47] **Performance on CSI 2000 Index**: - Multi-strategy annualized return: 32.40% - Long-only annualized return: 32.56% - Sharpe ratio: 1.62 (long-only) - Maximum drawdown: -25.59% (long-only) [55][56] **Performance on CSI All Share Index**: - Multi-strategy annualized return: 18.74% - Long-only annualized return: 18.83% - Sharpe ratio: 1.26 (long-only) - Maximum drawdown: -16.95% (long-only) [55][56] Quantitative Factors and Construction Methods - **Input Features** **Construction Idea**: Use common technical indicators and derived metrics from daily K-line data as model inputs [16][18] **Construction Process**: 1. **Technical Indicators**: - RSI: $ RSI=(N\text{-day absolute closing price increase})/(N\text{-day absolute closing price decrease}) $ - OBV: $ OBV=\text{sum of closing price change signs} \times \text{turnover rate} $ - MACD: $ DIF=12\text{-day EMA}-26\text{-day EMA} $ $ DEA=DIF\text{'s 9-day EMA} $ $ MACD=DIF-DEA $ [16][17] 2. **Derived Metrics**: Rolling averages, relative positions of moving averages, volatility metrics, and other derived indicators [16][18] **Evaluation**: The feature set is comprehensive but not optimized, as no additional filtering was applied to avoid overfitting [18] Factor Backtesting Results - **RSI, OBV, MACD** **Performance**: Incorporated into the SAE model, contributing to the overall strategy performance across indices [16][18] Key Observations - The SAE model performs better on smaller-cap indices like CSI 2000 and CSI 1000 compared to CSI 500, indicating its effectiveness in smaller market segments [62] - Multi-strategy returns are balanced between long and short positions, with no significant bias toward either direction [42][54] - The model's robustness and sparsity design mitigate overfitting risks and enhance generalization across different market conditions [11][21] - Setting appropriate thresholds for signal generation improves strategy stability and reduces transaction costs [66]

- The report primarily focuses on tracking and analyzing the performance of broad-based indices in the A-share market, including metrics such as daily returns, moving averages, turnover rates, risk premiums, PE-TTM, dividend yields, and net asset ratios[1][3][4] - **Risk Premiums**: The risk premium is calculated using the yield of 10-year government bonds as the risk-free rate. It measures the relative investment value and deviation of indices. For example, the current risk premium for the SSE 50 is 1.64%, with a 5-year historical percentile of 94.21%, while the CSI 500 has a negative risk premium of -0.98% and a 5-year historical percentile of 16.35%[27][31][34] - **PE-TTM**: The PE-TTM (Price-to-Earnings Trailing Twelve Months) is used as a valuation reference. The CSI All Share Index and CSI 500 have the highest 5-year historical percentiles at 99.92% and 99.75%, respectively, indicating high valuation levels. In contrast, the SSE 50 and ChiNext Index have lower percentiles at 85.87% and 62.89%, respectively[39][42][44] - **Dividend Yields**: Dividend yield reflects the cash dividend return rate. The current dividend yield for the SSE 50 is 3.19%, while the CSI 500 and CSI 2000 have lower yields at 1.21% and 0.71%, respectively. The ChiNext Index has a 5-year historical percentile of 56.20%, indicating a relatively high historical level[48][53][55] - **Net Asset Ratios**: The net asset ratio measures the proportion of stocks trading below their net asset value. Currently, the SSE 50 has the highest ratio at 24.0%, while the CSI 2000 has the lowest at 2.35%, reflecting market valuation attitudes[54][57]

Core Viewpoint - The article discusses the significant growth of ETF products tracking the CSI A500 index and the potential introduction of A500 ETF options in early 2026, prompting investors to consider the long-term fundamentals behind their investment decisions rather than short-term market fluctuations [1][8]. Group 1: Understanding Broad-Based Indices - Broad-based indices are not uniform; differences in compilation rules and characteristics significantly affect their long-term risk-return profiles and performance in various economic environments [3][4]. - The CSI A500 and CSI 300 indices, while both categorized as large-cap balanced styles, have distinct design intentions and compilation paths, with the CSI 300 focusing on large, liquid companies and the CSI A500 emphasizing broader industry representation and sustainability considerations [4][6]. - The CSI A500 includes a more balanced industry distribution and a lower concentration in traditional sectors compared to the CSI 300, which is more focused on core blue-chip assets [4][6]. Group 2: Importance of Index Selection and Tracking Effectiveness - Selecting the right index is crucial, but the effectiveness of the tracking product is key to realizing investment returns, as investors cannot directly invest in indices [9][10]. - Key metrics for evaluating ETF products include tracking deviation and tracking error, which indicate how closely a fund captures the index's returns and the stability of that tracking over time [10][11]. - Factors influencing an ETF's tracking performance include fees, cash drag from dividends and investor redemptions, and the fund manager's operational capabilities [11][12].

- The report tracks and analyzes the market data of major indices, including their daily performance, moving averages, trading volume, and turnover rates[2][3][4] - The report evaluates the distribution of daily returns for various indices, highlighting the kurtosis and skewness of these distributions[25][26] - The report assesses the risk premium of different indices relative to the 10-year government bond yield, providing insights into their relative investment value and deviation[28][29][30] - The report examines the PE-TTM (Price-to-Earnings ratio based on trailing twelve months) of various indices, considering their historical percentiles and current values to gauge investment attractiveness[40][43][44] - The report analyzes the stock-bond yield ratio, comparing the inverse of the PE-TTM with the 10-year government bond yield to determine the relative attractiveness of stocks versus bonds[47] - The report tracks the dividend yield of different indices, noting their historical percentiles and current values to assess the attractiveness of dividend-paying stocks[48][49][54] - The report monitors the percentage of stocks trading below their book value (PB ratio < 1) within each index, indicating market valuation attitudes and potential undervaluation[55][58][60]

- The report tracks and analyzes the market data of major indices, including their performance, moving averages, turnover rates, and risk premiums[1][2][3] - The indices' daily performance is evaluated, with the CSI 500 showing the highest annual increase of 13.95%, followed by the CSI 1000 and CSI 2000[10] - The comparison of indices with their moving averages and the highest and lowest points over the past 250 trading days is provided, showing significant pullbacks after reaching new highs[12][13] - The turnover rates of various indices are analyzed, with the CSI 2000 having the highest turnover rate of 5.34%[16] - The distribution of daily returns is examined, with the ChiNext Index showing the largest negative skewness and the CSI 500 the smallest[22][23] - The risk premiums of the indices relative to the 10-year government bond yield are calculated, with the Shanghai 50 and CSI 300 having the highest 5-year percentile values[25][26][29] - The PE-TTM ratios of the indices are analyzed, with the CSI 500 and CSI 1000 having the highest 5-year percentile values of 99.92%[37][40][41] - The dividend yields of the indices are tracked, with the ChiNext Index and CSI 300 having the highest 5-year historical percentile values[45][51][53] - The percentage of stocks trading below their net asset value is analyzed, with the Shanghai 50 having the highest percentage of 24.0%[52][55]

- The report primarily focuses on tracking and analyzing the performance of broad-based indices in the A-share market, including metrics such as daily returns, moving averages, turnover rates, risk premiums, PE-TTM, dividend yields, and price-to-book ratios[1][3][4] - The turnover rates of various indices on January 23, 2026, were as follows: CSI 2000 (4.97%), ChiNext Index (4.05%), CSI 1000 (3.96%), CSI 500 (2.86%), CSI All Share (2.46%), CSI 300 (0.96%), and SSE 50 (0.41%)[4][20] - The risk premium of indices relative to the 10-year government bond yield was observed, with CSI 500 (2.41%) and CSI 1000 (1.93%) showing higher premiums, while SSE 50 (-0.69%) and CSI 300 (-0.46%) had lower premiums. The 5-year percentile rankings for risk premiums were highest for CSI 500 (98.10%) and CSI 1000 (94.21%)[28][32][35] - The PE-TTM (Price-to-Earnings Trailing Twelve Months) values and their historical percentiles were analyzed. CSI 500 and CSI 1000 had the highest PE-TTM percentiles (100.0% for both), while SSE 50 had a lower percentile (80.33%). The current PE-TTM values were: SSE 50 (11.49), CSI 300 (14.09), CSI 500 (39.02), CSI 1000 (51.94), CSI 2000 (174.36), CSI All Share (22.63), and ChiNext Index (43.64)[43][44] - Dividend yields were tracked, with SSE 50 (3.31%) and CSI 300 (2.76%) having relatively higher yields, while CSI 500 (1.20%) and CSI 2000 (0.68%) had lower yields. The 5-year historical percentiles for dividend yields were highest for ChiNext Index (57.11%) and CSI 300 (38.18%)[54][56] - The price-to-book ratio (P/B) was analyzed through the "break net ratio," which measures the proportion of stocks trading below their book value. Current break net ratios were: SSE 50 (24.0%), CSI 300 (16.33%), CSI 500 (10.0%), CSI 1000 (6.8%), CSI 2000 (2.2%), and CSI All Share (5.22%)[58]

- The report primarily focuses on tracking and analyzing the performance of broad-based indices in the A-share market, including metrics such as daily returns, moving averages, turnover rates, risk premiums, PE-TTM, dividend yields, and net asset break rates[1][3][4] - The moving average analysis highlights that indices like the ChiNext Index and CSI 500 have broken above their 250-day highs, indicating strong momentum in these segments[15][16] - Turnover rates are highest for the CSI 2000 (4.46%) and CSI 1000 (3.31%), while the Shanghai Stock Exchange 50 Index has the lowest turnover rate at 0.38%, reflecting varying levels of liquidity across indices[18] - The risk premium analysis, using the 10-year government bond yield as a risk-free rate, shows that the ChiNext Index (1.00%) and CSI 2000 (0.99%) have the highest current risk premiums, while the Shanghai Stock Exchange 50 Index has a negative risk premium of -0.47%[27][31] - PE-TTM analysis reveals that the CSI 500 and CSI 1000 indices are at their 100% historical percentiles, indicating high valuation levels, while the ChiNext Index is at a relatively lower 63.47% over the past five years[42][44] - Dividend yield analysis shows that the ChiNext Index (57.85%) and CSI 300 (37.02%) are at relatively high historical percentiles over the past five years, while the CSI 500 (3.39%) and CSI 2000 (0.41%) are at lower levels[53][55] - The net asset break rate analysis indicates that the Shanghai Stock Exchange 50 Index has the highest break rate at 24.0%, while the CSI 2000 has the lowest at 2.3%, reflecting varying market valuation attitudes across indices[57]

- The report tracks the performance of various broad-based indices in the A-share market, including the CSI 500, CSI 2000, and others, highlighting their daily, weekly, monthly, and yearly changes[2][3][11] - The report compares the indices with their moving averages and their positions relative to the highest and lowest points in the past 250 trading days, noting that indices like CSI 1000, CSI 2000, and CSI All Share have broken through their 5-day moving averages[3][15][16] - The report analyzes the trading volume and turnover rates of the indices, with CSI 2000 having the highest turnover rate at 4.36, followed by CSI 1000 at 3.28[3][18] - The report examines the distribution of daily returns, noting that the ChiNext Index has the largest negative skewness and kurtosis, while the CSI 500 has the smallest[3][23][24] - The report evaluates the risk premiums of the indices relative to the 10-year government bond yield, with CSI 500 and CSI 2000 having high risk premiums at 84.37% and 75.87% respectively[3][26][27] - The report assesses the PE-TTM ratios of the indices, with CSI 500 and CSI 1000 having high percentile values at 100.0% and 99.83% respectively[4][41][42] - The report tracks the dividend yields of the indices, noting that the ChiNext Index and CSI 300 have relatively high 5-year historical percentile values at 58.18% and 37.77% respectively[4][50][52] - The report monitors the net asset value break rates of the indices, with the current break rates being 24.0% for SSE 50, 16.33% for CSI 300, and 10.4% for CSI 500[4][56]